attached are details
#140.pdf
Journal of Public Economics 116 (2014) 73–88
Contents lists available at ScienceDirect
Journal of Public Economics
journal homepage: www.elsevier.com/locate/jpube
Defined benefit pension plan distribution decisions by public sector employees☆
Robert L. Clark a, Melinda Sandler Morrill b,⁎, David Vanderweide c
a Poole College of Management, North Carolina State University, USA b Department of Economics, North Carolina State University, USA c Fiscal Research Division, North Carolina General Assembly, USA
☆ This research was supported in part by a grant fro ministration (SSA) funded as part of the Financial Liter opinions and conclusions expressed herein are solely th represent the opinions or policy of SSA, any agency o any other institution with which the authors are affili paper was presented at the “Retirement Benefits for St signing Pension Plans for the Twenty-First Century” c by the Smith Richardson Foundation. The authors wo participants for useful comments, as well as seminar William and Mary. The authors would also like to than ell, Thayer Morrill, Doug Pearce, James Poterba, and Jo and comments. ⁎ Corresponding author at: Department of Economics
sity, Box 8110, Raleigh, NC 27695-8110, USA. Tel.: +1 9 E-mail address: [email protected] (M.S. Mo
0047-2727/$ – see front matter © 2013 Elsevier B.V. All http://dx.doi.org/10.1016/j.jpubeco.2013.05.005
a b s t r a c t
a r t i c l e i n f o
Article history: Received 16 October 2012 Received in revised form 22 February 2013 Accepted 28 May 2013 Available online 11 June 2013
JEL Classification: H7 J4 J3
Keywords: Public employees Defined benefit pensions Distribution choices
Studies examining pension distribution choices have found that the tendency of private-sector workers is to select lump sum distributions instead of life annuities resulting in leakage of retirement savings. In the public sector, defined benefit pensions usually offer lump sum distributions equal to employee contributions, not the present value of the annuity. Thus, for terminating employees that are younger or have shorter tenures, the lump sum distribution amount may exceed the present value of the annuity. We discuss the factors that may influence the choice to withdraw funds or not in this environment. Using administrative data from the North Carolina state and local government retirement systems, we find that over two-thirds of public sector workers under age 50 separating prior to retirement from public plans in North Carolina left their accounts open and did not request a cash distribution from the pension system within one year of separation. Further- more, the evidence suggests many separating workers, particularly those with short tenure, may be forgoing substantial monetary benefits due to lack of knowledge, understanding, or accessibility of benefits. We find no evidence of a bias toward cash distributions for public employees in North Carolina.
© 2013 Elsevier B.V. All rights reserved.
1. Introduction
Each year, millions of American workers leave their jobs prior to retirement either by choice or due to termination by their employers. Many of these job changers participate in defined benefit pension plans. On leaving their employers, these workers are often given a choice of keeping their retirement accounts open, thus maintaining a claim on a future life annuity, or accepting an immediate lump sum distribution (LS) of their pension assets. This decision is distinct from that faced upon retirement, since workers maintaining their ac- count will not receive any cash benefits until reaching retirement age.
m the U.S. Social Security Ad- acy Research Consortium. The ose of the authors and do not f the Federal Government, or ated. An earlier version of the ate and Local Employees: De- onference, which was funded uld like to thank conference participants at the College of k Julie Agnew, Olivia S. Mitch- sh Rauh for useful discussions
, North Carolina State Univer- 19 515 0331. rrill).
rights reserved.
Workers who accept the LS are then given a choice of whether they want to roll the funds over into an IRA or to accept the cash as taxable income and also pay a tax penalty for early withdrawal if under age 59.5. These choices can have significant long run implications for fu- ture retirement income and shed light on the magnitude of leakages from retirement saving. In a report describing sources of leakage of workers' retirement savings from 401(k) plans, the Government Accountability Office (2009) concluded that cashing out benefits at job separation represents the principle form of leakage of retirement savings and has the largest impact on retirement wealth accumula- tion. The problem of leakages is greater among younger workers and males, who have been found to cash out benefits at higher rates (AonHewitt, 2011).
Economic theory argues that to maximize lifetime utility one should consume such that utility levels are smooth over time. One method of achieving utility smoothing is through the purchase of annuities (Yaari, 1965). However, a series of national surveys and economic studies found that individuals rarely purchase annuities in the open market (see, e.g., Mitchell et al., 1999). Further, when given the choice in their pension plans of a life annuity or a LS, workers often chose the LS (see, e.g., Brown, 2001; Engelhardt, 2002; Hurd and Panis, 2006). Thus, many workers tend to reject the opportunity to receive a certain flow of income throughout retire- ment in favor of receiving cash now, which therefore results in indi- viduals assuming the task of managing funds on their own during their retirement years. This conflict between theory and individual
74 R.L. Clark et al. / Journal of Public Economics 116 (2014) 73–88
choices has been called the “Annuity Puzzle.”1 If cashed out benefits are spent on immediate consumption rather than saved for retire- ment, this leakage will result in lower income and income security in retirement.
Under federal pension regulations, defined benefit plans in the private sector must offer an annuity and provide participants with in- formation on their future annuities. The LS's for these plans are re- quired to be calculated as at least equal to the present value of the retirement annuity using approved interest and mortality tables.2
Things are very different in the public sector. Public sector defined benefits plans usually require explicit employee contributions each pay period, and LS's are based on the employee contributions and not the present value of the annuity. Thus, a public sector worker's choice of whether to take a LS reflects both his/her individual prefer- ence for annuitization and potential differences in the net value of the LS and annuity options. Defined benefit plans continue to cover most state and local employees and virtually all of the plans offer workers the option of a LS at job separation or retirement (Clark et al., 2011).
We examine the choices terminated workers younger than age 50 make using data from the North Carolina Teachers' and State Em- ployees' Retirement System (TSERS) and the North Carolina Local Governmental Employees' Retirement System (LGERS) by examining information contained in the administrative records of the two retire- ment plans.3 We restrict our attention to individuals under age 50 as they are not yet eligible to retire and receive immediate annuity ben- efits. As of the end of 2010, these two public pension plans covered 803,636 employees and retired workers. Our unique dataset contains all terminations from state and local government employment in North Carolina between 2007 and 2008 and tracks behavior through the end of 2009, allowing us to observe choices made within one year of separation for all terminated workers. The dataset includes relevant economic and demographic information on all individuals who left state or local employment during this time period.
Public sector defined benefit plan participants face a series of choices concerning their pension accounts when terminating employment prior to retirement, as illustrated in Fig. 1. The first decision a worker must make is whether to maintain his/her pension account or accept an immediate LS.4 From an economic perspective, a worker should compare the value of the LS to the present discounted value of the life annuity (PDVA) which is set to begin at some point in the future. How- ever, as we will see later, there are a number of factors that make this decision more complicated that a simple wealth comparison.
The default option is for the worker to maintain the pension ac- count; a departing worker must file a request with the retirement system in order to receive a LS. Depending on the rules of the pension plan, a worker might also have the opportunity to return to work with the same employer and have prior service credits count toward a future retirement benefit.5 Fig. 1 also shows that workers who re- quest a LS must specify whether they want to receive cash or have
1 See Benartzi et al. (2011) for an excellent overview of the annuity puzzle literature. 2 The Pension Protection Act requires that beginning in 2008 the LS be calculated
using a three-segment interest rate yield curve based on the rates of return on invest- ment grade corporate bonds of varying maturities. Purcell (2007) provides additional information on this process and how it affects workers at various ages at termination.
3 While these plans have separate governing boards, they are administered by the same staff and have similar, but not identical, benefits and contributions requirements. Further details of TSERS and LGERS can be found by visiting the retirement systems' home page at: http://www.nctreasurer.com/dsthome/RetirementSystems.
4 The term “maintain” is used because workers may have the opportunity to request a LS at any time after separating from public employment and prior to starting a retire- ment benefit; thus not accepting the immediate LS leaves open the option of requesting such a distribution at some time in the future instead of waiting until one is eligible to start a retirement annuity from the plan. In our analysis, “immediate” means that the terminated worker requested a LS within one year of termination.
5 Returning to work and being covered by the same retirement plan is probably much more likely in the public sector where a single plan typically covers all state em- ployees and teachers in the state. This allows workers to change jobs and government agencies and to move within the state while remaining in the same retirement system.
the funds rolled over into another approved tax qualified retirement plan such as an IRA. If the worker is sent a check, she could subse- quently deposit the funds into an IRA and avoid current taxes and penalties if she follows the IRS guidelines. It is important to remem- ber that individuals preferring to insure against longevity risk by annuitizing have the option to withdraw funds, roll them over into an IRA, and ultimately purchase an annuity. Thus, an informed worker should decide whether to withdraw funds based on the highest pres- ent value of the distribution options, appropriately measured, taking into account predicted inflation, interest rates, and various types of risk.
We calculate how the decisions made by separating workers are affected by the value of the distributional options available to them. The relative generosity of the two options is estimated using details of the plan characteristics and information provided by the retire- ment system. We find that fewer than one-third of all terminating public employees requested a LS within one year of separation, de- spite the finding that for over 70% of terminations, the LS was larger than the estimated PDVA. These results indicate a low probability of leakage from retirement funds, although many workers are seeming- ly forgoing the possibility of higher retirement income possible from rolling over funds to an IRA.
We offer several potential explanations for why the distributional choice from a public pension plan is more complex than a simple wealth comparison at a point in time. First, separating participants in TSERS qualify for retiree health insurance from the State Health Plan with no premium as long as they are receiving a monthly annu- ity from TSERS. This option is available for virtually all vested state employees (participants in TSERS), but local employees (participants in LGERS) are not covered by the State Health Plan.6 Comparing dis- tributional decisions by state employees in TSERS to those of local employees in LGERS provides some indication of the effect of retiree health insurance on the choice to ultimately receive a retirement an- nuity. Despite the difference in coverage of retiree health insurance in the two systems, we do not see a large difference in the distributional choices between separating workers that will qualify for retiree health insurance and those that will not.
Second, we consider the likelihood that terminated participants may plan to return to public employment. The expectation of returning to public employment might make maintaining the account the optimal choice for these individuals. However, we document that workers who ultimately returned to work by December 2010 were actually more likely to withdraw funds within one year of separation. Third, we discuss the influence of alternative investment options, macroeconomic conditions, and confidence in the retirement system. Maintaining the account still allows for the option of requesting a LS at some future date. Because the account balance accrues interest at a guaranteed rate of 4%, financially savvy individuals may choose to maintain their account balances and accept larger LS's at a future date as part of an investment portfolio. However, we do not find that the 12-month return on the S&P 500 is related to the probability of withdrawing funds, once local macroeconomic conditions are added to the model. There are mixed results when considering the 1-year Treasury bond rate, but, if anything, higher bond rates are as- sociated with a reduced probability of withdrawing funds. Moreover, we do not see a large difference between the disposition choice of non-vested workers (who do not earn interest) and vested workers. This indicates that workers are not responding to incentives of out- side investment options. We do find that when the state unemploy- ment rate rises, individuals are significantly less likely to withdraw
6 With a few minor exceptions, workers and retirees covered by LGERS are not cov- ered by the State Health Plan; however, they may be covered by locally-managed health plans that extend coverage to retirees. We cannot match the local health plans to the LGERS retirement data.
Fig. 1. Choices facing separating employees to take a lump sum distribution (LSD) or to maintain their retirement account.
75R.L. Clark et al. / Journal of Public Economics 116 (2014) 73–88
funds. This could be due to selection into who is separating employ- ment, or it may be that individuals more heavily rely on defaults in times of economic turmoil.
The final explanations we consider for why public sector workers in North Carolina do not withdraw funds at a higher rate are financial literacy, peer effects, and inertia. The default is to leave funds in the system. The behavior we observe is consistent with many individuals accepting the default option and forgoing potentially more valuable benefits. We find evidence consistent with peer effects, but cannot distinguish between correlation in unobserved characteristics and the influence of peers in this study.
After the analysis of the decision to accept a LS rather than maintaining one's account balance, we then examine the decision between cash and a rollover of pension assets by those who opted for a LS. The decision on spending versus saving the LS distribution has received considerable attention by economists; however, only a few studies have been able to observe this choice in administrative records rather than survey data (see Bryant et al., 2011). We find that nearly 90% of separating workers that request a LS elect to re- ceive the funds as cash, rather than rolling over, suggesting a high probability of leakage of retirement funds among these individuals. Of course, individuals who select a cash distribution can still move the funds into a retirement account, pay off debts, or save in non- retirement accounts, rather than spending the money on immediate consumption.
2. Relevance of findings for participants in public and private DB plans
Due to similarity of TSERS and LGERS to other state and local pen- sion plans, the results presented in this analysis should be relevant to understanding worker behavior in most public pension plans. While the findings also will shed light on potential behavior of participants in private defined benefit plans, the difference in pension coverage and plan characteristics between the public and private sectors of the U.S. economy is striking. The Bureau of Labor Statistics (2011a) found that in November 2011 only 22% of full-time private sector workers were participating in defined benefit plans, compared to 87% of full-time public sector workers. With 19.2 million individuals working as state and local employees, this implies that there were approximately 15 million public sector employees participating in defined benefit plans (Bureau of Labor Statistics, 2011b).
Historically, most defined benefit plans provided only annuities to their participants; however, over time increasingly plan sponsors have adopted provisions that allow their retirees to choose between receiving a lump sum distribution (at or prior to retirement) or accepting an annuity at retirement. Under federal pension regula- tions, defined benefit plans in the private sector must offer an annu- ity. Traditional plans typically provide participants with information on the expected monthly payout amount of their future annuity. According to federal guidelines, if a lump sum distribution is offered, it must be at least equal to the present value of the retirement annuity using approved interest and mortality tables. As discussed further below, things are very different in the public sector where plans usually require employee contributions and lump sum distributions are based on the employee contributions and not the present value of the annuity.
The lump sum option is becoming increasingly more common in private sector defined benefit plans. In 1989, only 2% of defined ben- efit plans offered by medium and large firms gave workers the option of taking a lump sum distribution, but by 1997 this number had risen to 23% (Bureau of Labor Statistics, 1990, 1999; also see Moore and Muller, 2002). According to data from the National Compensation Survey, in 2007 52% of all workers were in plans that provided em- ployees the option of selecting a lump sum distribution instead of accepting the life annuity (Bureau of Labor Statistics, 2007; Purcell, 2009). Some of the increase in defined benefit plans allowing lump sum options may be due to the growth of cash balance plans and other hybrid plans that specify the account balance as a lump sum throughout the worker's career. Hybrid plans almost always offer a lump sum option for departing and retiring workers. As more and more pension participants in both the public and private sectors of the economy confront distributional choices in their defined benefit plans, it is increasing important to understand the determinants of this choice and its implications for retirement income.
When making comparisons between choices made in the public and private sector, it is important to note that differences in plan de- sign and pension preferences may reflect, in part, a labor market sorting of workers based on workers' risk preferences. Using survey questions designed to measure risk aversion, previous studies in the United States and Europe indicated that employees in the public sector tend to be more risk averse than those in the private sector (e.g., Bellante and Link, 1981; Bonin et al., 2007; Hartog et al., 2002; Pfeifer, 2010). Similarly, public sector workers tended to choose less risky options in experiments (Buurman et al., 2009), took fewer
76 R.L. Clark et al. / Journal of Public Economics 116 (2014) 73–88
financial risks (Roszkowski and Grable, 2009), and were observed to select jobs that have smaller fluctuations in annual earnings and greater job stability (Bonin et al., 2007). Thus, one should be cautious in extending the findings regarding the determinants of choices made by public sector workers to workers in the private sector with DB plans that allow for lump sum distributions.
3. Previous literature examining lump sum distributions
Economists have long been interested in how workers access and utilize the wealth accumulated in their retirement accounts. For the most part, research studies have focused on (1) the choice between a lump sum distribution (LS) and an annuity at retirement, and (2) the decision by terminating workers who take a LS to accept a cash distribution or roll over the funds over into another tax qualified re- tirement plan. Papers on the first topic are often linked to the ‘annuity puzzle’ and try to explain why economic theory suggests individuals would prefer an annuity but retiring workers largely prefer LS's.7
Most studies on the second point use survey data which relies on in- dividuals' ability to recall whether they spent or saved the LS. There are only a few papers that consider the choice at termination prior to retirement between a LS and maintaining the account balance in defined benefit plans.8
Several previous papers examined the distributional choice at re- tirement in public sector retirement plans and found an important role for defaults and for personal preferences and discount rates. Butler and Teppa (2007) found that retirees in Swiss pension funds were more likely to accept the default option in the plan, leading to what they called an “acquiescence bias.” Warner and Pleeter (2001) estimated the decisions of individuals to leave the US military pen- sion plan during the 1990s in response two separation benefit pack- ages offered to mid-career personnel. They found that many more eligible participants accepted an offer of a lump sum payment than analysts had expected based on conventional interest rates. The au- thors argue that this was due to high personal discount rates relative to the interest rate used to equate the lump sum to the annuity. Chalmers and Reuter (2012) examined the distribution decisions of 32,060 retiring public employees in Oregon between 1990 and 2002. They found that 85% of Oregon state employees choose an an- nuity from the state retirement plan and that retirees respond to changes in annuity pricing, although this effect was relatively small.
Most studies that have examined the choice of a LS have focused on respondents in large national data sets (e.g., SIPP, HRS). Economic theory indicates that workers will compare the cost of purchasing an annuity that is based on population age-specific mortality rates to the present value of the annuity using their personal discount rates and their own life expectancies. Workers who believe that an annuity based on population life expectancy will be less than actuarially fair to them should accept the LS (Hurd and Panis, 2006). Individuals with high personal discount rates will place a lower value on the fu- ture annuity and thus be more likely to accept the LS.
Earlier studies have found that when the value of the cash settle- ment is relatively small, there is a greater likelihood that workers
7 Benartzi et al. (2011) discuss distributions options chosen by workers over age 50 the private sector. They find relatively high rates of annuitization among retiring workers thus providing evidence against the “Annuity Puzzle.” They found that institu- tional arrangements, framing of choices and defaults influence the decision to opt for an annuity or a LS.
8 An expanded model of pension decisions by individuals would include the initial choice of whether to select a DB plan or a DC plan as their primary retirement plan. This choice is a function of investment risk, labor market risk, and a variety of other fac- tors including whether the worker prefers their retirement plan to provide a retire- ment annuity or a LS. In the past decade, a number of states have given newly hired employees this option (Clark et al., 2011). Several recent papers have examined the choice of pension plans in the public sector (e.g., Brown and Weisbenner, 2012; Papke, 2004; Yang, 2005)
will take the LS and not roll these funds over into another retirement account, thus rejecting a future life annuity (Hurd and Panis, 2006; Poterba et al., 1998, 2001; Sabelhaus and Weiner, 1999; Engelhardt, 2002). Hurd and Panis (2006) found that about 20% of terminating workers opted for a LS when available and observed that women were more likely to request cash settlements than men, as were workers with less formal education. However, others find that men are more likely to take LS's (Butler and Teppa, 2007; Purcell, 2009). Older workers were found to be more likely to have rolled over their pension distributions (Burman et al., 1999; Moore and Muller, 2002; Warner and Pleeter, 2001). Many of these previous studies addressed workers' implied discount rates and the effect of high dis- count rates that minimize the value of the future annuity compared to the LS.9 The choice between money now and a lifetime annuity begin- ning years in the future is also influenced by financial literacy. Consid- erable recent evidence indicates that American workers have a relatively low level of financial literacy (Lusardi and Mitchell, 2007). Workers that lack a good understanding of financial mathematics, fi- nancial market risks, and the uncertainty associated with mortality might not be able to determine the optimal choice when faced with important financial decisions such as the choice of a LS versus a future annuity (see, e.g., Clark et al., 2012).
Despite the impressive list of studies that have examined distribu- tional choices and the use of LS's, there remain two important short- comings in these analyses. First, relatively few studies have examined the choices made by public sector employees. This is an important gap because the distributional options in public sector plans quite dif- ferent than those in the private sector, and defined benefit plans are much more prevalent in the public sector. Second, most prior studies used survey data and hence relied on respondents' recall of decisions made years earlier. The reliance on memory of these events undoubt- edly introduces considerable noise. In contrast, our analysis focuses on separations from a public defined benefit plan using administra- tive records showing real-time decisions. Thus, we are able to use ac- tual administrative data on the distributional decision, the timing of separation, and the value of the distributional options.
4. Estimating the value of distribution options in the North Carolina retirement plans
4.1. Background on distributional choices in state-managed defined benefit plans
In public sector defined benefit plans, the default option for departing workers who are vested is to leave their funds in the pen- sion plan and receive an annuity when they have attained the re- quired age for starting benefits.10 All public defined benefit plans that we have examined offer departing workers the option of leaving their funds in the pension system, thus retaining their eligibility to re- ceive a retirement annuity when they reach the specified age and ser- vice requirements of the plan.11 Most public plans allow separated workers to request a lump sum distribution (LS) at any point up until the individual starts the retirement annuity.
9 Other papers that examine the utilization of a LS include Bassett et al. (1998), Chang (1996), Copeland (2009), and Yakoboski (1997). 10 Ultimately, the default is that no benefits are paid. Terminated workers who do not request a lump sum distribution are defaulted into keeping their account open. When workers finally satisfy age and service requirements for a benefit, they still must re- quest that their retirement benefits be paid. No request from the terminated worker means that no benefit is paid. Data from the North Carolina retirement system show that only in a relatively small number of cases did workers leave public employment and never request either a LS or the start of an annuity. 11 Workers who had not yet been employed sufficient years to achieve vesting would have to return to a public job covered by the same pension and work additional years to satisfy the vesting requirements before they would be eligible to receive a future pension benefit.
77R.L. Clark et al. / Journal of Public Economics 116 (2014) 73–88
As described above in Section 2, private sector defined benefit plans usually do not entail employee contributions.12 In public retire- ment plans, on the other hand, employee contributions are typically required.13 All state retirement plans that require employee contribu- tions for all plan participants offer a LS option to terminated em- ployees. Separating workers in these plans are offered a LS at least equal to their own contributions. In some states, individuals are also awarded interest payments on their contributions. The interest rate varies across states and is often a function of years of service. The av- erage interest rate paid on employee contributions among those states with interest payments is 4% per year with a standard deviation of 2% (Clark and Hanson, 2011). While the empirical analysis of the distribu- tional choices reported in this paper uses administrative records only of North Carolina retirement plans, the choices and plan parameters imbedded in the North Carolina system are similar to those in other retirement plans covering teachers and state employees.14
16 Workers with 30 years of service can receive an unreduced benefit at any age; however, in the sample of separated employees that we examine, there are no individ- uals with 30 years of service. In addition, early retirement benefits are available to em- ployees with 20 years of service at age 50; however, there are substantial reductions for accepting early retirement benefits. The magnitude of the reduction in annual ben- efits for starting benefits prior to reaching the normal retirement age vary with age and years of service. The benefit reductions for TSERS are presented in the employee hand- book page 8, http://www.nctreasurer.com/NR/rdonlyres/223AE566-7BA0-471F-B02C- 0A18ABDB97C0/0/NC_TeaState_070111_Final.pdf. System records indicate that only about 25% of terminated vested workers wait until age 65 to start benefits; however,
4.2. Choices facing separating public sector workers in North Carolina
Employees who leave public employment in North Carolina must decide whether they will accept a LS or leave their pension account open in anticipation of a retirement annuity payable from the re- quired age for retirement benefits. The LS can be known with certain- ty; however, the present value of the annuity involves a more difficult calculation which should reflect personal discount rates, expected in- flation rates, and the likelihood of returning to public employment in North Carolina. In order to understand the choice between accepting a LS and leaving pension assets in the system, one must consider key parameters of the pension plan and how they affect the value of the LS that is available at separation versus the annuity expected in the future. Public sector workers in North Carolina are also covered by Social Security and Medicare.
Like most public retirement plans, both retirement systems in North Carolina (TSERS and LGERS) require employee contributions. The required employee contributions are equal to 6% of total annual salary and are deducted from paychecks every pay period. These con- tributions are deposited in the retirement funds of the two state sys- tems and help finance the benefits for retirees. In both North Carolina systems, vesting occurs when an employee completes five years of service.15 If workers leave public employment prior to being vested, their LS is simply the total of their own contributions to the system; in other words, non-vested separating workers do not receive any interest credited on these contributions and they do not receive any portion of the employer pension contributions. Workers leaving public employment with at least five years of service are offered a LS equal to the total of their own contributions during their employ- ment plus interest credited at 4% per year. As is typical of most state defined benefit plans, even once vested North Carolina public em- ployees who request a LS have no claim on the implied employer con- tributions to the retirement plan.
12 The Bureau of Labor Statistics (2011a) reports that only 4% of workers that were participating in defined benefit plans in the private sector were enrolled in plans that required an employee contribution. 13 According to Clark and Hanson (2011), only a few state retirement plans did not require workers to contribute a portion of their salary in support of the retirement plan. These plans include Arkansas PERS, Connecticut SERS, Florida FRS, Hawaii ERS, Michigan PSERS and SERS, Missouri MSEP, Tennessee CRS, and Utah SRS. In these noncontributory plans, non-vested terminated workers were not eligible to receive a future retirement annuity, nor were they eligible for a LS. The Bureau of Labor Statistics (2011a) reported that 79% of state and local workers that were participating in defined plans were enrolled in plans that require employee contributions with the mean con- tribution rate being 6.5% of earnings. 14 Clark and Hanson (2011) provide a detailed summary of the distribution choices available to teachers and state employees in all 50 states. 15 Legislation in 2011 raised the vesting requirement from five years of service to ten years for all newly hired teachers and state employees; however, in the sample we consider, all workers are covered by the five year vesting provision.
The value of the LS is equal to the total employee contributions (plus interested if vested) and can be calculated directly from the sal- ary history. Appendix A describes the calculation, which is a direct function of starting salary, wage growth, years of service, and the in- terest rate, but is independent of sex or age. Departing employees can learn the value of their LS by checking their account balances on-line or by directly contacting the retirement system. Thus, the value of one's LS can be known with certainty at the time of separation.
The retirement benefit is calculated in a similar fashion to that typically found in the private sector, using a benefit formula based on years of service and final average salary. The systems do not pro- vide an estimate of the present discounted value of the annuity (PDVA) to its members. Using the estimated benefit for each de- parting worker, we derive the present value of a future annuity for vested workers in the North Carolina TSERS or LGERS retirement sys- tem using the same assumptions employed by the retirement plans to calculate their pension liabilities. Details of this calculation are pro- vided in Appendix A. The PDVA is calculated assuming that the indi- vidual will begin receiving an unreduced benefit at age 65.16
To reiterate, the PDVA is not used by the plan to calculate the LS and this value is never provided to terminated workers. Instead, the PDVA variable represents our estimate using the same life tables used by plan actuaries to evaluate the financial status of the plan, along with real and nominal interest rates, described in Appendix A. Workers with higher personal discount rates will place a smaller value on the annuity, as will those that believe that they have lower life expectancies. The value of the annuity is increasing in salary level and the rate of salary growth, as well as number of years of ser- vice, similar to the LS. However, the PDVA is also an increasing func- tion of age at separation. In addition, because women's survival probabilities are higher than men's, women's PDVA will be (slightly) higher than men's with the same annual retirement benefit.17
A potentially important component of the retirement benefits for public workers in North Carolina is that the state will continue to pro- vide health insurance for retirees in the TSERS system at no premium, provided that they are receiving a retirement annuity.18 Benefits are also available for the spouses and dependents of retirees, with only an implicit subsidy.19 For retirees over age 65, Medicare is the prima- ry insurer and the state health plan (SHP) becomes the secondary in- surer. For eligible state employees and teachers, the value of health insurance should be included in the worker's decision whether to
the reduction factors imposed by the system for early retirement mean that this as- sumption does not substantially alter the expected present value of the annuity. In oth- er words, the reduction factors are, on average, approximately actuarially fair. 17 One could instead consider the size and terms of an annuity which could be pur- chased at the time of separation with the funds that are withdrawn. In the private an- nuity market, insurance companies will use similar interest rates to those we use in our calculations, but may also charge some commission and may adjust for adverse selec- tion (see, e.g., Mitchell et al., 1999). Because individuals could chose a variety of annu- ity products, we think framing the discussion in present value dollars using the assumptions adopted by the plan actuaries is a more straightforward comparison. 18 All states have some form of retiree health insurance for their employees; howev- er, the value of these plans differs markedly across the states, see Clark and Morrill (2010). 19 In North Carolina, spouses and dependents must pay the full price of the premium, as calculated based on prior years' expenditures, so we do not consider the value of spousal or dependent benefits. There is an implicit subsidy due to risk pooling. Ac- counting for this would obviously increase the estimated value of the health insurance option.
$5,000
$15,000
$25,000
$35,000
25 30 35 40
Age at Hire
Years of Service: 10
LS
PDVA
$5,000
$15,000
$25,000
$35,000
$45,000
$55,000
$65,000
$75,000
$85,000
$95,000
5 10 15 20
Years of Service
Hired at Age 30
LS
PDVA
Fig. 2. Simulation of relative values of lump sum distribution (LS) versus the present discounted value of the annuity (PDVA). Notes: The values are calculated for a hypo- thetical separating employee earning a starting salary of $30,000 per year with 3% wage growth. The top chart indicates the data points in dollar values calculated for a person with 10 years of service by the age of hire. The bottom chart indicates the data points in dollar values calculated for a person who was hired at age 30 by the number of years of service. The present discounted value of the annuity (PDVA) does not include the value of health insurance. Other simulation results (shown in Table 1) that vary the age of hire and years of service show a clear pattern that the lump sum distribution (LS) is greater relative to the PDVA for those hired at younger ages and with fewer years of service.
Table 1 Value of lump sum (LS) and present discounted value of annuity (PDVA) for a hypo- thetical worker.
Age at Hire
Age at Separation
Years of Service
LS PDVA
25 30 5 $10,741 $4,916 25 35 10 $25,521 $14,858 25 40 15 $45,485 $33,694 25 45 20 $72,074 $67,967 25 50 25 $107,089 $129,212
30 35 5 $10,741 $6,408 30 40 10 $25,521 $19,377 30 45 15 $45,485 $43,972 30 50 20 $72,074 $89,167
35 40 5 $10,741 $8,357 35 45 10 $25,521 $25,287 35 50 15 $45,485 $57,687
40 45 5 $10,741 $10,906 40 50 10 $25,521 $33,174
45 50 5 $10,741 $14,308
Notes: Values are for a hypothetical worker with a starting salary of $30,000 and wage growth of 3%. Calculations of the lump sum distribution value (LS) and present discounted value of the annuity (PDVA) are described in the text and in detail in Appendix A. The shaded boxes highlight the larger value between the LS and PDVA.
78 R.L. Clark et al. / Journal of Public Economics 116 (2014) 73–88
request a lump sum distribution. However, as discussed further below, it is difficult to know how much an individual worker values access to state-provided retiree health insurance. We describe our calculation of the present value of the health insurance option in Appendix A.
The literature on the “annuity puzzle” highlights a potentially im- portant role for health shocks (see, e.g., Brown, 2001). Individuals worried about unanticipated health care expenses may choose to keep assets liquid in order to have funds accessible in the event of a health shock. If a retiree does not have access to employer-provided health insurance, she may worry about the cost of health insurance coverage should an adverse health event occur. Retiree health insur- ance insures against this type of risk, and thus may be even more valuable to workers than the actuarially equivalent value.
4.3. Simulating the relative values of the annuity and lump sum distribution
As the above discussion indicates, the value of the LS depends on years of service but not on age at hire, while the PDVA is higher for those who are closer to the minimum required age of eligibility for retirement benefits. Thus, as employees accumulate years of service, the present value of the annuity will grow relative to the lump sum. The top portion of Fig. 2 illustrates this trend using a hypothetical male worker in the TSERS retirement system with a starting salary of $30,000 who experiences 3% wage growth per year. The values of the LS and PDVA are calculated for various ages of hire for a person with 10 years of service. The age where the two lines cross indicates the youngest age of hire at which the present value of the annuity exceeds the lump sum amount for a person with 10 years of service. The simulations indicate that for a separating employee with 10 years of service, workers hired at age 35 or older (thus age 45 or older at separation) have higher PDVA while workers hired before age 35 have higher LS values.
The bottom portion of Fig. 2 illustrates a similar pattern, this time varying the years of service. For a worker hired at age 30 with a starting salary of $30,000 and wage growth of 3%, the LS value will ex- ceed the PDVA until about 15 years of service, at which point the PDVA becomes relatively more valuable. Fig. 2 illustrates how age at hire and years of service affect the relative values of the LS and the PDVA; separating employees with fewer years of service or who are younger when hired are more likely to be facing LS values that exceed the PDVA values.
To get a more complete picture of how the various combinations of age at hire and years of service yield relative values of the two dis- tribution options, we calculated the LS and PDVA amounts for a hypo- thetical worker with starting salary of $30,000 per year and annual wage growth of 3%. Table 1 reports these simulated values for workers hired at various ages as their years of service increase from 5 to 25 years. The shaded boxes indicate the distributional option with the larger value for the indicated age/service combinations. One should note the years of service that must be completed before the PDVA overtakes the LS amount and how this crossing point varies by age of hire. For workers hired at age 25, the crossover point does not occur until after 20 years of service. At the other extreme, a work- er hired at age 40 should anticipate an annuity with a present discounted value that exceeds the LS by five years of service, when vesting begins.
These simple comparisons illustrate why it would not be surprising if a substantial proportion of terminated employees select the lump sum option. The LS will be greater than the present value of the annu- ity for many departing workers. This is in stark contrast to private sec- tor defined benefit plans which are required by law to price the LS to be at least equal to the present discounted value of the annuity. These relative values suggest that one should observe a considerable proportion of vested workers requesting a LS at termination.
It is important to recognize that if one were to add the estimated present value of health insurance (calculation described in Appendix A) to the discounted value of the annuity for participants in TSERS, the value of the (cash plus health insurance) annuity is larger than the LS for vested terminated workers throughout their career. Thus,
Table 2 Percent taking a lump sum distribution (LS) by vesting status.
