Principles of Finance Paper

The effect of financial constraints, investment policy, product market competition and corporate governance

on the value of cash holdings

Howard W. H. Chan a , Yufei Lu

b , Hong F. Zhang

b

a Department of Finance, Faculty of Business and Economics, University of Melbourne, Parkville,

VIC, Australia b School of Accounting, Economics and Finance, Faculty of Business and Law, Deakin University,

Burwood, VIC, Australia

Abstract

This study empirically investigates the value shareholders place on excess cash holdings and how shareholders’ valuation of cash holdings is associated with finan- cial constraints, firm growth, cash-flow uncertainty and product market competi- tion for Australian firms from 1990 to 2007. Our results indicate that the marginal value of cash holdings to shareholders declines with larger cash holdings and higher leverage. However, firms that are more financially constrained, that have higher growth rates and that face greater uncertainty exhibit a higher marginal value of cash holdings. These findings are consistent with the explanation that excess cash holdings are not necessarily detrimental to firm value. Firms with costly external financing and that also save more cash for current operating and future investing needs find that the market values these cash hoarding policies favourably. Finally, there is limited evidence of an association between various corporate governance measures and the value of cash holdings for a shorter sample period.

Key words: Financial constraints; Cash policy; Australian firms

JEL classification: G31, G32

doi: 10.1111/j.1467-629X.2011.00463.x

We thank Jim Psaros for the use of the Horwath Corporate Governance data. Also, we thank an anonymous Accounting and Finance reviewer, Robert Faff (the editor), confer- ence participants at the AsianFA 2011 annual meeting and the AFAANZ 2011, and semi- nar participants at the University of Newcastle and the University of Queensland for their helpful comments and suggestions.

Received 30 November 2010; accepted 19 November 2011 by Robert Faff (Editor).

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

Accounting and Finance 53 (2013) 339–366

1. Introduction

Areexcess cash holdingsgood or bad? Inthe real world, excess cash holdingsplay a vital role as a cash buffer in corporate investment and financing decisions. How- ever,Jensen(1986)holdstheviewthatexcesscashholdingsaredetrimentaltoshare- holder value because managers waste the excess cash through over-investment and value-destroyingacquisitions.Incontrast,havinglargecashholdingsprovidesfirms with flexibility in making investment decisions, as it avoids the need to raise more costlyexternalfinancing(Opleret al.,1999;MikkelsonandPartch,2003). A number of empirical studies, such as Mikkelson and Partch (2003), Pinko-

witz and Williamson (2004), and Faulkender and Wang (2006), investigate the value of corporate cash holdings and how excess cash holdings are related to stock returns in US markets. In Australia, Lee and Powell (2011) examine the value of excess cash holdings. Their findings support the agency cost argument of excess cash holdings by showing that firms with a longer duration of excess cash holdings have a lower marginal value of cash. However, Lee and Powell (2011) only show how the marginal value of cash is related to the persistence of excess cash holdings. Given the limited Australian evidence, the focus of this study is on how share-

holders value excess cash holdings associated with financial constraints, firm growth opportunities, uncertainty in cash flows, product market competition and corporate governance.

1

We first estimate the marginal value of cash holdings by following the method- ology in Faulkender and Wang (2006). In particular, we use excess stock returns as the dependent variable and unexpected changes in cash holdings and firm characteristics that are related to cash as the explanatory variables. Excess stock returns are calculated using returns from the 25 Fama and French portfolios formed on market capitalization (size) and book-to-market as benchmark returns.

2 Consistent with the results of Faulkender and Wang (2006), firms with

larger cash holdings and higher leverage ratios generate a lower marginal value of cash holdings. When we employ dividend-paying ability and book value of total assets to partition our sample according to the degree of financial con- straints, we find that more financially constrained firms have a significantly higher marginal value of cash holdings. This indicates that investors place greater

1 The Australian market differs from the US market. There are more natural resources

firms and fewer technology-related firms, in terms of both number and size. Natural resource firms have more tangible assets in place as compared to technology and internet- related firms. Finally, Australian firms are generally smaller in size and the Australian market has a much smaller and less liquid corporate bond market.

2 This approach follows Faulkender and Wang (2006). These benchmark portfolios

formed on size and book-to-market account for the common risk factors that affect stock returns. In contrast, Lee and Powell (2011) use excess returns adjusted by market or industry returns instead of the 25 Fama and French portfolio returns.

340 H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

value on excess cash holdings in financially constrained firms, as these firms are less likely than unconstrained firms to gain access to external capital. To shed light on how the value of cash holdings is associated with firms’

investment decisions, uncertainty in cash flows, product market competition and corporate governance, we further partition our sample using the following vari- ables: book-to-market for growth opportunities; average volatility in earnings; Herfindahl index constructed using the market share of a firm’s sales within its industry; and, finally, various corporate governance proxies. We find that firms with higher growth rates and higher levels of uncertainty in their cash flows exhi- bit a higher marginal value of cash holdings. However, product market competi- tion has little impact on firms’ value of cash holdings. Our findings indicate that internal financing has clear cost advantages over external financing for firms with high growth potential and those facing uncertain prospects. Costly external financing would force firms that are at a disadvantage to save more cash for cur- rent operating and future investing needs. Investors are aware of these cash hoarding policies and view them quite favourably. However, within industry product markets, competition seems to have little influence on a firm’s cash hoarding policy; for corporate governance, we find limited evidence for its asso- ciation with the value of cash holdings. Overall, our findings are mainly consis- tent with increased cash holdings being dependent on the firm’s ability to access external capital, as in the study of Hennessy and Whited (2005). The remainder of this study is organized as follows. Section 2 examines the exist-

ingliterature,whichaimstodiscussthestudiessurroundingcorporatecashholdings and to link the cash-holding behaviour to various firm-specific factors in Australia. Section 3 discusses our empirical methodology and outlines our main hypotheses. The sample and summary statistics are described in Section 4. Section 5 presents ourempiricalresultsandrobustnesschecks.Section 6concludesthestudy.

2. Literature review

Opler et al. (1999) examine the determinants and implications of cash holdings and cash equivalents based on data from 1048 publicly traded US firms during the period 1971–1994. Their findings show that the level of corporate cash hold- ings is positively correlated with future investment opportunities, cash-flow-to- assets ratios, capital investment, industry volatility and investments in fixed assets and is negatively correlated with firm size, leverage, and networking capi- tal and dividend payments. In a more recent paper, Faulkender and Wang (2006) extend this line of

research by analysing the value that shareholders placed on the cash held by a firm.

3 These authors argue that the value of one additional dollar of cash

3 The focus of their paper is not on how much cash is saved out of cash flow but on how

the shareholders would value this by examining their excess stock returns.

H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366 341

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

reserves should decline with larger cash holdings, higher leverage and better access to capital markets. Their empirical findings support all of these argu- ments, including the idea that excess cash holdings are more valuable for share- holders in financially constrained firms. On the other hand, Pinkowitz and Williamson (2004) examine the value placed on a firm’s cash holdings under dif- ferent growth scenarios. These authors find that investors placed a higher value on cash holdings of firms that had higher growth opportunities. More recently, MacKay and Phillips (2005) investigate the effect of product

market competition on a firm’s financial choices, in particular, leverage. These authors find that industry-related factors and financial choices such as leverage are jointly determined. In addition, they find that firms in competitive industries used less financial leverage than those in less competitive industries. Fresard (2010) examines directly the role of cash holdings in a firm’s product market decision-making. This author finds that cash holdings can be used to support competitive strategies against industry rivals. However, he does not directly investigate whether firms in competitive industries will retain greater cash hold- ings than those in less competitive industries, and he does not examine whether investors place a different value on excess cash holdings. How corporate governance is associated with the value of cash holdings has

also been explored both internationally and in the United States Pinkowitz et al. (2006) investigate how minority shareholders in countries with poorer investor protection value a firm’s cash holdings. These authors find that a firm’s cash is valued at a discount in countries with weaker investor rights, because controlling shareholders might use their position to extract private benefits from cash hold- ings. Dittmar and Mahrt-Smith (2007) document that shareholders in the United States assign a lower value to an additional dollar of cash reserves when a firm has a more entrenched management team or lower institutional ownership. These investigators argue that investors discount more heavily the cash holdings of a firm with a higher likelihood of having agency problems. Finally, the main focus of Lee and Powell (2011) is to examine the determi-

nants of the level of cash holdings in Australia. These authors find results similar to Opler et al. (1999). In addition, they investigate the value of excess cash hold- ings in Australia. They show that firms with a longer duration of excess cash holdings have a lower marginal value of cash. However, they do not examine how shareholders value cash holdings with respect to firm growth, cash-flow uncertainty and corporate governance.

3. Empirical methodology

This section outlines the baseline empirical model involved in examining the value of cash holdings for Australian firms, followed by a discussion of the impact of financial constraints, firm growth opportunities, uncertainty in cash flows, product market competition and corporate governance on the marginal value of cash holdings.