Vested (5+ yrs) Not vested (b5 yrs)
N % LS N % LS
Full sample 11,368 32.36 35,545 35.29
Separation year Year: 2007 5619 34.95 17,836 38.34 Year: 2008 5749 29.83 17,709 32.22
Sex Men 3948 34.75 11,822 35.31 Women 6903 26.08 21,924 30.19 Unreported gender 517 98.07 1799 97.33
Total years of service (reported) Yrs service less than 1 11,839 28.46 Yrs service 1–3 16,606 37.84 Yrs service 4 2753 41.30 Yrs service 5–19 11,039 32.60 Yrs service 20–39 280 12.14
Age at separation (calculated) Age 18–24 17 29.41 5183 29.89 Age 25–34 3256 30.62 15,297 33.95 Age 35–49 7055 33.37 13,257 38.63
Retirement system LGERS 3644 40.45 11,023 40.82 TSERS 7724 28.55 24,522 32.80
Job classification (October 2007–December 2008 only)
Education professionals (excludes higher ed) (1) 2798 19.16 8690 23.27 Skilled labor (2) 772 47.28 2982 36.82 Professional, government, admin (3) 2076 35.69 6148 39.75 University, extension, and community college (4) 184 14.67 323 35.60 Public safety (5) 1148 45.21 3486 43.49 Health and social service professionals (6) 622 27.01 2226 33.38
Regression sample (non-missing salary and gender)
Regression sample 10,818 29.30 LS > PDVA 7977 29.55 LS ≤ PDVA 2841 28.62
Notes: The sample includes all separating employees ages 18–49 who are not eligible to start an immediate retirement annuity. The sample size varies across worker and plan characteristics due to missing values for some workers. Note that for the regression sample of vested workers, 550 observations were dropped because the present discounted value of the annuity (PDVA) could not be determined from the data due to missing gender and/or salary. We report the number of workers and the percent taking a lump sum distribution (LS) versus maintaining their account.
79R.L. Clark et al. / Journal of Public Economics 116 (2014) 73–88
for vested workers who are eligible for retiree health insurance when they start receiving their retirement annuity, the simple present value calculation would suggest that virtually all of these terminated em- ployees should maintain their funds with the state retirement plan. The value of retiree health is not very sensitive to age at separation due to the assumption that medical care costs are increasing at about the same rate as inflation, so the discounting effect on future health insurance is relatively small. For this calculation we assumed that workers retire at age 65 and do not claim retiree health insurance benefits until age 65, at which point they are eligible for Medicare as the primary insurer. If workers were to request an annuity and claim retiree health insurance earlier, the value of health insurance would obviously be larger, and we would predict even more individuals to choice the annuity option.
5. Separating public employees in North Carolina: 2007 and 2008
The state retirement system maintains records on current em- ployees, terminated workers, and retirees consistent with the data needed to calculate and pay retirement benefits to plan participants. The data presented here are from the State of North Carolina's retire- ment systems (TSERS and LGERS) and contain information on all workers who left public employment during 2007 and 2008. The data include the employee's date of birth, sex, salary, and the retire- ment plan. In addition, the status of the account is included indicating whether the retiree is currently receiving retirement benefits (and when the benefits were initiated), whether and when she took a lump sum distribution (LS), or whether she left the funds in the plan and the account remained active (the retirement system refers to these as “dormant” accounts).20
20 In 2007, the state adopted a new reporting system, ORBIT, that records much more detailed information about the workers' separations. Data from earlier years do not provide sufficient information to analyze economic factors that influence the distribu- tional choice.
Our sample includes workers who terminated employment in 2007 and 2008 and who did not retire and begin an annuity within one year of leaving the system. We restrict our attention to separating employees younger than 50 years old, in order to more closely ap- proximate a sample that is not eligible to immediately begin a pen- sion, even at a reduced level. Our sample includes 11,368 vested and 35,545 non-vested separating employees. Appendix B provides details on the data construction and how specific variables are de- fined, including vesting status and years of service.
To illustrate the distribution choices made by departing workers, Table 2 reports the number of vested and non-vested workers who left public employment in each year and the percent of each of the groups that accepted the LS within one year of separation. In the first column of Table 2, we see that about one-third of vested workers who left the retirement systems requested a LS within a year of termi- nation. The second column of Table 2 reports a similar breakdown for non-vested workers. These are individuals who, based on service to date, will not be eligible for a retirement annuity and will not receive any interest on funds left with the system. While one might have pre- dicted that nearly all non-vested terminated workers would select a LS, this is clearly not the case. Thus, it is important to attempt to ex- plain why individuals made a choice that, on its face, seems to be fi- nancially costly. The patterns of distributional decisions are reported separately for vested and non-vested workers for subgroups based on economic and demographic characteristics.
Several similarities are observed in the behavior of vested and non-vested workers reported in Table 2. Interestingly, roughly one- third of both groups, vested and non-vested, accepted the LS within one year of termination. Women in both groups were significantly less likely to withdraw funds. Older workers in both groups were more likely to request a LS and those with more years of service in the non-vested group were also more likely to withdraw their pen- sion funds, perhaps due to having a larger payment. All of the non-vested workers had relatively small account balances. For exam- ple, an individual that separated after three years of service whose
80 R.L. Clark et al. / Journal of Public Economics 116 (2014) 73–88
annual salary was $30,000 would have had approximately $5500 in his retirement account. Hence, there may be a threshold level that provides an incentive for workers to make a positive election for a LS, while those with only a few thousand dollars in their account may be less inclined to seek an immediate distribution.21 In contrast, among vested workers, those with the most years of service were the least likely to withdraw, which is not surprising given that the pen- sion system is most generous for longer tenure workers. This is also consistent with findings that private sector workers tend to be less likely to request a LS the larger the account balance. Vested and non-vested participants in the LGERS were more likely to desire a cash distribution than those in the TSERS system. As described above, workers in TSERS are covered by the state health plan (SHP) and are eligible for free retiree health insurance, but only if they are currently receiving a retirement annuity from TSERS.
There are interesting differences in the desire for a LS across em- ployment groups. The administrative records sort individuals by broad job classifications. Teachers and other educational profes- sionals were much less likely to request a LS compared to other groups, with only about 20% having cashed out their pension ac- counts. On the other hand, skilled labor and public safety officers are among the most likely to have withdrawn.
For each of the individuals in our data, the exact value of the LS that they could have received at the time of separation is reported. For those that have non-missing salary and sex information, we use the assumptions described above to calculate an estimated present discounted value of the retirement annuity (PDVA) for vested partic- ipants. The value of the LS for each worker is then compared to our estimate of the PDVA. The bottom rows of Table 2 show that, of the 10,818 vested terminated workers for whom we can calculate the PDVA, the LS exceeds the PDVA for 7977 individuals (73.7% of all vest- ed terminations).22 Surprisingly, only about one third of separating workers in both groups (those where the LS exceeds the PDVA and those where the LS is less than the PDVA) requested a LS within one year of termination. This suggests that the relative value of the two distribution options did not strongly influence the choice made by separating employees.23
6. Distributional decisions of vested workers
Next, we conduct a multivariate regression analysis of the choice to withdraw funds and accept a lump sum distribution (LS) within one year of separation for vested workers. Theoretically, this assumes that the decision to leave is made and then the individual considers what to do with his retirement accounts. Access to a LS option and the size of account balance may influence a worker's decision to leave government employment; however, we do not model this relationship.
Earlier discussion has shown that we should anticipate differences in distributional choices based on certain personal and plan charac- teristics for two reasons. First, as the simulations reported in Section 4.3 demonstrate, the relative values of the distribution op- tions are a function of a worker's age at hire, years of service, sex, and salary. Given differences in the two pension plans, one might
21 See Benartzi et al., 2011, for a discussion of threshold levels from behavioral economics. 22 Remember that this measure of PDVA includes only the value of the cash retire- ment benefit and does not include the estimated value of having access to the subsi- dized retiree health insurance. When this value is included, practically all vested workers have a higher PDVA compared to their account balance. 23 Butler and Teppa (2007) describe a traditional measure of an annuity's value as its Money's Worth Ratio (MWR), which is the ratio of the present discounted value of the annuity payments and the initial cost. The MWR is then determined to be equal to one if the annuity is well-priced, with the difference usually attributed to adverse selection and administrative costs. In our formulation, the PDVA equal to the LS would be theo- retically equivalent to a MWR of one.
also anticipate that distributional decisions will vary by participation in TSERS or LGERS. Second, previous research has shown that the choice to annuitize, holding constant the relative generosity of the distribution options, varies by sex, age, and the size of the pension account.
We seek to determine whether the choice to withdraw funds is due to underlying demographic characteristics affecting desire to annuitize, or to plan parameters affecting the relative generosity of the distribution options. We attempt to measure these two avenues by including both demographic controls (to the extent available in the data), as well as the size of the LS and our approximation of the present discounted value of the annuity (PDVA). Not only are some of the variables closely related, but the size of the LS and PDVA are both functions of salary and years of service, and age is an important determinant of the PDVA through its discounting effect (i.e., the same annual retirement benefit starting at age 65 has a higher present value for those age 45 compare to those age 35). The annual retire- ment benefit is exactly determined by annual salary and years of ser- vice, and the present value of this benefit is based on the assumed interest rate and age of the employee at termination. Thus, one should be concerned about the inclusion of age, years of service, sal- ary, the value of the LS and the PDVA in the same specification, and we should expect that the estimated coefficients will be sensitive to the inclusion of all of these variables in the same specification.
With these caveats in mind, Table 3 presents coefficients estimat- ed from a linear probability model of the decision to withdraw funds within one year of separation (request a LS) among workers who were vested in the retirement plan.24 We estimate the LS decision as a function of the value of the LS (the worker's account balance at separation), the calculated PDVA, and an indicator for whether the value of the LS exceeds the PDVA. We also include a separate inter- cept by year of termination to account for differences in economic conditions between 2007 and 2008. In columns (2) through (5), we incrementally add variables controlling for gender, state or local re- tirement plan (TSERS versus LGERS), a quadratic in final average sal- ary, a quadratic in age at separation, a quadratic in years of service to observe how these variables affect the estimated coefficients on the values of the LS and PDVA.
First, we observe that the value of the LS, which is equal to the em- ployee contributions (6% of salary) plus interest, has a quadratic rela- tionship whereby workers with larger values are less likely to request a LS until the account balances reaches approximately $73,000. Simi- larly, the estimate of the PDVA has a nonlinear effect on the distribu- tional decision with greater values increasing the likelihood of selecting a LS up to about $93,000 and larger values reducing the probability of requesting a LS. The final variable in column (1) is an indicator variable for having an account balance (value of the LS) larger than the approximated PDVA. The estimated coefficient indi- cates that having a LS that is larger than the PDVA is associated with a 5.4 percentage point higher probability of requesting a LS. This is consistent with expectations, although, as discussed further below, the effect disappears when age at separation is added in Col- umn (4). The estimates indicate that workers separating in 2008 were about 2 percentage points more likely to request a LS than those who terminated in 2007, and this difference becomes slightly larger once additional covariates are added to the model.
Columns (2) through (5) of Table 3 sequentially add covariates to the model. First, in Column (2), we see that men were 10 percentage points more likely to request the LS than were women who terminat- ed employment. This is consistent with women being more likely to accept defaults. Terminated workers in TSERS were approximately 10 percentage points less likely to request a LS compared to
24 The coefficients reported in Tables 3, 4, and 5 were estimated using linear probabil- ity models. Marginal effects from probit models are nearly identical and are available from the authors upon request.
Table 3 Withdrawal decisions of vested workers.
Mean/percent (1) (2) (3) (4) (5)
Value of the LS (10 K) $2.02 −0.188** −0.209** −0.193** −0.217** −0.236** (0.018) (0.018) (0.018) (0.019) (0.024)
Value of the LS (10 K)2 0.013** 0.014** 0.012** 0.013** 0.017** (0.002) (0.002) (0.002) (0.002) (0.003)
PDVA (10 K) $1.75 0.093** 0.100** 0.108** 0.136** 0.162** (0.013) (0.013) (0.013) (0.015) (0.016)
PDVA (10 K)2 −0.005** −0.005** −0.005** −0.006** −0.007** (0.001) (0.001) (0.001) (0.001) (0.001)
LS > PDVA 73.7% 0.054** 0.050** 0.061** −0.017 −0.009 (0.015) (0.015) (0.015) (0.018) (0.018)
Male 36.4% 0.101** 0.104** 0.115** 0.119** (0.009) (0.009) (0.009) (0.009)
TSERS 68.3% −0.104** −0.105** −0.099** −0.097** (0.009) (0.009) (0.009) (0.009)
Final average salary (10 K) $3.36 −0.027** −0.045** −0.053** (0.008) (0.009) (0.012)
Final average salary (10 K)2 0.001 0.002* 0.001* (0.001) (0.001) (0.001)
Age at separation 38.47 0.082** 0.075** (0.010) (0.010)
Age at separation2/100 −0.115** −0.107** (0.013) (0.013)
Years of service 9.01 0.024** (0.006)
Years of service2 −0.001** (0.0002)
Separated in 2008 52.9% 0.018* 0.025** 0.026** 0.027** 0.027** (0.009) (0.009) (0.009) (0.009) (0.009)
Constant 0.418** 0.477** 0.511** −0.809** −0.742** (0.017) (0.018) (0.021) (0.171) (0.171)
Notes: The sample is all workers ages 18–49 that terminated employment in 2007 and 2008 and who were vested with valid entries for the above covariates, N = 10,818. For more information on the sample for this table, see Table 2 and Appendix B. The dependent variable is the decision to withdraw the account balance and take a lump sum distribution (LS) within one year of separation versus maintaining the account (leaving it open with the possibility of electing for an annuity once eligible), approximately 29.3% of the sample requests a LS. The (LS > PDVA) is an indicator for whether the value of the LS is greater than the calculated present discounted value of the annuity (PDVA). Coefficients are esti- mated from a linear probability model with standard errors in parentheses. *Significant at 5%; ** significant at 1%.
81R.L. Clark et al. / Journal of Public Economics 116 (2014) 73–88
comparable workers leaving LGERS, which is expected given the po- tential value of retiree health insurance for workers covered by TSERS. Introducing these two variables has virtually no effect on the estimated coefficients in the specification shown in Column (1).
In Column (3), we observe that the final average salary (i.e., the average salary over the past four full years of employment) has a u-shaped relationship with the probability of requesting a LS. The ef- fect is negative up until a salary of over $112,500 (depending on the specification) and then for higher salaries becomes positive. Adding the salary variable also has little effect on the other coefficients. Col- umns (4) and (5) report the estimates when age at separation and years of service are added to the model. Age has an inverted u-shaped relationship with distributional choice, where the youngest and oldest workers are least likely to choose a LS. Depending on the specification, the effect of age on the probability of receiving a LS is positive but declining up until the worker reaches approximately age 35 after which age has a negative effect on accepting a LS. One possible explanation for this pattern is that older workers are closer to being able to start a retirement annuity, so experience less discounting due to having to wait to claim the benefit. It may also re- flect a greater confidence by older workers that retirement benefits will not be reduced for them or greater salience of the need for retire- ment income among workers nearer to retirement. Note that adding a quadratic polynomial in age to the regression reduces the estimated impact of having a larger value of the LS than the PDVA from being positive and significant to being negative and insignificant.
The relative size of the LS and PDVA is highly correlated with age, as illustrated in the simulations reported in Table 1 and shown in Fig. 2. The annuity value is discounted back to the current age, so those who are closer to retirement have less discounting. Meanwhile, the LS is not a function of age, so older individuals are more likely to have higher PDVA than LS relative to younger individuals. We see this
in the data where, for example, among workers age 45 and older at separation only 11% have larger LS's than PDVA's, while almost 90% of workers less than age 45 have a higher value of their LS than PDVA. It is therefore difficult to separately identify the effects of age and the relative value of the LS and PDVA.
In the final column of Table 3, we see that adding a quadratic in years of service leaves the other estimates basically unchanged. Hold- ing all else constant, including the values of LS, PDVA, and age, workers are more likely to withdraw with more years of service up to 12 years of service, at which point longer tenures are associated with a reduction in the probability of accepting a LS. In general, the observed relationships between both demographic characteristics and work history and the probability of withdrawing funds conform to expectations. We next propose several reasons why workers might not be highly responsive to the relative size of the LS and PDVA.
7. Potential explanations for the observed distributional decisions
We postulate four main hypotheses on why the relative size of the lump sum distribution (LS) and the present discounted value of the annuity (PDVA) might not affect the distributional choice in the man- ner initially expected: (1) the potential of subsidized health insurance in retirement if one selects an annuity, (2) the likelihood of returning to work and continuing to build years of service, (3) economic condi- tions and alternative investment opportunities, and (4) inertia, inad- equate financial literacy, peer effects, and the lack of knowledge about the choices and their relative value. We now consider each of these relationships and their potential effect on the distributional choices of terminated vested workers. A discussion of how these fac- tors might influence non-vested workers follows in Section 8.
The calculation of the PDVA makes a series of assumptions includ- ing a personal discount rate and a life expectancy from an actuarial
82 R.L. Clark et al. / Journal of Public Economics 116 (2014) 73–88
life table. In addition, we are assuming that individuals are risk neutral. In this context, risk neutrality is a benign assumption, since technically a worker could withdraw funds and immediately roll them over into an- other tax qualified account. Because workers that request a LS have the option of rolling funds over into another tax qualified account without paying a penalty, or may withdraw funds but still save for retirement using other means, attitudes towards risk cannot explain choices in this particular context. An individual that has a higher personal discount rate or a lower life expectancy would value the annuity less than our calculation and would be more likely to take a LS. Similarly, separating workers that have a bequest motive would be more likely to withdraw funds. These and other personal characteristics have been proposed in the literature to explain the annuity puzzle that people do not purchase annuities, but do little to explain our results.25
7.1. Access to subsidized health insurance in retirement
The present value of the retirement annuity in the regression anal- ysis was based solely on the cash benefit one could expect to receive in retirement. However, as described above, vested employees in the TSERS (teachers and state government workers) system who leave their pension account open and ultimately receive a retirement ben- efit are also eligible to participate in the state health plan (SHP) once they begin receiving the pension. The state will pay 100% of the health insurance premium for these former employees.26 Persons who accepted the lump sum are not eligible for participation in the state health plan in the future.
Appendix A provides a calculation of the present discounted value of health insurance beginning when the retirement annuity starts and ending with death. Health insurance is a relatively valuable benefit, and according to our calculations described in Section 4.3, those who anticipate taking advantage of this benefit would see the PDVA plus the present value of the health insurance exceed the LS amount regard- less of years of service and/or age at hire. To give a sense of the magni- tude of the health insurance benefit relative to the annuity in the data, we estimate that the present discounted value of health insurance for our sample is between $37,225 and $47,854, depending on the individ- uals' age at separation and sex.27 We find that all but ten vested separat- ing workers have smaller LS's when compared to the combined value of the PDVA and health insurance benefit. When considering the choices of workers covered by retiree health insurance, it is much less surprising that only 29% choose to withdraw funds within one year of separation.
Of course, this assessment of the relative value of the distribution- al options assumes that the departing worker believes that the benefit will still be provided by the time she retires and that she intends to claim the health insurance benefit. The cost and liabilities associated with state retiree health plans have been critically examined since new reporting standards were required by the Governmental Accounting Standards Board (Pew Center on the States, 2011; Clark
25 Brown (2001) discusses the annuity puzzle in detail in a similar context for private sector workers. He surveys the empirical work on this issue and develops a concept of annuity equivalent wealth variable to partially explain decisions to annuitize wealth in defined contribution retirement plans. 26 In 2011, the North Carolina General Assembly passed legislation that for the first time required a premium to be paid by active and retired workers for the Standard Plan offered by the state; however, workers and retirees still had access to the Basic Plan without having to pay a premium (Clark and Morrill, 2011). 27 To the extent that some vested workers will start their retirement annuity prior to age 65, the value of retiree health insurance is underestimated, perhaps by a consider- able amount. Individuals who are receiving a retirement annuity are covered by the state health plan regardless of age or whether the person is receiving a normal retire- ment benefit or one reduced due to age and service. For example, a worker who was hired at 25 and left state employment at age 45 could select to begin a reduced retire- ment benefit at age 50, she would also be eligible to participate in the state health plan at no premium. The subsidy for the health insurance does not vary with age at which the individual retires. As noted earlier, the value of the pension benefit is actuarially re- duced to reflect earlier retirement ages; but as we see here, the present value of the health insurance would be much higher for those who accept benefits prior to age 65.
and Morrill, 2010). The unfunded liabilities have been widely reported in the popular press, and many states (including North Carolina) have been modifying the terms of these plans. Thus, it would not be surprising if public employees doubted that the current- ly promised benefits will still be provided in 10 or 20 years. Reflecting this concern, terminated workers may further discount the value of future health insurance in retirement provided by the state. In addi- tion, some workers may have access to health insurance through spousal coverage, so they might not value this benefit as much.
7.2. Potential for returning to work and the distributional choice
If terminated workers anticipate that they may return to public employment in North Carolina, they may wish to keep their accounts open. Terminated workers who return to public employment will re- tain their service based on previous public employment provided they kept their accounts open and do not take a LS. Thus, an employee who temporarily leaves her job due to medical or family reasons with the intent of returning to public employment within a few years may find it convenient and cost-effective to leave her account open. More- over workers who accept the LS can “purchase back” their prior years of service at a price specified by the plan.
To explore this question, we consider all workers who left the re- tirement systems in 2007 and 2008 and observe whether they had returned to public employment by the end of 2009. Surprisingly, a greater proportion of those who returned to public employment had accepted a LS. Among those that returned to employment, 44% of the vested and 48% of the non-vested terminators had selected a LS. In contrast, only about one-third of both vested and non-vested employees who had not returned to public employment chose a LS. It should be emphasized that our time period for return to work is only one to two years, so the impact could be substantially different if we had data over a longer time period.
7.3. Economic conditions and alternative investment options
Accepting a LS gives terminated employees access to retirement funds that can be either rolled over into another tax qualified account, invested in a non-retirement account, or spent on consumption. A ter- minated worker can request a LS at any time after leaving public em- ployment up until she actually starts a retirement annuity. For vested individuals, the account balance continues to increase each year by a plan-specified interest rate of 4%. Thus, a well-informed individual could view leaving her retirement account open as an investment op- tion. In other words, she could request a LS and invest the money her- self or leave the money with the state plans and earn a guaranteed return of 4%.28 Given the uncertainty in the financial markets during this period, a guaranteed return of 4% may have been an attractive in- vestment. Data provided by the retirement system suggests that most LS's occur relatively close to the date of termination.29 A longer time series on when terminated workers requested a LS would provide bet- ter insight into this issue.30
28 The account balance is not adjusted for inflation. 29 In 2010, 12,501 terminated workers accepted a LS. Of these 8473 individuals re- ceived the distribution within one year of termination, another 1234 had been gone for between one and two years, and another 1677 requested a LS between two and five years after leaving the retirement systems. Thus, 91% of all LS's paid in 2010 were to individuals who left public employment within the last five years. 30 An interesting thought experiment is to consider a hypothetical pension plan with all the characteristics of the North Carolina plan except that there is no annuity benefit. This simplifies the distributional choice to taking an immediate LS or leaving the account open and take the LS at some future date with the account balance increasing by 4% per year. If we could observe individuals covered by such a plan, it would be interesting to know the distribution of when workers accepted a LS. In essence, this becomes a portfolio choice with the pension serving as a guaranteed value fund with a 4% return. Depending on per- sonal characteristics and the size of the pension account, we would probably observe some variation in the time since termination that the LS is requested.
4 5
6 7
8
U n e m
p lo
ym e n t R
a te
-4 0
-2 0
0 2 0
S &
P 5
0 0 E
st im
a te
d R
e tu
rn
.2 .2
5 .3
.3 5
.4 .4
5
F ra
ct io
n W
ith d ra
w
2007m1 2007m7 2008m1 2008m7 2009m1
Year and Month of Separation
Fraction Withdrawing S&P 500
Unemployment Rate
Fig. 3. Fraction withdrawing funds, alternative investment options, and local economic conditions.
83R.L. Clark et al. / Journal of Public Economics 116 (2014) 73–88
To the extent possible given the short time period over which our data span, we can consider the manner in which distributional deci- sions are influenced by outside investment opportunities. In Fig. 3, we plot the fraction of workers that withdraw funds within a year by the month of separation. We see that the probability of withdraw- ing funds drops fairly steadily over the two year period from January 2007 through December 2008. On this same graph, we plot the 12-month return in the S&P 500, which follows a similar pattern.31
However, one must recognize that returns to such investments are correlated with many other macro-level variables, such as the state unemployment rate, which may affect the need for immediate access to funds. Indeed, when adding a plot of the North Carolina state un- employment rate to Fig. 3, we see that the trends mirror those of the S&P 500.32 We expect that job market opportunities, the need for liquidity, and the opportunity costs of investments will all influ- ence an individual's choice of withdrawing funds. Note that over this same time period the 1-year Treasury bond rate reached a high of 5.06% and a low of 0.49%.33 We did not include this plot in Fig. 3 for simplicity, but the decline in the Treasury bond return rate closely tracks the other trends in the figure and is included in the regression analysis below.
In addition to this investment effect, adverse economic conditions may affect employees' confidence in the retirement system and their perception of the state's willingness and ability to honor future retire- ment payments. Over the past few years, the popular press has in- cluded many front page stories about the financial problems facing public pension plans, including the rising cost of providing these ben- efits and low funding ratios. North Carolina has one of the best funded public pension plans in the U.S. Analyzing 2009 pension data from the
31 The S&P 500 rate of return was calculated by comparing the adjusted close in the month prior to separation to that 12 months prior, so that the return for those separat- ing in December of 2007 was equal to the difference in the adjusted close in November 2007 and November 2006, divided by the adjusted close in November 2006. These data were downloaded from the http://finance.yahoo.com/q/hp?s=%5EGSPC+ Historical+Prices, [accessed February 8, 2013]. 32 The North Carolina monthly unemployment rate is from the Bureau of Labor Statis- tics, Local Unemployment Rate Series, LAUST37000003, available at http://data.bls. gov/timeseries/LAUST37000003, [accessed February 6, 2013]. 33 The 1-Year Treasury Constant Maturity Rate (GS1) data were obtained from http:// research.stlouisfed.org/fred2, [accessed February 4, 2013].
Comprehensive Annual Financial Reports of the states, the Pew Center on the States (2011) ranks North Carolina as the fourth best funded state retirement plan, with a funding ratio of 97%.34 Still, many states have been making major changes in their retirement plans. In most states, changes will apply only to new employees. However, some states whose plans are facing substantial funding problems have been altering the benefits for current workers and re- ducing COLAs for current retirees. In this environment, terminated workers in North Carolina might have questioned whether their pen- sion plans would remain unchanged for 10, 20 or 30 years. Doubts about the stability of the plans may have led some separated workers to be more likely to request a LS.
Because these factors tend to move together, it is difficult to disen- tangle the independent effects of each. Still, we explore these rela- tionships further in a regression context in Table 4, Columns 1–5. Using the specification in Column 5 of Table 3, we include the 1-year US Treasury bond rate, the 12-month prior return to the S&P 500, and the monthly unemployment rate.35 We also present a spec- ification where we drop the indicator variable for the year 2008 to allow for the full variation in these trends to be utilized.36 In Table 4, Column 1, we see that when entered individually into the specification, the estimated coefficient for the 1-year Treasury bond rate is negative and insignificant. In contrast, in Column 2, the esti- mated coefficient on the gain in equity values is positive and signifi- cant, indicating that a higher growth in equity values increases the likelihood of accepting a LS. Interestingly, as seen in Column 3, a 1% higher state unemployment rate in the month of termination is asso- ciated with a 3 percentage point decline in the probability of with- drawing funds. This could reflect a difference in who is terminating employment in a given month, or it could indicate that when job
34 While most economists believe that the assumed rates of return in these reports are too high, the relative ranking of the North Carolina retirement system as one of the best funded retirement plans does not change when lower rates of return are employed (Novy-Marx and Rauh, 2011). 35 These parameters are defined in footnotes 31–33. 36 Each of the investment opportunity/macroeconomic indicator variables are mea- sured at the month of termination, although the dependent variable is whether funds were withdrawn within a year of separation. While one could conceive of a model where the cumulative effects of these factors are accounted for, with only two years of data estimating such a model is not practical.
Table 4 Economic conditions, peers, and the withdrawal decisions of vested workers.
Mean (1) (2) (3) (4) (5) (6)
Investment opportunities 1-year treasury bond constant maturity rate 3.1 −0.003 (0.007) −0.017 (0.011) −0.031** (0.001) S&P 500 12 month return −1.3 0.001* (0.0005) −0.0001 (0.001) 0.0004 (0.001)
NC economic conditions State unemployment rate 5.63 −0.030** (0.007) −0.038** (0.014) −0.029* (0.013)
Actions of peers Fraction in 3-digit zip 0.302 0.288** (0.079) Fraction in agency 0.301 0.458** (0.033)
Selected covariates LS > PDVA 0.737 −0.009 (0.018) −0.009 (0.018) −0.010 (0.018) −0.011 (0.018) −0.011 (0.018) −0.010 (0.018) Separated in 2008 0.529 0.019 (0.021) 0.061** (0.016) 0.075** (0.015) 0.040 (0.023) 0.029** (0.008)
Notes: The sample and specification are identical to Table 3, Column (5) with the inclusion of investment opportunities, local economic conditions, and peer behavior, as indicated. Column (5) includes dummy variables for living in a zip code or separating from an agency with fewer than 5 peers in the sample. Coefficients are estimated from a linear probability model with standard errors in parentheses. *Significant at 5%; ** significant at 1%.
84 R.L. Clark et al. / Journal of Public Economics 116 (2014) 73–88
opportunities are fewer then demand for LS fall. This finding does suggest that liquidity constraints are not that important to this deci- sion, since we would expect cash needs to rise when the unemploy- ment rate is higher. In Column 4 of Table 4, we include all three variables in the same specification and find that only the state unem- ployment rate has a significant effect. However, when we do not in- clude the year 2008 dummy variable in Column 5 we see that the estimated coefficient on the 1-year Treasury bond rate becomes larg- er and is statistically significantly negative.37
Although our data only span two years, there is quite a bit of monthly variation in these trends. However, to truly understand the effects of investment options and economic conditions would require a much longer time series and a richer variety of economic and investing environments. Still, the results presented in Column 5 are not consistent with an investment opportunity cost story, where indi- viduals are more likely to take money out when investment opportu- nities are good. Nor are the results consistent with a story about liquidity or the need for cash during an economic downturn. Similar- ly, if confidence in the system is correlated with economic conditions, we again do not see evidence that as “confidence” falls, withdrawals rise. One alternative explanation is that when economic conditions are uncertain, then individuals do not make financial decisions and are more reliant on defaults.
7.4. Financial literacy, plan knowledge, peer effects, and inertia
Considerable survey evidence indicates that workers have a low level of financial literacy, inadequate knowledge about their pension plans, and poor understanding of how choices can affect the value of retirement accounts (Lusardi and Mitchell, 2007; Clark et al., 2012). If workers who leave the North Carolina retirement system possess the same low levels of knowledge, it should not be surprising that they do not always select the option that has the greatest present value. While information about the size of the LS is easily available, separating workers may not be able to determine the value of the re- tirement annuity. Calculating the present value of an annuity 20 or even 30 years in the future is not a simple task, even for individuals who have high levels of financial literacy.
The default option is to maintain the retirement account until the terminated worker either requests a LS or, once eligible, a retirement benefit. There were no changes in the default during our sample peri- od and thus, we are not able to investigate how changes in the default might have altered the distributional choices of departing workers.
37 In a related context, Goda et al. (2012) consider how retirement intentions are influenced by investment returns in the year prior to survey for respondents in the Health and Retirement Study (HRS). They also document that the collinearity of stock returns and labor (and housing) market conditions makes separately identifying the effects difficult.
However, recent research has shown that defaults matter in the selection of various pension options and inertia associated with the acceptance of defaults could also be affecting the distributional choices (e.g., Madrian and Shea, 2001). Brown et al. (2008b) described an important role for framing. If workers accept defaults due to inertia or lack of understanding, or are not appropriately valuing benefits, then public employers could improve separating workers' welfare by providing timely and accessible financial education and information.
The retirement system sends all separated employees who request a LS a personalized form letter (shown in Appendix C), regardless of their vesting status or the relative size of their benefits. The letter contains a warning that if the refund is processed the individual will forfeit a future annuity benefit. A separating worker who is not confi- dent in his/her choice may be swayed by the strong wording in this letter. We do not know how many individuals first applied but then ultimately chose not to withdraw funds after having received this letter.
Workers who are unsure about their distributional decisions may rely on their colleagues or neighbors for advice (Brown et al., 2008a). We investigate the importance of peer effects by adding two variables to the specification in Column 6, Table 3: the fraction of terminating participants who live in the same 3-digit zip code who selected a LS and the fraction of terminating participants who worked in the same agency who chose a LS.38 Both of these variables are positively and significantly related to the probability of selecting a LS. This is consistent with peer effects influence distributional decisions. However, as described in Manski (1993), the estimated coefficients may instead reflect the fact that peers share similar (unobservable) characteristics and so their choices may be correlated. Although we find that individuals behave similarly to their peers, this is not neces- sarily a causal effect.
8. Distributional choices of non-vested workers
Workers leaving public employment with fewer than five years of service are not vested according to the rules of both retirement plans (TSERS and LGERS), so they are not eligible for a retirement annuity based on service at the time of termination. Accordingly, the lump sum distribution (LS) available to them is the sum of their own pension contributions during their employment without any interest. Nevertheless, they are not required to immediately request a LS and the default is to maintain the account with the system. Given the choice of money now or the same amount of money at some future date, we would expect that all non-vested terminated workers would request immediate LS's. Yet, Table 2 shows that only about one-third of these
38 These variables are defined by taking the average across all workers within the cell, excluding the individual.
Table 5 Withdrawal decisions of non-vested workers.
Mean/percent (1) (2) (3) (4)
Value of the LS (1 K) $3.15(K) 0.030** 0.029** 0.028** 0.022** (0.001) (0.001) (0.001) (0.002)
Value of the LS (1 K)2 −0.001** −0.001** −0.001** −0.001** (0.000) (0.000) (0.000) (0.000)
Male 33.3% 0.043** 0.045** 0.047** (0.005) (0.005) (0.005)
TSERS 69.0% −0.062** −0.061** −0.064** (0.005) (0.005) (0.005)
Age at separation 33.3 0.016** 0.017** (0.003) (0.003)
Age at separation2 −0.019** −0.019** (0.004) (0.004)
0–0.99 Years of service 33.3% −0.053** (0.010)
1–1.99 years of service 28.2% 0.009 (0.008)
3–3.99 years of service 12.2% −0.019* (0.009)
4–4.99 years of service 7.8% −0.025* (0.012)
Separated in 2008 49.8% −0.067** −0.003 −0.003 −0.002 (0.005) (0.005) (0.005) (0.005)
Constant 0.311** 0.277** −0.049 −0.023 (0.005) (0.006) (0.050) (0.051)
Notes: The sample is all workers ages 18–49 that terminated employment in 2007 and 2008 and who were not vested (less than five years of membership plus non-contributory service) with valid entries for the above covariates, N = 35,545. For more information on the sample for this table, see Table 2 and Appendix B. The dependent variable is the de- cision to withdraw the account balance and take a lump sum distribution (LS) within one year of separation; approximately 35.29% chose this option. The omitted category is 2– 2.99 years of service. Also included in the specifications in Columns (2)–(4), but not reported, is a dummy variable for gender unknown (5.1% of the sample). Coefficients are es- timated from a linear probability model with standard errors in parentheses. *Significant at 5%; ** significant at 1%.
85R.L. Clark et al. / Journal of Public Economics 116 (2014) 73–88
former public employees requested a LS in the first year following termination.39
At first glance, this is quite puzzling. Unlike the vested workers, non-vested terminated employees cannot look forward to a retire- ment annuity, will not be eligible for state-provided retiree health insurance, and do not earn interest on the money left with the retire- ment system. But workers with short service may have paid very little attention to their pension accounts, and upon termination, may be un- aware of the value of their accounts and the distributional options available to them. Inertia is often given as an explanation of certain types of behavior and could also be a factor in lack of immediate LS's.40
Still, there may be a fully rational reason for a separating employee to leave the monies in the system, even if not vested. Employees who leave public employment but who anticipate returning to a govern- ment job may have an economic incentive to leave their pension ac- counts open, as returning civil servants who have not closed their pension accounts can count prior years of service in the determina- tion of future retirement benefits. If this motive explains the distribu- tional choices of non-vested employees, it would indicate rational decision making based on considerable knowledge of the pension plan. Family circumstances, such as the birth of a child or relocation, can also result in individuals quitting current employment and having temporary periods outside the labor force. The public sector is rela- tively large and all public employees are covered by the same system, offering considerable opportunities for future employment in either TSERS or LGERS. Nevertheless, the analysis of 2007–2008 termina- tions described in Section 7.2 does not support the hypothesis that
39 Using a longer time series, it would be interesting to discover whether these indi- viduals ever return to public employment in North Carolina and ultimately become vested in the retirement plan, whether they ever request a LS, or whether these funds are permanently lost to the individual. 40 Interestingly, inertia may be overcome by certain events. The state retirement sys- tem reports that requests for lump sum distributions from previously terminated workers often spike just before Christmas.
expectations of returning to work is a cause of keeping one's account open since a larger proportion of those that returned to work had ac- cepted a LS than those that had not yet returned to work.
To further examine the distributional choices of non-vested em- ployees, we estimated a linear probability model with the dependent variable being an indicator for whether separating workers chose to withdraw their accounts and accept the LS's from the retirement plan within one year of terminating employment. The results of this regression are presented in Table 5. We first consider how the value of the possible LS (the account balance) influences the choice of with- drawing funds. This relationship is shown to be quadratic, whereby the probability of withdrawing is increasing until the value of the ac- count reaches approximately $15,000, at which point the relationship becomes negative. Since none of these workers is eligible for an annu- ity, it is somewhat surprising that we observe this pattern, although it may be due to the possibility of returning to work in the future.
In Table 5, Column 2, we observe that men were more likely to withdraw money. This could be due to less inertia or more knowledge among men. As was the case for vested employees, members of TSERS were significantly less likely to accept a LS than those in LGERS. Again, consistent with the patterns for vested workers, the youngest and oldest non-vested separating workers were least likely to withdraw funds, with the highest probability of withdrawing around age 42. As discussed earlier, this might be due to lack of knowledge or be- cause of a higher likelihood to return to work among the youngest workers. In the final column of Table 5, we observe that controlling for years of service diminishes the coefficient on the account balance at separation somewhat. Here the omitted category is 2–2.99 years of service and we observe that among non-vested workers those with approximately 1–2.99 years of service are the most likely to with- draw. We observe across the columns of Table 4 that the importance of the size of the LS is only partially explained by observed work his- tory and demographics, and the basic pattern suggests that those with the smallest and largest potential LS values are the least likely to withdraw within one year of separation.
41 In addition, the retirement annuity from the state plan is approximately a real an- nuity with benefits typically being increased each year by the legislature at a rate near the level of inflation. In contrast, the annuity that one could purchase in the market un- der these assumptions would be a nominal annuity.
Table 6 The decision to cash out versus rollover benefits among vested and non-vested workers accepting a lump sum distribution (LS).
Full sample (88.7% cash out) Vested (87.3% cash out) Non-vested (89.1% cash out)
(1) (2) (3)
Mean Coeff. Mean Coeff. Mean Coeff.
Value of the LS (10 K) 0.66 −0.238** 1.75 −0.141** 0.35 −0.487** (0.013) (0.036) (0.029)
Value of the LS (10 K)2 0.020** 0.007* 0.075** (0.002) (0.003) (0.012)
Final average salary (10 K) 3.12 −0.008 (0.018)
Final average salary (10 K)2 0.002 (0.001)
Vested 22.7% 0.074** (0.011)
Male 34.2% 0.031** 43.3% 0.027* 33.3% 0.033** (0.005) (0.012) (0.006)
Unreported gender 13.9% 0.030** 14.0% 0.033** (0.008) (0.009)
TSERS 63.2% −0.017** 60.0% −0.007 64.1% −0.020** (0.005) (0.012) (0.006)
Age at separation 34.9 0.009** 38.4 0.008 34.0 0.010** (0.003) (0.012) (0.003)
Age at separation2/100 −0.010* −0.009 −0.012* (0.004) (0.015) (0.005)
Years of service 3.42 0.024** 8.48 0.014 1.95 0.047** (0.004) (0.011) (0.010)
Years of Service2 −0.0004 0.0001 0.002 (0.0002) (0.0004) (0.002)
Separated in 2008 45.7% 0.024** 54.0% 0.029* 45.5% 0.026** (0.005) (0.012) (0.006)
Constant 0.744** 0.783** 0.734** (0.055) (0.221) (0.060)
Observations 16,213 3,167 12,7537
Notes: The samples include only those separating workers who take a lump sum distribution (LS). For more information on the sample for this table, see Table 2 and Appendix B. Note that in Column (2) only workers whose final average salary could be calculated are included in the sample, as in Table 3. The dependent variable is the decision to cash out the account balance (active termination refund or active termination refund federal tax) instead of directly rolling over into an IRA within one year of separation. Coefficients are estimated from a linear probability model with standard errors in parentheses. *Significant at 5%; ** significant at 1%.
86 R.L. Clark et al. / Journal of Public Economics 116 (2014) 73–88
9. Cash distributions or rollovers: leakages from retirement wealth
The analysis thus far indicates that only about one third of all ter- minating public employees in North Carolina request a LS distribution while two thirds leave their retirement funds in the system. Thus, the extent of retirement saving leakage among these workers is limited. However, among those requesting a LS distribution the risk of leakage is high. Terminated employees who have requested a lump sum dis- tribution (LS) have the option of directly receiving a check or having the funds sent from the retirement system directly to another tax qualified account, often an IRA. This form of distribution from a de- fined benefit plan is typically called a “rollover” of pension funds (see Fig. 1). If the funds are rolled over, the monies are not counted as current income to the taxpayer, nor does the individual incur any tax penalty associated with the early withdrawal of funds from a retirement account. Thus, assets rolled over remain part of the individual's retirement wealth and can be invested through the new tax qualified plan.
The impact of the rollover amount on retirement income will de- pend on the investment choices made and subsequent returns earned compared to the ultimate annuity that a vested worker could receive in the future. In our calculations for vested workers, the future annu- ity is discounted at a nominal rate of 5.8%. Thus, if the vested worker earned returns in excess of 5.8%, she might be able to purchase an an- nuity at retirement with a benefit that exceeded the benefit paid by the pension system. But the retail annuity market for an individual is relatively thin and includes fees, so the worker would likely have
to earn a return greater than 5.8% in order to be able to purchase a comparable benefit in retirement.41
When a terminated worker requests that a check be sent directly to her, the distribution is subject to personal income tax in the year it is received. In addition, because all workers in our sample are under age 50, they will have to pay a 10% tax penalty for an early dis- tribution. Once received, the payment can be spent on current con- sumption, used to pay off outstanding debts, or saved. Of course, if the monies are spent, potential income in retirement is reduced. Our data identify whether the LS was rolled over or paid as a cash dis- tribution; however, we have no information on how the funds were subsequently used by terminated workers.
The possibility that the funds are spent, creating “leakage” from retirement saving, is a concern to many policy analysts. To investigate this pattern, we estimate a regression model exploring the determi- nants of how LS's are sent to terminated employees. The sample in- cludes all individuals who left either of the two North Carolina retirement systems in 2007 and 2008, and who requested the LS. Overwhelmingly, workers who requested the LS opted for a cash dis- tribution; almost 90% of these individuals were sent a check directly
87R.L. Clark et al. / Journal of Public Economics 116 (2014) 73–88
from the retirement system.42 We estimate the decision separately for vested and non-vested workers. Non-vested workers seeking an annuity do not have the option of maintaining their account and eventually receiving a retirement annuity from the pension plans. We might therefore expect that among workers choosing to with- draw funds, the non-vested group would be more likely to rollover than the vested group, holding all else equal.
Table 6 reports the estimated coefficients from a linear probability model of the decision to cash out (versus rollover) benefits among those electing a LS. The estimates cover three alternative samples: all terminated employees who requested the LS, all vested workers receiving the LS, and all non-vested individuals that received the LS. Estimated coefficients are similar across the three data sets used in the analysis. For all groups, larger account balances significantly in- creased the probability of rolling the funds over into a tax qualified account. This may reflect the desire to avoid the higher tax and penalties associated with the cash distribution. Consistent with ex- pectations given the alternative options for annuitizing, in Column (1) we observe that, holding all else constant, including the value of the LS, vested employees were 7.4 percentage points more likely to request a cash payment.
Across all three samples we see that among those requesting a LS, men are significantly more likely to cash out rather than directly roll- over benefits. In Column (3) of Table 6 we see that non-vested partic- ipants in TSERS were 2.0 percentage points less likely to receive a cash distribution; however, there were no differences between vested members of TSERS and LGERS found in Column (2). The pattern of cashing out has an inverted u-shape by age for non-vested em- ployees, while we do not find an effect for either age or years of ser- vice among vested employees, holding all else equal. For non-vested workers, an additional year of service increased the probability of accepting a check by 4.7 percentage points. Among separating workers requesting a LS, those terminating employment in 2008 were over two percentage points more likely to request cash relative to those separating in 2007.
The most important finding from this analysis is that almost 90% of terminated workers that requested a LS opted for a cash distribution. Given the economic conditions that prevailed during this period, one should not necessary conclude that this magnitude of leakage from retirement saving would prevails under normal situations. Combining these results with those presented earlier, that roughly one-third of all terminated workers request a LS, we estimate that about 30% of all terminated workers close their retirement accounts and receive a cash distribution within one year of separation.
10. Key findings and conclusions
Our analysis shows that public employees face very different choices than do private sectors employees. Whereas private sector plans are constrained by law to offer lump sum distributions (LS's) that are greater than or equal to the present value of the future annu- ity, public sector pension plans base the LS on employee contributions and credited interest. Hence, the LS value is not directly linked to the value of the life annuity.
Leakages of retirement savings when participants in defined ben- efit plans change jobs is a two step decision process. First, if the indi- vidual decides to leave his/her funds in the pension plan, no leakage
42 From October 2007 on, separating workers had the option of taking a partial roll- over and requesting the balance in cash. These are recorded as rollovers in the data, and we cannot distinguish between full or partial rollovers. Therefore, our estimate of “leakage” may be understated, since some of those rolling over funds could also be taking out a portion in cash. We also expect that some separating employees do take cash and deposit it into a tax-qualified account themselves within the allowed 60 day period. We have no way of knowing how many workers exercise this option, either. Thus, the estimate of 90% leakage is slightly low because of partial rollovers and slightly high because of indirect rollovers not being observed.
occurs at this time; however, individuals can request a LS in the fu- ture. Second, having requested a LS, the individual has the option to take the distribution as cash or to directly rollover funds into an IRA. Using administrative records from North Carolina retirement plans, we provide a detailed picture of the distribution decisions of workers ages 18 to 49 that separated prior to retirement from public pension plans in North Carolina between 2007 and 2008. We show that, for younger workers and those with fewer years of service, the LS typically is larger in value than our approximation of the present value of the annuity (PDVA), yet only one-third elected the LS. This fraction does not differ considerably by vesting status or by eligibility for retiree health insurance.
Among participants in the North Carolina retirement system, about one third of terminating workers choose to withdraw funds. However, this is an overestimate of potential leakages of retirement assets. Of those who request a LS, approximately 90% requested cash rather than rolling over directly to another tax qualified retire- ment account. This could reflect a perceived need for cash for current consumption or paying off debts. It might also be the result of poor understanding of the tax consequences of this choice and the need to save these funds for retirement. Of course, workers could still de- posit the cashed-out benefits into an IRA themselves. The high rate of cash-outs suggests a sizeable reduction in retirement wealth accu- mulation and suggests that there is a considerable amount of “leak- age” from the retirement savings of public sector workers in North Carolina.
In a related paper, Clark and Morrill (2012) find that among workers who separated from public employment in 2007–2008 and were eligible for an immediate reduced annuity (age 50 with at least 20 years of service), 90% opted to receive an immediate annuity. Of those who were eligible for an immediate unreduced annuity (30 years of service, age 62 with 25 years of service, or age 65 with 5 years of service), 99% selected some type of immediate annu- ity offered by the plan. Thus, for retiring public employees in North Carolina, almost all select an annuity option and reject the offer of a LS. On the basis of these findings and those in the current paper, it appears that public sector retirees in North Carolina are not part of annuity puzzle and instead overwhelming select annuities when they are offered.
One might expect that all non-vested terminations request a lump sum distribution since they are not entitled to a future retirement benefit and earn no interest on funds left with the system. Yet we ob- serve that two thirds of those leaving the systems in 2007 and 2008 left their accounts open. Given the evidence on financial literacy and inertia in the general population, one might speculate that non-vested terminated workers are unaware of their ability to access these funds, do not understand that they have no claim on a future benefit, do not understand that the funds will not earn any interest, or simply do not take the time to request a LS. Economic and psycho- logical studies indicate that workers often merely accept default op- tions. In this case, the default is to leave the account open, thus we may think that workers leaving the system do not take the time to re- quest a distribution of their pension account. To address this concern, the plan could change the default to be a LS for non-vested workers. Clark and Morrill (2012) find a similar result for non-vested workers over the age of 50 with only 36% of terminated workers aged 50 to 59 selecting a LS. While the proportion of those choosing a LS rises some- what with advancing age (50% of those over age 65 chose the LS), it is hard to explain why these older non-vested terminating workers would leave their funds with the system.
We postulate several factors that might explain why terminating workers for the most part do not appear to respond to the relative size of the PDVA and LS. Given that vested employees receive a 4% an- nual return when funds are left in the system, individuals can consid- er this as an investment option. However, regression analysis does not support the hypothesis that greater returns on investments
88 R.L. Clark et al. / Journal of Public Economics 116 (2014) 73–88
outside the retirement system increase the likelihood that workers will request a LS There is some evidence that as the economy wors- ened, as proxied by state-level unemployment rates, individuals were less likely to withdraw funds. However, we have a limited time series available, so are not able to disentangle the effects eco- nomic conditions, labor market conditions, outside investment op- tions, and confidence in the retirement system. We find that there may be an important role for defaults and workers may not be well informed about the value of their benefits.
Appendix A. Supplementary data
Supplementary data to this article can be found online at http:// dx.doi.org/10.1016/j.jpubeco.2013.05.005.
References
AonHewitt, 2011. Leakage of Participants' DC Assets: How Loans, Withdrawals, Cashouts are Eroding Retirement Income. http://www.aon.com/attachments/thought-leadership/ survey_asset_leakage.pdf (last accessed February 14, 2013).
Bassett, William, Fleming, Michael, Rodriguez, Anthony, 1998. How workers use 401(k) plans: the participation, contribution, and withdrawal decisions. National Tax Journal 51 (2), 263–289.
Bellante, Don, Link, Albert, 1981. Are public sector workers more risk averse than private sector workers? Industrial & Labor Relations Review 34, 408–412.
Benartzi, Shlomo, Previtero, Alessandro, Thaler, Richard, 2011. Annuitization puzzles. Journal of Economic Perspectives 25 (4), 143–164.
Bonin, Holger, Dohmen, Thomas, Falk, Armin, Huffman, David, Sunde, Uwe, 2007. Cross-sectional earnings risk and occupational sorting: the role of risk attitudes. Labour Economics 14 (6), 926–937.
Brown, Jeffrey R., 2001. Private pensions, mortality risk, and the decision to annuitize. Journal of Public Economics 82, 29–62.
Brown, Jeffrey R., Weisbenner, Scott, 2012. Why do Individuals Choose Defined Contri- bution Plans? Evidence from participants in a large public plan, paper presented at Retirement Benefits for State and Local Employees: Designing Pension Plans for the Twenty-First Century, NBER Conference, Jackson Wyoming.
Brown, Jeffrey R., Ivkovic, Z., Smith, P.A., Weisbenner, Scott, 2008a. Neighbors matter: causal community effects and stock market participation. Journal of Finance 63 (3), 1509–1531.
Brown, Jeffrey R., Kling, Jeffrey R., Mullainathan, Sendhil, Wrobel, Marian V., 2008b. Why don't people insure late-life consumption? A framing explanation of the under-annuitization puzzle. American Economic Review: Papers & Proceedings 98 (2), 304–309.
Bryant, Victoria, Holden, Sarah, Sabelhaus, John, 2011. Qualified Retirement Plans: Analysis of Distribution and Rollover Activity. Pension Research Council Working Paper WP2011-01.
Bureau of Labor Statistics, 1990. Employee Benefits in Medium and Large Firms, 1989. Bulletin 2363.
Bureau of Labor Statistics, 1999. Employee benefits in medium and large establish- ments, 1997. Bulletin 2517.
Bureau of Labor Statistics, 2007. National Compensation Survey: Employee Benefits in Private Industry in the United States 2005. Bulletin 2589.
Bureau of Labor Statistics, 2011a. Employee Benefits Survey. http://bls.gov/ncs/ebs/ benefits/2011/benefits_retirement.htm.
Bureau of Labor Statistics, 2011b. The Employment Situation: November 2011 (Decem- ber 2, 2011).
Burman, Leonard, Coe, Norma, Gale, William, 1999. Lump sum distributions from pen- sion plans: recent evidence issues for policy and research. National Tax Journal 52 (3), 553–562.
Butler, Monika, Teppa, Federica, 2007. The choice between an annuity and a lump sum: results from Swiss pension funds. Journal of Public Economics 91 (10), 1944–1966.
Buurman, Margaretha, Dur, Robert, Van den Bossche, Seth, 2009. Public sector em- ployees: risk averse and altruistic? Journal of Economic Behavior & Organization 83 (3), 279–291.
Chalmers, John, Reuter, Jonathan, 2012. How do retirees value life annuities? Evidence from public employees. Review of Financial Studies 25 (8), 2601–2634.
Chang, Angela, 1996. Tax policy, lump-sum pension distributions, and household saving. National Tax Journal 49 (2), 235–252.
Clark, Robert, Hanson, Emma, 2011. Distribution Options in State Pension Plans. NCSU Working Paper.
Clark, Robert, Morrill, Melinda S., 2010. Retiree Health Plans in the Public Sector: Is There a Funding Crisis? Edward Elgar Publishing, Northhampton, MA.
Clark, Robert, Morrill, Melinda S., 2011. Containing Health Insurance Costs for Active and Retired Public Sector Employees: Lessons from the State of North Carolina. NCSU Working Paper.
Clark, Robert, Morrill, Melinda S., 2012. Retiring Public Sector Employees Prefer Annu- ities to Lump Sum Distribution. North Carolina State University Working Paper.
Clark, Robert, Craig, Lee, Sabelhaus, John, 2011. State and Local Retirement Plans in the United States. Edward Elgar Publishing, Northhampton, MA.
Clark, Robert, Morrill, Melinda S., Allen, Steven, 2012. The role of financial literacy in determining retirement plans. Economic Inquiry 50 (4), 851–866.
Copeland, Craig, 2009. Lump Sum Distributions at Job Change. EBRI Notes. (January, 2-10).
Engelhardt, Gary, 2002. Pre-retirement lump-sum pension distributions and retire- ment income security: evidence from the Health and Retirement Study. National Tax Journal 55 (4), 553–562.
Goda, Gopi Shah, Shoven, John B., Slavov, Sita Nataraj, 2012. Does stock market per- formance influence retirement intentions? Journal of Human Resources 47 (4), 1055–1081.
Government Accountability Office (GAO), 2009. 401(k) plans: policy changes could re- duce the long-term effects of leakage on workers' retirement savings, GAO-09-715 (August).
Hartog, Joop, Ferrer-i-Carbonell, Ada, Jonker, Nicole, 2002. Linking measured risk aversion to individual characteristics. Kyklos 55 (1), 3–26.
Hurd, Michael, Panis, Constantijn, 2006. The choice to cash out pension rights at job change or retirement. Journal of Public Economics 90 (12), 2213–2227.
Lusardi, Annamaria, Mitchell, Olivia S., 2007. Baby Boomer retirement security: the roles of planning, financial literacy, and housing wealth. Journal of Monetary Economics 54 (1), 205–224.
Madrian, Brigitte, Shea, Dennis, 2001. The power of suggestion: inertia in 401(k) participation and savings behavior. Quarterly Journal of Economics 116 (4), 1149–1187.
Manski, C.F., 1993. Identification of endogenous social effects: the reflection problem. Review of Economic Studies 60 (3), 531–542.
Mitchell, Olivia S., Poterba, James M., Warshawsky, Mark J., Brown, Jeffrey R., 1999. New evidence on the money's worth of individual annuities. The American Economic Review 89 (5), 1299–1318.
Moore, James, Muller, Leslie, 2002. An analysis of lump-sum pension distribution recip- ients. Monthly Labor Review 125, 29–46.
Novy-Marx, Robert, Rauh, Joshua, 2011. Public pension liabilities: how big are they and what are they worth? Journal of Finance 66 (4), 1207–1245.
Papke, Leslie, 2004. Pension plan choice in the public sector: the case of Michigan State employees. National Tax Journal 57 (1), 329–340.
Pew Center on the States, 2011. The Widening Gap: The Great Recession's Impact on State Pension and Retiree Health Cost. http://www.pewcenteronthestates.org/ uploadedFiles/Pew_pensions_retiree_benefits.pdf.
Pfeifer, Christian, 2010. Risk aversion and sorting into public sector employment. German Economic Review 12 (1), 85–99.
Poterba, James, Venti, Steven, Wise, David, 1998. Lump-sum distributions from retire- ment saving plans: receipt and utilization. In: Wise, David (Ed.), Inquiries into the Economics of Aging. University of Chicago Press, Chicago, pp. 85–105.
Poterba, James, Venti, Steven, Wise, David, 2001. Preretirement cashouts and foregone retirement saving: implications for 401(k) asset accumulation. In: Wise, David (Ed.), Themes in the Economics of Aging. University of Chicago Press, Chicago, pp. 23–58.
Purcell, Patrick, 2007. Lump-sum distributions under the Pension Protection Act, CRS Report For Congress, Order Code RS22765 (December 3).
Purcell, Patrick, 2009. Pension issues: lump-sum distributions and retirement income security, CRS Report for Congress (January 7).
Roszkowski, Michael, Grable, John, 2009. Evidence of lower risk tolerance among pub- lic sector employees in their personal financial matters. Journal of Occupational and Organizational Psychology 82 (2), 453–463.
Sabelhaus, John, Weiner, David, 1999. Disposition of lump-sum pension distributions: evidence from tax returns. National Tax Journal 52, 593–614.
Warner, John, Pleeter, Saul, 2001. The personal discount rate: evidence from military downsizing programs. American Economic Review 91 (1), 33–53.
Yaari, Menahem E., 1965. Uncertain lifetime, life insurance, and the theory of the consumer. Review of Economic Studies 32 (2), 137–150.
Yakoboski, Paul, 1997. Large plan lump sums: rollovers and cashouts. EBRI Issue Brief, vol. 188. EBRI, Washington, DC.
Yang, Tongxuan, 2005. Understanding the defined benefit versus defined contribution choice, Pension Research Council WP 2005-4.
- Defined benefit pension plan distribution decisions by public sector employees
- 1. Introduction
- 2. Relevance of findings for participants in public and private DB plans
- 3. Previous literature examining lump sum distributions
- 4. Estimating the value of distribution options in the North Carolina retirement plans
- 4.1. Background on distributional choices in state-managed defined benefit plans
- 4.2. Choices facing separating public sector workers in North Carolina
- 4.3. Simulating the relative values of the annuity and lump sum distribution
- 5. Separating public employees in North Carolina: 2007 and 2008
- 6. Distributional decisions of vested workers
- 7. Potential explanations for the observed distributional decisions
- 7.1. Access to subsidized health insurance in retirement
- 7.2. Potential for returning to work and the distributional choice
- 7.3. Economic conditions and alternative investment options
- 7.4. Financial literacy, plan knowledge, peer effects, and inertia
- 8. Distributional choices of non-vested workers
- 9. Cash distributions or rollovers: leakages from retirement wealth
- 10. Key findings and conclusions
- Appendix A. Supplementary data
- References
#143.pdf
Journal of Banking & Finance 59 (2015) 538–549
Contents lists available at ScienceDirect
Journal of Banking & Finance
j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / j b f
Corporate social responsibility and Eurozone corporate bonds: The moderating role of country sustainability
http://dx.doi.org/10.1016/j.jbankfin.2015.04.032 0378-4266/� 2015 Elsevier B.V. All rights reserved.
⇑ Corresponding author. Tel.: +49 89 24207574; fax: +49 3212 6308830. E-mail address: [email protected] (C. Stellner).
Christoph Stellner ⇑, Christian Klein, Bernhard Zwergel University of Kassel, Henschelstr. 4, 34109 Kassel, Germany
a r t i c l e i n f o a b s t r a c t
Article history: Received 29 July 2014 Accepted 28 April 2015 Available online 2 July 2015
JEL classification: G12 G24 M14
Keywords: European corporate bond markets Corporate social responsibility (CSR) Rating Z-spread
In this paper, we empirically examine whether superior performance in corporate social responsibility (CSR) results in lower credit risk, measured by credit ratings and zero-volatility spreads (z-spreads). We are especially interested in how the environmental, social, and governance (ESG) related performance of the corresponding countries moderates this relationship. We find only weak evidence that superior corporate social performance (CSP) results in systematically reduced credit risk. However, we do find strong support for our hypothesis that a country’s ESG performance moderates the CSP–credit risk rela- tionship. Superior CSP is regarded as risk-reducing and rewarded with better ratings and lower z-spreads only if it is recognized by the environment. In addition, we find a reduction of corporate bonds’ z-spreads by approx. 9.64 basis points if the CSP of a company mirrors the ESG performance of the country it is located in.
� 2015 Elsevier B.V. All rights reserved.
1. Introduction
The discussion of the role that a company should play in an economy, organizations’ core values, and how business is or should be conducted has significantly gained in importance in recent years, particularly since the beginning of the financial crisis. Primarily banks but also companies from other industries have been accused of unethical decision-making and shortsighted behavior. From a scientific perspective, scholars have especially focused on corporate social responsibility (CSR) and corresponding corporate social performance (CSP) as a strategic decision by senior management that affects corporate financial performance (CFP) or security prices. Although there is no universally valid definition and understanding of the concept of CSR (see Griffin, 2000; van Beurden and Gössling, 2008), one could regard CSR as a certain way in which companies consider environmental, social, or gover- nance (ESG) factors in their business decisions and processes and how good the relationships with the various stakeholders of the firm are (see Oikonomou et al., 2011).
The main question of interest has been whether CSR pays off or whether the costs associated with being a more responsible com- pany are a waste of scarce resources. The results from several meta
studies (e.g. Orlitzky et al., 2003; Margolis et al., 2009) are mixed and point to a weak positive relationship, i.e. CSP has a positive impact on CFP. The vast majority of studies that examine the CSP-CFP link focus either on some measure of corporate (account- ing) performance (e.g. return on assets) or a market-based measure (e.g. share price development). There is only a very limited amount of literature that focuses on the relationship between CSP and the cost of debt or ratings (e.g. Menz, 2010; Goss and Roberts, 2011; Oikonomou et al., 2011), and the results do not consistently reveal the direction of the relationship.
Our study aims to contribute to the strand of literature that investigates the CSP-CFP relationship in several ways. First and most important, by explicitly considering the equivalent of CSR on the country level—the degree to which a country pays attention to ESG matters—we try to identify one of the missing pieces that might help to explain the divergent findings with regard to the CSP-CFP relationship in the context of debt capital. With this con- cept, we extend the approach of a recent paper by Jiraporn et al. (2014), which finds that a firm’s CSR policy is influenced by the CSR policies of firms in the same United States (US) three-digit zip code. Second, as described above, only a very limited number of studies investigate the relationship between CSP and credit instruments. Given the importance of debt financing for companies today, we want to shed light on the role of CSR in this market. Third, this is the first study that utilizes zero-volatility spreads
1 This argumentation is in line with a previous study by Pirinsky and Wang (2010) They show that investors from the region affect the behavior of local firms.
C. Stellner et al. / Journal of Banking & Finance 59 (2015) 538–549 539
(z-spreads) instead of credit spreads and thus eliminates problems associated with the latter measure such as term structure effects. Fourth, by focusing on the European corporate bond market, we can examine a geographical area that has seen enormous growth in bond markets since the inception of a single currency more than ten years ago. With regard to the special focus of this study—the simultaneous consideration of country sustainability in the analy- sis of the CSP-CFP relationship—the Eurozone is the natural frame- work to test our hypotheses. Since we obviously have to incorporate bonds from various countries in our data sample against the background of our specific research question, we would have to adjust for currency risk if we compare yield spreads from countries with different currencies. In a data sample drawn from a monetary union, this problem does not occur.
A selection of research questions this paper addresses is the question of whether CSP is positively or negatively related to cor- porate bond ratings and z-spreads in the Eurozone? Are the results different depending on whether ratings or z-spreads are utilized? What influence does country sustainability have on the CSR-rating or z-spread relationship? Are companies with superior CSP rewarded in particular with lower cost of debt if also their country of residence ranks high with regard to sustainability so that the companies’ efforts to maintain or improve its CSR level are recognized and rewarded economically? On the other hand, will companies with superior CSP be penalized with higher cost of debt if the respective country scores below average with regard to ESG criteria?
Why should CSR have an impact on the cost of debt? There are divergent theories on what the direction of this relationship should be. The risk mitigation view (Goss and Roberts, 2011) states that companies with superior CSP have—ceteris paribus—a more favor- able risk profile than an otherwise identical company with worse CSP. Spicer (1978) shows that an investment in a company with below average CSP might be inefficient from an investor’s perspec- tive (see also Izzo and Magnanelli, 2012). The better risk profile and the greater ability to repay the principal at maturity are rewarded by rational investors with a lower spread demanded from the bond-issuing company. Companies with a superior CSP are expected to build or to have built internal resources and intan- gibles, such as reputation, customer loyalty, or long-term relation- ships with various stakeholder groups (e.g. suppliers or the government), which might result in competitive advantages (Hart, 1995; Jones, 1995; Hillman and Keim, 2001; Kim et al., 2009). As an example, companies with a reputation as equal oppor- tunity employer might have lower costs for recruiting than an otherwise identical organization and attract more talented person- nel. Customers might be willing to pay a price premium on prod- ucts from a company considered committed to sustainability and the protection of the environment. Long-term and loyal suppliers might accept longer payment terms and thus reduce financing needs. Hence, the generation of internal resources, intangibles, and moral capital (Godfrey, 2005) should finally result in higher profitability, a more stable financial performance, and thus a more favorable risk profile. Bauer and Hann (2010) argue that—in the context of environment-related CSR—firms that conduct business in an irresponsible manner are more subject to legal, reputational, and regulatory risks that might result in penalties and fines and subsequently more volatile cash flows and higher default risk. In addition, the successful implementation of CSR in an organization might be perceived as a signal of the competence and commitment of the management, which reduces agency risks and the overall risk profile (Waddock and Graves, 1997; Oikonomou et al., 2011).
The opposite view, referred to as the overinvestment view by Goss and Roberts (2011), regards investments in CSR as a waste of scarce resources. The theory traces back to Friedman (1962, 1970), who considers investments in CSR value-destroying from
a shareholder perspective. Excessive costs for handling the various relations to a high number of stakeholders increase complexity and reduce profitability (Aupperle et al., 1985; Kim et al., 2009). Alexander and Buchholz (1978) as well as Frooman et al. (2008) conclude that the increase in fixed costs related to sustainable investments in CSR increases the volatility of earnings and thus default risk. From a principal-agency perspective, senior manage- ment might benefit personally from investing in CSR activities by improving their own reputation to the detriment of shareholders (Barnea and Rubin, 2010; Kim et al., 2009; Goss and Roberts, 2011). All the mechanisms described above might result in decreasing profitability and an increase in volatility. An increase in default risk should result in higher spreads demanded by lenders or investors (Frooman et al., 2008; Goss and Roberts, 2011).
Oikonomou et al. (2011) provide several arguments why bond markets in particular are suitable to investigate the CSP-CFP link. Due to the shorter maturity of credit instruments compared to stocks and the subsequent need for regular refinancing, investors have the ability to impose pressure on management. If investors regard high CSP as risk-reducing, they will be able to stipulate a stronger focus on CSR or otherwise demand a higher level of com- pensation for the risk borne. This is in line with Menz (2010), who argues that, due to the importance of bond markets for a com- pany’s refinancing, investors possess the power to promote their view of CSR by changing financing terms. In addition, institutional investors are the main participants in credit markets. As Oikonomou et al. (2011) outline, they might be better informed and are more likely to incorporate CSR in their investment deci- sions. In combination with the limited free-float resulting from institutional ownership, this investor type has a strong influence on management and therefore indirectly on how CSR is promoted within the organization.