342 H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

3.1. Baseline empirical model

The primary goal of this study is to investigate the value investors place on an extra dollar of cash held by Australian firms and how various factors that affect a firm’s external financing conditions would alter this value. Following Faulk- ender and Wang (2006), we employ the following baseline model to regress excess stock returns over a fiscal year on the unexpected change in various firm- specific characteristics that affect cash positions in that fiscal year. This is repre- sented by the following:

ri;t � RBPi;t ¼ a0 þ b1 DCi;t Mi;t�1

þ b2 DEi;t Mi;t�1

þ b3 DNAi;t Mi;t�1

þ b4 DRNDi;t Mi;t�1

þ b5 DIi;t Mi;t�1

þ b6 DDi;t Mi;t�1

þ b7 Ci;t�1 Mi;t�1

þ b8Li;t þ b9 NFi;t Mi;t�1

þ b10 Ci;t�1 Mi;t�1

� DCi;t Mi;t�1

þ b11Li;t DCi;t Mi;t�1

þ ei;t

ð1Þ

where D represents the change in the variable X of firm i between fiscal year t and t ) 1. The dependent variable is excess stock return, where ri,t is stock i’s annualized

return in fiscal year t and RBPi;t is annualized return of stock i’s benchmark port- folio during fiscal year t. The benchmark portfolio is based on the whole sample of the Australian Graduate School of Management (AGSM) Share Price and Price Relative (SPPR) database. We use the 25 Fama and French (1993) portfo- lios formed on market capitalization (size) and book-to-market equity ratios as benchmark portfolios. This is because Fama and French (1993) find that size and book-to-market proxy for common risk factors. By controlling for these two common risk proxies, any relationship found between excess stock return and cash holdings would not be attributed to common risk factors. Ct is cash includ- ing short-term deposits, Et is earnings before interest and tax (EBIT), and NAt is total book assets minus Ct. RNDt is capitalized research and development expenses, It is net interest expense, Dt is total common dividend paid, Lt is total debt divided by total book assets, and NFt is net changes in total financing cash flow. D is notation for the change of variables from fiscal year t ) 1 to t. All vari- ables except Lt (leverage) and excess stock return are deflated by the lagged mar- ket value of equity (Mt)1). As indicated by Faulkender and Wang (2006), this methodology is a type of long-term event study that exploits unexpected change in firm-specific factors to explain abnormal returns. Specifically, the change in the value of cash reserves is the event, while the entire fiscal year is defined as the event window. Our benchmark portfolios formed on size and book-to-market equity ratios

may not be free from industry bias, because the US market is quite different

H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366 343

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

from the Australian stock market, which is characterized by a high proportion of resources firms the ASX. These resources firms are rich in cash reserves, and the time-series association between cash holdings and stock returns is likely to be volatile owing to the structural influence of the resources sector. In addition, Masulis et al. (2009) argue that the Faulkender and Wang (2006) approach suf- fers a potential endogeneity problem because a firm’s book-to-market equity ratio is endogenous. Therefore, we also use RBIi;t , industry value-weighted annual- ized benchmark returns, as in the study of Masulis et al. (2009), where industries are defined based on the AGSM Centre for Research in Finance (CRIF) 26 industry classifications. For our baseline regression, we estimate the pooled ordinary least square

(OLS) regression model given by Equation (1) with year dummies. We allow residuals to be correlated within years by using the Huber–White variance/ covariance matrix estimator to correct for potential heteroscedasticity. Petersen (2009) argues that both time effect and firm effect should be properly dealt with in a panel data set to mitigate estimation biases. Industry effects are also impor- tant for an Australian sample given that cash holdings are particularly skewed across resources industries. In robustness checks, we also re-estimate our baseline model using the industry fixed-effects model and the firm fixed-effects model. Our main results are qualitatively similar. For comparison with the results obtained in Faulkender and Wang (2006) and Lee and Powell (2011), we use pooled OLS in our baseline regressions.

3.2. Financial constraints and the value of cash

To examine the impact of financial constraints on the marginal value of cash holdings, we need to classify our sample into financially constrained (FC) and non-financially constrained (NFC) firms.

4 A firm is said to be FC if its cost of

external capital exceeds the cost of internal funds. However, this definition does not provide us with clear-cut guidance on identifying constrained firms. Chang et al. (2007) suggest that FC firms generally tend to have one or more of the fol- lowing characteristics: small or unprofitable, high growth potential, high leverage and low debt capacity. Standard corporate finance theory suggests that smaller firms are more financially constrained than larger firms. As a result, we use an approach similar to Chang et al. (2007). Our sample of firms is evenly divided into two groups according to their median book value of total assets. We define

4 Some studies have used the KZ index (Kaplan and Zingales, 1997) to classify firms as

financially constrained (above-median KZ index) or unconstrained (below-median KZ index). The KZ index is constructed and based on a small sample of 49 US firms; it may not be appropriate for Australian firms. Nevertheless, and as a robustness check, we use the methodology from Kaplan and Zingales (1997) to partition our sample into finan- cially constrained and unconstrained firms. We find qualitatively similar results to those reported in this study. The results are not reported here but are available upon request.

344 H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

below-median firms as FC firms and above-median firms as NFC firms. 5 Smaller

firms are more likely to be financially constrained than larger firms because they are typically young and less known to the market. Smaller firms are more likely to encounter information asymmetry and agency problems, which will make their external financing more expensive. Fazzari et al. (1988) used the dividend payout approach to classify firms into

FC and NFC firms. They argue that owing to information asymmetries in capi- tal markets, FC firms have limited access to external financing. As a result, FC firms tend to retain most of their income. We follow Chang et al. (2007) to parti- tion our sample of firms into two groups according to their dividend payout ratios (as measured by dividend/EBIT). Non-dividend payers are firms that do not pay dividends and are more likely to be financially constrained. Dividend payers are those firms paying dividends in a particular year and are viewed as unconstrained.

6 We first follow Faulkender and Wang (2006) to test the follow-

ing hypothesis.

Hypothesis 1: The marginal value of cash holdings is negatively associated with the level of a firm’s cash position and the level of a firm’s leverage. Investors in financially constrained firms value excess cash holdings more than those in non- financially constrained firms.

3.3. Growth opportunities, uncertainty, product market competition and the value of cash

Firms with strong growth opportunities and investment needs are likely to hold more cash (Opler et al., 1999). As a result, investors value cash holdings by firms with good growth opportunities at a premium to those with poor growth opportunities (Pinkowitz and Williamson, 2004). We use book-to-market ratios (BTMs) as a proxy for investment opportunities to partition our sample of firms into two groups: a low BTM group and a high BTM group.

7

Hypothesis 2: Investors value excess cash holdings of firms with higher growth opportunities more than excess cash holdings of firms with lower growth opportuni- ties.

Firms facing higher uncertainty in their cash flows are likely to hoard excess cash in fear of future cash shortfalls. Firms with highly uncertain cash flows

5 We also partition our sample of firms into tertiles (quintiles) and then compare the low-

est tertile (quintile) with the highest tertile (quintile). Our results still hold.

6 We do not use debt ratings as less than 5 per cent of firms in our sample have debt rat-

ings. Also, during the majority of our sample period, there were very few corporate debt issues.

7 Using alternative proxies, such as growth in total assets, yield quite similar results.

H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366 345

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

face higher external funding costs when compared to internally generated funds. As a result, firms with a higher level of uncertainty are expected to rely more on internal funds and to save more cash. Opler et al. (1999) find that firms with high-risk cash flows generally hold relatively high levels of cash. We use the standard deviation of earnings ratios (as measured by EBIT/total book assets) for the past 5 years to proxy for uncertainty in cash flows. Our sample is partitioned into high-uncertainty and low-uncertainty groups according to their standard deviations of earnings ratios. We propose the following hypothesis.

Hypothesis 3: Investors value excess cash holdings of firms with higher cash-flow uncertainty more than excess cash flows of firms with lower cash-flow uncertainty.

Finally, it has been argued in the literature by Phillips (1995), MacKay and Phillips (2005) and Fresard (2010) that intense product market competition affects firm financial choices. Firms in highly competitive industries are more likely to hoard more cash reserves as a buffer for their future liquidity needs. Therefore, firms with excess cash holdings are viewed positively by stock mar- ket investors. We use the Herfindahl–Hirschman index (HHI) as a proxy for product market competition. HHI is calculated by summing up the squares of the individual market shares by sales for firms in a specific industry. In this study, we use the CRIF 26 industry classifications to calculate HHIs. Our sam- ple is partitioned into high industry competition (with low HHIs) and low industry competition (with high HHIs) groups according to HHI at the indus- try level.

8

Hypothesis 4: Investors value excess cash holdings of firms in highly competitive industries more than excess cash holdings of firms in industries with less competi- tion.

3.4. Corporate governance and the value of cash

Firms with higher agency costs are likely to misuse their cash reserves. So, investors would value cash holdings less when controlling shareholders might have the opportunity to expropriate minority shareholders in countries with poorer shareholder protection (Pinkowitz et al., 2006). Even in countries with strong shareholder protection, shareholders are still concerned about whether managers will waste cash reserves, especially for firms with a high level of managerial entrenchment or for firms that lack investor oversight by large institutional shareholders (Dittmar and Mahrt-Smith, 2007). We use two

8 We obtain similar results for Tables 4, 5, 6 and 7 when comparing the lowest tertile

(quintile) with the highest tertile (quintile) by using tertile or quintile partition. The results are not reported but are available upon request.

346 H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

corporate governance measures to investigate their association with the value of cash holdings. These are the Horwath Corporate Governance index (HCG index hereafter) of Australian firms and the ownership of large shareholders (block- holders) in the firm.

9

3.4.1. HCG index

The Horwath Corporate Governance Report is a review of Australian cor- porate governance that was published annually from 2002 to 2006. The report is based on annual report disclosures of Australia’s top 250 firms based on market capitalization. The report intends to provide an overall assessment of each firm’s corporate governance structures and constructs a star rating with a maximum value of 5 and a relative corporate governance ranking from 1 to 250. The fundamental focus of the report is to assess the independence of a firm’s board of directors and associated committees, including audit commit- tees, nomination committees and remuneration committees. The report also measures ‘the level of perceived independence of the firm from the external auditors, and disclosures relating to the existence of a code of conduct, risk management and share trading policy’. If a firm has a 5-star rating, this indi- cates the firm has outstanding corporate governance structures and ‘the struc- tures met all best practise standards and could not be faulted’. If a firm is assigned a 1-star rating, its corporate governance structures are in very poor condition and ‘almost without exception the board of directors and the associ- ated committees (where they existed) contained no independent members’. We employ both the Horwath star and ranking (from number 1, the highest gover- nance ranking, to 250, the lowest) measures in the value of cash holdings regressions.