In line with Goss and Roberts (2011), we assume a rational investor who does not follow a social agenda. Investors determine the value of a debt investment (and thus the spread demanded) mainly based on the ability of the borrower to repay the principal at maturity. As long as the marginal benefits from investing in CSR exceed the marginal costs of these investments, investors should be willing to reward the better risk profile of the respective com- pany and demand lower spreads. As soon as investors believe that the marginal costs exceed the marginal benefits and managers overinvest in CSR for their own benefit, investors should demand higher spreads. In this paper, we argue that the relationship between CSP and credit risk (measured by corporate bond ratings and z-spreads) is moderated by the country in which the respec- tive company is located. We argue that the benefits resulting from CSR investments as outlined above (the generation of resources and intangibles, the signaling of superior management skills, etc.) are context-driven and depend on the external environment (Flammer, 2013; Jiraporn et al., 2014). Stakeholders in a company that is located in a country that scores below average in ESG crite- ria are believed to be less interested in CSR-related matters. Customers in a country that scores below average in the environ- mental dimension of ESG should be less likely to pay a premium for a product from a company committed to the highest standards of environmental protection.1 The generation of moral capital that might function as insurance in a downturn requires not only a company investing to build this resource but also an environment that recognizes and acknowledges the relevance of such a concept. The context-dependency of CRS investments has already been investigated on the industry level (e.g. Bauer and Hann, 2010; Flammer, 2013) and on geographical areas (Jiraporn et al., 2014).
.
540 C. Stellner et al. / Journal of Banking & Finance 59 (2015) 538–549
Flammer (2013) argues that ‘‘institutional norms of CSR affect the financial returns from CSR investments.’’ Risk-reducing mechanisms induced by closer ties to stakeholders might not work if they are not rewarded by the external environment. If this is the case, there will be a reduction of the marginal benefits from CSR investments that will be below the marginal costs of such investments. Rational investors will not be willing to accept lower compensation for their risk. On the contrary and in line with the overinvestment theory, they might even demand higher spreads since the waste of scarce resources increases costs and worsens the company’s risk profile. Briefly, we expect companies that adapt to their local country ESG performance to pay the lowest spreads. High CSR companies should be rewarded with lower spreads if their country scores above average in ESG criteria and penalized with higher spreads if their country ranks below average. Companies with below average CSP should be rewarded with lower spreads compared to their high-ranking competitors in below average ESG countries. Rational investors should consider that below average companies in these countries operate efficiently with their scarce resources and do not spend on CSR initiatives that are not rewarded by their environment.
Closely related to our research is a recent study by Jiraporn et al. (2014). They find robust empirical evidence that firms located in the same three-digit zip code in the US exhibit similar CSR policies. They argue that ‘‘due to market segmentation, investor clientele, local competition, and social interactions, a firm is likely to take into account the levels of CSR of surrounding firms when formulat- ing its own CSR policy.’’ In contrast to Jiraporn et al. (2014), we do not examine whether the degree of CSR of a company is influenced by the average degree of CSR of geographically proximate firms. We focus on the question whether companies with different degrees of CSR in the same area (country) experience different impacts on their credit risk with countries moderating this CSP– credit risk relationship. Additionally we use z-spreads to remove well-known problems like term structure effects.
Based on a sample of 872 bonds from companies located in twelve countries of the Economic and Monetary Union (EMU) in the period from 2006 to 2012, we find no statistically significant evidence that companies that are performing well in CSR are sys- tematically rewarded with better ratings. However, the results from ordered logistic regressions indeed show that companies ben- efit from better ratings if they show superior CSP in a country with above average ESG. More generally, companies benefit from better ratings if their CSP matches the ESG performance of their countries, which obviously also incorporates the case in which both the com- pany and country ESG performance are below average. Our results are robust to the inclusion of a broad set of control variables that have proven to affect corporate bond ratings.
Interestingly, we find a reduction in corporate z-spreads if com- panies perform well in CSR. However, in line with the corporate rating sample, results from pooled time-series, cross-sectional regressions show that companies are especially rewarded for supe- rior CSP with lower z-spreads if the ESG performance of the respec- tive country is above the mean. In addition, we find that bonds from companies that have either high CSP in high ESG countries or low CSP in low ESG countries pay lower spreads than companies that do not match their country’s ESG performance. Applying the adjustment of Kennedy (1981) to dummy variable coefficients in semilogarithmic equations and based on the mean spread of 125.5 basis points, their spreads are approx. 9.6 basis points lower than their counterparts’.2
We organize the remainder of the paper as follows. Relevant lit- erature on the link between CSP and CFP/credit risk and the context-dependency of this relationship is reviewed in the next
2 See also Goss and Roberts (2011).
section. Section 3 describes details of our dataset, the empirical tests performed, the findings of our study, and several robustness checks. A conclusion and summary are provided in Section 4.
2. Related literature
In the following, we provide an overview of the relevant litera- ture for the topic covered by this paper. While a significant number of studies have investigated the relationship between CSP and CFP as well as its causal direction, relatively little research has tried to shed light on how credit risk is affected by CSP. In addition, we will provide an overview of papers that investigate how the contextual framework influences the relationship between CSP and CFP.
2.1. CSR and credit risk
Jiraporn et al. (2014) use US Postal Service zip codes to exploit the variation in CSR policies across geographic locations within a country and explore the impact of CSR on credit ratings. Their sam- ple consists of 2,516 firm-year observations from 1995 to 2007 with CSR scores from the Kinder Lydenberg Domini (KLD) database and Standard and Poor’s (S&P) credit ratings. They regress the ‘‘CSR score of a company’’, while controlling for other firm characteris- tics, on the average CSR score of geographically proximate firms and find that the average CSR score of the neighboring firms is sig- nificant and positive. The authors conclude that a firm’s CSR policy is significantly influenced by the CSR policies of the neighboring firms. This outcome is robust: Besides a bunch of robustness checks the authors execute a two-stage fixed effects analysis to ensure that the results are not confounded by the omitted variable bias nor by reverse causality. Concerning the beneficial effect of CSR, the authors find that more socially responsible firms enjoy better credit ratings.
A recent study closely related to our work has been conducted by Oikonomou et al. (2011). Based on a sample of 3,240 bonds in the period from 1994 to 2008, the authors investigate the impact of aggregated and disaggregated measures of CSP—KLD strengths and concerns—on corporate bond spreads and bond ratings. In gen- eral, they find that companies with CSR strengths benefit from lower spreads and better ratings, while companies with CSR weak- nesses are penalized with higher spreads and lower ratings. The impact is more pronounced for bonds with longer maturities and for either very high or very low ratings. With regard to the context-dependency of the relationship between CSP and CFP, the authors find no evidence that the effect of CSP on credit risk differs systematically between industries.
The study of Menz (2010) is of special interest for our work, as it is one of the few studies that focuses on a European data set. Menz (2010) uses CSR data from Sustainable Asset Management Research (SAM) and a sample of 498 corporate bonds in the period from July 2004 to August 2007. Interestingly, he finds a positive— though statistically only weakly significant—relationship between CSR and corporate spreads, i.e. firms with better performance with regard to CSR face higher spreads for their corporate bonds.
In contrast to the two aforementioned studies, Goss and Roberts (2011) do not use corporate bond spreads but all-in-drawn spreads of 3,996 US bank loans from 1991 to 2006 to test their hypotheses. They use KLD strengths and concerns separately and report several interesting findings. Borrowers are penalized with modestly higher spreads if they are subject to CSR concerns, and the effect is stron- ger if no security has been pledged.3 Interestingly, CSR strengths are accompanied with higher spreads if the credit quality of the bor- rower is low. This lends support to the overinvestment hypothesis
3 Spreads are between seven and 18 basis points higher.
C. Stellner et al. / Journal of Banking & Finance 59 (2015) 538–549 541
that spending in CSR can be considered a waste of scarce resources that should be allocated to other parts of a company, which espe- cially applies to Non-Investment Grade borrowers with a lack of resources.
Izzo and Magnanelli (2012) is among the few studies covering non-US companies, namely companies in France, Germany, Italy, and Japan.4 Based on a sample of 332 companies from 2005 to 2009, an accounting-based measure of the cost of debt as a depen- dent variable (interest expenses divided by debt) and CSR data from the SAM group, the authors find no evidence for a negative relationship between CSP and the cost of debt (or for an ethical financial premium, as it is called in their paper). In line with Menz (2010), their results reveal a positive relationship, i.e. better CSP is penalized with higher cost of debt. While a slightly differ- ent research question is examined by Baran and Zhang (2012), the overall results support the findings of Menz (2010) and Izzo and Magnanelli (2012). The authors examine how the inclusion of a company’s stock in the KLD 400 Index—an index that comprises companies with superior CSP—influences the company’s cost of debt. They find that the yield spreads of newly issued bonds increase systematically after companies have been included in the sustainability index. Frooman et al. (2008) use five measures of CFP to investigate the effect of CSP on CFP. Besides sharehold- ers, strategic partners, suppliers, and (short-term) creditors, they examine how bondholders are affected by different levels of CSP. Using ratings as a measure for bondholder risk and KLD data on CSP, they find that bondholders are the only group to benefit from superior CSP or suffer from weak CSP. Ge and Liu (2012) investi- gate how the degree of disclosure of CSR relevant information affects yield spreads. Companies that disclose superior CSP benefit from lower yield spreads, while there is no difference between disclosing firms with below average CSP and firms that do not dis- close relevant information on CSR.
Analyzing the results of the studies described above reveals the very divergent results when the effect of CSP on credit risk is exam- ined. The studies presented above have in common that they inves- tigate this relationship by trying to quantify the impact of some overall measure of performance in ESG on credit risk, which is measured by ratings, corporate bond spreads, or spreads on bank loans. In the following, we will provide an overview of studies that examine the effect of only one dimension of ESG—environmental, social, or governance—on credit risk.
2.2. Environmental performance and credit risk
The effect of the environmental performance or risk on credit risk has been examined by, among others, Chava (2011), Schneider (2011), Bauer and Hann (2010), Sharfman and Fernando (2008), and Graham et al. (2001). Chava (2011) as well as Sharfman and Fernando (2008) investigate the impact of envi- ronmental risk on the cost of capital. While Chava (2011) finds that firms with environmental risks are penalized with higher cost of debt, Sharfman and Fernando (2008) find that—despite an overall reduction in the weighted average cost of capital (WACC)—firms with better environmental risk management have a higher cost of debt. Schneider (2011) draws a sample of 48 companies from 1996 to 2006 from the pulp and paper industry as well as chemical industry in the US. He finds that poor environmental performance results in higher spreads but that this effect is less pronounced when credit quality increases and the risk of bankruptcy resulting from high payments for environmental clean-up costs, etc., decreases. The findings of Schneider (2011) are confirmed by Bauer and Hann (2010) and Graham et al. (2001), who find that
4 They also include US companies in their sample (see also Bassen et al., 2006).
low performance in the environmental dimension of ESG results in a higher cost of debt and lower ratings.
2.3. Employees and credit risk
Chen et al. (2012) and Bauer et al. (2009) investigate the impact that employees as stakeholders and employee relations have on credit risk. The first find that companies in industries that are more subject to unionization benefit from lower yields, which the authors explain by the influence that unions have in preventing management from investments in risky projects and the lower pos- sibility of being acquired by another company. Bauer et al. (2009) find that superior employee relations result in better ratings and a lower cost of debt.
2.4. Corporate governance and credit risk
Various studies examine the impact that good corporate gover- nance has on credit risk (among others, Bradley et al., 2007; Ashbaugh-Skaife et al., 2006; Klock et al., 2005; Bhojraj and Sengupta, 2003). These studies point toward a negative relation- ship between corporate governance and credit risk. Better corpo- rate governance is associated with lower credit risk and thus to better ratings and lower spreads.
2.5. What moderates the relationship between CSR and CFP?
The following studies in particular investigate the context in which the relationship between CSP and CFP is embedded. Kim et al. (2009) not only examine how a borrower’s CSP relates to loan spreads but also how the lender’s CSP moderates this relationship. Using a sample of 175 companies from a worldwide sample (excluding Asia) in the period from 2003 to 2006, they find that the relationship between (the borrower’s) CSP and CFP to be an inverted U-shape. In addition, if lenders score above average in CSR, borrowers can expect an additional reduction in loan spreads. Kim et al. (2009) conclude that only lenders with superior CSP rec- ognize the risk-reducing effect of superior borrower CSP and sub- sequently reduce loan spreads. Besides her main finding of a positive effect of CSP on CFP in a setup that considers a clear causal relationship between the two, Flammer (2013) also investigates the impact of the environment or institutional norms of CSR on this relationship. Indeed, she finds industry affiliation to moderate the relationship and that, ‘‘in industries with higher institutional norms of CSR (‘‘clean’’ industries) stakeholders are more sensitive to companies’ CSR efforts,’’ which finally translates into superior financial performance. Goll and Rasheed (2004) also find superior CSP to translate into higher CFP in an environment that is more dynamic and munificent. Surroca et al. (2010) find intangible resources to moderate the impact of CSP on CFP and of CFP on CSP.
An overview of the relevant literature on the relation between CSP and credit risk clearly shows that the results differ substan- tially and that the context in which the relationship is embedded is of importance. There should be additional effort to identify the missing link(s) that help to better understand and define this rela- tionship, both theoretically and empirically.
2.6. The impact of geographic location on stakeholders preferences
Pirinsky and Wang (2010) review the literature on the link between geographic location of firms and corporate finance. As a result, they show that the geographic location of firms and finan- ciers plays an important role in financial decision-making. This results in a geographical segmentation of capital markets. Pirinsky and Wang (2010) conclude that this segmentation
3 3 12 20 27 29 31
56 74
91 207
319
0 100 200 300 400
Ireland Greece
Luxembourg Portugal
Austria Finland
Belgium Netherlands
Spain Italy
Germany France
Fig. 1. Country distribution of bonds.
542 C. Stellner et al. / Journal of Banking & Finance 59 (2015) 538–549
‘‘exposes the firm to a wide variety of individual and institutional characteristics from the region’’.
Jiraporn et al. (2014) also provide a literature review on the relationship between geography and corporate policy and on the connection between geography and CSR. They argue, ‘‘Investors may have a negative view of a firm if its CSR policy is much weaker than those of the surrounding firms’’. We go one step further and claim that investors may consider it a waste if a firm’s CSR policy is much more involved than those of the surrounding firms are.
3. Main empirical tests
3.1. Methodology
In general, our empirical tests are based on two models and try to shed light on the relationship between CSP and credit risk. More precisely, we are interested in how our measure of CSP—the Thomson Reuters ASSET4 ESG ratings universe—impacts S&P credit ratings and corporate bond z-spreads, our two measures for credit risk. We are particularly interested in how Bloomberg ESG Country Ratings moderate this relationship by introducing several interac- tion terms and dummy variables in our basic specifications.
Considering the ordinal scaling of ratings as a dependent vari- able, we utilize ordered logistic regressions to examine the relation between CSP and credit ratings. Due to the frequency of ASSET4 score publications (yearly), the impact of CSP on ratings is exam- ined on a yearly basis. One of the main aspects that has to be taken into account with regard to the impact of CSP on CFP is the causal- ity of the relationship. Since there might also be an impact of prior CFP on subsequent CSP (see Surroca et al., 2010 and others), we fol- low the methodology proposed by Oikonomou et al. (2011) and lag independent variables in our models to minimize problems that might exist due to potential endogeneity. In addition, a set of company-specific and global control variables that are expected to influence credit ratings, both theoretically and empirically, are included in the model. While the baseline model incorporates only ASSET4 scores and control variables as independent variables, we interact CSP with a variable that captures country ESG perfor- mance, incorporate a dummy variable if the company ESG perfor- mance matches the country ESG performance, and finally split the sample into high- and low-performing countries. Robust Huber (1967) and White (1980) standard errors are presented for each setup.
For the setup that uses z-spreads as the measure for credit risk, we perform pooled time-series, cross-sectional regressions of yearly corporate bond z-spreads on the prior year’s CSP and control variables. The following setup is applied:
ZCi;t;c ¼ a þ b1ESGi;t�1 þ b2W i;t�1 þ b3Xi;t�1 þ b4 Zt�1 þ b5Pc þ eit; ð1Þ
where the yearly z-spread ZCi;t;c for corporate bond i at time t issued by a company from country c depends on the prior year’s ESG company rating, a set of bond-specific, time-varying variables represented by W i;t�1; a set of company-specific, time-varying vari- ables represented by Xi;t�1; a set of global, time-varying variables represented by Zt�1, and country dummies represented by Pc . Standard errors have been clustered by country and time as per Petersen (2009).
3.2. Sample overview and data description
After matching Thomson Reuters ASSET4 ESG ratings with data on z-spreads, bond- and company-specific control variables, our final sample includes 872 corporate bonds issued by non-financial companies located in the following twelve EMU
countries: Austria, Belgium, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, and Spain. While most studies so far have focused on US bond markets, European bond markets have recently gained increased attention (Menz, 2010). While the first are still unique with regard to the broad range of credit instruments and credit qualities traded, their size and diversified investor base, the latter have recently caught up due to the formation of more integrated markets which has reduced transactions costs and increased liquidity (Pagano and von Thadden, 2004; Laganá et al., 2006; Avadanei, 2010). We exclude floating-rate notes and structured or asset-backed securi- ties and consider only Euro-denominated, option-free, fixed cou- pon bonds. The period covered by our sample is from 2006 to 2012. Distributions of bonds by country and industry are provided in Figs. 1 and 2.
Bond ratings are obtained from S&P and from Moody’s if S&P ratings are not available. For the ordered logistic regressions, we group ratings into seven broad categories from ‘‘1’’ (AAA) to ‘‘7’’ (CCC). Z-spreads from Bloomberg are collected for the second setup. A z-spread is defined as the size of the parallel shift of a cer- tain benchmark spot rate curve to equal a fixed income instru- ment’s discounted cash flows to its market price (see Fabozzi and Choudhry, 2004). This means that—in contrast to the concept of conventional yield spreads which implicitly assumes a flat yield curve—z-spreads incorporate information of the complete yield curve. In an iterative process, a certain spread which is equal for all points of the underlying benchmark curve is added to the curve. The respective bond’s cashflows are then discounted with the appropriate discount rate from the shifted benchmark curve. The equal spread above the benchmark curve is adapted until the sum of the discounted cashflows equals the market price of the bond. The benchmark used for our z-spreads is the Euro Swaps Curve, which is based on Euro-denominated interest-rate swaps. We use natural logs of z-spreads in our regressions.
The measurement of CSR is of special importance for the relia- bility of results presented in any study that investigates the CSP-CFP relationship. Fortunately, accompanying the significant rise in interest in ESG-related topics, there has been a substantial increase in the number and quality of organizations that provide ESG data. In this study, we use Thomson Reuters ASSET4 ESG scores. Besides ESG data from KLD, the ASSET4 rating universe has a reputation as one of the most diligent and trustworthy sources for CSR data covering approximately 4,500 companies. ASSET4 mostly collects information from publicly available sources to fill more than 750 data points that form 280 ESG-related key performance indicators (KPIs). The KPIs are structured into 18 cat- egories, which in turn are aggregated to z-scored ratings in the fol- lowing four pillars: economic, environmental, social, and corporate governance. Further details regarding the sustainability ratings of ASSET4 can be found in Ioannou and Serafeim (2012) and Chatterji et al. (2014).
1
11
23
55
74
103
135
153
157
160
0 50 100 150 200
Other
Technology
Healthcare
Energy
Non-Cyclical Consumer
Basic Materials
Telecommunica�ons
Cyclical Consumer
Industrials
U�li�es
Fig. 2. Industry distribution of bonds.
5 Bauer and Hann (2010) investigate only the environmental dimension of ESG.
C. Stellner et al. / Journal of Banking & Finance 59 (2015) 538–549 543
The environmental pillar consists of three categories: emission reduction, product innovation, and resource reduction. The gover- nance pillar comprises five categories: board functions, board structure, compensation policy, shareholders rights, and vision and strategy. The social pillar encompasses seven categories: com- munity, diversity, employment quality, health and safety, human rights, product responsibility, and training and development. We construct an equal-weighted aggregated rating from the environ- mental, social, and corporate governance pillar following Cheng et al. (2014). The economic dimension is not relevant for the ques- tions to be answered by this study.
Data on ESG country ratings is obtained from Bloomberg. Based on 36 KPIs, Bloomberg derives an overall score for more than 175 countries (as of 2010) as well as an individual score in the dimen- sions of environmental, social, and strategic governance that matches three of the four categories provided by Thomson Reuters ASSET4 ESG data.
The first set of control variables includes the following company-specific variables: revenue, EBIT margin, debt/capital, capital expenditure (capex)/revenue, return on invested capital (ROIC), EBITDA/interest expenses, and equity volatility. Revenue should be positively related to better ratings and lower spreads (see Altman, 2000). Larger companies should have the ability to cope better with fluctuations in profitability and cash flow during financial crises. More leveraged companies with higher debt/capi- tal and lower EBITDA/interest expenses ratios should be more sub- ject to default risk and have lower ratings and higher spreads (see Merton, 1974; Altman, 2000). Higher profitability (EBIT margin and ROIC) should reduce the default risk and therefore result in higher ratings and lower spreads (see Altman, 2000). We expect a high capex/revenue ratio to be related to higher ratings and lower spreads, as only financially healthy companies should be able and more likely to spend cash for capital-intensive projects, which also represent a drain on cash flow. Several studies that examine the relationship between credit spreads and equity volatility (e.g. Campbell and Taksler, 2003) indicate that higher equity volatility should be related to lower ratings and higher spreads.
Several control variables that proxy for the state of the overall economy and have proved to affect credit risk are included in both, the rating and the z-spread setup. Among others, Elton et al. (2001) show that systematic risk factors account for a large part of the variation of credit spreads. We therefore include returns of the EURO STOXX 50�, a broad Eurozone stock index. Two other power- ful indicators of the state of the economy are the level and the slope of the risk-free term structure. Longstaff and Schwartz (1995), Duffee (1998), and Collin-Dufresne et al. (2001) find a neg- ative relationship between credit spread changes and these two indicators (see also Van Landschoot, 2008). Finally, higher volatility indicates higher risk, which should be associated with lower
ratings and higher spreads (see also Cavallo and Valenzuela, 2010). We therefore include the VDAX, a German volatility index.
In the second setup that uses corporate z-spreads as the mea- sure for credit risk, we include two additional control variables: maturity, which proxies for term risk, and bid-ask spreads, which proxy for liquidity risk. We expect maturity to be positively related to z-spreads. Holding all other factors constant, the higher duration is, the later interest and principal payments have to be made, which increases risk and should translate into higher spreads (see King and Khang, 2005). The liquidity risk for asset and corpo- rate bond pricing has been investigated by several studies recently, including Acharya and Pedersen (2005), de Jong and Driessen (2006), and Lin et al. (2011). The lower the bid-ask spread is, the higher liquidity and the lower spreads should be, ceteris paribus. The bid-ask spreads used in this study have been calculated from Bloomberg bond ask and bid prices.
To answer the main questions of this paper with regard to the context-dependency of the CSP-credit risk relationship, we create several interaction terms and dummy variables. We create a dummy variable taking a value of ‘‘1’’ (the High ESG Country Rating variable) if the respective country’s overall ESG rating is above average. This dummy variable is interacted with ASSET4 company scores. Analogous to countries, we then separate the companies into two groups depending on their relative ASSET4 overall scores (above average vs. below average). We create a dummy variable (Equal Company-Country ESG Rating Segment) that takes a value of ‘‘1’’ if a company and the corresponding country are either both above average or both below average with regard to their overall ESG rating.
Table 1 provides a complete overview of all variables used in this study.
Summary statistics on bond and issuer characteristics are pro- vided in Table 2.
In the following section, results from our ordered logistic and panel regressions are presented, separated into two subsections depending on the credit risk measure utilized: rating or z-spreads.
3.3. CSP and credit risk: Ratings
As described in the section on methodology, we perform ordered logistic regressions to examine whether superior ASSET4 scores lead to a more favorable assessment of a company’s credit risk by rating agencies and systematically better ratings. Standard errors have been adjusted as per Huber (1967) and White (1980).
Table 3 shows results for five different models, including a base- line model, enhancements with different interaction terms/ dummy variables, and split samples.
Model I represents the baseline specification, including corpo- rate ratings as the dependent variable and ASSET4 scores and con- trol variables as independent variables. A negative coefficient would indicate that superior CSP would relate to better (lower) credit ratings. Interestingly, we do not find a statistically signifi- cant relationship between the two measures. While the coefficient is positive, it seems that rating agencies do not systematically include CSP in their assessment of a company’s credit quality and that ‘‘hard’’ financial ratios play a much more important role than the risk reduction mechanism described by the risk mitigating view. This is in contrast to the findings of Oikonomou et al. (2011) and Bauer and Hann (2010), who find firms with superior CSP to benefit from better ratings.5 One explanation for the diver- gent findings might be that these two studies use a US sample while our study draws a Eurozone sample. Oikonomou et al. (2011) note
Table 1 Overview of variables.
Variable Description Unit Source
Ratings Corporate rating S&P or Moody’s long-term corporate issue credit rating, ratings have been coded from ‘‘1’’ (AAA) to
‘‘7’’ (CCC) None Bloomberg/S&P
Z-spreads Corporate z-spread Corporate bond z-spread over Euro swaps curve Basis points (in
natural logs) Bloomberg
Company and country sustainability factors ESG Company Rating ASSET4 ESG Company Rating None Thomson Reuters High ESG Country Rating Dummy variable taking value of ‘‘1’’ if Bloomberg ESG Country Rating is above average in a
respective year None Bloomberg
Equal Company-Country ESG Rating Segment
Dummy variable taking value of ‘‘1’’ if both, ASSET4 ESG Company Rating and Bloomberg ESG Country Rating are either above or below average in a respective year
None Thomson Reuters/ Bloomberg
Company factors Revenue Total revenue EURbn S&P EBIT margin EBIT/Total revenue None S&P Debt/Capital (Short-term debt + long-term debt)/(Total equity + preferred equity + short-term debt + long-term
debt + minority interest) None S&P
Capex/Revenue Capex/Total revenue None S&P ROIC NOPLAT/(Total equity + preferred equity + short-term debt + long-term debt + minority interest) None S&P EBITDA/Interest expenses EBITDA/Total interest expenses None S&P Equity volatility Annualized standard deviation of continuously compounded daily stock returns for the respective
most recent year None S&P
Global/external factors EURO STOXX 50 Continuously compounded return of the EURO STOXX 50� Index Basis points Bloomberg German risk-free 3-month German sovereign bond yield Percent Bloomberg German slope 10-year German sovereign bond yield minus 3-month German sovereign bond yield Percent Bloomberg VDAX Continuously compounded return of the German VDAX volatility Index Basis points Bloomberg
Bond characteristics Maturity Time to maturity Years Bloomberg Bid-ask spread Closing ask price minus bid price divided by midpoint between ask and bid price None Bloomberg
Table 2 Summary statistics on bond and issuer characteristics.
Mean Median Standard deviation
Bond characteristics Coupon (%) 5.1 4.9 1.3 Initial time to maturity (years) 7.9 7.0 4.2 Amount issued (EURm) 818.1 750.0 514.4
Issuer characteristics Revenue (EURbn) 17.0 6.0 32.5 EBIT margin (%) 11.9 9.9 14.9 Debt/Capital (%) 49.3 46.1 29.5 Capex/Revenue (%) 10.0 5.6 14.7 ROIC (%) 7.1 6.4 5.5 EBITDA/Interest expenses 12.1� 7.1� 32.0�
This table provides summary statistics (mean, median, and standard deviation) on key bond and issuer characteristics. Information on bond and issuer characteristics is obtained from Bloomberg and S&P.
544 C. Stellner et al. / Journal of Banking & Finance 59 (2015) 538–549
that Europe might lag in the recognition of the risk-reducing benefits of investments in CSR compared to the US as Menz (2010) also finds no significant impact of CSP on credit risk using a European sample.6
Almost all company-specific control variables and variables that proxy for the state of the economy are highly statistically significant and have the expected signs throughout all five models.7
While geographical differences might be an explanation, we perform additional regressions, as we argue that the relationship is conditional on a country’s ESG performance. Model II addition- ally incorporates an interaction term between ASSET4 scores and the dummy variable High ESG Country Rating, which takes a value
6 Menz (2010) uses spreads and no ratings. 7 Only EURO STOXX 50 has a different sign than expected.
of ‘‘1’’ if the respective country scores above average with respect to ESG criteria. The interaction term proves to be highly statisti- cally significant with a negative sign, indicating that bonds’ credit ratings indeed benefit from better ratings caused by superior CSP if the corresponding country also scores above average in ESG crite- ria. This provides support for the hypothesis that the relationship is conditional on the environment that companies are operating in and that the creation of risk-reducing CSR-induced intangibles actually requires stakeholders to recognize and value CSR effort by companies. For an additional understanding of how country ESG performance moderates the relationship, we include a dummy variable in Model III that takes a value of ‘‘1’’ if the company and country ESG performance are both either above or below the aver- age. We argue that not only do bonds benefit from superior CSP if the corresponding country performs above average but also that bonds that score below average benefit from lower credit risk if the corresponding country scores below average in ESG criteria compared to non-matching company-country pairs. In line with the overinvestment view, investors reward the fact that no value-destroying investments in CSR activities are conducted in an environment that does not reward these efforts. Indeed, we find the dummy variable to be highly statistically significant with a negative sign. Bonds are better rated if the company and country ESG performance is either jointly positive or negative.
To validate these findings further, we split the sample into two groups. The first group comprises bonds assigned to countries with superior ESG performance, and the second group comprises bonds from countries with below average ESG performance. We then per- form the baseline specification in Models IV and V. The results are as expected based on the results from Model II and Model III. In the group that comprises only bonds from above average ESG coun- tries, the coefficient on ESG Company Rating is negative and highly
Table 3 Ordered logistic regression results for corporate bond ratings.
Full sample High ESG Country Rating
Yes No (I) (II) (III) (IV) (V)
Dependent variable Corporate rating Corporate rating Corporate rating Corporate rating Corporate rating
Corporate sustainability ESG Company Rating 0.0051 0.0156⁄⁄⁄ �0.0150⁄⁄⁄ 0.0167⁄⁄⁄
(0.0034) (0.0052) (0.0045) (0.0054)
Control factors Revenue �0.0479⁄⁄⁄ �0.0487⁄⁄⁄ �0.0480⁄⁄⁄ �0.0506⁄⁄⁄ �0.0460⁄⁄⁄
(0.0020) (0.0020) (0.0020) (0.0033) (0.0024) EBIT margin �8.8308⁄⁄⁄ �9.0824⁄⁄⁄ �8.7749⁄⁄⁄ �10.1320⁄⁄⁄ �7.9246⁄⁄⁄
(0.9183) (0.9314) (0.9341) (1.2789) (1.2874) Debt/Capital 4.5553⁄⁄⁄ 4.6547⁄⁄⁄ 4.6548⁄⁄⁄ 6.4693⁄⁄⁄ 3.6803⁄⁄⁄
(0.5752) (0.5765) (0.5689) (0.6133) (0.6462) Capex/Revenue �6.7156⁄⁄⁄ �6.7768⁄⁄⁄ �6.8570⁄⁄⁄ �9.8064⁄⁄⁄ �6.0762⁄⁄⁄
(0.9361) (0.9624) (0.9650) (1.1724) (1.3294) ROIC �8.4080⁄⁄⁄ �8.2850⁄⁄⁄ �8.9321⁄⁄⁄ �8.2022⁄⁄⁄ �12.8991⁄⁄⁄
(1.9525) (1.9493) (1.9532) (2.2142) (2.9042) EBITDA/Interest expenses �0.0261⁄⁄⁄ �0.0252⁄⁄⁄ �0.0241⁄⁄⁄ �0.0331⁄⁄⁄ �0.0110
(0.0079) (0.0077) (0.0077) (0.0122) (0.0092) Equity volatility 3.8947⁄⁄⁄ 3.7890⁄⁄⁄ 3.8597⁄⁄⁄ 0.8631 6.6875⁄⁄⁄
(0.5371) (0.5611) (0.5769) (0.7393) (0.6129) EURO STOXX 50 0.0402⁄⁄⁄ 0.0398⁄⁄⁄ 0.0400⁄⁄⁄ 0.0086 0.0598⁄⁄⁄
(0.0050) (0.0051) (0.0051) (0.0086) (0.0060) German risk-free �1.0653⁄⁄⁄ �1.0811⁄⁄⁄ �1.0993⁄⁄⁄ �1.2673⁄⁄⁄ �0.7770⁄⁄⁄
(0.1388) (0.1397) (0.1393) (0.2351) (0.1740) German slope �0.9293⁄⁄⁄ �0.9411⁄⁄⁄ �0.9683⁄⁄⁄ �0.8488⁄⁄⁄ �0.8888⁄⁄⁄
(0.1210) (0.1214) (0.1217) (0.2047) (0.1503) VDAX 0.0271⁄⁄⁄ 0.0274⁄⁄⁄ 0.0274⁄⁄⁄ 0.0270⁄⁄⁄ 0.0248⁄⁄⁄
(0.0036) (0.0037) (0.0037) (0.0065) (0.0045)
Interaction terms and dummy variables High ESG Country Rating 2.3364⁄⁄⁄
(0.8925) ESG Company Rating � High ESG Country Rating �0.0230⁄⁄⁄
(0.0067) Equal Company-Country ESG Rating Segment �0.4098⁄⁄⁄
(0.0912) LR Chi-square 1,168.7⁄⁄⁄ 1,161.7⁄⁄⁄ 1,203.7⁄⁄⁄ 500.8⁄⁄⁄ 784.2⁄⁄⁄
Country dummies Yes Yes Yes Yes Yes N 3,017 3,017 3,017 1,161 1,856
This table presents coefficients and standard errors from ordered logistic regressions of yearly corporate bond ratings on the prior year’s ESG company rating, control variables, and interaction terms. The control variables comprise a set of company-specific and global time-varying variables as well as country dummy variables. For reasons of clarity and readability, the country dummy variables are not reported in Table 3. ESG Company Rating � High ESG Country Rating interacts ESG Company Rating with a dummy variable taking a value of ‘‘1’’ if the respective country has an ESG country rating above the mean. Equal Company-Country ESG Rating Segment is a dummy variable taking a value of ‘‘1’’ if both ESG Company Rating and ESG Country Rating are either above or below the mean. The robust standard errors presented are corrected as suggested by Huber (1967) and White (1980). The sample period is from 2006 to 2012. The baseline regression of Model I is utilized in both Model IV and V, which split the sample into bonds from countries with an ESG country rating above or below the mean. Information is obtained from Bloomberg, S&P, and Thomson Reuters. ⁄, ⁄⁄, ⁄⁄⁄ indicate significance at the ten percent, five percent, and one percent level, respectively.
Table 4 Summary statistics on corporate z-spreads, ESG company ratings, and ESG country ratings.
Mean Median Standard deviation
Corporate bond z-spreads (basis points)
125.5 80.9 179.5
ESG Company Rating 78.3 82.4 14.5 ESG Company/Country Rating H/H or L/L H/L or L/H t(diff) Mean corporate bond z-spreads
(basis points) 114.7 131.0 �2.33
This table provides summary statistics (mean, median, and standard deviation) on corporate bond z-spreads and ESG company ratings. The lower part of the table shows the average z-spreads for bonds grouped by their relative ESG company and country ratings. ‘‘H’’ refers to above average and ‘‘L’’ to below average. T-statistics on the difference in the mean z-spreads between the two groups are provided in the third column. Information is obtained from Bloomberg and Thomson Reuters.
C. Stellner et al. / Journal of Banking & Finance 59 (2015) 538–549 545
statistically significant. Investments in CSR and a superior CSR per- formance are rewarded with better ratings, supporting the risk mitigating view. This is in clear contrast to Model V, which
comprises bonds from below average performing countries. The coefficient on ESG Company Rating is positive and highly statisti- cally significant. Firms that invest in CSR in these countries and have a high CSP are penalized with lower ratings. This is line with the overinvestment view: investments in CSR are considered value-destroying in these countries.
In the following section, we examine how z-spreads are affected by CSP and how this relationship is moderated by country ESG performance.
3.4. CSP and credit risk: z-spreads
Before outlining the results of panel regressions with z-spreads as the measure for credit risk, we present summary statistics on z-spreads and ASSET4 scores as well as average z-spreads condi- tional on two combinations of relative company ESG scores vs. rel- ative country ESG scores (high company ESG/high country ESG or low company ESG/low country ESG vs. high company ESG/low country ESG or low company ESG/high country ESG) in Table 4.
546 C. Stellner et al. / Journal of Banking & Finance 59 (2015) 538–549
The means for these groups of equal pairings (high/high or low/low vs. high/low or low/high) and corresponding t-statistics on the dif- ference between the two means are also provided.
Results from the comparison of means between the two groups indicate that companies that mirror their respective country ESG performance are rewarded with lower spreads, which is also in line with our findings from the rating setup.
Table 5 Regression results for corporate bond z-spreads.
(I) (II) (III) Dependent variable Corporate z-
spread Corporate z- spread
Corporate z- spread
Corporate sustainability ESG Company Rating �0.0019⁄ 0.0000
(0.0011) (0.0002)
Control factors Revenue �0.0056⁄⁄⁄ �0.0057⁄⁄⁄ �0.0057⁄⁄⁄
(0.0011) (0.0011) (0.0011) EBIT margin �0.8991⁄⁄ �0.9378⁄⁄ �0.9176⁄⁄
(0.4504) (0.4666) (0.4522) Debt/Capital 0.6837⁄⁄⁄ 0.6896⁄⁄⁄ 0.6771⁄⁄⁄
(0.1566) (0.1558) (0.1465) Capex/Revenue �0.5693 �0.5520 �0.5357
(0.3571) (0.3609) (0.3395) ROIC �1.9373⁄⁄ �1.8960⁄ �1.9664⁄⁄
(0.9554) (0.9664) (0.9585) EBITDA/Interest expenses �0.0021 �0.0019 �0.0018
(0.0017) (0.0017) (0.0017) Equity volatility 1.9700⁄⁄⁄ 1.9453⁄⁄⁄ 1.9887⁄⁄⁄
(0.2708) (0.2802) (0.2660) EURO STOXX 50 �0.0227⁄⁄⁄ �0.0229⁄⁄⁄ �0.0226⁄⁄⁄
(0.0035) (0.0036) (0.0035) German risk-free �0.5436⁄⁄⁄ �0.5438⁄⁄⁄ �0.5363⁄⁄⁄
(0.1139) (0.1153) (0.1099) German slope �0.1235 �0.1254 �0.1251
(0.0800) (0.0822) (0.0794) VDAX 0.0100⁄⁄⁄ 0.0100⁄⁄⁄ 0.0099⁄⁄⁄
(0.0020) (0.0020) (0.0020) Maturity 0.0624⁄⁄⁄ 0.0625⁄⁄⁄ 0.0624⁄⁄⁄
(0.0130) (0.0129) (0.0130) Bid-ask spread 97.0245⁄⁄⁄ 96.8017⁄⁄⁄ 96.7616⁄⁄⁄
(16.5467) (16.6259) (16.5047)
Interaction terms and dummy variables High ESG Country Rating 0.1694
(0.1442) ESG Company Rating � High ESG
Country Rating �0.0040⁄⁄⁄ (0.0014)
Equal Company-Country ESG Rating Segment
�0.0795⁄⁄⁄ (0.0290)
Adjusted R-squared 0.624 0.625 0.625 Country dummies Yes Yes Yes Cluster (Country � time) Yes Yes Yes N 2,952 2,952 2,952
This table presents coefficients and standard errors from pooled time-series, cross- sectional regressions of yearly corporate bond z-spreads on the prior year’s ESG company rating, control variables, and interaction terms. The full econometric specification of the baseline regression in Model I is given by ZCi;t;c ¼ a þ b1 ESGi;t�1 þ b2 W i;t�1 þ b3 Xi;t�1 þ b4 Zt�1 þ b5 Pc þ eit , where the yearly z-spread ZCi;t;c for corporate bond i at time t issued by a company from country c depends on the prior year’s ESG company rating, a set of bond-specific, time- varying variables represented by W i;t�1; a set of company-specific, time-varying variables represented by Xi;t�1; a set of global, time-varying variables represented by Zt�1 , and country dummies represented by Pc . For reasons of clarity and read- ability, the country dummy variables are not reported in Table 5. ESG Company Rating � High ESG Country Rating interacts ESG Company Rating with a dummy variable taking a value of ‘‘1’’ if the respective country has an ESG country rating above the mean. Equal Company-Country ESG Rating Segment is a dummy variable taking a value of ‘‘1’’ if both the ESG Company Rating and ESG Country Rating are either above or below the mean. Standard errors are clustered by country and time. The sample period is from 2006 to 2012. Information is obtained from Bloomberg, S&P’s, and Thomson Reuters. ⁄, ⁄⁄, ⁄⁄⁄ indicate significance at the ten percent, five percent, and one percent level, respectively.
Table 5 provides results from pooled time-series, cross-sectional regressions of corporate z-spreads on ASSET4 scores, control variables, and several interaction terms/dummy variables.
The setup for Model I is the same as for the regressions with rat- ings as the measure for credit risk, with the only difference being that maturity and the bid-ask spread are added as additional bond-specific control variables. We find a negative relationship between CSP and corporate z-spreads that is statistically signifi- cant at the ten percent level. This is the result that would be expected by the risk mitigation view. Investments in CSR and supe- rior CSP are regarded as improving the risk profile of a company. Companies that invest in CSR are able to strengthen their relation- ships with key stakeholders and to build internal resources and intangibles that provide stability and a buffer in times of downturn and should result in lower cash flow volatility (Bauer and Hann, 2010). Although the statistical significance is rather weak, this result is in line with findings from Oikonomou et al. (2011) and Bauer and Hann (2010). All control variables have the expected signs, with the vast majority being highly statistically significant. Larger, more profitable, and less leveraged companies benefit from lower spreads. If control variables that proxy for the state of the economy indicate favorable economic conditions, spreads are lower. With the exception of German slope, all variables are highly statistically significant. With regard to the bond-specific variables, Maturity and Bid-ask spread are highly statistically significant and have the expected signs—interest rate and liquidity risk increase spreads.
Model II is the equivalent to Model II in the rating setup in Table 3. Z-spreads are regressed on control variables and the vari- able ESG Company Rating � High ESG Country Rating, which inter- acts ASSET4 scores with a dummy variable for the relative ESG country performance (above vs. below average). In line with the rating setup, the coefficient is negative and statistically highly sig- nificant at the one percent level. This provides further support for the conditionality of the CSP-credit risk relationship. Companies benefit from CSR investments if they operate in a country with superior ESG performance in which their CSR-related efforts are recognized and finally transfer to credit risk-reducing economic advantages.
In Model III, which refers to Model III from Table 3, we include Equal Company-Country ESG Rating Segment, which has a value of ‘‘1’’ if the country and company ESG ratings are both either above or below average. Based on the results from tests concerning differ- ences between the means of the two groups, we would expect spreads to be lower if company efforts in CSR mirror the impor- tance of CSR-related matters in their respective countries. Results from Model III support this hypothesis. The coefficient is negative and statistically highly significant at the one percent level. In coun- tries that are high-performing with regard to ESG, companies ben- efit from investments in CSR, in line with the risk mitigation view, while in low-performing countries, they are rewarded by investors for not conducting potential value-destroying investment in CSR, which is in line with the overinvestment view. We follow Goss and Roberts (2011) and use the adjustment of Kennedy (1981) to allow the correct interpretation of the coefficient Equal Company-Country ESG Rating Segment.8 Being assigned to the group of bonds in which the company ESG matches the country ESG reduces spreads by approx. 7.7 percent compared to the reference group. Based on the mean value of corporate z-spreads in our sample of 125.5 basis points, this would transfer to a decrease in spread of approx. 9.6 basis points.
8 Adjusted coefficient: expðb � 0:5r2Þ� 1, where b is the coefficient and r is the standard error.
Table 6 2SLS regression analysis of the influence of ESG Company Rating on corporate bond z-spreads.
Full sample High ESG Country Rating
Yes No (I) (II) (III) (IV)
Dependent variable Corporate z-spread Corporate z-spread Corporate z-spread Corporate z-spread
Corporate sustainability ESG Company Rating �0.0004 0.0039⁄ �0.0037 0.0043⁄
(0.0017) (0.0022) (0.0023) (0.0023)
Control factors Revenue �0.0057⁄⁄⁄ �0.0058⁄⁄⁄ �0.0049⁄⁄⁄ �0.0073⁄⁄⁄
(0.0006) (0.0006) (0.0007) (0.0008) EBIT margin �0.9033⁄⁄⁄ �0.9688⁄⁄⁄ �1.5946⁄⁄⁄ �0.6880⁄⁄
(0.1966) (0.2035) (0.3329) (0.2817) Debt/Capital 0.6736⁄⁄⁄ 0.6752⁄⁄⁄ 0.8406⁄⁄⁄ 0.6355⁄⁄⁄
(0.1035) (0.1021) (0.1478) (0.1368) Capex/Revenue �0.5531⁄⁄⁄ �0.5124⁄⁄⁄ �0.7576⁄⁄⁄ �0.5789⁄⁄⁄
(0.1452) (0.1517) (0.2631) (0.1905) ROIC �1.9223⁄⁄⁄ �1.8448⁄⁄⁄ �1.2192⁄⁄ �1.9922⁄⁄⁄
(0.4566) (0.4548) (0.6076) (0.6770) EBITDA/Interest Expenses �0.0022 �0.0019 �0.0038 �0.0001
(0.0021) (0.0021) (0.0029) (0.0026) Equity volatility 1.9898⁄⁄⁄ 1.9653⁄⁄⁄ 1.4957⁄⁄⁄ 2.4740⁄⁄⁄
(0.1623) (0.1645) (0.2244) (0.1960) EURO STOXX 50 �0.0226⁄⁄⁄ �0.0228⁄⁄⁄ �0.0309⁄⁄⁄ �0.0166⁄⁄⁄
(0.0015) (0.0015) (0.0022) (0.0019) German risk-free �0.5363⁄⁄⁄ �0.5317⁄⁄⁄ �0.4837⁄⁄⁄ �0.6079⁄⁄⁄
(0.0589) (0.0589) (0.0842) (0.0775) German slope �0.1199⁄⁄ �0.1203⁄⁄ �0.0485 �0.2176⁄⁄⁄
(0.0561) (0.0561) (0.0780) (0.0737) VDAX 0.0100⁄⁄⁄ 0.0098⁄⁄⁄ 0.0083⁄⁄⁄ 0.0113⁄⁄⁄
(0.0012) (0.0012) (0.0018) (0.0015) Maturity 0.0623⁄⁄⁄ 0.0625⁄⁄⁄ 0.0924⁄⁄⁄ 0.0569⁄⁄⁄
(0.0043) (0.0044) (0.0085) (0.0047) Bid-ask spread 97.1927⁄⁄⁄ 96.9453⁄⁄⁄ 96.8737⁄⁄⁄ 86.3204⁄⁄⁄
(9.9575) (9.9311) (15.6199) (11.0129)
Interaction terms and dummy variables High ESG Country Rating 0.3581
(0.2751) ESG Company Rating � High ESG Country Rating �0.0066⁄⁄
(0.0030) Adjusted R-squared 0.624 0.623 0.652 0.619 Country dummies Yes Yes Yes Yes N 2,952 2,952 1,189 1,763
This table presents coefficients and standard errors from second stage regressions from a 2SLS regression analysis of the influence of ESG Company Rating on corporate bond z-spreads which include the instrumented values of ESG company rating as independent variable. ESG Company Rating is instrumented with the average ESG company rating of all other companies in the same country in the same year. For reasons of clarity and readability, the country dummy variables are not reported in Table 6. ESG Company Rating � High ESG Country Rating interacts ESG Company Rating with a dummy variable taking a value of ‘‘1’’ if the respective country has an ESG country rating above the mean. The sample period is from 2006 to 2012. The baseline regression of Model I is utilized in both Model III and IV, which split the sample into bonds from countries with an ESG Country Rating above or below the mean. Information is obtained from Bloomberg, S&P’s, and Thomson Reuters. ⁄, ⁄⁄, ⁄⁄⁄ indicate significance at the ten percent, five percent, and one percent level, respectively.
9 Jiraporn et al. (2014) use a similar instrument. 10 There is no regression similar to Model III from Table 5 as the variable Equa
Company-Country ESG Rating Segment cannot be instrumented with the average ESG company rating of all other companies in the same country in the same year as in the other models.
C. Stellner et al. / Journal of Banking & Finance 59 (2015) 538–549 547
3.5. Further analysis and robustness checks
In this section, we report the results from a bunch of robustness checks, in particular to mitigate concerns of reverse causality or other types of endogeneity.
We run each model with year dummies and with industry dum- mies, the results are robust. Chatterji et al. (2014) suggest that studies need to validate their results using multiple ratings or proxies. We replicate all our results with ESG indicators provided by another European ESG rating agency and receive significant results that are consistent with our previous outcomes.
As outlined in Section 3.1, we lag the independent variables by one period to account for potential problems with endogeneity. As additional robustness check, we lag ESG company ratings also by two and three periods in the rating setup with no change in the overall results. In the z-spread setup, we employ a two-stage least squares (2SLS) regression analysis. Jiraporn et al. (2014) suggest using this instrumental variable (IV) technique as one possible
solution to the endogeneity problem. We instrument ESG Company Rating with the average ESG company rating of all other companies in the same country in the same year.9 Results are presented in Table 6, while for reasons of brevity only the results of the second stage regressions, which include the instrumented values of ESG Company Rating as independent variable are shown.10
Our findings confirm our hypothesis: The relationship between CSP and credit risk (measured by z-spreads) is moderated by the country in which the respective company is located: There is no significant connection between ESG Company Rating and corporate z-spread per se (Model I). However, in Model II the interaction term ESG Company Rating � High ESG Country Rating remains statistically sig-
l
548 C. Stellner et al. / Journal of Banking & Finance 59 (2015) 538–549
nificant; companies with superior ESG performance are rewarded with lower z-spreads if they are located in a country that has above-average ESG performance. In Models III and IV, we split the sample into two groups, countries with superior ESG perfor- mance (III) and countries with below average ESG performance (IV). The coefficient on [ESG Company Rating] of Model IV is positive and significant confirming our previous results: In line with the overinvestment view, we find that companies investing in CSR in these countries are penalized with lower ratings. In Model III, the coefficient of ESG Company Rating has the correct sign (negative), but is not significant anymore.
In addition, we re-run our baseline specification combining the different robustness check specifications. For example, we repli- cated our research using ESG scores from another European rating agency in a 2SLS regression analysis. Our results survive this bat- tery of robustness tests: We find results (unreported) that are qual- itatively similar to our outcomes so far.
4. Summary and conclusion
In this study, we examine whether corporate sustainability reduces a company’s credit risk, measured by ratings or corporate z-spreads. Only a limited number of studies investigate the CSP-CFP relationship with credit risk as the dependent variable. In addition, findings from these studies are very divergent and point only slightly toward a weak negative relationship between the two. This would be in line with the perspective of the risk mit- igating view that companies can reduce their risk profile by engag- ing in CSR spending that helps to develop and maintain close relationships to key stakeholders and the subsequent creation of valuable internal resources and intangibles. In contrast, the overin- vestment view implies that companies will have lower ratings and higher spreads if their investments in CSR are regarded as a waste of scarce resources, often to the personal benefit of senior manage- ment at the expense of the company. We are particularly inter- ested if the relationship is conditional on the ESG performance of the corresponding country where the company is located. Rational investors should consider investments in CSR as value-enhancing and risk-reducing only if the marginal benefits exceed the marginal costs of these investments. As already shown on the industry level, we would argue that companies can create valuable resources and intangibles only to the extent that their efforts are rewarded by stakeholders in the environment in which the company is embedded.
Based on a sample of 872 bonds from twelve countries of the EMU between 2006 and 2012, we find support for our hypotheses. While there is only statistically weak support for the unconditional benefits of CSR investments in the z-spread setup, we show that superior CSP is rewarded in countries with above average ESG per- formance in the rating as well as in the z-spread setup. In addition, we find that companies benefit from better ratings and lower spreads if their relative ESG performance (above vs. below average) matches those of the corresponding country (above vs. below aver- age). Being a high ESG performing company in an environment that rewards investments in CSR or vice versa can reduce spreads by approx. 7.7% compared to companies whose CSR performance does not mirror those of the corresponding country.
There are several natural possible extensions of this study. It would be interesting to conduct the same analyses performed in this study with ASSET4 ratings disaggregated into individual scores for the environment, social, and corporate governance dimensions and to verify how the context-dependency of the CSP-credit risk relationship relates to the individual dimensions. In addition, it would also be interesting to investigate which operationalization of ‘‘environment’’ is more successful in moderating the CSP-credit risk relationship. Is supranational industry classification
more important than individual country factors? Answers to these questions would further help to understand this relationship better.
Future research may also investigate which economic and insti- tutional conditions drive our results. This could be done based on the work of Campbell (2007), who develops an institutional theory of CSR and proposes several economic and institutional conditions that drive socially responsible corporate behavior. It would be interesting to see which country-specific factors like ‘‘state regula- tions demanding that firms act in socially responsible ways’’ or ‘‘existence of NGOs’’ are linked to our results.
References
Acharya, V.V., Pedersen, L.H., 2005. Asset pricing with liquidity risk. Journal of Financial Economics 77, 375–410.
Alexander, G.J., Buchholz, R.A., 1978. Corporate social responsibility and stock market performance. Academy of Management Journal 21, 479–486.
Altman, E., 2000. Predicting financial distress of companies: revisiting the Z-score and Zeta� models. Working paper, New York University, Stern School of Business.
Ashbaugh-Skaife, H., Collins, D.W., LaFond, R., 2006. The effects of corporate governance on firms’ credit ratings. Journal of Accounting and Economics 42, 203–243.
Aupperle, K., Carroll, A., Hatfield, J., 1985. An empirical examination of the relationship between corporate social responsibility and profitability. Academy of Management Journal 28, 446–463.
Avadanei, A., 2010. European corporate bond market integration: lessons from EMU. MPRA Paper No. 27309. Available from: http://mpra.ub.uni-muenchen. de/27309/1/MPRA_paper_27309.pdf.
Baran, L.C., Zhang, C.X., 2012. KLD 400 Index Inclusion and Corporate Bonds. Midwest Finance Association 2013, Annual Meeting Paper.
Barnea, A., Rubin, A., 2010. Corporate social responsibility as a conflict between shareholders. Journal of Business Ethics 97, 71–86.
Bassen, A., Meyer, K., Schlange, J., 2006. The Influence of Corporate Responsibility on the Cost of Capital. Working paper, Available at SSRN: http://papers. ssrn.com/sol3/papers.cfm?abstract_id=984406.
Bauer, R., Derwall, J., Hann, D., 2009. Employee Relations and Credit Risk. Working paper, European Centre for Corporate Engagement (ECCE).
Bauer, R., Hann, D., 2010. Corporate Environmental Management and Credit Risk. Working paper, European Centre for Corporate Engagement (ECCE).
Bhojraj, S., Sengupta, P., 2003. Effect of corporate governance on bond ratings and yields: the role of institutional investors and outside directors. Journal of Business 76, 455–475.
Bradley, M., Chen, D., Dallas, G., Snyderwine, E., 2007. The Relation Between Corporate Governance and Credit Risk, Bond Yields and Firm Valuation. Working paper, Duke University.
Campbell, J.L., 2007. Why would corporations behave in socially responsible ways? An institutional theory of corporate social responsibility. Academy of Management Review 32, 946–967.
Campbell, J.Y., Taksler, G.B., 2003. Equity volatility and corporate bond yields. Journal of Finance 58, 2321–2350.
Cavallo, E.A., Valenzuela, P., 2010. The determinants of corporate risk in emerging markets: an option-adjusted spread analysis. International Journal of Finance & Economics 15, 59–74.
Chatterji, A., Durand, R., Levine, D., Touboul, S., 2014. Do ratings of firms converge? Implications for strategy research. Strategic Management Journal, forthcoming.
Chava, S., 2011. Environmental Externalities and Cost of Capital. Working paper, College of Management, Georgia Institute of Technology.
Chen, H., Kacperczyk, M., Ortiz-Molina, H., 2012. Do nonfinancial stakeholders affect the pricing of risky debt? Evidence from unionized workers. Review of Finance 16, 347–383.
Cheng, B., Ioannou, I., Serafeim, G., 2014. Corporate social responsibility and access to finance. Strategic Management Journal 35, 1–23.
Collin-Dufresne, P., Goldstein, R.S., Martin, J.S., 2001. Determinants of credit spread changes. Journal of Finance 56, 2177–2208.
De Jong, F., Driessen, J., 2006. Liquidity risk premia in corporate bond markets. Working paper, Tilburg University and University of Amsterdam.
Duffee, G.R., 1998. The relation between treasury yields and corporate bond yield spreads. Journal of Finance 53, 2225–2241.
Elton, E.J., Gruber, M.J., Agrawal, D., Mann, C., 2001. Explaining the rate spread on corporate bonds. Journal of Finance 56, 247–277.
Fabozzi, F.J., Choudhry, M., 2004. The Handbook of European Fixed Income Securities. John Wiley & Sons, Hoboken, NJ.
Flammer, C., 2013. Does Corporate Social Responsibility Lead to Superior Financial Performance? A Regression Discontinuity Approach. Working paper, MIT Sloan School of Management.
Friedman, M., 1962. Capitalism and Freedom. University of Chicago Press, Chicago, IL. Friedman, M., 1970. The social responsibility of business is to increase its profits.
The New York Times Magazine 13, 32–33. Frooman, J., Zietsma, C., McKnight, B., 2008. There is no good reason not to be good.
Administrative Science Association of Canada (ASAC), Halifax, Nova Scotia.
C. Stellner et al. / Journal of Banking & Finance 59 (2015) 538–549 549
Ge, W., Liu, M., 2012. Corporate Social Responsibility and the Cost of Corporate Bonds. Working paper, University of Manitoba.
Godfrey, P.C., 2005. The relationship between corporate philanthropy and shareholder wealth: a risk management perspective. Academy of Management Review 30, 777–798.
Goll, I., Rasheed, A.A., 2004. The moderating effect of environmental munificence and dynamism on the relationship between discretionary social responsibility and firm performance. Journal of Business Ethics 49, 41–54.
Goss, A., Roberts, G.S., 2011. The impact of corporate social responsibility on the cost of bank loans. Journal of Banking and Finance 35, 1794–1810.
Graham, A., Maher, J.J., Northcut, W.D., 2001. Environmental liability information and bond ratings. Journal of Accounting, Auditing & Finance 16, 93–116.
Griffin, J.J., 2000. Corporate social performance: research directions for the 21st century. Business & Society 39, 479–491.
Hart, S.L., 1995. A natural resource-based view of the firm. Academy of Management Review 20, 986–1014.
Hillman, A.J., Keim, G.D., 2001. Shareholder value, stakeholder management, and social issues: what’s the bottom line? Strategic Management Journal 22, 125–139.
Huber, P.J., 1967. The behavior of maximum likelihood estimates under nonstandard conditions. Proceedings of the fifth Berkeley symposium on mathematical statistics and probability. University of California Press, Berkeley, pp. 221–233.
Ioannou, I., Serafeim, G., 2012. What drives corporate social performance? The role of nation-level institutions. Journal of International Business Studies 43, 834–864.
Izzo, M.F., Magnanelli, B.S., 2012. Does It Pay or does Firm Pay? The Relation between CSR Performance and the Cost of Debt. Available at SSRN: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1986131.
Jiraporn, P., Jiraporn, N., Boeprasert, A., Chang, K., 2014. Does corporate social responsibility (CSR) improve credit ratings? Evidence from geographic identification. Financial Management 43, 505–531.
Jones, T.M., 1995. Instrumental stakeholder theory: a synthesis of ethics and economics. Academy of Management Review 20, 404–437.
Kennedy, P.E., 1981. Estimation with correctly interpreted dummy variables in semilogarithmic equations. The American Economic Review 71, 801.
Kim, M., Surroca, J., Tribó, J.A., 2009. The Effect of Social Capital on Financial Capital. Working paper. Business Economic Series. Wp.09-02.
King, T.-H.D., Khang, K., 2005. On the importance of systematic factors in explaining the cross-section of corporate bond yield spreads. Journal of Banking and Finance 29, 3141–3158.
Klock, M.S., Mansi, S.A., Maxwell, W.F., 2005. Does corporate governance matter to bondholders? Journal of Financial and Quantitative Analysis 40, 693–719.
Laganá, M., Peřina, M., von Köppen-Mertes, I., Persaud, A., 2006. Implications for liquidity from innovation and transparency in the European corporate bond market. European Central Bank Occasional Paper Series, No. 50. Available from: http://www.ecb.europa.eu/pub/pdf/scpops/ ecbocp50.pdf.
Lin, H., Wang, J., Wu, C., 2011. Liquidity risk and expected corporate bond returns. Journal of Financial Economics 99, 628–650.
Longstaff, F.A., Schwartz, E., 1995. A simple approach to valuing risky fixed and floating rate debt. Journal of Finance 50, 789–820.
Margolis, J.D., Elfenbein, H.A., Walsh, J.P., 2009. Does it Pay to be Good... and does it Matter—A Meta-Analysis of the Relationship between Corporate Social and Financial Performance. Available at SSRN: http://papers.ssrn.com/sol3/papers. cfm?abstract_id=1866371.
Menz, K.M., 2010. Corporate social responsibility: is it rewarded by the corporate bond market? A critical note. Journal of Business Ethics 96, 117–134.
Merton, R.C., 1974. On the pricing of corporate debt: the risk structure of interest rates. Journal of Finance 29, 449–470.
Oikonomou, I., Brooks, C., Pavelin, S., 2011. The Effects of Corporate Social Performance on the Cost of Corporate Debt and Credit Ratings. ICMA Centre Discussion Papers in Finance DP2011-19. Available at SSRN: http://papers. ssrn.com/sol3/papers.cfm?abstract_id=1944164.
Orlitzky, M., Schmidt, F.L., Rynes, S.L., 2003. Corporate social and financial performance: a meta-analysis. Organization Studies 24, 403–411.
Pagano, M., von Thadden, E.-L., 2004. The European bond markets under EMU. Oxford Review of Economic Policy 20, 531–554.
Petersen, M.A., 2009. Estimating standard errors in finance panel data sets: comparing approaches. The Review of Financial Studies 22, 435–480.
Pirinsky, C., Wang, Q., 2010. Geographic location and corporate finance: a review. Handbook of emerging issues in corporate governance. World Scientific Publishing.
Schneider, T.E., 2011. Is environmental performance a determinant of bond pricing? Evidence from the U.S. pulp and paper and chemical industries. Contemporary Accounting Research 28, 1537–1561.
Sharfman, M.P., Fernando, C.S., 2008. Environmental risk management and the cost of capital. Strategic Management Journal 29, 569–592.
Spicer, B.H., 1978. Investors, corporate social performance and information disclosure: an empirical study. The Accounting Review 53, 94–111.
Surroca, J., Tribó, J.A., Waddock, S., 2010. Corporate responsibility and financial performance: the role of intangible resources. Strategic Management Journal 31, 463–490.
Van Beurden, P., Gössling, T., 2008. The worth of values: a literature review on the relation between corporate social and financial performance. In: Journal of Business Ethics 82, The European Identity in Business and Social Ethics: The Eben 20th Annual Conference in Leuven, pp. 407–424.
Van Landschoot, A., 2008. Determinants of yield spread dynamics: euro versus US dollar corporate bonds. Journal of Banking and Finance 32, 2597–2605.
Waddock, S.A., Graves, S.B., 1997. The corporate social performance-financial performance link. Strategic Management Journal 18, 303–319.
White, H., 1980. A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 48, 817–838.
- Corporate social responsibility and Eurozone corporate bonds: The moderating role of country sustainability
- 1 Introduction
- 2 Related literature
- 2.1 CSR and credit risk
- 2.2 Environmental performance and credit risk
- 2.3 Employees and credit risk
- 2.4 Corporate governance and credit risk
- 2.5 What moderates the relationship between CSR and CFP?
- 2.6 The impact of geographic location on stakeholders preferences
- 3 Main empirical tests
- 3.1 Methodology
- 3.2 Sample overview and data description
- 3.3 CSP and credit risk: Ratings
- 3.4 CSP and credit risk: z-spreads
- 3.5 Further analysis and robustness checks
- 4 Summary and conclusion
- References
#144.pdf
Business & Society 2016, Vol. 55(4) 576 –593
© The Author(s) 2013 Reprints and permissions:
sagepub.com/journalsPermissions.nav DOI: 10.1177/0007650313500216
bas.sagepub.com
Research Note
Socially Responsible Investment in France
Patricia Crifo1,2,3 and Nicolas Mottis2,4
Abstract Socially responsible investment (SRI) in France is based on a “best in class” approach as opposed to the “exclusion” approaches used in other countries such as the United States or United Kingdom, where the rejection of sin stocks has been dominant historically. The objective of this research note is to examine whether the French SRI market, by focusing more on financial rather than on ethical considerations, compared with other countries such as the United States, the United Kingdom, or even Sweden, may lead to a form of “mainstreaming” of SRI processes. The authors explore several convergent mechanisms. First, the authors analyze the importance of the mainstreaming issue in the history of SRI as well as in the contemporaneous debate in the academic literature on the links between financial and extrafinancial (SRI) performance. Second, the authors review the role played by ethical finance laws adopted in France in the early 2000s in the development of the SRI market. Finally, the authors discuss the results of a survey of French SRI analysts working both for large institutional investors and asset managers in France in 2009.
Keywords socially responsible investments, France, mainstreaming, asset management, ESG performance
1Université Paris Ouest Nanterre La Défense, France 2Ecole Polytechnique, Palaiseau Cedex, France 3Center for Interuniversity Research and Analysis on Organizations, Montréal, Québec, Canada 4ESSEC Business School, Cergy-Pontoise Cedex, France
Corresponding Author: Patricia Crifo, University Paris West Nanterre la Defense, Ecole Polytechnique & CIRANO (Montreal); Ecole Polytechnique Department of Economics, Route de Saclay, 91120 Palaiseau Cedex, France. Email: [email protected]
The article was accepted during the editorship of Duane Windsor.
500216BAS55410.1177/0007650313500216Business & SocietyCrifo and Mottis research-article2013
at Northcentral University on June 30, 2016bas.sagepub.comDownloaded from
Crifo and Mottis 577
In the United States or Europe, up to one dollar out of nine incorporates a socially responsible dimension that considers not only financial performance but also extrafinancial performance criteria in the investment decision pro- cess (European Fund Asset Management Association, 2008; European Sustainable Investment Forum [Eurosif], 2008; Social Investment Forum [now U.S. SIF—Forum for Sustainable and Responsible Investment], 2008). Consequently, the potential impact of socially responsible investment (SRI) decisions on firms’ nonfinancial policies and performance can be a very pow- erful mechanism to influence business practices. The evolution of SRI mar- kets is therefore an important issue for business ethics and corporate social responsibility (Scholtens, 2006). In most industrialized countries, SRI has tended to grow from a niche market of individual ethical investors to embrace institutional investors (e.g., pension funds) resulting, for instance, in the United Kingdom in £764 billion in assets under management (Eurosif, 2008; see Lewis & Juravle, 2010).
Considerable attention has been given in the academic literature to the issue of SRI performance. According to the “doing well by doing good” argu- ment, by relying on sound ESG (environmental, social, and governance) risk management, SRI strategies would positively impact performance. In con- trast, according to the “whatever is better is worth a premium” argument, imposing nonfinancial screens reduces diversification, thereby adversely affecting performance. Despite many years of academic studies, no consensus has emerged so far on whether corporate social responsibility (CSR) leads to superior financial performance. (For a review of results from these empirical studies, see Margolis & Walsh, 2003; Margolis, Elfenbein, & Walsh, 2007.)
In turn, rather than focusing on SRI outperformance or underperformance, a growing number of studies have recently started to document the varieties of practices and principles of SRI in different countries. One striking feature of these studies is that, relying on a historical and social movement perspec- tive, a common trend seems to characterize the history of many different markets, in particular Anglo-Saxon, Scandinavian, or Continental European, namely, the transition from niche funds to broad-based SRI (Arjaliès, 2010; Bengtsson, 2008; Louche & Lydenberg, 2006).
This research note contributes to this literature on sustainable finance by presenting an overview of SRI in France and discussing whether SRI is becoming “mainstream” in this specific market. This so-called mainstream- ing movement refers to the fact that traditional actors of the asset manage- ment (AM) industry would integrate into their analysis and decision-making processes the ESG criteria formerly only produced and used by SRI actors.
Although research on comparative national varieties of SRI has received an important attention in the literature, only a few papers focus on the French
at Northcentral University on June 30, 2016bas.sagepub.comDownloaded from
578 Business & Society 55(4)
SRI market (see Arjaliès, 2010; Déjean, Giamporcaro, Gond, Leca, & Penalva-Icher, 2013; Eurosif, 2006, 2008; Louche & Lydenberg, 2006).
Hence, the value-added contribution of this research note for the literature on SRI is twofold. First, it contributes to the understanding of national variet- ies of SRI by gathering observations from the French market structure and legislation, as well as from the perceptions of some French SRI analysts themselves. Second, relying on the French example, it contributes to the debate on nationally idiosyncratic, socially responsible investing regarding the issue of SRI mainstreaming.
This research note is organized as follows. We first document the impor- tance of the debate in the academic literature on the links between financial and extrafinancial performance for the issue of SRI mainstreaming. We then examine the specificities of the French SRI market, namely, its recent evolu- tion and the role played by ethical finance laws adopted in France in the early 2000s. The research note finally reports the results of a field survey of French SRI analysts.