3.4.2. Block holdings

We follow the study of Dittmar and Mahrt-Smith (2007) and use the sum of all ownership positions >5 per cent held by large investors as our measure for large shareholder monitoring. Prior research, such as the study of Dlugosz et al. (2004), indicates that large shareholders have more incentive to monitor and influence managers’ decisions, because they have a large capital stake in the firm. However, Pagano and Röell (1998) suggest that large shareholders could end up

9 The Horwarth Governance index is published by the University of Newcastle and is

viewed as an independent and reputable measure of corporate governance by the media and sections of the investment community. The index is publicly available only for the period 2002–2006. Blockholders are shareholders who own more than 5 per cent of a firm’s issued capital. These data are hand-collected from annual reports with all nominee holdings excluded.

H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366 347

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

using their position for ex post opportunism and to expropriate wealth from minority shareholders. Our regression model for the association between the value of cash holdings

and corporate governance is

ri;t � RBi;t ¼ a0 þ b1 DCi;t Mi;t�1

þ b2 DEi;t Mi;t�1

þ b3 DNAi;t Mi;t�1

þ b4 DRNDi;t Mi;t�1

þ b5 DIi;t Mi;t�1

þ b6 DDi;t Mi;t�1

þ b7 Ci;t�1 Mi;t�1

þ b8Li;t þ b9 NFi;t Mi;t�1

þ b10 Ci;t�1 Mi;t�1

� DCi;t Mi;t�1

þ b11Li;t � DCi;t Mi;t�1

þ b12Govi;t

þ b13Govi;t � DCi;t Mi;t�1

þ ei;t

ð2Þ

where Govi,t represents corporate governance measures such as the Horwath gov- ernance star and ranking, or the ownership of blockholders. We also follow Ditt- mar and Mahrt-Smith (2007) to include corporate governance in our analysis as a binary dummy by splitting the sample into subgroups. For the HCG index, a firm with more than three stars is coded one (strong governance) and less than three stars is coded zero (weak governance), while firms with a top 100 gover- nance ranking are coded one and firms in the bottom 100 are coded zero. For block ownership, the highest tercile of ownership is coded one (strong gover- nance), while the lowest tercile of ownership is coded zero (weak governance). Dittmar and Mahrt-Smith (2007) argue that using a dummy variable could allow for more intuitive interpretation of the coefficients on the interaction terms. This also helps us to avoid difficulties in interpreting how changes in governance measures could lead to very different management independence or investor monitoring.

Hypothesis 5: Investors value excess cash holdings of firms with strong corporate governance mechanisms more than those of firms with weak corporate governance mechanisms.

4. Data

4.1. Sample selection

We start from a merged sample of firms listed on the ASX over the 1990–2007 period with accounting data and stock return data available from the Aspect Financial Database and the Australian Graduate School of Man- agement Share Price and Price Relative (AGSM_SPPR) database. Firms are required to have no missing data for any of the following key variables: cash,

348 H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

earnings before interest and tax, total book assets, net interest expense, total common dividend paid, total debt, monthly stock returns and book value of equity from fiscal year t ) 1 to t. We limit our sample to the 500 largest firms listed on the ASX according to their market capitalizations in the fiscal year period. We also exclude firms in the financial and utilities sector (with CRIF industry code ‘18’, banks ‘20’, insurance ‘22’, real estate investment trusts and utilities ‘26’) owing to the relatively low physical capital investment for finan- cials and the regulated nature of utilities. Our sample consists of 1108 individ- ual firms and 6412 firm-year observations from 1990 to 2007.

10 All variables

have been winsorized at the 1st and 99th percentiles. This approach reduces the impact of extreme observations by assigning the cut-off value to values beyond the cut-off point.

11

The dependent variable in the baseline regression is excess stock return. Monthly stock returns are required to calculate individual stock returns and benchmark portfolio returns. Following Faulkender and Wang (2006), we use the 25 Fama and French (1993) portfolios formed on market capitaliza- tion (size) and BTM. In particular, for each fiscal year, we sort firms into 25 size and BTM portfolios based on their market capitalization and BTMs. Then, excess stock returns are calculated by subtracting annualized bench- mark portfolio returns from annualized stock raw returns. We also use the industry value-weighted annualized benchmark return as in the study of Masulis et al. (2009) to examine whether our main results suffer industry bias. In addition, we use two measures of corporate governance, the independence

of corporate governance structures (the HCG) and the presence of large share- holders who monitor the firm. We sum all ownership positions >5 per cent held by blockholders. The HCG star and ranking measures are manually collected from the Horwath Corporate Governance Report. The original Horwath Corpo- rate Governance Report includes 1250 observations. Our final sample drops to 557 observations after excluding firms in the financial and utilities sectors. The percentage ownership of blockholders is manually collected from annual report disclosures from Australia’s top 500 firms based on market capitalization from 2000 to 2007. Our final blockholder sample has 1798 observations after exclud- ing firms in the financial and utilities sectors and observations with missing values.

10 The minimum number of firms in any year is 221 (1990), and the maximum is 404

(2002, 2007). The average (median) over this period is approximately 356 (389) firms in a year. The number of firm-year observations compares favourably with the 5876 firm-year observations over the same sample period for the study of Lee and Powell (2011).

11 Our results are qualitatively very similar when we truncate the distribution instead of

winsorizing it.

H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366 349

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

4.2. Summary statistics

The summary statistics of the main variables are reported in Table 1. As all the explanatory variables except leverage ratio are scaled by the 1-year lagged market value of equity, we interpret our variables as changes in dollar value. Table 1 indicates that, on average, earnings before interest and taxes (Et), non- cash book assets (NAt) and total common dividends paid (Dt) increase over the sample period, as both their mean and median values are positive. Panel A of Table 2 reports summary statistics of firms in our sample after

we classify them into as constrained (FC) or unconstrained (NFC). Accord- ing to size and dividend payout, a FC firm has on average a higher annual- ized excess return, a higher change in cash holdings, a higher level of cash holdings, higher leverage and higher change in financing cash flow than does a NFC firm. Similarly, Panel B of Table 2 indicates that firms with lower BTM (higher growth opportunities) and higher level of cash-flow uncertainty have higher annualized excess returns, higher changes in cash holdings and higher changes in financing cash flow. However, firms in highly competitive industries have lower annualized excess returns, lower changes in cash

Table 1

Sample summary statistics (1990–2007)

Variable Observations Mean Median SD Min Max

Ri;t � RBPi;t 6412 0.0476 )0.0416 0.7021 )1.9737 3.4540 Ri;t � RBIi;t 6412 0.2138 0.0278 0.7796 )0.9353 4.2872 DCt 6412 0.0390 0.0033 0.2166 )0.8363 1.5223 Ct)1 6412 0.1177 0.0547 0.2127 0 2.0023

DEt 6412 0.0246 0.0107 0.1800 )1.0969 1.6511 DNAt 6412 0.2371 0.0907 0.8052 )3.6493 5.8598 DIt 6412 0.0002 )0.0001 0.0335 )0.1676 0.2463 DDt 6412 0.0078 0.0015 0.029 )0.1025 0.1342 Lt 6412 0.1939 0.1862 0.1658 0 0.8669

NFt 6412 0.0911 )0.0012 0.4551 )1.1248 3.3568

Accounting data are obtained from the Aspect Financial Database, and stock returns are obtained

from the AGSM_SPPR Database for fiscal years 1990–2007. Firms are required to have available

information for all key variables needed in the study and to be among the top 500 largest firms listed

in the ASX according to market capitalization in the study period. Ri;t �RBPi;t and Ri;t � R BI i;t are

excess stock returns, where Ri,t is the annualized stock return of firm i in fiscal year t, Ri;t �RBPi;t is stock i’s annualized benchmark portfolio return in fiscal year t calculated on value-weighted returns

of 25 portfolios formed on size and book-to-market (5 · 5) as in the study of Fama and French (1993), and Ri;t � RBIi;t is industry value-weighted annualized benchmark return as in the study of Masulis et al. (2009). All variables except Lt (leverage) and excess stock return are deflated by the

lagged market value of equity (Mt)1). Ct is cash including short-term deposits; Et is earnings before

interest and tax; and NAt is total book assets minus Ct; It is net interest expense; Dt is total common

dividend paid; Lt is total debt divided by total book assets, and NFt is net changes in total financing

cash flow. D is notation for the change of variables from fiscal year t ) 1 to t.