SRI Mainstreaming: History and Literature Review
Brief Historical Insight into SRI Funds
The history of socially responsible investment in Europe and in the United States offers interesting insights into the mainstreaming of SRI processes.
Ethical funds appeared in the United States in the 1920s, relying on the religious values of their promoters—religious congregations—and excluding firms belonging to the alcohol, gambling, pornography, tobacco, and weap- ons sectors. Socially responsible funds developed in the 1960s, relying on the moral values, not necessarily religious, of their promoters—trade unions, nongovernmental organizations (NGOs), and consumers associations—and applying selection criteria based on human resources, environment, and product quality. Unlike ethical funds or socially responsible funds, sustain- able development funds developed since the 1990s on the basis of an analysis of long-run performance and sustainable growth. (The reader should see the description of the history of SRI in Reference Louche & Lydenberg, 2006.) These sustainable development funds apply selection criteria with an objec- tive of a long-run return associated with lower volatility. They target pension funds and may embed shareholder engagement, suggesting that the main- streaming of SRI into conventional financial analyses could become a key point to promote sustainable development goals on financial markets.
Hence, the past two decades tended to witness a shift from an activist SRI movement to a commercial project (Louche, 2004), and SRI is no longer
at Northcentral University on June 30, 2016bas.sagepub.comDownloaded from
Crifo and Mottis 579
restricted to ethical funds but rather involves a mainstream investment strat- egy (McCann, Solomon, & Solomon, 2003).
In this retrospect, European markets deserve close attention. Not only do the assets under management with extrafinancial criteria grow rapidly and already represent several dozens of billion of euros, but also the conventional funds which admittedly refer to these criteria continuously increase (Novethic, 2009a).
More fundamentally, unlike Anglo-Saxon countries where SRI originally developed for ethical reasons, SRI in Continental European countries has fol- lowed a financial approach based on the development of positive screening methods relying on extrafinancial—environment, social, and governance— criteria (Déjean, 2006).
The French asset management industry is one of the largest in the world with assets under management exceeding €2.6 trillion at end of December 2010. France’s SRI market is of particular interest as it is the most dynamic and successful in Europe (Eurosif, 2008). Moreover, the development of the French SRI market was mostly based on “positive” or “best-in-class” approaches consisting in selecting the most socially responsible companies whatever their sector (Arjaliès, 2010) and explicitly aiming at diffusing to the conventional asset management sector (Europlace, 2008).
SRI Mainstreaming in the Literature
The rapid growth of sustainable investments and the shift in SRI from margin to mainstream has been documented recently (Louche & Lydenberg, 2006; Schueth, 2003; Sparkes & Cowton, 2004).
From a theoretical perspective, examining the mainstreaming of SRI pro- cesses is rooted in the abundant literature on the links between financial per- formance and corporate social responsibility (see Capelle-Blancard & Monjon, 2012; Margolis, Elfenbein, & Walsh, 2007; Mercer, 2009; UN Environment Programme Finance Initiative [UNEP-FI] & Mercer, 2007).
This literature focuses on the trade-off between different types of perfor- mances. One possibility is that environmental or social performance improves to the detriment of classical financial performance, for instance, measured by shareholder value creation. Another possibility is that both types of perfor- mances are correlated, in the short run, or at least in the long run.
Despite the considerable attention devoted to this issue in the academic literature over the past decades, no consensus has emerged so far. A brief comparison of SRI indices and conventional stock market indices does not reveal underperformance or superior performance. For example, Figure 1 represents one of the leading SRI indices, the “ASPI Eurozone” relative to the Dow Jones Euro Stoxx.
at Northcentral University on June 30, 2016bas.sagepub.comDownloaded from
580 Business & Society 55(4)
Analyzing the “mainstreaming” of SRI decision processes offers an inter- esting and novel contribution to this debate. In fact, following a mainstream strategy may mean that extrafinancial criteria at the root of SRI would be considered as additional means to obtain a higher financial performance (Azoulay & Zeller, 2006). But then, because it is valuable, it seems consistent to assume that there is a price to pay—perhaps in the form of underperfor- mance—to socially responsible investing (Voisin & Jeaneau, 2010).
In turn, observing a convergence between SRI and traditional asset man- agement leads to reframing the question of SRI performance. Convergence implies both that SRI criteria are perceived by investors as leading to higher financial performance and that because it is valuable, there is a price to SRI.
The economics literature raises another important argument related to the costs of corporate social responsibility and the conflict of interests between shareholders and managers and the objective functions of both parties. Simply stated, this literature raises the issue of at which level CSR should be implemented and who should bear its cost. CSR might be the initiative of CEOs or of shareholders. In other words, the literature raises the question of who should best be in charge of corporate social responsibility.
For Friedman (1970), the social responsibility of business is to act in the name of owners (shareholders), that is, to ensure firm profitability: “to use its resources and engage in activities designed to increase its profits so long as it stays within the rules of the game, which is to say, engages in open and free competition without deception or fraud.” If managers spend corporate resources in a different way than stockholders would expect, they are in fact imposing taxes on shareholders and deciding without legitimacy how this tax revenue shall be spent, whereas nobody has the legitimacy to tax or substitute oneself to an elected government in charge of public goods. In this approach,
Figure 1. Compared performance of ASPI Eurozone and Dow Jones Euro Stoxx Indices.
at Northcentral University on June 30, 2016bas.sagepub.comDownloaded from
Crifo and Mottis 581
managers and shareholders are in an agency relationship in which sharehold- ers own the firm capital and act as principals toward managing directors, who act as agents whose duties are to serve the principal’s interests. If sharehold- ers wish to pursue social goals, they should do so by spending their own revenues rather than through corporate social responsibility.
More recently, Cespa and Cestone (2007) show that leaving CSR in the hands of managers may favor the emergence of an entrenchment strategy for the least efficient ones. The key argument is that referring to nonfinancial performance metrics may lead to undue justifications of any kind of decisions and a lack of financial performance. To increase the value of investing in the corresponding firm, shareholders thus should take in charge CSR issues: They should invest in SRI, to prevent such entrenchment strategies. In this view, SRI mainstreaming could take place.
For Baron (2009), consumers’ warm glow preferences for personal giving to social causes can help reconcile managers and shareholders’ interests. Indeed, such warm glow preferences motivate managers to adopt CSR strate- gies, without imposing costs on shareholders. Strategic CSR therefore is not incompatible with shareholder value maximization. In this view, SRI may exist as a niche market, targeted toward consumers caring for social causes.
Accounting for social responsibility within asset management then becomes a real challenge concerning whether CSR criteria should be left to specialized funds designed to niche markets (mutual funds, pension funds with social objectives, etc.) or could add value to conventional asset management, mainly relying on traditional strategic and financial analyses. In other words, a key empirical question is whether SRI will converge toward mainstream asset man- agement or whether both types of asset management will continue a kind of parallel trajectory for clearly segmented clients and investors.
Is SRI Becoming Mainstream in France?
The evolution of the French market offers interesting insights into this debate. First, to develop the specifics of the French SRI market and examine the relevance of SRI mainstreaming in this context, we present a brief overview of the market size and legislation in France. Second, we report the results of a survey conducted on some French SRI analysts, and which offers an origi- nal perspective
SRI in France: Market Size and Legislation
The French market for SRI amounted to €30 billion in 2008, including €22.5 billion for institutional investors (Novethic, 2009a).
at Northcentral University on June 30, 2016bas.sagepub.comDownloaded from
582 Business & Society 55(4)
In this market, there are many signals showing that an increasing number of French mainstream investors (“traditional” investors usually only focused on financial performance) are now integrating SRI criteria, into their so- called SRI funds and their conventional funds as well. In particular, in 2009, 63% of the French conventional funds in terms of assets integrated at least one SRI criterion. In contrast, the “pure” SRI funds themselves represented only 2% of the assets under management (Novethic, 2009b). So even if this segment remains limited, the influence of ESG criteria on asset management goes far beyond SRI funds.
Several laws starting in the late 1990s played an important role in the development of long-term investing and SRI in France and may help explain the emergence of SRI mainstreaming in this context. The same enactments have occurred in many Organisation for Economic Co-Operation and Development (OECD) countries (see de Brito, Desmartin, Lucas-Leclin, & Perrin, 2001; Scott, 2001).
The first set of laws directly promoted long-term investing and SRI on the French market. In 1999, the French government created (with the decree of July 2001) a Pension Trust Fund (Fonds de Réserve des Retraites or FRR) whose main objective was to introduce some public funding in the “pay as you go” basic pension scheme to cope with its expected financial nonsustain- ability within the next decade. More precisely, the FRR has been granted a dedicated SRI policy: its “responsible investment” strategy in fact explicitly encourages mainstream investment managers to adopt responsible invest- ment practices, and relies on SRI mandates that integrate ESG (environmen- tal, social, and governance) issues into investment decision making and portfolio management. The creation of the FRR in turn explains to a large extent the entry of mainstream actors in the French SRI market. Indeed, in 2005, the FRR put out a request for proposal that included several mandates for investment managers with expertise in SRI. The 5-year mandates are for European equities and to an aggregate sum of US$800 million. The mandates required the integration of ESG issues into investment decision making on a best-in-class basis (see UNEP-FI & UK Social Investment Forum, 2007).
The corresponding rise in the demand for SRI induced by the FRR’s SRI policy was accompanied by the “Fabius law” of February 2001 (institutional- ized by the “Fillon law” on pensions of August 2003). These laws established a “voluntary partnership employee savings scheme” (Plan partenarial d’épargne salariale volontaire or PPESV) with the sums invested frozen for a 10-year period (as opposed to the 5 years in the usual employee savings scheme) thereby developing a long-term perspective on savings and thus on SRI demand.
This rise in demand on the SRI market was also confirmed by the creation in 2001 of the Comite Intersyndical de l’Epargne Salariale (Committee of the
at Northcentral University on June 30, 2016bas.sagepub.comDownloaded from
Crifo and Mottis 583
Inter-Union Employee Savings or CIES), which provided a trade union “SRI label” to a range of SRI employee saving funds. In fact, to obtain the CIES label, asset management companies have to devote internal resources to SRI. The first SRI analysis department was created in 2002 (see Arjaliès, 2010).
A second set of laws contributed to the development of the French SRI market by promoting more transparency and information to investors, by focusing on corporate responsibility reporting. The Nouvelles Régulations Economiques (New Economic Regulations or NRE) law of July 2001 (Article 116) obliges all companies listed on the first market (the largest market capi- talizations) to report on a yearly basis on the social and environmental impacts of their activities. There are four sections to the Paris Stock Exchange: The first market (generally referred to as the official list) is composed of the largest publicly traded companies; the second market is made up of medium- sized companies; the new market covers new companies that are quickly expanding and need to access capital to fund this expansion; and other securi- ties come under the free market.
In 2011, the Grenelle II law extended the reporting obligation to two types of actors. (The Grenelle I law followed the “Grenelle environnement”—a conference held in 2007 bringing together the government, local authorities, trade unions, business, and voluntary sectors to draw up a plan of action of concrete measures to tackle the environmental issue.) Article 225 expands the perimeter of corporations concerned by mandated disclosure not only to listed companies but also to other nonlisted large French companies with over 500 employees and French subsidiaries of foreign companies. It also expands the range of information required, and requests external verification. Moreover, Article 224 expands disclosure requirements to asset managers and open-ended collective investment companies (Organismes de placement collectif en valeurs mobilières or OPCVM) as well. In fact, asset manage- ment companies now have to disclose whether an SRI policy is in place, by reporting to which extent social, environmental, or ethical considerations are taken into account in the selection, retention, and realization of investment.
As a consequence, since the early 2000s, the diffusion of SRI into French mainstream asset management is gaining momentum, thanks to significant legislative changes.
SRI Mainstreaming in France: Results From a Field Survey on French SRI Analysts
To document the debate on the issue of SRI mainstreaming in France, we conducted a “field survey” which was sent to French asset management com- panies, with the support of the French Asset Management Association (AFG)
at Northcentral University on June 30, 2016bas.sagepub.comDownloaded from
584 Business & Society 55(4)
and the Chair for Sustainable Finance and Responsible Investment (Finance Durable et Investissement responsible or FDIR). The Chair FDIR was cre- ated in 2007 by French asset management companies and institutional inves- tors engaged in the areas of responsible investment and sustainable finance to contribute to the emergence of new valuation models that take into account the long-term environmental and social consequences of firm behavior (see http://www.idei.fr/fdir/en/).
The questionnaire was discussed with many people involved in the matter, and formally tested on two key actors of the field (one of the biggest asset management actors and a specialized actor) at the end of 2008. This testing led to some fine-tuning and improvements of the questions.
The responses to the questionnaire were collected between December 2008 and March 2009. Fourteen questionnaires were received, 12 from asset management companies (Dexia AM, Natixis AM, Macif Gestion, Ecofi, Banque Postale AM, Credit Agricole Asset Management [CAAM], Groupama, Federis AM, La Financière Responsable [LFR], Alcyone Finance, Financière de Champlain, and Oddo Securities) and 2 from institutional investors (FRR, Fonds de Réserve des Retraites, one of the major pension funds in France, and CDC, Caisse des Dépôts et Consignations, one of the largest public banks and a key asset management arm for the French Government). The responses have been treated with strict anonymity and confidentiality.
The number of questionnaires received represent 25% of the number of asset management establishments on the French market (from the Novethic, 2009a, study), a relatively low proportion which may reasonably raise a sig- nificant validity issue. In our view, the pros and cons of this survey procedure are as follows. Clearly, such a survey only illustrates some trends on the French SRI market, but we do consider that the results allow characterizing some important trends for several reasons.
First, the responses come from organizations with assets managed repre- senting roughly €17 billion, that is 77% of the relevant market in terms of collective asset management. Hence, the number of responses may seem low as a simple count, but the representativeness of the respondents appears much larger. Moreover, the diversity of the establishments interviewed allows the coverage of a majority of SRI profiles. In fact, both sell-side SRI analysts (working for a brokerage or firm that manages individual accounts and makes recommendations to the clients of the firm) and buy-side SRI analysts (usually working for a pension fund or mutual fund company) are represented in the sample. Moreover, the European leaders (which are large influential actors) operating on the French market are also represented in our sample.
at Northcentral University on June 30, 2016bas.sagepub.comDownloaded from
Crifo and Mottis 585
In sum, though the sample is relatively small (25% of the number of French asset management companies) and therefore not strictly representa- tive of what a large sample would show, we do believe that it is representative enough of the French market (77% of the market in terms of collective asset management).
Finally, from a statistical standpoint, if the validity issue is important, unfortunately there is no objective way to determine the sample size needed. Textbooks offer no simple formula for determining the minimum sample size, in part because the true underlying distributions are virtually never known in advance. Besides, given that the validity of our results is related somehow to the sample size, it is important to note that the adequacy of the sample for hypothesis testing is also related to the sample variability. Low variability (as measured by, for example, the standard deviation of the distri- bution estimated from the sample) means that a relatively small sample is more likely to be sufficient than when the variability is high.
The questionnaire contains 20 questions decomposed into three sub- themes: composition of the SRI team, nature of activities of the SRI team, and diffusion and use of the SRI teamwork.
These three subthemes allow examining whether a SRI mainstreaming is taking place as follows.
The profile of the SRI team. Mainstreaming may imply a growth trend in terms of size, together with team members possessing some seniority.
The nature of activities of the SRI team. Mainstreaming could rely on the emer- gence of some SRI leaders (as this is the case for mainstream analysts), as well as important time spent on information gathering (professionalization of the domains) and wide diffusion of ESG factors in the future.
The diffusion and use of the SRI teamwork. Mainstreaming would clearly imply a growing use and diffusion of SRI work by other (conventional) analysts and asset managers.
We report the main results of this survey in light of the mainstreaming issue by focusing on two dimensions: the conviction of SRI analysts and the diffusion and use of SRI teams’ outputs. The detailed questionnaire and the overall set of results are available from us on request.
The conviction of SRI analysts: Mainstreaming is clearly taking place. The first striking result of our study on the convergence between SRI processes and conventional asset management relates to the analysts’ opinion on the future of SRI and on its main advantages.
at Northcentral University on June 30, 2016bas.sagepub.comDownloaded from
586 Business & Society 55(4)
More than 60% of the respondents consider that SRI is likely to dissolve itself into conventional asset management (cf. Figure 2). A few analysts though consider that both phenomena will coexist (i.e., dissolution of SRI into conventional asset management together with niche market).
The path to mainstreaming can be easily understood when we observe that for most respondents, the major value added by SRI works is related to a bet- ter risk management (cf. Figure 3). This reflects a classical key factor of financial performance management: Any information allowing risk reduction in portfolio selection does contribute to increase value.
Figure 2. The future of SRI. Note. SRI = socially responsible investment.
Figure 3. The main advantage of the SRI approach. Note. SRI = socially responsible investment.
at Northcentral University on June 30, 2016bas.sagepub.comDownloaded from
Crifo and Mottis 587
Given that for most SRI analysts surveyed mainstreaming is taking place, one may naturally wonder whether this belief is reflected in the profile, the nature of activities, and the use of the SRI teamwork.
From this retrospect, we do observe a professionalization of SRI teams, but mainstreaming tends to occur only at the margin.
A first dimension of mainstreaming may be reflected in the professional- ization of SRI teams. In fact, in the early 2000s, the French SRI market was characterized by institutional SRI demand by the creation of public pension funds which made SRI conspicuous leading SRI actors to build mobilizing structures to meet this demand (Arjaliès, 2010). In light of this phenomenon, the organizational positioning of the SRI teams reveals that in more than 60% of the responses, it is outside conventional financial analysis (cf. Figure 4).
This result may be explained by the fact that a number of institutions rep- resented in our sample do not have buy-side analysts. However, in light of a potential convergence toward the mainstream asset management, such a pro- portion interestingly suggests that in this phase of constitution of the domain, things essentially occur at the margin. An alternative could have been the more systematic building of SRI skills and teams within the existing tradi- tional financial analysts’ units.
The diffusion and use of SRI teams’ outputs: A clear sign of mainstreaming. One of the most important dimensions in which mainstreaming in SRI processes
Figure 4. Functional organization. Note. SRI = socially responsible investment.
at Northcentral University on June 30, 2016bas.sagepub.comDownloaded from
588 Business & Society 55(4)
may be observed is reflected in the use of SRI teams’ works. Over a 6-year period, the exclusive use of these analyses by “niche market” SRI funds switches from a norm—67% 3 years ago—to a marginal case—13% in 3 years from now (cf. Figure 5). Moreover, for almost half of the respondents, these works will be used predominantly for conventional funds management. If there is a convergence between mainstream asset management and SRI asset management, it clearly appears here: Corporate social and environmen- tal performance is declared to be growingly incorporated into conventional asset management and the materiality of environmental, social, and gover- nance factors therefore diffuses.
This trend is confirmed by the fact that traditional asset managers tend to take into account SRI analyses in their investment decisions: The general tendency is toward a systematic integration with vanishing marginal integra- tion, from 47% to 7% in 6 years (Figure 6).
Similarly, the use of other SRI analyses is going to develop but not inten- sively: A marginal integration will evolve from 33% at the time of survey to 13% in 3 years, and systematic integration of other analysts’ works will rise from 13% to 20%.
Conclusion
The diffusion of SRI criteria into conventional asset management is complex but could confer a crucial scope for finance to promote socially and environ- mentally desirable activities. Recent research focused on the behavior of
Figure 5. Diffusion of SRI analyses to conventional funds. Note. SRI = socially responsible investment.
at Northcentral University on June 30, 2016bas.sagepub.comDownloaded from
Crifo and Mottis 589
financial analysts has highlighted their difficulty to go beyond traditional financial approaches and use nonfinancial, in particular environmental and social, information in their diagnoses (Saghroun & Eglem, 2008).
The objective of this research note was to document the French SRI mar- ket and examine this issue of mainstreaming within this national context. The study shows that the convergence toward the mainstream financial analysts and asset management seems to be engaged in France. The themes worked on are becoming more and more important for the asset management sector in general. SRI experts are more and more frequently consulted. Their recom- mendations have a growing impact on the decision-making processes of tra- ditional actors of the financial community.
However, as the French SRI field is still emerging and growing at a fast pace, the diversity of practices remains significant. This wide heterogeneity of practices and positioning in the respective organizations can be interpreted as a clear sign of a transition phase. But if one had to predict the next phase, betting on a continuing mainstreaming would probably not be a bad option.
The limitation of our illustrative survey is that the sample of responses is relatively small (25% of the number of French asset management companies). However, we believe that it may still be considered as representative of the French market given that the responses come from organizations representing 77% of that market in terms of collective asset management, with lower vari- ability than what a bigger sample would show. We appreciate that this view may be disputed but consider that their view is meritorious.
Figure 6. SRI and the asset management sector.
at Northcentral University on June 30, 2016bas.sagepub.comDownloaded from
590 Business & Society 55(4)
Acknowledgments
The authors would like to thank the editor Duane Windsor and anonymous referees for helpful remarks on a previous draft of this article.
Authors’ Note
An earlier version of information in this research note appeared in a research report form as “SRI Analysis and Asset Management: Independent or Convergent? A Field Study on the French Market” (DR 10006) by P. Crifo and N. Mottis (April 2010). Cergy, France: ESSEC Business School Paris–Singapore. Retrieved from http:// halshs.archives-ouvertes.fr/docs/00/57/23/79/PDF/DR10006.pdf.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, author- ship, and/or publication of this article: Financial support from the Chair for Sustainable Finance and Responsible Investment (Chair FDIR) is gratefully acknowledged by P. Crifo.
References
Arjaliès, D. L. (2010). A social movement perspective on finance: How socially responsible investment mattered. Journal of Business Ethics, 92, 57-78.
Azoulay, O., & Zeller, V. (2006). ISR: Stratégie de niche ou mainstream? [SRI: Niche strategy or mainstream?]. Revue d’économie financière [Review of Financial Economics], 85, 191-208.
Baron, D. P. (2009). A positive theory of moral management, social pressure, and corpo- rate social performance. Journal of Economics & Management Strategy, 18, 7-43.
Bengtsson, E. (2008). A history of Scandinavian socially responsible investing. Journal of Business Ethics, 82, 969-983.
Capelle-Blancard, G., & Monjon, S. (2012). Trends in the literature on socially responsible investment: Looking for the keys under the lamppost. Business Ethics: A European Review, 21(3), 239-250.
Cespa, G., & Cestone, G. (2007). Corporate social responsibility and managerial entrenchment. Journal of Economics and Management Strategy, 16, 741-777.
de Brito, C., Desmartin, J. P., Lucas-Leclin, V., & Perrin, F. (2001). L’investissement soci- alement responsible [Socially responsible investment]. Paris, France: Economica.
Déjean, F. (2006). La création du marché de l’ISR en France: Logique d’offre et stratégie de communication [The creation of the SRI market in France: Logic of supply and communication strategy]. Revue d’economie financière [Review of Financial Economics], 85, 273-284.
at Northcentral University on June 30, 2016bas.sagepub.comDownloaded from
Crifo and Mottis 591
Déjean, F., Giamporcaro, S., Gond, J.-P., Leca, B., & Penalva-Icher, E. (2013). Mistaking an emerging market for a social movement? A comment on Arjaliès’ social-movement perspective on socially responsible investment in France. Journal of Business Ethics, 112, 205-212.
European Fund Asset Management Association. (2008). Annual asset management report: Facts and figures (first annual report). Retrieved from http://www.ethe. org.gr/files/pdf/9B318B7FD40B4D4F8185E9DFB23564BA.pdf
European Sustainable Investment Forum. (2006). European SRI Study 2006. Retrieved from http://www.eurosif.org/research/eurosif-sri-study/2006
European Sustainable Investment Forum. (2008) European SRI Study 2008. Retrieved from http://www.eurosif.org/research/eurosif-sri-study/2008
Europlace. (2008). Rapport de la Commission Europlace: Investissement Socialement Responsable [Report of the Europlace Commission: Socially responsible invest- ment]. Paris, France: Author. Retrieved from http://translate.google.com/ translate?hl=en&sl=fr&u=http://www.paris-europlace.net/files/rapport_isr_ europlace.pdf&prev=/search%3Fq%3DRapport%2Bde%2Bla%2BCommission %2BEuroplace:%2BInvestissement%2BSocialement%2BResponsable%26hl%3 Den%26tbo%3Dd%26rls%3Dcom.microsoft:en-US%26rlz%3D1I7GGLL_en& sa=X&ei=ZMP0UJeYKYnWqAHp0YGwDQ&ved=0CDcQ7gEwAA
Friedman, M. (1970, September 13). The social responsibility of business is to increase its profits. New York Times Magazine. Retrieved from http://www.colo- rado.edu/studentgroups/libertarians/issues/friedman-soc-resp-business.html
Lewis, A., & Juravle, C. (2010). Morals, markets and sustainable investments: A qualitative study of “champions.” Journal of Business Ethics, 93, 483-494.
Louche, C. (2004). Opening the channels of communication. European Business Forum, p. 37-39.
Louche, C., & Lydenberg, S. (2006). Socially responsible investment: Differences between Europe and the United States (Vlerick Leuven Gent Management School Working Paper Series 2006-22). Retrieved from http://public.vlerick. com/Publications/67642c0d-6aa9-e011-8a89-005056a635ed.pdf
Margolis, J. D., Elfenbein, H. A., & Walsh, J. P. (2007, July 26). Does it pay to be good? A meta-analysis and redirection of research on the relationship between corporate social and financial performance (Harvard University Working Paper). Retrieved from http://stakeholder.bu.edu/docs/walsh,%20jim%20does%20it%20 pay%20to%20be%20good.pdf
Margolis, J. D., & Walsh., J. (2003) Misery loves companies: Rethinking social initia- tives by business. Administrative Science Quarterly, 48, 268-305.
McCann, L., Solomon, A., & Solomon, J. F. (2003). Explaining the growth in U.K. socially responsible investment. Journal of General Management, 28, 15-37.
Mercer, L. L. C. (2009, November). Shedding light on responsible investment: Approaches, returns and impacts. Retrieved from http://www.mercer.com/arti- cles/1423880
Novethic. (2009a). Chiffres 2008 et analyse du marché français de l’ISR [2008 Figures and analysis of the French SRI market]. Paris, France: Author. Available at
Dow
http://books.google.com/books/about/Chiffres_2008_et_analyse_
at Northcentral University on June 30, 2016bas.sagepub.comnloaded from
592 Business & Society 55(4)
Novethic. (2009b). L’essentiel de l’ISR n°17, janvier/février 2009 [SRI essentials, No. 17, January/February 2009]. Retrieved from
Saghroun, J., & Eglem, J. Y. (2008). À la recherc l‘entreprise: La perception des analystes financie mance of the enterprise: The perception of financia Audit [Accounting, Controlling, Audit], 14, 93-11
Scholtens, B. (2006). Finance as a driver of corpora Business Ethics, 68, 19-33
Schueth, S. (2003). Socially responsible investing Business Ethics, 43, 189-194.
Scott, P. (2001, April). The pitfalls in mandatory re 24-25. Retrieved from http://www.nextstep.co.
Sparkes, R., & Cowton, C. (2004). The maturing o A review of the developing link with corporat Business Ethics, 52, 45-57.
UN Environment Programme Finance Initiative and M responsible investment performance: A revie research on ESG factors. Retrieved from documents/Demystifying_Responsible_Investm
UN Environment Programme Finance Initiative an (2007). Responsible investment in focus: How meeting the challenge. Retrieved from https://w responsible_investment_in_focus.pdf
Social Investment Forum. (2008). 2007 Report o trends in the United States. Washington, DC: A munity-wealth.org/sites/clone.community-we sif-exec-sum07.pdf
Voisin, S., & Jeaneau, H. (2010). SRI as sustai Responsible investing is worth a premium. In J.- (Eds.), The economics of sustainable developmen France: Economica.
Author Biographies
Patricia Crifo (PhD, University of Lyon) is a prof Paris West and Ecole Polytechnique. Her research i responsibility and sustainable growth. Her articles Annals of Economics and Statistics, Economic M [Understanding and Managing], International Economics, Macroeconomic Dynamics, and Revue Economic Review].
at Northcentral Ubas.sagepub.comDownloaded from
http://www.novethic.fr/novethic/
upload/etudes/Etude_Marche_ISR_2009.pdf
du_march%C3%A9_fran.html?id=wIZ8QwAACAAJ. Additional information available (in French) at http://www.novethic.fr/novethic/les-produits-de-taux/ gestion-dediee/le-marche-isr/120636.jsp
he de la performance globale de rs [In search of the overall perfor- l analysts]. Comptabilité, Contrôle, 8. doi:10.3917/cca.141.0093.
te social responsibility. Journal of
in the United States. Journal of
porting. Environmental Finance, uk/uploadedfiles/pdf/article4.pdf f socially responsible investment: e social responsibility. Journal of
ercer, LLC. (2007). Demystifying w of key academic and border http://www.unepfi.org/fileadmin/ ent_Performance_01.pdf d UK Social Investment Forum. leading public pension funds are ww.gpf.or.th/download/general/
n socially responsible investing uthor. Retrieved from http://com- alth.org/files/downloads/report-
nable and responsible insurance: M. Lasry, D. Lautier, & D. Fessler t (Pt. 5, Ch. 2, pp. 326-340). Paris,
essor of economics at University nterests focus on corporate social have appeared in such journals as odelling, Gérer et Comprendre
Journal of Manpower, Labour Francaise d’Economie [French
niversity on June 30, 2016
Crifo and Mottis 593
Nicolas Mottis (PhD, Ecole Polytechnique) is a professor at the Department of Accounting and Management Control, ESSEC Business School. His research inter- ests focus on strategic control and corporate social responsibility. His articles have appeared in such journals as Comptabilité Contrôle Audit [Accounting, Controlling, Audit], European Business Forum, Gérer et Comprendre [Understanding and Managing], Revue Economique [Economic Review], and Revue Francaise de Gestion [French Management Review].
at Northcentral University on June 30, 2016bas.sagepub.comDownloaded from
- http://www.novethic.fr/novethic/upload/etudes/Etude_Marche_ISR_2009.pdf
#159.pdf
J. of Multi. Fin. Manag. 29 (2015) 46–65
Contents lists available at ScienceDirect
Journal of Multinational Financial Management
journal homepage: www.elsevier.com/locate/econbase
CEO compensation and corporate social responsibility
Ming Jian a, Kin-Wai Lee b,∗
a Nanyang Technological University, Singapore, Singapore b S3-B2A-19 Nanyang Avenue, Nanyang Business School, Nanyang Technological University, Singapore 639798, Singapore
a r t i c l e i n f o
Article history: Received 15 October 2014 Accepted 25 November 2014 Available online 3 December 2014
JEL classification: G30 G34 M1 M2
Keywords: Corporate social responsibility (CSR) CEO compensation Corporate governance
a b s t r a c t
We examine the association between CEO compensation and cor- porate social responsibility (CSR). We find that CEO compensation is negatively associated with CSR investment. We find CEO com- pensation is positively associated with normal CSR, suggesting that CEO is rewarded for investing in optimal level of CSR. The positive association between CEO compensation and normal CSR is more pronounced in firms with stronger corporate governance. However, CEO compensation level is negatively associated with abnormal CSR, suggesting that when CSR investment deviates from its opti- mal level, CEOs receive lower compensation level for excessive CSR investments. Firms with good corporate governance penalize abnormal CSR.
© 2014 Elsevier B.V. All rights reserved.
1. Introduction
Conventional wisdom suggests that firms should reward CEO for undertaking corporate social responsibility (CSR) which improves firm performance. Corporate governance and CSR advocates such as Global Reporting Initiatives and Corporate Register recommend that compensation of top level management should reflect CSR. For instance, the 2013 joint report by the Investor Responsibility
∗ Corresponding author. Tel.: +65 6790 4663; fax: +65 6792 4217. E-mail addresses: [email protected] (M. Jian), [email protected] (K.-W. Lee).
http://dx.doi.org/10.1016/j.mulfin.2014.11.004 1042-444X/© 2014 Elsevier B.V. All rights reserved.
M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65 47
Research Center and the Sustainable Investments Institutes suggest that 43% of the Fortune 500 firms tie executive compensation to CSR.1 The overall empirical evidence on the association between CEO compensation and CSR is inconclusive. On one hand, Berrone and Gomez-mejia (2009) find that in polluting industries, good environmental performance increases CEO compensation.2 On the other hand, contrary to conventional wisdom, other studies find that CEO compensation level is negatively associated with CSR (Coombs and Gilley, 2005; Russo and Harrison, 2005; Stanwick and Stanwick, 2001).
While the preceding studies differ in sample, time period and method, they do not explicitly con- sider the heterogeneity in CSR investments. For example, Borghesi et al. (2014: 164) find that “in some instances, CSR investments enhance shareholder value. However, in other cases, altruistic managers or managers who privately benefit from the positive attention arising from these activities may choose to make CSR investments even if they are not value enhancing.” By introducing the concepts of nor- mal (value increasing) CSR and abnormal (value decreasing) CSR, our paper revisits the association between CEO compensation and CSR investment and aims to provide new insights to the puzzling findings of the previous papers.
We posit that the association between CEO compensation and CSR depends on whether CSR invest- ments are value increasing or value decreasing. Furthermore, it is plausible that association between CEO compensation and CSR may vary systematically across different corporate governance structures. Accordingly, we examine whether there is an interplay between corporate governance structures and CSR investments in affecting CEO compensation.
We begin our analysis by considering two alternative views on the association between CEO compensation and CSR. Under the first view, greater CSR investment enhances shareholders’ value because better CSR investment is associated with better retention of high quality employees (Greening and Turban, 2000), higher demand for the firm’s products (Navarro, 1988), higher customer loyalty (Maignan et al., 1999; Sen and Bhattacharya, 2001) and higher access to valuable resources (Cochran and Wood, 1984; Cheng et al., 2014). Other studies find that CSR is associated with better non-financial performance such as higher operational efficiencies (Sharma and Vredenburg, 1998) and higher prod- uct quality (Johnson and Greening, 1999). These studies draw extensively from the stakeholder value maximization theory (Cornell and Shapiro, 1987; Hill and Jones, 1992; Jensen and Meckling, 1976; Oliver et al., 2014; Servaes and Tamayo, 2013; Tang et al., 2014), the theme of which is that a firm is a nexus of contracts between shareholders and other stakeholders (such as customers, suppliers and employees). Each group of stakeholders supplies the firm with critical resources in exchange for claims outlined in explicit contracts (e.g., wage contracts and product warranties) or suggested in implicit contracts (e.g., promises of job security to employees and continued service to customers). If higher CSR investment is associated with greater firm-specific focus on the interests of other stakeholders (such as customers, suppliers and employees), these stakeholders are more likely to support the firm’s operation, which increases shareholders’ value. Stated differently, CSR activities have a positive effect on shareholders’ value because focusing on the interests of other stakeholders increases their will- ingness to support a firm’s operation, which in turn increases shareholders’ value.3 In the context of our study, if higher CSR is associated with higher shareholders’ value, we expect CEO to be rewarded for his effort in improving CSR investment. Hence, we predict a positive association between CSR and CEO compensation. We refer to this view as the value-creation hypothesis.