350 H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

T a b le

2

F in a n ci a l co n st ra in ts , g ro w th

o p p o rt u n it ie s, ca sh -fl o w u n ce rt a in ty

a n d co rp o ra te

g o v er n a n ce

P a n el A : F in a n ci a l co n st ra in ts

V a ri a b le

D iv id en d p a y in g

S iz e

F C

N F C

F C

) N F C

F C

N F C

F C

) N F C

R i; t � R

B P

i; t

0 .0 9 9

0 .0 2 3

0 .0 7 6 * * *

0 .0 8 3

0 .0 1 2

0 .0 7 1 * * *

R i; t � R

B I

i; t

0 .2 3 1

0 .0 4 8

0 .1 8 3 * * *

0 .2 2 7 7

) 0 .0 1 3

0 .2 4 1 * * *

D C t

0 .0 8 2

0 .0 1 8

0 .0 6 4 * * *

0 .0 6

0 .0 1 8

0 .0 4 2 * * *

C t) 1

0 .1 6 9

0 .0 9 3

0 .0 7 6 * * *

0 .1 2

0 .1 1 6

0 .0 0 4

D E t

0 .0 0 4

0 .0 3 4

) 0 .0 3 * * *

0 .0 2 8

0 .0 2 1

0 .0 0 7 *

D D

t 0 .0 0 3

0 .0 1

) 0 .0 0 7 * * *

0 .0 0 8

0 .0 0 8

0

L t

0 .1 7

0 .2 0 6

) 0 .0 3 6 * * *

0 .1 3 5

0 .2 5 3

) 0 .1 1 8 * * *

N F t

0 .2 1 8

0 .0 3

0 .1 8 8 * * *

0 .1 3 6

0 .0 4 7

0 .0 8 9 * * *

P a n el B : G ro w th , u n ce rt a in ty

a n d co m p et it io n

V a ri a b le

B o o k -t o -m

a rk et

ra ti o

C a sh -fl o w u n ce rt a in ty

In d u st ry

co m p et it io n

H ig h

L o w

L o w

) H ig h

L o w

H ig h

H ig h

) L o w

L o w

H ig h

H ig h

) L o w

R i; t � R

B P

i; t

) 0 .0 2 2

0 .1 1 8

0 .1 3 9 * * *

0 .0 2 5

0 .0 7 1

0 .0 4 6 * * *

0 .0 8 3

0 .0 1 2

) 0 .0 7 1 * * *

R i; t � R

B I

i; t

) 0 .0 7 0

0 .2 8 5

0 .3 5 6 * * *

0 .0 1 6

0 .1 9 9

0 .1 8 3 * * *

0 .1 5 1

0 .0 6 3

) 0 .0 8 8 * * *

D C t

0 .0 3 0

0 .0 4 8

0 .0 1 8 * * *

0 .0 1 9

0 .0 5 9

0 .0 4 * * *

0 .0 5

0 .0 2 9

) 0 .0 2 1 * * *

C t) 1

0 .1 3 4

0 .1 0 1

) 0 .0 3 3 * * *

0 .1 0 8

0 .1 2 7

0 .0 1 9 * * *

0 .1 2 1

0 .1 1 4

) 0 .0 0 7

D E t

0 .0 2 3

0 .0 2 6

0 .0 0 2

0 .0 1 3

0 .0 3 6

0 .0 2 3 * * *

0 .0 2 4

0 .0 2 5

0 .0 0 1

D D

t 0 .0 0 8

0 .0 0 7

) 0 .0 0 1

0 .0 0 8

0 .0 0 8

0 0 .0 0 7

0 .0 0 9

0 .0 0 2 * * *

L t

0 .2 0 9

0 .1 7 9

) 0 .0 3 0 * * *

0 .2 2 2

0 .1 6 5

) 0 .0 5 7 * * *

0 .1 9 7

0 .1 9 1

) 0 .0 0 6

N F t

0 .0 7 2

0 .1 1 1

0 .0 3 9 * * *

0 .0 2 9

0 .1 5 4

0 .1 2 5 * * *

0 .1 1 4

0 .0 6 9

) 0 .0 4 5 * * *

H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366 351

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

T a b le

2 (c o n ti n u ed )

P a n el C : C o rp o ra te

g o v er n a n ce

V a ri a b le

H C G

st a r

H C G

ra n k in g

B lo ck h o ld er

o w n er sh ip

S tr o n g

W ea k

S tr o n g

) W ea k

S tr o n g

W ea k

S tr o n g

) W ea k

S tr o n g

W ea k

S tr o n g

) W ea k

R i; t � R

B P

i; t

) 0 .0 3 1

) 0 .0 2 7

) 0 .0 0 4

) 0 .0 3 1

) 0 .0 3 8

0 .0 0 6

0 .1 3 1

0 .1 6 8

) 0 .0 3 7

R i; t � R

B I

i; t

) 0 .0 3 2

) 0 .0 3 8

0 .0 0 7

) 0 .0 2 7

) 0 .0 5 1

0 .0 2 4

0 .0 7 8

0 .1 0 9

) 0 .0 3 0

D C t

0 .0 1 6

0 .0 3 1

) 0 .0 1 5

0 .0 1 5

0 .0 3 5

) 0 .0 2 0

0 .0 2 2

0 .0 5 9

) 0 .0 3 8 * * *

C t) 1

0 .0 9 2

0 .0 8 9

0 .0 0 3

0 .0 8 0

0 .0 8 8

) 0 .0 0 8

0 .1 4 5

0 .1 2 4

0 .0 2 1

D E t

0 .0 1 1

0 .0 2 2

) 0 .0 1 1

0 .0 1 2

0 .0 2 1

) 0 .0 1 0

0 .0 2 6

0 .0 2 2

0 .0 0 4

D D

t 0 .0 0 6

0 .0 0 5

0 .0 0 1

0 .0 0 5

0 .0 0 6

) 0 .0 0 2

0 .0 0 6

0 .0 0 6

0 .0 0 0

L t

0 .2 3 5

0 .1 7 8

0 .0 5 7 * * *

0 .2 3 3

0 .1 8 1

0 .0 5 2 * * *

0 .1 7 1

0 .1 9 0

) 0 .0 1 9 * *

N F t

0 .0 2 7

0 .0 3 3

) 0 .0 0 6

0 .0 1 3

0 .0 4 7

) 0 .0 3 4

0 .0 4 0

0 .1 2 9

) 0 .0 8 9 * * *

A cc o u n ti n g d a ta

a re

o b ta in ed

fr o m

th e A sp ec t F in a n ci a l D a ta b a se , a n d st o ck

re tu rn s a re

o b ta in ed

fr o m

th e A G S M _ S P P R

D a ta b a se

fo r fi sc a l y ea rs

1 9 9 0 – 2 0 0 7 . F ir m s a re

re q u ir ed

to h a v e a v a il a b le in fo rm

a ti o n fo r a ll k ey

v a ri a b le s n ee d ed

in th e st u d y a n d to

b e a m o n g th e to p 5 0 0 la rg es t fi rm

s li st ed

o n th e

A S X

a cc o rd in g to

m a rk et

ca p it a li za ti o n in

th e st u d y p er io d . R

i; t � R

B P

i; t a n d R

i; t � R

B I

i; t a re

th e ex ce ss

st o ck

re tu rn s, w h er e R i, t is th e a n n u a li ze d st o ck

re tu rn

o f fi rm

i in

fi sc a l y ea r t, R

i; t � R

B P

i; t is st o ck

i’ s a n n u a li ze d b en ch m a rk

p o rt fo li o re tu rn

in fi sc a l y ea r t ca lc u la te d o n v a lu e- w ei g h te d re tu rn s o f 2 5 p o rt fo li o s,

w h ic h a re

fo rm

ed o n si ze

a n d b o o k -t o -m

a rk et

(5 · 5 ), a s in

th e st u d y o f F a m a a n d F re n ch

(1 9 9 3 ), a n d R

i; t � R

B I

i; t is

in d u st ry

v a lu e- w ei g h te d a n n u a li ze d

b en ch m a rk

re tu rn

a s in

th e st u d y o f M a su li s et

a l. (2 0 0 9 ). A ll v a ri a b le s ex ce p t L t (l ev er a g e)

a n d ex ce ss

st o ck

re tu rn

a re

d efl a te d b y th e la g g ed

m a rk et

v a lu e

o f eq u it y (M

t) 1 ). C t is ca sh

in cl u d in g sh o rt -t er m

d ep o si ts ; E t is ea rn in g s b ef o re

in te re st

a n d ta x ; N A t is to ta l b o o k a ss et s m in u s C t; I t is n et

in te re st

ex p en se ;

D t is

to ta l co m m o n d iv id en d p a id ; L t is to ta l d eb t d iv id ed

b y to ta l b o o k a ss et s; a n d N F t is n et

ch a n g e in

to ta l fi n a n ci n g ca sh

fl o w . D

is n o ta ti o n fo r th e

ch a n g e o f v a ri a b le s fr o m

fi sc a l y ea r t- 1 to

t. F ir m s a re

ca te g o ri ze d a s b ei n g fi n a n ci a ll y co n st ra in ed

(F C ) a n d u n co n st ra in ed

(N F C ) a cc o rd in g to

th ei r b o o k

v a lu e o f a ss et s a n d d iv id en d p a y o u t ra ti o . t- st a ti st ic s si g n ifi ca n t a t th e 1 0 , 5 a n d 1 p er

ce n t le v el s a re

d es ig n a te d w it h * , * * , a n d * * * , re sp ec ti v el y .

352 H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

holdings and slightly lower level of cash holdings. 12

Panel C of Table 2 indi- cates that firms with strong corporate governance measures have higher changes in cash holdings. However, the differences between strong and weak corporate governance firms are statistically significant only for the block- holder ownership measure and not for the HCG star and ranking measures. To summarize, summary statistics and univariate analyses indicate that financially constrained firms, firms with higher growth opportunities, firms with higher uncertainty and firms with lower industry competition exhibit higher annualized excess returns and hold more excess cash. Firms with higher blockholder ownership are associated with lower annualized excess returns and hold less excess cash. This evidence provides initial support for our hypotheses.

5. Empirical results

5.1. The marginal value of cash holdings

Table 3 presents estimates from the baseline model for the entire sample using the pooled OLS regression. The initial coefficient estimates on the changes in cash holdings are statistically significant and positive at the 1 per cent level. This suggests that an additional dollar of cash corresponds to AU$0.726 as valued by shareholders (Column (1)). The estimated coefficients on the other control vari- ables have the expected signs and are largely consistent with those reported in Faulkender and Wang (2006) and Lee and Powell (2011). In particular, the coef- ficients on changes in earnings, changes in dividends and level of cash holdings are positive and significant in all four columns. Further, the estimated coeffi- cients are qualitatively similar when the following interaction terms are both included in the estimation: change in cash with the level of cash holdings (Ct)1 * DCt) and the leverage ratio with the level of cash holdings (Lt * DCt). Based on the estimation in Column (2), the marginal value of cash to investors in the mean firm is equal to AU$0.867 (= AU$1.095 + ()0.471 * 0.1177) + ()0.891 * 0.1939)) for a firm with a 11.77 per cent level of cash to market value of equity and a 19.39 per cent leverage ratio. This result is consis- tent with Hypothesis 1 that the marginal value of cash holdings is negatively associated with the level of a firm’s cash position and the level of a firm’s lever- age ratio. Columns (3) and (4) use alternative excess stock returns, the annual- ized industry-adjusted excess returns. The results are very similar to those in

12 In the literature, there is no direct empirical evidence on whether firms in highly com-

petitive industries would hold more or less cash. MacKay and Phillips (2005) investigate only the association between industry competition and leverage. In Panel B, the leverage ratios for highly competitive industries are slightly lower than those for less competitive industries. This is consistent with MacKay and Phillips (2005).

H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366 353

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

Columns (1) and (2) using the 25 Fama and French (1993) portfolios’ adjusted excess returns.

5.2. Financial constraints and the value of cash holdings

Table 4 presents the estimated results for the association between financial constraints and the value of cash holdings. Columns (1) and (2) of Table 4 con- tain the regression results for the dividend payout groupings. Non-dividend pay- ers (FC) exhibit a higher value of cash holdings than dividend payers (NFC). Columns (4) and (5) report results obtained by using firm book value of assets as the measure of financial constraints. Similarly, small firms (FC) exhibit higher

Table 3

Regression results for the marginal value of cash holdings

Variables

(1) (2) (3) (4)

Ri;t �RBPi;t Ri;t � RBPi;t Ri;t �RBIi;t Ri;t � RBIi;t

DCt 0.726*** (8.50) 1.095*** (8.96) 0.735*** (8.12) 1.108*** (8.47) DEt 0.449*** (4.48) 0.450*** (4.86) 0.479*** (4.64) 0.480*** (4.99) DNAt 0.041 (1.50) 0.040 (1.54) 0.066** (2.31) 0.064** (2.43) DRNDt )0.526 ()0.44) )0.648 ()0.56) )0.381 ()0.32) )0.505 ()0.43) DIt 1.351*** (3.11) 1.059*** (2.63) 1.867*** (4.36) 1.569*** (3.97) DDt 0.823** (2.56) 0.738** (2.38) 1.040*** (3.01) 0.954*** (2.86) Ct)1 0.466*** (6.63) 0.416*** (6.60) 0.393*** (5.33) 0.342*** (5.26)

Lt )0.272*** ()4.88) )0.240*** ()4.43) )0.415*** ()7.22) )0.383*** ()6.86) NFt 0.094* (1.88) 0.065 (1.34) 0.206*** (3.98) 0.176*** (3.50)

Ct)1 * DCt )0.471*** ()2.98) )0.471*** ()3.13) Lt * DCt )0.891** ()2.53) )0.916** ()2.44) Intercept )0.098** ()2.26) )0.106** ()2.47) 0.106** (2.43) 0.098** (2.33) Year dummy

included

Yes Yes Yes Yes

Observations 6412 6412 6412 6412

R 2

0.13 0.14 0.18 0.19

This table presents the results of regressing the excess stock return on changes in firm characteristics,

including interaction terms, between cash and leverage over the fiscal year. Ri;t � RBPi;t and Ri;t �RBIi;t are the excess stock returns, where Ri,t is the annualized stock return of firm i in fiscal year t;

Ri;t � RBPi;t is stock i’s annualized benchmark portfolio return in fiscal year t calculated on value- weighted returns of 25 portfolios formed on size and book-to-market (5 · 5) as in the study of Fama and French (1993); and Ri;t � RBIi;t is industry value-weighted annualized benchmark return as in the study of Masulis et al. (2009). All variables except Lt (leverage) and excess stock return are deflated

by the lagged market value of equity (Mt)1). Ct is cash including short-term deposits; Et is earnings

before interest and tax; NAt is total book assets minus Ct; RNDt are capitalized research and develop-

ment expenses; It is net interest expense; Dt is total common dividends paid; Lt is total debt divided

by total book assets; and NFt is net changes in total financing cash flow. All variables are winsorized

at the 1st and 99th percentiles. This approach reduces the impact of extreme observations by assign-

ing the cut-off value to values beyond the cut-off point. t-statistics significant at the 10, 5 and 1 per

cent levels are designated with *, ** and ***, respectively.

354 H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

value of cash holdings than large firms (NFC). On average, the marginal value of cash holdings for small firms is AU$1.056 (= AU$1.213 + ()0.765 * 0.120) + ()0.479 * 0.135)), while the marginal value of cash holdings for large firms is AU$0.501 (= AU$0.701 + ()0.178 * 0.116) + ()0.708 * 0.253)). The value difference for an additional dollar of cash holdings is AU$0.555. The coefficients on the change in cash are statistically different across FC and NFC

Table 4

Regression results for financial constraints

Variables

FC NFC FC NFC

Non-dividend

payers Dividend payers Small firms Large firms

DCt 1.108*** (10.20) 0.520*** (6.78) 1.213*** (12.71) 0.701*** (8.68) P-value

(FC ) NFC „ 0) 0.00 0.05

DEt 0.315*** (3.84) 0.992*** (15.83) 0.465*** (6.41) 0.455*** (8.10) DNAt )0.000 ()0.01) 0.092*** (6.47) 0.035 (1.49) 0.066*** (5.32) DRNDt )0.573 ()0.40) )0.567 ()0.59) )0.804 ()0.70) )0.519 ()0.47) DIt 0.473 (1.02) 2.239*** (7.27) 0.124 (0.25) 1.194*** (4.98) DDt )0.852 ()1.11) 1.085*** (4.58) 1.473*** (2.95) 0.135 (0.52) Ct)1 0.477*** (6.28) 0.213*** (4.68) 0.772*** (9.44) 0.198*** (5.99)

P-value

(FC ) NFC „ 0) 0.03 0.00

Lt )0.322*** ()2.86) )0.103** ()2.18) )0.181* ()1.80) )0.225*** ()4.60) NFt 0.203*** (3.96) )0.190*** ()6.66) 0.109** (2.49) )0.070*** ()2.59) Ct)1 * DCt )0.667*** ()5.77) )0.001 ()0.01) )0.765*** ()6.23) )0.178*** ()2.79) Lt * DCt )0.782** ()2.39) )0.022 ()0.07) )0.479 ()1.05) )0.708*** ()3.64) Intercept )0.199* ()1.94) )0.154 ()1.19) )0.302*** ()4.36) 0.046 (1.28) Year dummy

included

Yes Yes Yes Yes

Observations 2081 4331 3211 3201

R 2

0.17 0.17 0.17 0.12

Difference

between FC

and NFC firms

(v2 of Chow test)

123.40*** 92.16***

This table presents the results of regressing the excess stock return Ri,t ) RBi,t on changes in firm characteristics for firms with and without financial constraints over the fiscal year. The baseline

model is a pooled ordinary least square model controlling for time effect. All variables except Lt (leverage) and excess stock return are deflated by the lagged market value of equity (Mt)1). Ct is cash

including short-term deposits; Et is earnings before interest and tax; NAt is total book assets minus

Ct; RNDt is capitalized research and development expenses; It is net interest expense; Dt is total com-

mon dividend paid; Lt is total debt divided by total book assets; and NFt is the net changes in total

financing cash flow. All variables are winsorized at the 1st and 99th percentiles. This approach

reduces the impact of extreme observations by assigning the cut-off value to values beyond the cut-

off point. t-statistics significant at the 10, 5 and 1 per cent levels are designated with *, ** and ***,

respectively.

H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366 355

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

groups (P-values reported in Table 4 are <0.05). 13

This implies that investors place a significantly higher value on an extra dollar of cash holdings for finan- cially constrained firms, because it is more difficult for these firms to access exter- nal financing. These results support Hypothesis 1.

5.3. Growth opportunities, uncertainty and product market competition

To investigate whether growth opportunities, uncertainty in cash flows and product market competition affect the value of cash holdings in a way similar to financial constraints, we use BTMs (proxy for growth opportunities), standard deviation of earnings (proxy for cash-flow uncertainty) and the HHI (proxy for product market competition) to partition our sample. Table 5 reports results for the association between growth opportunities and the value of cash holdings. Low-growth firms have a lower value of cash holdings than high-growth firms.