Under the second view, CSR is associated with investments in negative net present value projects that destroy shareholders’ value. The key to this view is that managers may over-invest in CSR that transfer wealth from shareholders to other stakeholders (such as community, regulators and
1 http://www.csrhub.com/blog/2013/05/top-companies-tie-compensation-to-sustainability.html. 2 The authors focus on firms from industries subject to reporting under the Environmental Protection Agency’s Toxics Release
Inventory, a program that requires facilities exceeding a threshold level to report their emissions. 3 We acknowledge that institutional forces can often lead to symbolic rather than genuine CSR actions and policies whereby
firms may appear to engage in CSR, but these initiatives are simply intended to appease stakeholder demands or meet the minimum requirements of standards. Under this view, if CSR is purely symbolic without any effect on shareholders’ value, we expect no association between CEO compensation and CSR. However, if symbolic CSR reduces shareholders’ value, we expect a negative association between CEO compensation and CSR.
48 M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65
employees), as managers have incentives to use CSR investment to build their personal reputations, but these investments may reduce shareholders’ value in at least three ways. First, managers’ career concerns might make them focus excessively on short-term profit and distort their investment decisions, such as myopic CSR investment (Narayanan, 1985) and overinvestment (Holmstrom and Costa, 1986). For example, managers often overinvest in CSR for private rent-seeking benefits to secure their personal reputations in the community, enhance their personal status with stakeholders, and leave personal legacies that destroy shareholders’ wealth (e.g., Barnea and Rubin, 2010; Cespa and Cestone, 2007; Hemingway and Maclagan, 2004; Fabrizi et al., 2014). Second, career concerns may drive managers to manipulate the flow of information relating to the resolution of uncertainty surrounding CSR investment (Hirshleifer, 1993; Hirshleifer and Thakor, 1992).4 Third, manage- rial reputation building can encourage herding of CSR investment and lead to over-investments (Scharfstein and Stein, 1990; Trueman, 1986). For example, CEOs might invest in CSR just for cosmetic or ceremonial reasons with little or no economic payoff accruing to the firm, but as a mechanism to enhance their stature as corporate citizens (e.g., Surroca and Tribó, 2008). We refer to this view as the value-destruction hypothesis. It predicts a negative association between CSR and CEO compensation.
In summary, the value-creation (value-destruction) hypothesis predicts a positive (negative) association between CEO compensation and CSR. Ultimately, it is an empirical issue whether the value-creation hypothesis dominates the value-destruction hypothesis in terms of the net impact of CSR on CEO compensation.
Our results suggest that CEO compensation level is negatively associated with CSR investment. This result holds after controlling for standard economic determinants of CEO compensation (such as firm size, growth opportunities, operating profitability and stock returns) and CEO characteristics (such as age and tenure). We interpret our results as consistent with the value-destruction hypothesis.
At first glance, the negative association between that CEO compensation level and CSR invest- ment may seem puzzling. A natural question is that why a CEO would undertake actions to increase firm-specific CSR investment if he is penalized for high CSR investment. To address this question, we draw on the insight from Larcker (2003), who suggest that although firms are continuously strive to optimize their corporate financial policies, there are many legitimate reasons to expect firm policies and managerial decision to deviate from their optimal levels. One reason is that firm characteristics and manager characteristics that drives the optimal levels change with time (Core and Guay, 1999). Another reason could be changes in legal and other institutional environment that shift the opti- mal level. In reality, firms and managers do exhibit sub-optimal decisions as organizations adapt by experimentation and imitation (Ittner and Larcker, 2001; Milgrom and Roberts, 1992).
To shed light on the prior inconclusive findings on the association between CEO compensation and CSR, we conjecture it is important to distinguish normal CSR (which relates to the optimal level of CSR investment that potentially increases shareholders’ value) and abnormal CSR (which relate to excessive CSR investment that can potentially destroy shareholders’ value), and incorporate it into a CEO compensation-CSR investments framework.
It is important to distinguish normal CSR and abnormal CSR for at least two reasons. First, Larcker (2003) argues that although firms continuously strive to optimize their corporate
financial policies, it is plausible that firm policies and managerial decisions deviate from the optimal levels.
If one were to subscribe to the extreme optimization perspective that all firms in the sample are optimizing with respect to their CSR investments all the time, there should be no statistically sig- nificant association between CEO compensation and abnormal CSR (Demsetz and Lehn, 1985; Ittner and Larcker, 2001). In such a case, any statistically significant association between CEO compensation related to the abnormal CSR ought to occur only because of measurement error, misspecification of functional form or an inadequate set of controls. However, this is an extreme view of the world but not a useful framework for structuring research. If we assume that “all firms are optimizing all the time,” there is no way for researchers to provide any insight into the consequences of managerial
4 Specifically, to increase his personal reputation in the managerial labor market, CEO may delay the release of bad news about inefficient CSR investments.
M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65 49
choices (Larcker, 2003). Ittner and Larcker (2001) and Ittner et al. (2003) argue that such an extreme optimization perspective that fails to acknowledge the possibility of any off equilibrium behavior is perhaps unrealistic. Instead, it is likely that all organizations are dynamically learning and moving toward the optimal level, but a cross-sectional sample will consist of firms that are distributed around the optimal choice. Thus, to allow for the possibility of such dynamic learning toward the optimal choice, we are able to assess whether the abnormal CSR is associated with CEO compensation.
Second, in the context of CSR investments, Borghesi et al. (2014) suggest that companies evaluate socially responsible investments in a way similar to all other investments. They are undertaken if (1) they create value for investors, and/or (2) managers perceive a personal benefit from the invest- ment. Hence managers might undertake CSR investments due to their career concerns, which may be enhanced by having a reputation for championing socially responsible investments.
We draw on the prior literature on the determinants of CSR (Johnson and Greening, 1999; Karpoff et al., 2005; McWilliams and Siegel, 2000; Wu, 2006) to isolate normal CSR from abnormal CSR. Extend- ing the prior literature, we suggest that normal CSR reflects the optimal level of CSR investment that potentially increase shareholders’ value and that the abnormal CSR reflects excessive investment in CSR that potentially reduce shareholders’ value (Fazzari et al., 1988; Hubbard, 1998; Titman et al., 2004).
Decomposing total CSR investment into a normal component and an abnormal component gener- ates two interesting insights. First, we find that CEO compensation level is positively associated with normal CSR. To the extent that normal CSR reflects the optimal level of CSR investment, this result suggests that CEO is rewarded for investing in optimal level of CSR. Second, we find CEO compensation level is negatively associated with abnormal CSR, which suggests that when CSR investment deviates from its optimal level, CEO is punished for excessive investments in CSR investment.
Next, we examine the effect of corporate governance on the association between CEO compensa- tion and CSR. In firms with strong corporate governance, we find that CEO compensation is negatively associated with total CSR investment. Stated differently, the negative association between CEO com- pensation and CSR is more pronounced in firms with stronger corporate governance. We interpret our result as suggesting that strong corporate governance curtails the incentives of CEO to over-invest in CSR. However, in firms with weak corporate governance, we find that CEO compensation is not associated with total CSR.
We then investigate whether there are systematic differences in the association between CEO compensation and normal CSR (abnormal CSR) across different corporate governance structures. In firms with strong corporate governance, we find that CEO compensation is positively associated with normal CSR investment. Stated differently, to the extent that normal CSR reflect optimal level of CSR investment, the result suggests that the CEO is rewarded for undertaking normal CSR investment in firms that have strong corporate governance. In contrast, we find that CEO compensation is negatively associated with abnormal CSR investment in firms with strong corporate governance. Hence, effective corporate governance structure curtails agency costs by reducing CEO’s compensation level in firm that over-invested in CSR.
Our paper makes four contributions to the literature. First, by providing evidence on the association between CEO compensation and CSR investment, we extend CEO compensation research that has extensively focused on the financial performance. We show that the incremental effect of CSR invest- ment (over and above traditional financial performance measures such as operating profitability and stock returns) on CEO compensation. Second, we contribute to the corporate governance literature by demonstrating that effective corporate governance structures play an important role in monitoring and rewarding CSR investment and thus affect the association between CEO compensation and CSR investment. Third, we provide evidence that in setting CEO compensation, firms appear to distinguish between normal CSR and abnormal CSR. This delineation between normal CSR and abnormal CSR highlights the potential pitfall in the “one-size fits all” recommendation by CSR advocates such as Global Reporting Initiatives and Corporate Register that CEO should be rewarded for all CSR activities. More generally, our results broadly support the findings in prior studies that compensation committee influence the CEO compensation setting process to promote optimal contracting incentives (Adut et al., 2003; Dechow et al., 1994). Fourth, by separating normal CSR and abnormal CSR, our results can potentially explain the prior puzzling finding in Coombs and Gilley (2005) and Cai et al. (2011) that
50 M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65
CEO compensation is negatively associated with total CSR. In this paper we document systematic differences between normal CSR and abnormal CSR in affecting CEO compensation. Furthermore, our results suggest that the association between abnormal CSR and CEO compensation is conditioned on corporate governance structure. Finally, our paper contributes to the financial management of multinational firms because our sample firms have extensive foreign operations, with foreign sales on average being almost 35% of total sales.
The rest of the paper is organized as follows. Section 2 describes the data and research design. Section 3 presents our results. Section 4 concludes.
2. Data and research design
2.1. Sample formation
We obtain CEO compensation data from Execucomp. Financial accounting information is from the Compustat and stock return data is from CRSP. We obtain CSR data from the Kinder, Lydenberg and Domini (KLD) Database. Our primary source of corporate governance data is the Risk Metrics database. We drop the following observations in the screening procedures to obtain our sample: (1) observations with CEO turnover during the year; (2) observations in which the current CEO has served the company for strictly less than two consecutive years; (3) firms in the regulated industries (SIC code 4900–4999) or in the financial industry (SIC code 6000–6999); and (4) observations with zero CEO compensation in the year. The final sample consists of 12,507 firm-years for 1680 firms for the period 1992–2011.
Table 1 describes the sample distribution over years. There was a significant increase in the number of observations per year in and after 2003. This is mainly due to the fact that KLD more than doubled its coverage in 2003, covering not only MSCI KLD 400 Social Index but also the 3000 largest US companies, while in earlier years it covered only the 1000 largest US firms.
2.2. Measuring CSR
KLD data have been used extensively in scholarly research to operationalize the CSR construct (e.g., Szwajkowski and Figlewicz, 1999; Turban and Greening, 1997; Waddock and Graves, 1997). Waddock
Table 1 Sample.
Year Number of firm-years Percentage (%)
1992 138 1.1 1993 286 2.29 1994 302 2.41 1995 291 2.33 1996 308 2.46 1997 312 2.49 1998 321 2.57 1999 320 2.56 2000 313 2.5 2001 458 3.66 2002 493 3.94 2003 906 7.24 2004 933 7.46 2005 924 7.39 2006 957 7.65 2007 1036 8.28 2008 1022 8.17 2009 1080 8.64 2010 1079 8.63 2011 1028 8.22
Total 12,507 100
This table presents the sample distribution over the sample period from 1992 through 2011.
M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65 51
(2003) argues that the KLD data are “the de facto research standard” for measuring CSR in scholarly research. Chatterji et al. (2009) contend that KLD’s social ratings are among the most influential and the most widely accepted CSR measure used by academics. Mattingly and Berman (2006) assert that the KLD dataset has become the standard for quantitative measurement of corporate social actions.
KLD evaluates CSR on seven main dimensions including community, corporate governance, diver- sity, employee relations, environment, human rights and product. Corporate governance is perceived as a distinct construct from CSR and its impact on CEO compensation is widely examined in the prior literature (e.g., Core et al., 1999). In order to disentangle the effect of CSR and corporate governance, we construct the CSR measure based on the six remaining dimensions, excluding corporate governance. Specifically, following prior studies (Chatterji et al., 2009; Johnson and Greening, 1999; Waddock and Graves, 1997), we construct CSR, measured as total strengths minus total concerns in KLD’s six social rating categories: community, diversity, employee relations, environment, human rights and product.
2.3. Empirical model
2.3.1. CEO compensation and CSR Following prior studies on the determinants of CEO compensation level (Core et al., 2008, 1999),
we employ the following model to test the association between CEO compensation and CSR:
CEO compensation = ˇ0 + ˇ1 × CSR + ˇ2 × FIRMSIZE + ˇ3 × ROA + ˇ4 × RETURN + ˇ5 × VOLAROA + ˇ6 × VOLARET + ˇ7 × MTB + ˇ8 × TENURE + ˇ9 × AGE + ˇ10 × BDINDEP + ˇ11 × BDOWN + ˇ12 × INSTI + INDUSTRY + YEAR (1)
where
CEO compensation = Natural logarithm of the sum of one and total CEO compensation level comprising salary, bonus, stock options granted, restricted stocks granted, long term incentive payouts and other annual compensation in the fiscal year. CSR = KLD strengths less KLD concerns for community, diversity, employee relations, environment, human rights and product. FIRMSIZE = Natural logarithm of total assets ROA = Operating income divided by total assets RETURN = Stock return in the fiscal year VOLAROA = ROA volatility in the past 5 years VOLARET = Stock Return volatility in the past 5 years MTB = Market value of equity divided by book equity TENURE = Tenure of CEO in the fiscal year. AGE = Age of CEO in the fiscal year. BDINDEP = percentage of independent directors on the board. Independent directors are directors who are neither current nor former employees of the firm. BDOWN = percentage of common stock owned by all directors. INSTI = percentage of common stock held by institutional shareholders. INDUSTRY = Dummy variables to control for industry fixed effects at the 2-digit SIC level. YEAR = Dummy variables to control for year fixed effects.
Under the value creation hypothesis, we predict ˇ1 to be positive. Under the value destruction hypothesis, we predict ˇ1 to be negative.
We include the following control variables. Past studies (Rosen, 1982; Smith and Watts, 1992) find that large firms are more complex and they demand managers with more equilibrium wages. We control for firm size with the natural logarithm of total assets (FIRMSIZE). Core et al. (1999) argue that CEO compensation level is positively associated with firm performance. Our proxies for firm performance are return on assets (ROA) and stock return in the fiscal year (RETURN). High growth firms are more complex to manage compared to low growth firms (Smith and Watts, 1992). We control
52 M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65
for the firm’s growth opportunities with the ratio of market value of common equity to book value of common equity (MTB). Firms operating in more volatile environment are typically riskier. Hence, CEOs helming riskier should be compensated with higher compensation level (Banker and Datar, 1989; Lee et al., 2008; Lee, 2014) . We control for uncertainty in operation with two proxies: standard deviation of return on assets in the past five years (VOLAROA) and standard deviation of stock returns in the past five years (VOLAROA). Following Core et al. (1999), Jian and Lee (2011) and Lee and Lee (2014), we also control for CEO characteristics such as CEO age in the fiscal year (AGE) and CEO tenure at the firm (TENURE). We control for the effect of corporate governance on CEO compensation by including the percentage of independent directors on the board (BDINDEP), percentage of common stock owned by all directors (BDOWN) and percentage of common stock held by institutional shareholders (INSTI). We also include industry dummy variables and year dummy variables to control for industry and time-series effects on CEO compensation.
2.3.2. Normal CSR and abnormal CSR To further distinguish between value creation hypothesis and value destruction hypothesis, we
draw on prior literature on the determinants of CSR which posits that based on the firm’s operating characteristics and industry factors, there is an optimal level of CSR investment (Johnson and Greening, 1999; Karpoff et al., 2005; McWilliams and Siegel, 2000; Wu, 2006). Under this approach, a deviation in the amount of CSR investment from this level is suboptimal.
We draw on the theoretical insights provided by Demsetz and Lehn (1985), Ittner and Larcker (2001), Ittner et al. (2003) and Borghesi et al. (2014) to motivate our discussion on the decomposition of total CSR into normal CSR and abnormal CSR. As emphasized by Larcker (2003), although firms continuously strive to optimize their corporate financial policies, there are many legitimate reasons to expect firm policies and managerial decision to deviate from their optimal levels. Potential rea- sons include changes in firm characteristics and manager characteristics (Core and Guay, 1999) and changes in legal and other institutional environment that shift the optimal level. Moreover, organiza- tions adapt by experimentation and imitation (Ittner and Larcker, 2001; Milgrom and Roberts, 1992). In other words, firms and managers do exhibit sub-optimal decisions in reality. We acknowledge that if one were to adopt an extreme optimization perspective that all firms in the sample are optimizing with respect to their CSR investments all the time, there should be no statistically significant asso- ciation between CEO compensation and abnormal CSR (Demsetz and Lehn, 1985; Ittner and Larcker, 2001). Following this logic, any statistically significant association found between CEO compensation and abnormal CSR should occur only when there is measurement error or an inadequate set of con- trols. Such an extreme optimization perspective is perhaps unrealistic as it fails to acknowledge the possibility of any off equilibrium behavior (Ittner and Larcker, 2001; Ittner et al., 2003). Instead, we follow the insights from Hanlon et al. (2003), Ittner and Larcker (2001) and Ittner et al. (2003) and we posit that it is likely that all organizations are dynamically learning and moving toward the opti- mal level, while a cross-sectional sample will consist of firms that are distributed around the optimal choice. Thus, to allow for the possibility of such dynamic learning toward the optimal choice, we are able to assess whether the abnormal CSR is associated with CEO compensation.
Following prior literature we decompose total CSR investment into two components: (a) the com- ponent that can be explained by investment based factors and (b) the component that is unrelated to investment based factors. We refer to the first component as the “normal CSR”, and the latter as the “abnormal CSR”. Specifically, we determine the optimal CSR and deviation for each firm by estimating the following model:
CSR = ˛0 + ˛1 × ATO + ˛2 × PM + ˛3 × CASH + ˛4 × CFO + ˛5 × LEVERAGE + ˛6 × MTB + ˛7 × FIRMSIZE + ˛8 × R&D + ˛9 × ADV + ˛10 × BDINDEP + ˛11 × BDOWN + ˛12 × INSTI + INDUSTRY+YEAR (2)
where
CSR = KLD strengths less KLD concerns for community, diversity, employee relations, environment, human rights and product.
M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65 53
ATO = Sales over total assets. PM = Income before extraordinary items divided by sales. CASH = Cash divided by total assets. CFO = Cash flow from operations divided by sales. LEVERAGE = Total debt divided by total assets. MTB = Market value of equity divided by book equity. FIRMSIZE = Natural logarithm of total assets. R&D = Research and development expenditure divided by sales. ADV = Advertising expenditure divided by sales. BDINDEP = percentage of independent directors on the board. BDOWN = percentage of common stock owned by all directors. INSTI = percentage of common stock held by institutional shareholders. INDUSTRY = Dummy variables to control for industry fixed effects at the 2-digit SIC level. YEAR = Dummy variables to control for year fixed effects.
We use the fitted value of CSR investment from Eq. (2) as a proxy for the normal (optimal) CSR investment and the residual from Eq. (2) as a proxy for abnormal CSR (i.e. the deviation from the optimal CSR).
Drawing from previous literature that examines the major drivers of CSR investment, we include the following variables in our model on the determinants of CSR. To control for the effect of firm performance on CSR, we include return on assets and cash flow from operations divided by sales. Rather than including contemporaneous ROA, we split ROA into its constituent components: Asset Turnover (ATO) and Profit Margin (PM), as asset turnover and profit margin measure different aspects of profitability and are therefore likely to have different persistence (Nissim et al., 2001). We include cash as a percentage of total assets and leverage to proxy for financial flexibility because firms with more financial resources are more likely to invest in CSR (Karpoff et al., 2005; Baumann-Pauly et al., 2013). To control for firm size, we include the natural logarithm of total assets because larger firms have greater resources for CSR investment (Wu, 2006). Prior studies (McWilliams and Siegel, 2000; Wieser, 2005) find that firms with higher intangibles have higher investments in CSR due to higher sensitivity of firm value to growth opportunities. We control for intangibles by including advertising intensity (advertising expenditure divided by sales) and research and development intensity (research and development expenditure divided by sales). Leverage and market-to-book equity are included as stable firms with lower risk are more likely to invest in CSR (Cochran and Wood, 1984; Orlitzky and Benjamin, 2001). Stronger corporate governance is associated with greater effectiveness of CSR investment (Johnson and Greening, 1999). Thus, we include various corporate governance attributes such as the percentage of independent directors on the board (BDINDEP), percentage of common stock owned by all directors (BDOWN) and percentage of common stock held by institutional shareholders (INSTI). Lastly, we include industry fixed effects and year fixed effects. We acknowledge that our paper identifies abnormal CSR based mainly on accounting and governance variables. Given that firms do CSR to enhance stakeholder relations, the level of CSR is likey to vary with the firm’s immediate environment (such as religion and politics). For example, Di Giuli and Kostovetsky (2014) find that firms have higher CSR when they are head-quartered in Democratic rather than Republican-leaning states. We address these issues in the robustness tests section.
We take the fitted and residual values from equation (2), and test the association between CEO compensation and these components of CSR investment using the following specification:
CEO compensation = �0 + �1 × NORMAL CSR + �2 × ABNORMAL CSR + CONTROLS (3)
The value creation hypothesis predicts that CEO compensation level be positively associated with normal CSR and abnormal CSR. Thus, the value creation hypothesis implies that �1 > 0 and �2 > 0. In contrast, the value destruction hypothesis, predicts that (i) CEO compensation level be positively associated with normal CSR because CEO should be rewarded for optimal investments in CSR (i.e., �1 > 0); and (ii) CEO compensation level be negatively associated with abnormal CSR because CEO should be penalized for deviation from the optimal investments in CSR (i.e., �2 < 0).
54 M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65
Table 2 Descriptive statistics.
Variable Mean Standard deviation 25th Percentile Median 75th Percentile
CEO Compensation (USD mil) 5.552 9.691 1.679 3.329 6.45 CSR 0.280 2.268 −1 0 1 FIRMSIZE 7.647 1.455 6.588 7.546 8.594 ROA 0.106 0.08 0.062 0.101 0.149 VOLAROA 0.039 0.038 0.015 0.027 0.049 RETURN 1.066 0.364 0.834 1.015 1.23 VOLARET 0.384 0.309 0.2 0.294 0.447 MTB 1.71 1.133 0.988 1.372 2.019 TENURE 12.875 11.297 4 9 20 AGE 55.692 6.832 51 56 60 BDINDEP 68.13% 18.37% 36.00% 70.00% 82.50% BDOWN 4.17% 2.59% 0.72% 1.63% 2.94% INSTI 63.12% 27.91% 38.52% 60.19% 71.62% ATO 1.126 0.681 0.655 0.966 1.406 PM 0.058 0.105 0.025 0.058 0.101 CASH 0.103 0.105 0.025 0.069 0.147 CFO 0.114 0.072 0.069 0.109 0.154 LEVERAGE 0.202 0.158 0.056 0.195 0.308 R&D 0.042 0.072 0 0.005 0.05 ADV 0.012 0.027 0 0 0.011
This table presents summary statistics of the variables used in later analysis. Our sample consists of 12,705 firm-year observa- tions from 1992 through 2011. CEO compensation is the total CEO compensation level (million USD) comprising salary, bonus, stock options granted, restricted stocks granted, long term incentive payouts and other annual compensation in the fiscal year. CSR is computed as the KLD strengths less KLD concerns for community, diversity, employee relations, environment, human rights and product. FIRMSIZE is the natural logarithm of total assets. ROA is calculated as the operating income divided by total assets. RETURN is the firm’s gross stock return in the fiscal year. VOLAROA measures the ROA volatility in the past 5 year. VOLARET is the firm’s stock return volatility in the past 5 years. MTB is computed as the market value of equity divided by book equity of the firm. TENURE represents the tenure of CEO in the fiscal year. AGE denotes the age of CEO in the fiscal year. R&D is calculated as the research and development expenditure divided by sales. ADV is the advertising expenditure divided by sales. BDINDEP is the percentage of independent directors on the board. Independent directors are directors who are neither current nor former employees of the firm. BDOWN is the percentage of common stock owned by all directors. INSTI is the percentage of common stock held by institutional shareholders. ATO is sales over total assets. PM is calculated as income before extraordinary items divided by sales. CASH is computed as cash divided by total assets. CFO represents cash flow from operations divided by sales. LEVERAGE is computed as total debt divided by total assets. MTB is market value of equity divided by book equity. FIRMSIZE is the natural logarithm of total assets. R&D is calculated as the research and development expenditure divided by sales. ADV is the advertising expenditure divided by sales.
3. Results
3.1. Descriptive statistics
Table 2 presents the descriptive statistics. Mean (median) CEO total compensation is $5.552 ($3.329) million. Mean CSR is 0.280. On average, the sample firms are profitable with a mean return on assets (ROA) of 0.106. The mean buy-and-hold gross stock return during the fiscal year is 1.066.5 Mean standard deviation of return on assets in the past five years (VOLAROA) is 0.039 and mean standard deviation of stock return in the past five years (VOLARET) is 0.384. The mean market to book value of common equity (MTB) is 1.710. Mean CEO age is 56 years and the mean CEO tenure is 12.875 years. Mean board independence (BDINDEP) is 68%. Mean percentage of common stock owned by the board of directors (BDOWN) is 4%. Mean percentage of common stock owned by the institutional shareholders is 63%.
Table 3 presents the Spearman correlation among selected variables. Several results are note- worthy. First, total CEO compensation level is positively associated with CSR investment at the 5%
5 This implies that $100 invested at the beginning of the year will be worth $106.6 at the end of the year, generating a net return of 6.6%.
M .
Jia n
, K
.-W .
Lee /
J. o
f M
u lti.
Fin .
M a n
a g.
2 9
(2 0
1 5
) 4
6 –
6 5
5
5
Table 3 Spearman correlations.
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)
(1) CEO Compensation 1 (2) CSR 0.0933* 1 (3) FIRMSIZE 0.6466* 0.1364* 1 (4) ROA 0.1673* 0.1236* 0.0580* 1 (5) VOLAROA −0.1058* −0.0531* −0.2821* −0.0995* 1 (6) RETURN 0.1028* −0.0336* 0.0134 0.1561* −0.0115 1 (7) VOLARET −0.1098* −0.1256* −0.3268* −0.1415* 0.4005* 0.0954* 1 (8) MTB 0.1002* 0.1616* −0.0830* 0.6095* 0.1035* 0.2523* 0.0354* 1 (9) TENURE −0.0427* 0.0375* 0.0535* 0.0981* −0.0634* 0.0005 −0.0723* 0.0711* 1 (10) AGE 0.0084 −0.0381* 0.0733* 0.0315* −0.0725* −0.0083 −0.1104* −0.0471* 0.3231* 1 (11) BDINDEP 0.0219* −0.1352* 0.0682* 0.0393* −0.0293* 0.0181 −0.0435* 0.0527* 0.0198* 0.0025 1 (12) BDOWN 0.1096* −0.2175* 0.1625* 0.0121 −0.1399* 0.0088 −0.1719* −0.0839* −0.0716* 0.0169 0.0731* 1 (13) INSTI 0.0253* −0.2807* −0.0201* −0.0479* −0.0729* 0.01 −0.0409* −0.1221* −0.1037* 0.0035 0.0014 0.7174*
This table presents Spearman correlation between variables used in later analysis later. Our sample consists of 12,705 firm-year observations from 1992 through 2011. CEO compensation (log) is the natural logarithm of the sum of one and total CEO compensation level, which comprising salary, bonus, stock options granted, restricted stocks granted, long term incentive payouts and other annual compensation in the fiscal year. CSR is computed as the KLD strengths less KLD concerns for community, diversity, employee relations, environment, human rights and product. FIRMSIZE is the natural logarithm of total assets. ROA is calculated as the operating income divided by total assets. RETURN is the firm’s gross stock return in the fiscal year. VOLAROA measures the ROA volatility in the past 5 year. VOLARET is the firm’s stock return volatility in the past 5 years. MTB is computed as the market value of equity divided by book equity of the firm. TENURE represents the tenure of CEO in the fiscal year. AGE denotes the age of CEO in the fiscal year. BDINDEP is the percentage of independent directors on the board. Independent directors are directors who are neither current nor former employees of the firm. BDOWN is the percentage of common stock owned by all directors. INSTI is the percentage of common stock held by institutional shareholders. * denotes significance at 5% level.
56 M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65
significance level. Second, we find that CSR is positively associated with firm size, operating profit- ability and market-to-book ratio. Third, CSR is negatively associated with volatility in profitability, volatility in stock return, CEO age, board independence, directors’ stock ownership and institutional ownership. We caution that these simple correlations are univariate correlations that do not control for differences in other firm characteristics such as firm size. We conduct a formal multivariate analysis below where we control for these other important differences.
3.2. Regressions of CEO compensation on CSR
Table 4 presents the regressions of CEO compensation on CSR. The dependent variable is CEO total compensation comprising salary, bonus, stock options granted, restricted stocks granted, long term incentive pay and other annual compensation. In column (1), the estimated coefficient on CSR
Table 4 Regression of CEO compensation on CSR.
(1) (2)
CSR −0.021*** −0.024*** (2.673) (2.851)
FIRMSIZE 0.337*** 0.464*** (9.838) (32.299)
ROA 1.710*** 2.261*** (10.747) (11.777)
VOLAROA 0.405 0.096 (1.192) (0.259)
RETURN 0.087*** 0.311*** (4.301) (11.904)
VOLARET 0.042 0.098** (0.926) (1.974)
MTB 0.060*** 0.084*** (2.917) (4.429)
TENURE −0.003** −0.001 (2.517) (0.397)
AGE 0.003 0.012*** (1.631) (6.108)
BDINDEP −0.029* (1.960)
BDOWN −0.052** (2.070)
INSTI −0.107*** (2.410)
GOVSTRENGTH −0.185** (2.370)
Constant 4.319*** 2.827*** (13.325) (10.095)
YEAR Yes Yes INDUSTRY Yes Yes Adjusted R2 0.718 0.473
This table presents the OLS regression results of CEO compensation on CSR. Our sample consists of 12,705 firm-year obser- vations from 1992 through 2011. Standard errors are clustered by firm. Coefficients are presented with t-statistics below in parentheses. ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively. The dependent variable is CEO compensation. It is computed as the natural logarithm of the sum of one and total CEO compen- sation level, which comprising salary, bonus, stock options granted, restricted stocks granted, long term incentive payouts and other annual compensation in the fiscal year. CSR is computed as the KLD strengths less KLD concerns for community, diversity, employee relations, environment, human rights and product. FIRMSIZE is the natural logarithm of total assets. ROA is calculated as the operating income divided by total assets. RETURN is the firm’s gross stock return in the fiscal year. VOLAROA measures the ROA volatility in the past 5 year. VOLARET is the firm’s stock return volatility in the past 5 years. MTB is computed as the market value of equity divided by book equity of the firm. TENURE represents the tenure of CEO in the fiscal year. AGE denotes the age of CEO in the fiscal year. BDINDEP is the percentage of independent directors on the board. Independent directors are directors who are neither current nor former employees of the firm. BDOWN is the percentage of common stock owned by all directors. INSTI is the percentage of common stock held by institutional shareholders.
M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65 57
is negative and significant at the 1% level, which suggests that CEO total compensation is negatively associated with CSR investment. In other words, after controlling for standard economic determinants of CEO compensation such as firm size, profitability, stock return, firm’s operating risk and growth opportunities, and corporate governance measures such as board independence, board ownership and institutional ownership, CEO receive lower total compensation in firms with higher CSR investment. This result is consistent with the value destruction hypothesis of CSR investment.
In column (2), we construct a composite measure of corporate governance strength (GOV- STRENGTH) based on the principal components analysis of the percentage of independent directors on the board (BDINDEP), percentage of common stock owned by all directors (BDOWN) and percentage of common stock held by institutional shareholders (INSTI). Higher scores of GOVSTRENGTH denote higher corporate governance strength. After controlling for firm-level corporate governance strength, we still find CEO total compensation is negatively associated with CSR investment. In column (2), the estimated coefficient on CSR is −0.024 (significant at the 1% level).
Based on the estimated coefficients model (1), if the firm increases its CSR from the 25th percentile to the 75th percentile, CEO compensation decreases by 4.29%.6 Hence, the result is economically significant.
3.3. Determinants of CSR
Table 5 presents the regression results of the determinants of CSR based on Eq. (2). We conduct a number of robustness checks on the model. In column (1) we include all firm characteristics in addi- tion to industry and year fixed effects. In column (2), we include all firm characteristics, the corporate governance measures as well as industry and year fixed effects. In column (3), we use the composite index of corporate governance strength (GOVSTRENGTH) to replace the three governance measures: the percentage of independent directors on the board (BDINDEP), percentage of common stock owned by all directors (BDOWN) and percentage of common stock held by institutional shareholders (INSTI). In general, results are qualitatively consistent. Consistent with prior studies (Johnson and Greening, 1999; Karpoff et al., 2005; McWilliams and Siegel, 2000; Wu, 2006), we find that CSR is positively asso- ciated with operating cash flow, firm size, research and development divided by sales, and advertising divided by sales. On the other hand, CSR is negatively associated with corporate governance strength.
In our next set of tests, we use the fitted values of CSR based on estimated coefficients in Table 5 column (1) to compute the normal CSR (optimal level of CSR based on firm characteristics). Thus, the residual values from the regression in column (1) Table 5 reflect the abnormal CSR (deviations from the optimal level of CSR).7
3.4. Regressions of CEO compensation on normal CSR and abnormal CSR
In Table 6, we examine whether there are systematic differences between normal CSR and abnor- mal CSR in affecting CEO compensation. We repeat the regressions reported in Table 4 but decompose CSR into normal and abnormal component using the model shown in Table 5 column (1). In all spec- ifications we find similar results. First, we find CEO compensation level is positively associated with normal CSR at the 1% significance level. To the extent that normal CSR reflects the optimal level of CSR investment, this result suggests that CEO is rewarded for investing in optimal level of CSR. Second, we find CEO compensation level is negatively associated with abnormal CSR at the 1% significance level. This result suggests that when CSR investment deviates from its optimal level, CEO is punished for excessive investments in CSR. For example, based on the estimated coefficients in model 4 of Table 6 and holding all other variables at their means, when abnormal CSR increases from the 25th percentile to the 75th percentile, the CEO’s total compensation decreases 2.17%. Hence, the results are economically significant.