On average, the marginal value of cash holdings for low-growth firms is AU$0.675 (= AU$0.828 + ()0.225 * 0.120) + ()0.630 * 0.200)), while the marginal value of cash holdings for high-growth firms is AU$0.979 (= AU$1.233 + ()0.741 * 0.116) + ()0.897 * 0.187)). The dollar value difference is AU$0.304 per additional dollar of cash holdings. The coefficients on the change in cash are statistically different between low-growth and high-growth groups (reported P-values <1 per cent). This confirms Hypothesis 2 that inves- tors value excess cash holdings of firms with high sales growth rates more than those of firms with low sales growth rates. The results for the association between cash-flow uncertainty and the value of

cash holdings are presented in Table 6. It is evident from the table that firms with high uncertainty of cash flows exhibit higher value of cash holdings than firms with low uncertainty. On average, the marginal value of cash holdings for high-uncertainty firms is AU$1.014 (= AU$1.207 + ()0.410 * 0.127) + ()0.856 * 0.165)), while the marginal value of cash holdings for low-uncertainty firms is AU$0.626 (= AU$0.799 + ()0.399 * 0.108) + ()0.585 * 0.222)). The P-values for the coefficient tests on the change in cash show that the two group coefficients are significantly different. The results support Hypothesis 3 that firms with high cash-flow uncertainty have higher marginal value in excess cash hold- ings than firms with low cash-flow uncertainty. Table 7 reports results for the association between product market competi-

tion and the value of cash holdings. In contrast to the findings for sales growth and cash-flow uncertainty, product market competition seems to have little influ- ence on the value of excess cash holdings. The coefficients on the change in cash do not statistically differ between more competitive and less competitive groups

13 In additional analysis, we perform a Chow test to see whether the model estimation dif-

fers statistically across these two financial constraint groups. The statistics in the last row of Table 4 show that the differences between the constrained and the non-constrained for dividend payout ratios are statistically significant with P-values of <1 per cent.

356 H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

(P-values reported are more than 15 per cent). However, when we calculate the difference in the value of excess cash holdings, the marginal value of cash hold- ings for firms in highly competitive industries (AU$0.878 = AU$1.167 + ()0.367 * 0.114) + ()1.292 * 0.191)) is slightly higher than the marginal value of cash holdings for firms in industries with less competition (AU$0.804 = AU$0.986 + ()0.527 * 0.121) + ()0.602 * 0.197)).

5.4. Corporate governance and value of cash holdings

To investigate whether corporate governance affects the value of cash hold- ings, we first employ HCG stars (HWS, from 1 star to 5 stars, representing weak to strong corporate governance structures) and HCG rankings (HWR, from 1,

Table 5

Regression results for growth opportunities

Variables High book-to-market (HBM) Low book-to-market (LBM)

DCt 0.828*** (9.75) 1.233*** (14.28) P-value (HBM ) LBM „ 0) 0.00 DEt 0.472*** (7.47) 0.423*** (5.85) DNAt 0.073*** (3.91) 0.019 (0.96) DRNDt )2.487** ()2.39) 0.500 (0.41) DIt 1.485*** (4.94) 0.945** (2.10) DDt 1.034*** (3.17) 0.442 (0.95) Ct)1 0.313*** (7.02) 0.598*** (8.28)

P-value (HBM ) LBM „ 0) 0.00 Lt )0.149** ()2.51) )0.302*** ()3.58) NFt 0.050 (1.27) 0.053 (1.45)

Ct)1 * DCt )0.225*** ()2.70) )0.741*** ()6.54) Lt * DCt )0.630** ()2.57) )0.897*** ()2.70) Intercept )0.060 ()1.33) )0.170*** ()2.63) Year dummy included Yes Yes

Observations 3211 3201

R 2

0.11 0.16

Difference between HBM

and LBM firms

(v2 of Chow test)

42.90***

This table presents the results of regressing the excess stock return Ri,t ) RBi,t on changes in firm characteristics for firms with different book-to-market ratios over the fiscal year. The baseline model

is a pooled ordinary least square model controlling for time effect. All variables except Lt (leverage)

and excess stock return are deflated by the lagged market value of equity (Mt)1). Ct is cash including

short-term deposits; Et is earnings before interest and tax; NAt is total book assets minus Ct; RNDt is

capitalized research and development expenses; It is net interest expense; Dt is total common dividend

paid; Lt is total debt divided by total book assets; and NFt is the net changes in total financing cash

flow. All variables are winsorized at the 1st and 99th percentiles. This approach reduces the impact

of extreme observations by assigning the cut-off value to values beyond the cut-off point. t-statistics

significant at the 10, 5 and 1 per cent levels are designated with *, ** and ***, respectively.

H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366 357

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

highest, to 250, lowest). Table 8 reports results for the association between the HCG index and the value of cash holdings. The coefficients for HWS, HWR and their interactions with excess cash holdings have the expected signs but are not statistically significant, except for HWR * DCt, which has marginal signifi- cance. The negative coefficient of HWR * DCt indicates that the stronger the HCG (high HWR represents weak governance), the higher the value of excess cash holdings, which is consistent with Hypothesis 5. Columns (1) and (2) of Table 9 report the results for the ownership of large

shareholders and the value of cash holdings. BlockHolding is the sum of all per- centage ownership of blockholders. BlockDummy equals 1 if a firm is in the high- est tercile of ownership (strong governance) and zero if a firm in the lowest tercile of ownership (weak governance). As shown in Table 9, both coefficients on BlockHolding and BlockDummy are negative and significant, suggesting

Table 6

Regression results for cash-flow uncertainty

Variables Low uncertainty (LUC) High uncertainty (HUC)

DCt 0.799*** (10.92) 1.207*** (13.09) P-value (LUC ) HUC „ 0) 0.08 DEt 0.183* (1.95) 0.471*** (7.23) DNAt 0.024 (1.58) 0.042** (2.01) DRNDt )3.464*** ()2.98) 0.320 (0.28) DIt 1.145*** (4.17) 0.920** (2.14) DDt 0.274 (0.96) 1.310*** (2.79) Ct)1 0.215*** (6.05) 0.705*** (9.23)

P-value (LUC ) HUC „ 0) 0.00 Lt )0.218*** ()4.30) )0.238*** ()2.66) NFt 0.076*** (2.59) 0.037 (0.89)

Ct)1 * DCt )0.399*** ()5.87) )0.410*** ()3.38) Lt * DCt )0.585*** ()2.86) )0.856** ()2.43) Intercept )0.073** ()1.97) )0.161** ()2.31) Year dummy included Yes Yes

Observations 3211 3201

R 2

0.10 0.17

Difference LUC and HUC

firms (v2 of Chow test) 67.89***

This table presents the results of regressing the excess stock return Ri,t ) RBi,t on changes in firm characteristics for firms with different cash-flow uncertainty over the fiscal year. The baseline model

is a pooled ordinary least square model controlling for time effect. All variables except Lt (leverage)

and excess stock return are deflated by the lagged market value of equity (Mt)1). Ct is cash including

short-term deposits; Et is earnings before interest and tax; NAt is total book assets minus Ct; RNDt is

capitalized research and development expenses; It is net interest expense; Dt is total common dividend

paid; Lt is total debt divided by total book assets; and NFt is net change in total financing cash flow.

All variables are winsorized at the 1st and 99th percentiles. This approach reduces the impact of

extreme observations by assigning the cut-off value to values beyond the cut-off point. t-statistics sig-

nificant at the 10, 5 and 1 per cent levels are designated with *, ** and ***, respectively.

358 H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

investors put less value on the excess cash held by firms with higher blockholder ownership. Our results are inconsistent with Hypothesis 5 and results docu- mented in the United States by Dittmar and Mahrt-Smith (2007).

14 When a firm

holds more excess cash, investors discount the value of that cash holding. A pos- sible reason for this is concerns over potential expropriation or ex post oppor- tunism by large shareholders (Pagano and Röell, 1998). As the proportion of blockholder ownership increases, there is a higher probability for ex post

Table 7

Regression results for industry competition

Variables High industry competition (HIC) Low industry competition (LIC)

DCt 1.167*** (14.73) 0.986*** (10.85) P-value (HIC ) LIC „ 0) 0.15 DEt 0.356*** (5.96) 0.564*** (7.41) DNAt 0.079*** (4.61) 0.012 (0.60) DRNDt 0.548 (0.51) )1.453 ()1.21) DIt 0.944*** (3.03) 1.424*** (3.23) DDt 0.816** (2.34) 0.715 (1.59) Ct)1 0.388*** (7.90) 0.416*** (6.39)

P-value (HIC ) LIC „ 0) 0.75 Lt )0.213*** ()3.26) )0.261*** ()3.34) NFt )0.031 ()0.94) 0.150*** (3.61) Ct)1 * DCt )0.367*** ()4.46) )0.527*** ()4.70) Lt * DCt )1.292*** ()4.72) )0.602** ()2.03) Intercept )0.155*** ()3.16) )0.064 ()1.04) Year dummy included Yes Yes

Observations 3211 3201

R 2

0.15 0.14

Difference between HIC

and LIC firms

(v2 of Chow test)

26.07

This table presents the results of regressing excess stock return Ri,t-RBi,t on changes in firm character-

istics for firms with different industry competition provided by the Herfindahl index over the fiscal

year. The baseline model is a pooled ordinary least square model controlling for time effect. All vari-

ables except Lt (leverage) and excess stock return are deflated by the lagged market value of equity

(Mt)1). Ct is cash including short-term deposits; Et is earnings before interest and tax; NAt is total

book assets minus Ct; RNDt is capitalized research and development expenses; It is net interest

expense; Dt is total common dividend paid; Lt is total debt divided by total book assets; and NFt is

the net change in total financing cash flow. All variables are winsorized at the 1st and 99th percen-

tiles. This approach reduces the impact of extreme observations by assigning the cut-off value to val-

ues beyond the cut-off point. t-statistics significant at the 10, 5 and 1 per cent levels are designated

with *, ** and ***, respectively.

14 Unlike in studies of the United States, the blockholding type cannot be perfectly identi-

fied from the data that we manually collected from the annual reports. This is one possi- ble limitation in our blockholding analysis.

H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366 359

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

opportunism to occur. Under the imputation tax system with a preference for fully franked dividends, non-blockholder shareholders are more likely to prefer that excess cash be paid out as dividends. We also investigate how the HCG index and blockholder ownership

together are associated with the value of excess cash holdings in Columns (3) and (4) of Table 9.

15 The results are largely consistent with using the two

measures separately. Taken together, we find limited evidence on the associa- tion between corporate governance and the value of excess cash holdings in Australia.

Table 8

Regression results with Horwath Corporate Governance index

Variables (1) (2) (3) (4)

DCt 0.513*** (1.60) 1.307*** (4.04) 0.873*** (5.02) 1.289*** (5.88) DEt 0.839*** (6.03) 0.874*** (6.27) 0.839*** (4.62) 0.847*** (4.28) DNAt 0.129*** (3.39) 0.126*** (3.32) 0.173*** (3.08) 0.352*** (4.55) DRNDt 1.446 (0.89) 1.444 (0.89) 0.947 (0.49) )0.358 ()0.13) DIt 0.795 (1.06) 0.825 (1.10) 1.341 (1.39) 0.271 (0.24) DDt 0.856 (1.54) 0.846 (1.53) 1.275* (1.82) 0.790 (1.01) Ct)1 0.460*** (3.94) 0.467*** (3.99) 0.438*** (2.60) 0.611*** (3.06)

Lt 0.005 (0.06) 0.008 (0.09) 0.033 (0.30) 0.095 (0.77)

NFt )0.164** ()2.28) )0.163** ()2.27) )0.175* ()1.73) )0.414*** ()2.95) Ct)1 * DCt )0.149 ()0.52) )0.207 ()0.72) 0.561 (1.34) 0.477 (0.76) Lt * DCt )0.223 ()0.44) )0.249 ()0.51) )2.451*** ()3.37) )4.019*** ()4.16) HWS 0.02 (1.32) 0.032 (0.90)

HWR 0.001 (1.16) 0.056 (1.34)

HWS * DCt 0.111 (1.01) 0.322 (1.18) HWR * DCt )0.003* ()1.70) )0.043 ()0.11) Observations 938 938 557 427

R 2

0.14 0.15 0.16 0.21

This table presents the results of regressing excess stock return Ri,t-RBi,t on changes in firm character-

istics for firms with strong and weak corporate governance measures over the fiscal year. The baseline

model is a pooled ordinary least square model controlling for time effect. All variables except Lt (leverage) and excess stock return are deflated by the lagged market value of equity (Mt)1). Ct is cash

including short-term deposits; Et is earnings before interest and tax; NAt is total book assets minus

Ct; RNDt is capitalized research and development expenses; It is net interest expense; Dt is total com-

mon dividend paid; Lt is total debt divided by total book assets; NFt is net changes in total financing

cash flow; HWS is the Horwath star rating; and HWR is Horwath ranking of corporate governance.

All variables are winsorized at the 1st and 99th percentiles. This approach reduces the impact of

extreme observations by assigning the cut-off value to values beyond the cut-off point. t-statistics sig-

nificant at the 10, 5 and 1 per cent levels are designated with *, ** and ***, respectively.

15 For this analysis, we restrict the blockholder ownership data to the period 2002–2006.

360 H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

5.5. Robustness checks

The results reported in the preceding sections are obtained using pooled OLS regressions corrected for heteroscedasticity. Petersen (2009) shows that in the presence of time effects and firm effects, the pooled OLS regressions in a panel

Table 9

Regression results with blockholdings

Variables (1) (2) (3) (4)

DCt 1.141*** (7.83) 0.948*** (6.20) 1.005*** (4.52) 1.320*** (4.82) DEt 0.774*** (8.12) 0.711*** (5.67) 1.101*** (4.71) 0.967*** (3.65) DNAt 0.049* (1.76) 0.071** (1.97) 0.161** (2.20) 0.366*** (3.38) DRNDt )2.011 ()1.12) )2.484 ()1.00) )0.703 ()0.24) )6.062 ()1.47) DIt 0.991 (1.57) 0.886 (1.16) 2.146* (1.67) 0.897 (0.56) DDt 1.095** (1.98) 0.762 (1.18) 0.907 (1.17) 0.153 (0.17) Ct)1 0.379*** (5.33) 0.391*** (4.36) 0.451** (2.32) 0.508** (2.28)

Lt )0.238** ()2.48) )0.355*** ()2.88) 0.134 (0.88) 0.108 (0.63) NFt 0.104** (1.97) 0.035 (0.52) )0.267** ()2.22) )0.501*** ()2.92) Ct)1 * DCt )0.261** ()2.12) 0.091 (0.49) 0.771 (1.31) )0.210 ()0.28) Lt * DCt )1.585*** ()4.14) )1.811*** ()3.56) )3.224*** ()2.74) )3.160** ()2.57) BlockHolding )0.003 ()0.04) BlockDummy )0.005 ()0.13) 0.046 (0.99) 0.006 (0.12) HWS 0.028 (0.62)

HWR 0.053 (0.98)

HWSD * DCt 0.341 (1.13) HWRD * DCt )0.304 ()0.69) BlockHolding * DCt )0.610* ()1.91) BlockDummy * DCt )0.327* ()1.65) )0.826*** ()2.66) )0.616 ()1.57) Observations 1798 1201 375 288

R 2

0.16 0.12 0.18 0.21

This table presents the results of regressing the excess stock return Ri,t-RBi,t on changes in firm char-

acteristics for firms with strong and weak corporate governance measures over the fiscal year. The

baseline model is a pooled ordinary least square model controlling for time effect. All variables except

Lt (leverage) and excess stock return are deflated by the lagged market value of equity (Mt)1). Ct is

cash including short-term deposits; Et is earnings before interest and tax; NAt is total book assets

minus Ct; RNDt is capitalized research and development expenses; It is net interest expense; Dt is total

common dividend paid; Lt is total debt divided by total book assets; and NFt is net changes in total

financing cash flow. HWSD is a dummy variable for the Horwath star rating. A firm with more than

three stars is coded as 1 (strong governance) and less than three stars as zero (weak governance).

HWRD is a dummy variable for the Horwath ranking, while firms with top 100 governance ranking

are coded as 1 and those in the bottom 100 are coded as zero. BlockHolding is the sum of all owner-

ship positions >5 per cent held by large shareholders. BlockDummy is a dummy variable where the

highest tercile of ownership is coded as 1 (strong governance), and the lowest tercile of ownership is

coded as zero (weak governance). All variables are winsorized at the 1st and 99th percentiles. This

approach reduces the impact of extreme observations by assigning the cut-off value to values beyond

the cut-off point. t-statistics significant at the 10, 5 and 1 per cent levels are designated with *, ** and

***, respectively.

H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366 361

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

data set are biased. The literature advocates the firm fixed-effects model to con- trol for unobservable time-invariant firm heterogeneity (for example, Himmel- berg et al., 1999). It is possible that the effect of changes in cash on excess stock returns is caused by some unobserved firm-specific factor(s). In addition, indus- try effects are important for an Australian sample given that resources industries are likely to harbour more cash. We employ both the firm fixed-effects model and the industry fixed-effects model to check the robustness of our findings using the pooled OLS regressions in Table 3. The results are reported in Table 10. Consistent with the results estimated using the pooled OLS approach, the main estimated coefficients have the same predicted signs and magnitudes. This sug- gests that using alternative estimation approaches would generate qualitatively similar results. In all our excess-return model specifications, the dependent variable is defined

as excess stock returns, while the other variables are scaled by the lagged market value of equity. This allows us to interpret our findings as to how investors value

Table 10

Robustness checks

Variables Industry fixed effects Industry fixed effects Firm fixed effects Firm fixed effects

DCt 0.720*** (15.76) 1.085*** (18.11) 0.807*** (15.78) 1.074*** (16.15) DEt 0.440*** (9.18) 0.442*** (9.23) 0.477*** (8.97) 0.496*** (9.32) DNAt 0.044*** (3.28) 0.042*** (3.16) 0.046*** (3.06) 0.042*** (2.81) DRNDt )0.808 ()0.99) )0.910 ()1.12) )1.616* ()1.92) )1.752** ()2.08) DIt 1.398*** (5.33) 1.112*** (4.23) 1.178*** (4.11) 0.938*** (3.25) DDt 0.863*** (3.03) 0.774*** (2.74) 0.861*** (2.97) 0.815*** (2.82) Ct)1 0.462*** (11.45) 0.414*** (10.23) 0.913*** (15.49) 0.847*** (14.11)

Lt )0.322*** ()5.78) )0.291*** ()5.20) )0.460*** ()5.24) )0.415*** ()4.72) NFt 0.090*** (3.44) 0.062** (2.35) 0.079** (2.54) 0.063** (2.02)

Ct)1 * DCt )0.466*** ()6.89) )0.148* ()1.81) Lt * DCt )0.879*** ()4.34) )1.143*** ()5.20) Intercept )0.094** ()2.36) )0.082* ()1.75) )0.161*** ()3.84) )0.167*** ()3.98) Year dummy

included

Yes Yes Yes Yes

Observations 6412 6412 6412 6412

R 2

0.14 0.15 0.37 0.38

This table presents the results of regressing the excess stock return Ri,t ) R_BPi,t on changes in firm characteristics using an industry fixed-effects model and a firm fixed-effects model over the fiscal year.

All variables except Lt (leverage) and excess stock return are deflated by the lagged market value of

equity (Mt)1). Ct is cash including short-term deposits; Et is earnings before interest and tax; NAt is

total book assets minus Ct; RNDt is capitalized research and development expenses; It is net interest

expense; Dt is total common dividend paid; Lt is total debt divided by total book assets; and NFt is

net changes in total financing cash flow. All variables are winsorized at the 1st and 99th percentiles.

This approach reduces the impact of extreme observations by assigning the cut-off value to values

beyond the cut-off point. t-statistics significant at the 10, 5 and 1 per cent levels are designated with

*, ** and ***, respectively.