6 We hold the control variables at their sample means. 7 The fitted and residual values for CSR investment from each of the other columns in Table 5 produce qualitatively similar
results in subsequent analysis.
58 M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65
Table 5 Determinants of CSR investment.
(1) (2) (3)
ATO 0.127 0.134 0.099 (1.492) (1.578) (1.194)
PM 0.358 0.508** 0.405 (1.349) (1.981) (1.590)
CASH 0.128 0.095 0.074 (0.333) (0.252) (0.206)
CFO 2.525*** 2.382*** 2.310*** (4.638) (4.531) (4.703)
LEVERAGE −0.309 −0.232 −0.184 (0.943) (0.714) (0.599)
MTB 0.053 0.04 0.042 (1.322) (0.998) (1.135)
FIRMSIZE 0.469*** 0.417*** 0.375*** (9.272) (8.492) (8.441)
R&D 3.940*** 4.078*** 4.011*** (5.359) (5.439) (5.607)
ADV 8.754*** 9.485*** 8.336*** (4.427) (4.807) (4.624)
BDINDEP −0.172** (1.885)
BDOWN −0.209** (2.061)
INSTI −0.286*** (2.492)
GOVSTRENGTH −1.454*** (13.561)
Constant −5.085*** −4.529*** −3.556*** (8.535) (7.393) (4.881)
INDUSTRY Yes Yes Yes YEAR Yes Yes Yes Adjusted R2 0.179 0.187 0.226
This table presents the OLS regressions of the determinants of CSR. Our sample consists of 12,705 firm-year observations from 1992 through 2011. Standard errors are clustered by firm. Coefficients are presented with t-statistics below in parentheses. ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively. The dependent variable is CSR, which is computed as the KLD strengths less KLD concerns for community, diversity, employee relations, environment, human rights and product. ATO is sales over total assets. PM is calculated as income before extraordinary items divided by sales. CASH is computed as cash divided by total assets. CFO represents cash flow from operations divided by sales. LEVERAGE is computed as total debt divided by total assets. MTB is market value of equity divided by book equity. FIRMSIZE is the natural logarithm of total assets. R&D is calculated as the research and development expenditure divided by sales. ADV is the advertising expenditure divided by sales. BDINDEP is the percentage of independent directors on the board. Independent directors are directors who are neither current nor former employees of the firm. BDOWN is the percentage of common stock owned by all directors. INSTI is the percentage of common stock held by institutional shareholders.
Collectively, our results highlight the systematic differences between normal CSR and abnormal CSR in affecting CEO compensation. By separating normal CSR and abnormal CSR, our results can potentially explain the prior puzzling finding in Coombs and Gilley (2005) and Cai et al. (2011) that CEO compensation is negatively associated with total CSR.
3.5. Does corporate governance affect the association between CEO compensation and CSR?
In Table 7, we examine the effect of corporate governance on the association between CEO com- pensation and CSR investment. We construct a composite measure of corporate governance strength (GOVSTRENGTH) based on the principal components analysis of the percentage of independent directors on the board (BDINDEP), percentage of common stock owned by all directors (BDOWN) and percentage of common stock held by institutional shareholders (INSTI). Higher scores of GOV- STRENGTH denote higher corporate governance strength. Using the GOVSTRENGTH, we partition the observations into the sub-sample of firms with strong corporate governance and the sub-sample of
M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65 59
Table 6 Regression of CEO compensation on normal CSR and abnormal CSR.
(1) (2) (3) (4)
NORMAL CSR 0.055*** 0.057*** 0.209*** 0.212*** (5.513) (5.701) (10.623) (10.754)
ABNORMAL CSR −0.012*** −0.010*** −0.012*** −0.010*** (3.733) (−3.201) (3.575) (3.033)
FIRMSIZE 0.462*** 0.464*** 0.399*** 0.400*** (69.101) (69.423) (41.258) (41.379)
ROA 0.920*** 0.926*** 0.793*** 0.799*** (9.333) (9.412) (8.002) (8.076)
VOLAROA 0.905*** 0.837*** 0.586*** 0.517*** (4.588) (4.252) (2.935) (2.593)
RETURN 0.116*** 0.113*** 0.127*** 0.124*** (6.478) (6.346) (7.071) (6.947)
VOLARET 0.164*** 0.163*** 0.146*** 0.145*** (6.731) (6.702) (6.012) (5.987)
MTB 0.044*** 0.047*** 0.017** 0.020** (5.762) (6.108) (2.137) (2.441)
TENURE −0.006*** −0.006*** (9.143) (9.171)
AGE 0.003*** 0.003*** (3.238) (3.495)
BDINDEP −0.035 −0.033* (1.612) (1.872)
BDOWN −0.055** −0.049** (2.217) (2.019)
INSTI −0.128** −0.135** (2.035) (2.209)
Constant 3.602*** 3.561*** 4.125*** 4.072*** (20.587) (19.465) (22.412) (21.332)
Year dummies Yes Yes Yes Yes Industry dummies Yes Yes Yes Yes Adjusted R2 0.522 0.525 0.524 0.527
This table presents the OLS regression results of CEO compensation on normal and abnormal CSR. Our sample consists of 12,705 firm-year observations from 1992 through 2011. Standard errors are clustered by firm. Coefficients are presented with t-statistics below in parentheses. ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively. The dependent variable is CEO compensation. It is computed as the natural logarithm of the sum of one and total CEO compen- sation level, which comprising salary, bonus, stock options granted, restricted stocks granted, long term incentive payouts and other annual compensation in the fiscal year. NORMAL CSR is the predicted value of CSR from Table 5 model 4. ABNORMAL CSR is the residual value of CSR from Table 5 model 4. FIRMSIZE is the natural logarithm of total assets. ROA is calculated as the operating income divided by total assets. RETURN is the firm’s gross stock return in the fiscal year. VOLAROA measures the ROA volatility in the past 5 year. VOLARET is the firm’s stock return volatility in the past 5 years. MTB is computed as the market value of equity divided by book equity of the firm. TENURE represents the tenure of CEO in the fiscal year. AGE denotes the age of CEO in the fiscal year. BDINDEP is the percentage of independent directors on the board. Independent directors are directors who are neither current nor former employees of the firm. BDOWN is the percentage of common stock owned by all directors. INSTI is the percentage of common stock held by institutional shareholders.
firms with weak corporate governance. In firms with strong corporate governance (column (1)), we find that CEO compensation is negatively associated with CSR. However, in firms with weak corporate governance (column (2)), we find that CEO compensation is not associated with CSR. The Chi-square to test the difference in coefficient on CSR between strongly-governed firms and weakly-governed firms is 6.85, significant at 1% level. This result suggests that in strongly-governed firms, CEO compensation is lower when total CSR is higher.
In columns (3) and (4), we employ Gompers et al. (2003) G-score as an alternative measure of corporate governance. In column (3), in firms with strong corporate governance (i.e. low G-score), CEO compensation is negatively associated with CSR. In contrast, the results in column (4) indicate that in firms with weak corporate governance (i.e. high G-score), CEO compensation is not associated with CSR. In columns (5) and (6), we employ Bebchuk et al. (2009) entrenchment index (E-index) as an alternative measure of corporate governance. Results are qualitatively similar. Specifically,
60 M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65
Table 7 Regression of CEO compensation on CSR: Strong Corporate Governance versus Weak Corporate Governance.
GOVSTRENGTH G-score E-index
Strong CG Weak CG Strong CG Weak CG Strong CG Weak CG (1) (2) (3) (4) (5) (6)
CSR −0.010** 0.015 −0.023*** −0.006 −0.020*** −0.005 (2.277) (0.835) (4.676) (1.464) (4.879) (1.045)
FIRMSIZE 0.328*** 0.489*** 0.476*** 0.489*** 0.466*** 0.514*** (17.560) (3.937) (61.862) (70.977) (66.700) (66.422)
ROA 1.753*** 1.685*** 1.224*** 0.691*** 1.067*** 0.844*** (14.490) (2.854) (8.508) (5.233) (7.981) (5.936)
VOLAROA 0.508* 1.349 0.918*** 0.812*** 0.932*** 0.938*** (1.954) (1.064) (3.321) (2.891) (3.515) (3.236)
RETURN 0.079*** 0.073 0.080*** 0.149*** 0.105*** 0.105*** (4.635) (0.912) (3.068) (6.295) (4.300) (4.135)
VOLARET 0.077** −0.108 0.200*** 0.121*** 0.179*** 0.161*** (2.349) (0.577) (6.004) (3.375) (5.474) (4.494)
MTB 0.066*** 0.072 0.038*** 0.084*** 0.041*** 0.086*** (6.407) (1.311) (3.492) (8.027) (4.124) (7.614)
TENURE −0.003*** 0.001 −0.007*** −0.003*** −0.008*** −0.001* (3.205) (0.128) (7.994) (3.331) (9.088) (1.688)
AGE 0.003** 0.019** 0.002 0.004*** 0.002* 0.004*** (2.275) (2.352) (1.378) (3.164) (1.745) (2.991)
Constant 4.133*** 2.560** 3.306*** 3.228*** 3.810*** 2.701*** (22.989) (2.439) (10.328) (15.329) (14.816) (11.465)
INDUSTRY Yes Yes Yes Yes Yes Yes YEAR Yes Yes Yes Yes Yes Yes Adjusted R2 0.141 −0.906 0.487 0.566 0.495 0.557 Test the difference in coefficients on CSR between two subsamples Chi-square 6.85 8.78 7.18 p value (0.005) (0.003) (0.007)
This table presents the OLS regression results of CEO compensation on CSR in the sub-samples of strong and weak corporate governance. Our sample consists of 12,705 firm-year observations from 1992 through 2011. Standard errors are clustered by firm. Coefficients are presented with t-statistics below in parentheses. ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively. The sample is partitioned into two subsamples according to the median of three corporate governance measures: GOVSTRENGTH (column 1 and 2), G-score (column 3 and 4) and E-index (column 5 and 6) respectively. GOVSTRENGTH is a corporate governance index derived from the principal components analysis of the board independence (BDINDEP), board ownership (BDOWN) and institutional investors ownership (INSTI). G-score is the G-score for corporate gov- ernance from Gompers et al. (2003), E-index is the corporate governance measure from Bebchuk et al. (2009). The dependent variable is CEO compensation. It is computed as the natural logarithm of the sum of one and total CEO compen- sation level, which comprising salary, bonus, stock options granted, restricted stocks granted, long term incentive payouts and other annual compensation in the fiscal year. CSR is computed as the KLD strengths less KLD concerns for community, diversity, employee relations, environment, human rights and product. FIRMSIZE is the natural logarithm of total assets. ROA is calculated as the operating income divided by total assets. RETURN is the firm’s gross stock return in the fiscal year. VOLAROA measures the ROA volatility in the past 5 year. VOLARET is the firm’s stock return volatility in the past 5 years. MTB is computed as the market value of equity divided by book equity of the firm. TENURE represents the tenure of CEO in the fiscal year. AGE denotes the age of CEO in the fiscal year. R&D is calculated as the research and development expenditure divided by sales. ADV is the advertising expenditure divided by sales.
the difference in coefficient on CSR between strongly-governed firms and weakly-governed firms is significant at 1% level. Thus, in strongly-governed firms, the negative association between CEO compensation and total CSR is stronger.
In Table 8, we examine whether corporate governance affects the association between CEO compensation and normal (abnormal) CSR. Using the composite corporate governance score (GOV- STRENGTH), we partition the firms into the sub-sample of firms with strong corporate governance (column (1)) and the sub-sample of firms with weak corporate governance (column (2)).
In firms with strong corporate governance (column (1)), we find that CEO total compensation is positively associated with normal CSR, suggesting CEO is rewarded for optimal level of CSR investment. On the other hand, in well-governed firms CEO total compensation is negatively associated abnormal
M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65 61
Table 8 Regression of CEO compensation on normal CSR and abnormal CSR: Strong Corporate Governance versus Weak Corporate Governance.
GOVSTRENGTH G-score E-index
Strong CG Weak CG Strong CG Weak CG Strong CG Weak CG (1) (2) (3) (4) (5) (6)
NORMAL CSR 0.105*** 0.096** 0.070*** 0.032** 0.058*** 0.057*** (6.747) (2.545) (4.543) (2.486) (4.354) (3.575)
ABNORMAL CSR −0.020*** 0.003 −0.025*** −0.008* −0.023*** −0.009* (5.955) (0.277) (4.733) (1.807) (5.018) (1.823)
FIRMSIZE 0.439*** 0.451*** 0.446*** 0.474*** 0.442*** 0.490*** (46.928) (21.707) (43.651) (53.140) (48.295) (48.249)
ROA 0.888*** 0.669** 1.217*** 0.573*** 1.029*** 0.731*** (8.362) (2.317) (8.406) (4.297) (7.667) (5.099)
VOLAROA 0.640*** 1.428*** 0.795*** 0.787*** 0.773*** 0.870*** (2.947) (2.727) (2.857) (2.795) (2.910) (3.003)
RETURN 0.106*** 0.257*** 0.086*** 0.148*** 0.110*** 0.103*** (5.589) (4.262) (3.284) (6.261) (4.518) (4.021)
VOLARET 0.176*** 0.029 0.194*** 0.118*** 0.172*** 0.159*** (6.758) (0.403) (5.791) (3.283) (5.237) (4.422)
MTB 0.036*** 0.016 0.021* 0.080*** 0.036*** 0.078*** (4.375) (0.611) (1.939) (7.511) (3.536) (6.756)
TENURE −0.003** −0.001 −0.008*** −0.003*** −0.008*** −0.002* (2.547) (0.082) (8.688) (3.471) (9.671) (1.907)
AGE 0.003* 0.014 0.002 0.005*** 0.002 0.005*** (1.797) (1.317) (1.406) (3.303) (1.406) (3.163)
Constant 3.766*** 3.726*** 3.580*** 3.391*** 4.114*** 2.911*** (18.220) (8.713) (10.937) (15.518) (14.965) (12.036)
INDUSTRY Yes Yes Yes Yes Yes Yes YEAR Yes Yes Yes Yes Yes Yes Adjusted R2 0.523 0.498 0.495 0.569 0.506 0.56
Test the difference in coefficients on NORMAL CSR between two subsamples Chi-square 0.005 3.91 0 p value (0.820) (0.048) (0.965)
Test the difference in coefficients on ABNORMAL CSR between two subsamples Chi-square 8.672 7.65 5.02 p value (0.005) (0.006) (0.025)
This table presents the OLS regression results of CEO compensation on normal and abnormal CSR in the sub-samples of strong and weak corporate governance. Our sample consists of 12,705 firm-year observations from 1992 through 2011. Standard errors are clustered by firm. Coefficients are presented with t-statistics below in parentheses. ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively. The sample is partitioned into two subsamples according to the median of three corporate governance measures: GOVSTRENGTH (column 1 and 2), G-score (column 3 and 4) and E-index (column 5 and 6) respectively. GOVSTRENGTH is a corporate governance index derived from the principal components analysis of the board independence (BDINDEP), board ownership (BDOWN) and institutional investors ownership (INSTI). G-score is the G-score for corporate governance from Gompers et al. (2003), E-index is the corporate governance measure from Bebchuk et al. (2009). The dependent variable is CEO compensation. It is computed as the natural logarithm of the sum of one and total CEO compen- sation level, which comprising salary, bonus, stock options granted, restricted stocks granted, long term incentive payouts and other annual compensation in the fiscal year. NORMAL CSR is the predicted value of CSR from Table 5 model 4. ABNORMAL CSR is the residual value of CSR from Table 5 model 4. FIRMSIZE is the natural logarithm of total assets. ROA is calculated as the operating income divided by total assets. RETURN is the firm’s gross stock return in the fiscal year. VOLAROA measures the ROA volatility in the past 5 year. VOLARET is the firm’s stock return volatility in the past 5 years. MTB is computed as the market value of equity divided by book equity of the firm. TENURE represents the tenure of CEO in the fiscal year. AGE denotes the age of CEO in the fiscal year.
CSR, suggesting CEO is punished for excessive CSR investment. Our results underscore the importance of separating normal CSR and abnormal CSR in setting CEO compensation.
In firms with weak corporate governance (column (2)), we find that CEO total compensation is positively associated with normal CSR, suggesting CEO is rewarded for optimal level of CSR invest- ment. More importantly, in firms with weak corporate governance, there is no association between
62 M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65
CEO compensation and abnormal CSR. This result suggests that in poorly monitored firms, CEO is not punished for excessive investment in CSR.
The Chi-square that tests the difference in coefficients on normal CSR in the two subsamples (strong versus weak corporate governance) is 0.005 (insignificant), while the Chi-square that tests the differ- ence in coefficients on abnormal CSR in the two subsamples (strong versus weak corporate governance) is 8.672, significant at 1% level. Taken together, our results suggest that it is important to recognize the interplay among corporate governance structures, normal CSR and abnormal CSR in affecting CEO compensation.
We obtain qualitatively similar results using Gompers et al. (2003) G-score (column (3) and (4)) as an alternative measure of corporate governance to partition the sample. Our main inferences are also similar using Bebchuk et al. (2009) entrenchment index (E-index). In summary, in firms with stronger corporate governance structures, CEOs receive lower compensation when abnormal CSR is higher.
3.6. Robustness tests
3.6.1. Alternative measures of CSR In a sensitivity test, as in McWilliams and Siegel (2000), we also use an alternative measure of CSR,
CSR DSI400, an indicator variable that takes a value of 1 if the firm is included in the DSI400 in a given year (for having passed the “social screen”), and 0 otherwise. In order to be eligible for the DSI 400, a firm must derive less than 2% of its gross revenue from the production of military weapons, have no involvement in nuclear power, gambling, tobacco, and alcohol, and have a positive record in each of the remaining six categories. Our results are qualitatively similar.
In another supplementary test, we use U.S. firms in the FTSE4Good Index as an alternative sample of socially responsible firms. The FTSE4Good series measures the performance of firms that meet social and environmental criteria in five categories: (1) environmental sustainability, (2) human rights, (3) countering bribery, (4) supply chain labor standards, and (5) climate change. The FTSE4Good Index consists of 600–700 socially responsible firms around the world from 2001 to 2011, of which approx- imately 200 firms are U.S. listed firms. After merging the U.S. firms in the FTSE4Good Index with the U.S. firms in the Execucomp Database, Compustat, and CRSP, we have a sample with 170 US firms.
To examine whether FTSE4Good U.S. firms compensate their CEOs differently from non-FTSE4Good U.S. firms, we use a propensity score matching approach. We choose matching firms (i.e. non- FTSE4Good U.S firms) from the merged database of Execucomp and Compustat database using firm size, leverage, market-to-book ratio, industry dummies and year dummies. Untabulated results suggest the CEO compensation is approximately 1% lower for FTSE4Good U.S. firms than for non- FTSE4Good U.S. firms. Since FTSE4Good U.S. firms are determined independently from KLD firms, the results using FTSE4Good U.S. firms lend additional support to the value destruction view.
3.6.2. Financial constraints Another concern is that financially constrained firms have less resource to invest in CSR. We employ
several measures of “financial constraints” such as the Kaplan and Zingales (1997) measure, the Whited and Wu (2006) size–age measure, firm size and dividends payout. Our main results on the association between CEO compensation and CSR are robust across alternative measures of “financial constraints.” In addition, the results are qualitatively similar based on a balanced panel of firms for the sample period.
3.6.3. Endogeneity Although using an extensive list of control variables (in Eq. (1)) helps to reduce omitted variables
bias in estimating the relation between a firm’s CSR investment and CEO compensation, the results from the regression could still suffer from endogeneity bias caused by unobservable omitted variables. To address the potential endogeneity problem, we perform two-stage-least-squares (2SLS) regression analysis using religion rank and a blue state dummy as instrumental variables for the CSR investment (Deng et al., 2013). Religion rank measures the religion ranking of the state in which the firm’s head- quarters is located, which ranges between 1 and 50. The ranking is based on the ratio of the number
M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65 63
of religious adherents in the firm’s state to the total population in that state in 2000.8 A higher rank- ing indicates more religiosity. Angelidis and Ibrahim (2004) find that the degree of religiousness is positively correlated with attitudes toward CSR. This finding suggests that the religion rank variable is likely to be positively correlated with a firm’s CSR, thus satisfying the relevance requirement of instrumental variables. However, to the extent that the construction of the religion rank variable is based on the state in which a firm is located, it is unlikely that this variable has a significant effect on the CEO compensation, satisfying the exclusion condition of instrumental variables.
Blue state is a dummy variable that equals one if a firm’s headquarters is located in a blue/democratic state and zero otherwise.9 Rubin (2008) finds that firms with high CSR ratings tend to be located in democratic or blue states. We therefore expect this dummy variable to be highly cor- related with our sample firms’ CSR. It is unlikely, however, that the choice of locating in a blue or red state could has a direct significant effect on CEO compensation except via its effect on CSR.
Using religion rank and a blue state dummy as instrumental variables for the CSR investment, results (not tabulated) from 2SLS regression analyses indicate that our main inferences on the association between CEO compensation and CSR are qualitatively similar.
4. Conclusions
We examine whether CEO compensation is associated with corporate social responsibility (CSR) investment. The value creation (value destruction) hypothesis predicts a positive (negative) associa- tion between CEO compensation and CSR. Consistent with the value destruction hypothesis, we find that CEO total compensation level is negatively associated with CSR investment. In firms with strong corporate governance, we find that the negative association between CEO compensation and CSR is more pronounced than in firms with weak corporate governance.
Decomposing total CSR investment into a normal component and an abnormal component gen- erates two interesting insights. First, we find CEO compensation level is positively associated with normal corporate social responsibility. To the extent that normal CSR reflects the optimal level of CSR investment, this result suggests that CEO is rewarded for investing in optimal level of CSR. We also doc- ument that the positive association between CEO compensation and normal CSR is more pronounced in firms with stronger corporate governance. Second, we find CEO compensation level is negatively associated with abnormal corporate social responsibility. This result suggests that when CSR invest- ment deviates from its optimal level, CEOs receive lower compensation for excessive investments in CSR. Strong corporate governance structure penalizes CEO more by reducing CEO compensation if CEOs over-invest in CSR.
References
Adut, D., Cready, W.H., Lopez, T.J., 2003. Restructuring charges and CEO cash compensation: a reexamination. Account. Rev. 78, 169.
Angelidis, J., Ibrahim, N., 2004. An exploratory study of the impact of degree of religiousness upon an individual’s corporate social responsiveness orientation. J. Bus. Ethics 51, 119–128.
Banker, R.D., Datar, S.M., 1989. Sensitivity, precision, and linear aggregation of signals for performance evaluation. J. Account. Res. 27, 21.
Barnea, A., Rubin, A., 2010. Corporate social responsibility as a conflict between shareholders. J. Bus. Ethics 97, 71–86. Baumann-Pauly, D., Wickert, C., Spence, L., Scherer, A., 2013. Organizing corporate social responsibility in small and large firms:
size matters. J. Bus. Ethics 115, 693–705. Bebchuk, L., Cohen, A., Ferrell, A., 2009. What matters in corporate governance? Rev. Financ. Stud. 22, 783–827.
8 The Association of Religion Data Archive provides information on religiosity every decade. We use 2000 data since it covers the middle of our sample period (1992–2011). As a robustness test, we recalculate religion ranks for the periods 1992–1999 and 2000–2007 as the average religion rank based on 1990 and 2000 data and the average religion rank based on 2000 and 2010 data, respectively. Our results are qualitatively similar.
9 We obtain the list of blue states from http://en.wikipedia.org/wiki/Red states and blue states. We define the state as a blue state if it is listed as the blue state in the website. In untabulated tests, we redefine the blue state dummy in a certain year as an indicator that takes the value of one if a firm’s headquarters is located in a state in which the Democratic Party wins both previous and next presidential elections of that year. Our results are qualitatively similar.
64 M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65
Berrone, P., Gomez-mejia, L.R., 2009. Environmental performance and executive compensation: an integrated agency- institutional perspective. Acad. Manag. J. 52, 103–126.
Borghesi, R., Houston, J.F., Naranjo, A., 2014. Corporate socially responsible investments: CEO altruism, reputation, and share- holder interests. J. Corp. Financ. 26, 164–181.
Cai, Y., Jo, H., Pan, C., 2011. Vice or virtue? The impact of corporate social responsibility on executive compensation. J. Bus. Ethics 104, 159–173.
Cespa, G., Cestone, G., 2007. Corporate social responsibility and managerial entrenchment. J. Econ. Manag. Strateg. 16, 741–771. Chatterji, A.K., Levine, D.I., Toffel, M.W., 2009. How well do social ratings actually measure corporate social responsibility? J.
Econ. Manag. Strateg. 18, 125. Cheng, B., Ioannou, I., Serafeim, G., 2014. Corporate social responsibility and access to finance. Strateg. Manag. J. 35 (1), 1–23. Cochran, P.L., Wood, R.A., 1984. Corporate social responsibility and financial performance. Acad. Manag. J. 27, 42 (pre-1986). Coombs, J.E., Gilley, K.M., 2005. Stakeholder management as a predictor of CEO compensation: main effects and interactions
with financial performance. Strateg. Manag. J. 26, 827. Core, J., Guay, W., 1999. The use of equity grants to manage optimal equity incentive levels. J. Account. Econ. 28, 151–184. Core, J.E., Guay, W., Larcker, D.F., 2008. The power of the pen and executive compensation. J. Financ. Econ. 88, 1–25. Core, J.E., Holthausen, R.W., Larcker, D.F., 1999. Corporate governance, chief executive officer compensation, and firm perfor-
mance. J. Financ. Econ. 51, 371–406. Cornell, B., Shapiro, A.C., 1987. Corporate stakeholders and corporate finance. Financ. Manag. 16, 5. Dechow, P.M., Huson, M.R., Sloan, R.G., 1994. The effect of restructuring charges on executives’ cash compensation. Account.
Rev. 69, 138. Demsetz, H., Lehn, K., 1985. The structure of corporate ownership: causes and consequences. J. Polit. Econ. 93, 1155. Deng, X., Kang, J.-k., Low, B.S., 2013. Corporate social responsibility and stakeholder value maximization: evidence from mergers.
J. Financ. Econ. 110, 87–109. Di Giuli, A., Kostovetsky, L., 2014. Are red or blue companies more likely to go green? Politics and corporate social responsibility.
J. Financ. Econ. 111, 158–180. Fabrizi, M., Mallin, C., Michelon, G., 2014. The role of CEO’s personal incentives in driving corporate social responsibility. J. Bus.
Ethics 124, 311–326. Fazzari, S., Hubbard, R.G., Petersen, B.C., 1988. Financing Constraints and Corporate Investment. National Bureau of Economic
Research Working Paper Series, pp. 2387. Gompers, P.A., Ishii, J.L., Metrick, A., 2003. Corporate governance and equity prices. Q. J. Econ. 118, 107–156. Greening, D.W., Turban, D.B., 2000. Corporate social performance as a competitive advantage in attracting a quality workforce.
Bus. Soc. 39, 254–280. Hanlon, M., Rajgopal, S., Shevlin, T., 2003. Are executive stock options associated with future earnings? J. Account. Econ. 36,
3–43. Hemingway, C.A., Maclagan, P.W., 2004. Managers’ personal values as drivers of corporate social responsibility. J. Bus. Ethics
50, 33–44. Hill, C.W.L., Jones, T.M., 1992. Stakeholder-agency theory. J. Manag. Stud. 29, 131. Hirshleifer, D., 1993. Managerial reputation and corporate investment decisions. Financ. Manag. 22, 145. Hirshleifer, D., Thakor, A.V., 1992. Managerial conservatism, project choice, and debt. Rev. Financ. Stud. 5, 437–470. Holmstrom, B., Costa, J.R.I., 1986. Managerial incentives and capital management. Q. J. Econ. 101, 835–860. Hubbard, R.G., 1998. Capital–market imperfections and investment. J. Econ. Lit. 36, 193–225. Ittner, C.D., Larcker, D.F., 2001. Assessing empirical research in managerial accounting: a value-based management perspective.
J. Account. Econ. 32, 349–410. Ittner, C.D., Larcker, D.F., Randall, T., 2003. Performance implications of strategic performance measurement in financial services
firms. Account. Org. Soc. 28, 715–741. Jensen, M.C., Meckling, W.H., 1976. Theory of the firm: managerial behavior, agency costs and ownership structure. J. Financ.
Econ. 3, 305–360. Jian, M., Lee, K.W., 2011. Does CEO reputation matter for capital investments? J. Corp. Financ. 17, 929–946. Johnson, R.A., Greening, D.W., 1999. The effects of corporate governance and institutional ownership types on corporate social
performance. Acad. Manag. J. 42, 564–576. Kaplan, S.N., Zingales, L., 1997. Do investment–cash flow sensitivities provide useful measures of financing constraints? Q. J.
Econ. 112, 169–215. Karpoff, J.M., Lott Jr., J.R., Wehrly, E.W., 2005. The reputational penalties for environmental violations: empirical evidence. J.
Law Econ. 48, 653. Larcker, D.F., 2003. Discussion of “are executive stock options associated with future earnings?” J. Account. Econ. 36, 91–103. Lee, K.W., 2014. Compensation committee and executive compensation in Asia. Int. J. Bus. 19, 214–236. Lee, K.W., Lee, C.F., 2014. Are multiple directorships beneficial in East Asia? Account. Financ. 54, 999–1032. Lee, K.W., Lev, B., Yeo, H.H., 2008. Executive pay dispersion, corporate governance and firm performance. Rev. Quant. Financ.
Account. 30, 315–338. Maignan, I., Ferrell, O.C., Hult, G.T.M., 1999. Corporate citizenship: cultural antecedents and business benefits. Acad. Mark. Sci.
J. 27, 455–469. Mattingly, J.E., Berman, S.L., 2006. Measurement of corporate social action: discovering taxonomy in the Kinder Lydenburg
Domini ratings data. Bus. Soc. 45, 20–46. McWilliams, A., Siegel, D., 2000. Corporate social responsibility and financial performance: correlation or misspecification?
Strateg. Manag. J. 21, 603–609. Milgrom, P.R., Roberts, J., 1992. Economics, Organization, and Management. Prentice-Hall, Englewood Cliffs, NJ. Narayanan, M.P., 1985. Managerial incentives for short-term results. J. Financ. 40, 1469–1484. Navarro, P., 1988. Why do corporations give to charity? J. Bus. 61, 65. Nissim, D., Penman, S., 2001. Ratio analysis and equity valuation: from research to practice. Rev. Account. Stud. 6, 109–154. Oliver, B.R., McCarthy, S., Song, S., 2014. CEO overconfidence and corporate social responsibility. In: Working Paper.
M. Jian, K.-W. Lee / J. of Multi. Fin. Manag. 29 (2015) 46–65 65
Orlitzky, M., Benjamin, J.D., 2001. Corporate social performance and firm risk: a meta-analytic review. Bus. Soc. 40, 369–396. Rosen, S., 1982. Authority, control, and the distribution of earnings. Bell J. Econ. 13, 311. Rubin, A., 2008. Political views and corporate decision making: the case of corporate social responsibility. Financ. Rev. 43, 337. Russo, M.V., Harrison, N.S., 2005. Organizational design and environmental performance clues from the electronics industry.
Acad. Manag. J. 48, 582–593. Scharfstein, D.S., Stein, J.C., 1990. Herd behavior and investment. Am. Econ. Rev. 80, 465. Sen, S., Bhattacharya, C.B., 2001. Does doing good always lead to doing better? Consumer reactions to corporate social respon-
sibility. J. Mark. Res. 38, 225–243. Servaes, H., Tamayo, A., 2013. The impact of corporate social responsibility on firm value: the role of customer awareness.
Manag. Sci. 59, 1045–1061. Sharma, S., Vredenburg, H., 1998. Proactive corporate environmental strategy and the development of competitively valuable
organizational capabilities. Strateg. Manag. J. 19, 729 (1986–1998). Smith Jr., C.W., Watts, R.L., 1992. The investment opportunity set and corporate financing, dividend, and compensation policies.
J. Financ. Econ. 32, 263. Stanwick, P.A., Stanwick, S.D., 2001. CEO compensation: does it pay to be green? Bus. Strateg. Environ. 10, 176–182. Surroca, J., Tribó, J.A., 2008. Managerial entrenchment and corporate social performance. J. Bus. Financ. Account. 35, 748–789. Szwajkowski, E., Figlewicz, R.E., 1999. Evaluating corporate performance: a comparison of the fortune reputation survey and
the socrates social rating database. J. Manag. Issues 11, 137–154. Tang, Y., Qian, C., Chen, G., Shen, R., 2014. How CEO hubris affects corporate social (ir)responsibility. Strateg. Manag. J. (forth-
coming). Titman, S., Wei, K.C.J., Xie, F., 2004. Capital investments and stock returns. J. Financ. Quant. Anal. 39, 677–700. Trueman, B., 1986. The relationship between the level of capital expenditures and firm value. J. Financ. Quant. Anal. 21, 115–129. Turban, D.B., Greening, D.W., 1997. Corporate social performance and organizational attractiveness to prospective employees.
Acad. Manag. J. 40, 658–672. Waddock, S., 2003. Stakeholder performance implications of corporate responsibility. Int. J. Bus. Perform. Manag. 5, 114–124. Waddock, S.A., Graves, S.B., 1997. The corporate social performance–financial performance link. Strateg. Manag. J. 18, 303. Whited, T.M., Wu, G., 2006. Financial constraints risk. Rev. Financ. Stud. 19, 531–559. Wieser, R., 2005. Research and development productivity and spillovers: empirical evidence at the firm level. J. Econ. Surv. 19,
587–621. Wu, M.-L., 2006. Corporate social performance, corporate financial performance, and firm size: a meta-analysis. J. Am. Acad.
Bus. Camb. 8, 163–171.
- CEO compensation and corporate social responsibility
- 1 Introduction
- 2 Data and research design
- 2.1 Sample formation
- 2.2 Measuring CSR
- 2.3 Empirical model
- 2.3.1 CEO compensation and CSR
- 2.3.2 Normal CSR and abnormal CSR
- 3 Results
- 3.1 Descriptive statistics
- 3.2 Regressions of CEO compensation on CSR
- 3.3 Determinants of CSR
- 3.4 Regressions of CEO compensation on normal CSR and abnormal CSR
- 3.5 Does corporate governance affect the association between CEO compensation and CSR?
- 3.6 Robustness tests
- 3.6.1 Alternative measures of CSR
- 3.6.2 Financial constraints
- 3.6.3 Endogeneity
- 4 Conclusions
- References