362 H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

excess cash holdings in dollar terms. In the empirical literature, an alternative approach is to scale by the total book value of assets. To check the robustness of our findings, we next employ a value regression as outlined in Fama and French (1998). We use changes in market value over total book value of assets as the dependent variable and variables likely to affect the firms’ future cash flows (scaled by total book value of assets) as the explanatory variables. Specifically, we estimate the following regression for each measure of our financial constraint proxies, BTMs, cash-flow volatility, industry competition and corporate gover- nance measures:

Mi;t � Ai;t Ai;t

¼ a0 þb1 Ei;t Ai;t þ b2

dEi;t Ai;t þ b3

dEi;tþ2 Ai;t

þ b4 dAi;t Ai;t þ b5

dAi;tþ2 Ai;t

þ b6 RNDi;t Ai;t

þb7 dRNDi;t

Ai;t þb8

dRNDi;tþ2 Ai;t

þb9 Ii;t Ai;t

þ b10 dIi;t Ai;t þb11

dIi;tþ2 Ai;t

þb12 Di;t Ai;t þ b13

dDi;t Ai;t þ b14

dDi;tþ2 Ai;t

þ b15 dMi;tþ2 Ai;t

þ b16 DCi;t Ai;t þ ci;t

ð3Þ

where d Xt represents the 2-year change in the variable X, Xt ) Xt)2; Mt is total market value of assets; At is total book value of assets; Et is earnings before interest and tax (EBIT); RNDt is capitalized research and development expenses; It is net interest expense; Dt is total common dividend paid; and Ct is cash includ- ing short-term deposits. All variables are deflated by the total book value of assets (At) as in the study of Fama and French (1998). For brevity, we report only the estimated coefficients on DCt (b16) for the whole sample and for each measure of our financial constraints proxies, BTMs, cash-flow volatility, industry competition and corporate governance measures. Consistent with the results esti- mated using the stock return specification, the main estimated coefficients have the same predicted signs and magnitudes. This further confirms our main hypotheses that more financially constrained firms and firms with higher growth opportunities, higher product market competition, higher levels of uncertainty in cash flows, stronger HCG measures, and lower levels of blockholder ownership exhibit significantly higher market value (Table 11).

6. Conclusions

In this study, we investigate whether financial constraints, firms’ growth opportunities, uncertainty in cash flows and product market competition affect the value of cash holdings in the Australian context. We find that more finan- cially constrained firms have significantly higher marginal value of cash holdings. This indicates that investors value excess cash holdings of financially constrained

H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366 363

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

firms more than unconstrained firms. Further, firms with higher growth rates and with higher levels of uncertainty in their cash flows exhibit a higher marginal value of cash holdings. However, product market competition has little impact

Table 11

Regression results for the market value of assets

DCt Observations R 2

Panel A: Ordinary least square regressions

Whole sample 1.520*** (5.43) 4941 0.31

Non-dividend payers 0.859** (2.44) 1577 0.45

Dividend payers 0.765** (2.45) 3364 0.54

Small firms 1.248*** (3.85) 2476 0.36

Large firms 0.925** (2.37) 2465 0.35

Low BTM ratio 1.056*** (3.37) 2516 0.41

High BTM ratio 0.232*** (2.93) 2425 0.33

High cash-flow volatility 1.241*** (2.77) 2503 0.18

Low cash-flow volatility 1.157*** (3.57) 2438 0.38

High industry competition 2.318*** (5.05) 2438 0.34

Low industry competition 0.831** (2.44) 2503 0.37

High Horwath ranking 0.176 (0.09) 124 0.60

Low Horwath ranking 1.214 (0.96) 189 0.52

High block ownership 0.002 (0.00) 402 0.36

Low block ownership 2.207* (1.88) 395 0.50

Panel B: Industry fixed-effects regression

Whole sample 1.210*** (7.35) 4941 0.43

Non-dividend payers 0.800*** (2.98) 1577 0.50

Dividend payers 0.688*** (3.90) 3364 0.59

Small firms 1.058*** (4.59) 2476 0.44

Large firms 0.737*** (3.82) 2465 0.46

Low BTM ratio 0.952*** (4.23) 2516 0.46

High BTM ratio 0.187*** (3.29) 2425 0.37

High cash-flow volatility 1.056*** (5.38) 2503 0.33

Low cash-flow volatility 0.995*** (4.27) 2438 0.46

High industry competition 1.737*** (7.27) 2438 0.46

Low industry competition 0.852*** (3.78) 2503 0.43

High Horwath ranking 0.812 (0.82) 124 0.79

Low Horwath ranking 1.268 (1.40) 189 0.63

High block ownership 0.096 (0.21) 402 0.49

Low block ownership 1.330* (1.80) 395 0.58

This table presents the results of regressing the 2-year change in market value of assets on changes in

firm characteristics, scaled by total book value of assets. Firms are categorized as being financially

constrained (FC) and unconstrained (NFC) according to their book value of assets and dividend

payout ratio. DCt column reports the estimated coefficients on DCt in Equation (2). All explanatory variables are deflated by the total book value of assets. All variables are winsorized at the 1st and

99th percentiles. This approach reduces the impact of extreme observations by assigning the cut-off

value to values beyond the cut-off point. t-statistics (reported in parentheses) significant at the 10, 5

and 1 per cent levels are designated with *, ** and ***, respectively.

364 H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

on firms’ value of cash holdings. As to the role of corporate governance, we find limited evidence of its association with the value of cash holdings. Our findings indicate that internal financing has clear cost advantages over external financing for firms with high growth potential and facing uncertain prospects. Costly exter- nal financing would force firms to save more cash for current operating and future investing needs. Investors are aware of these cash hoarding policies and view them favourably. Our results are robust to using alternative model specifi- cations (the market value regressions) and alternative estimation models, such as the industry fixed-effects model and the firm fixed-effects model. Overall, our findings are mainly consistent with the cash regime of raising cash holdings based on the ability to access external capital, as in the study of Hennessy and Whited (2005).

References

Chang, X., T. J. Tan, G. Wong, and H. F. Zhang, 2007, The effects of financial con- straints on corporate policies in Australia, Accounting and Finance 47, 85–108.

Dittmar, A., and J. Mahrt-Smith, 2007, Corporate governance and the value of cash holdings, Journal of Financial Economics 83, 599–634.

Dlugosz, J., R. Fahlenbrach, P. Gompers, and A. Metrick, 2004, Large blocks of stock: prevalence, size, and measurement, Journal of Corporate Finance 12, 594–618.

Fama, E., and K. French, 1993, Common risk factors in the returns on stocks and bonds, Journal of Financial Economics 33, 3–56.

Fama, E., and K. French, 1998, Taxes, financing decisions and firm value, The Journal of Finance 53, 819–843.

Faulkender, M., and R. Wang, 2006, Corporate financial policy and the value of cash, The Journal of Finance 61, 1957–1990.

Fazzari, S., R. G. Hubbard, and B. Petersen, 1988, Financing constraints and corporate investment, Brookings Papers on Economic Activity 1, 141–195.

Fresard, L., 2010, Financial strength and product market behavior: the real effects of cor- porate cash holdings, The Journal of Finance 65, 1097–1122.

Hennessy, C., and T. Whited, 2005, Debt dynamics, The Journal of Finance 60, 1129–1165.

Himmelberg, C. P., R. G. Hubbard, and D. Palia, 1999, Understanding the determinants of managerial ownership and the link between ownership and performance, Journal of Financial Economics 53, 353–384.

Jensen, M. C., 1986, Agency costs of the free cash flow, corporate finance and takeovers, The American Economic Review 76, 323–329.

Kaplan, S., and L. Zingales, 1997, Do Investment-cash flow sensitivities provide useful measures of financing constraints?, Quarterly Journal of Economics 112, 169–215.

Lee, E., and R. Powell, 2011, Excess cash holdings and shareholder value, Accounting and Finance 51, 549–574.

MacKay, P., and G. Phillips, 2005, How does industry affect firm financial structure, Review of Financial Studies 18, 1433–1466.

Masulis, R. W., C. Wang, and F. Xie, 2009, Agency problems at dual-class companies, The Journal of Finance 64, 1851–1889.

Mikkelson, W. H., and M. M. Partch, 2003, Do persistent large cash reserves hinder per- formance?, Journal of Financial and Quantitative Analysis 38, 275–294.

H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366 365

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

Opler, T., L. Pinkowitz, R. Stulz, and R. Williamson, 1999, The determinants and impli- cations of corporate cash holdings, Journal of Financial Economics 52, 3–46.

Pagano, M., and A. Röell, 1998, The choice of stock ownership structure: agency costs, monitoring, and the decision to go public, Quarterly Journal of Economics 113, 187–225.

Petersen, M. A., 2009, Estimating standard errors in finance panel data sets: comparing approaches, Review of Financial Studies 22, 435–480.

Phillips, G. M., 1995, Increased debt and industry product markets: an empirical analysis, Journal of Financial Economics 37, 189–238.

Pinkowitz, L., and R. Williamson, 2004, What is a dollar worth? The market value of cash holdings, Working paper (Georgetown University).

Pinkowitz, L., R. Stulz, and R. Williamson, 2006, Does the contribution of corporate cash holdings and dividends to firm value depend on governance? A cross-country anal- ysis, The Journal of Finance 61, 2725–2751.

366 H. W. H. Chan et al./Accounting and Finance 53 (2013) 339–366

� 2011 The Authors Accounting and Finance � 2011 AFAANZ

Copyright of Accounting & Finance is the property of Wiley-Blackwell and its content may not be copied or

emailed to multiple sites or posted to a listserv without the copyright holder's express written permission.

However, users may print, download, or email articles for individual use.