economic guide questions

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In contrast, the Porter hypothesis (Porter and van der Linde 1995b) argues that more

stringent environmental policies can actually have a net positive effect on the competitiveness

of regulated firms because such policies promote cost-cutting efficiency improvements, which

in turn reduce or completely offset regulatory costs, and foster innovation in new technologies

that may help firms achieve international technological leadership and expand market share.

This article reviews the recent empirical literature that attempts to quantify the effects of

asymmetric environmental regulations on key aspects of firms’ competitiveness, including

trade, industry location, employment, productivity, and innovation. The first major review

on this topic (Jaffe et al. 1995) concluded that there is relatively little evidence that environ-

mental policies lead to large losses in competitiveness. Over the last two decades, both the

growth in the number of environmental policies worldwide and the availability of high-

quality data, especially at the firm and facility level, have enabled researchers to improve

their empirical analyses of the economic effects of asymmetric environmental policies. Our

aim is to critically assess this evidence to ascertain whether the conclusions of Jaffe et al.

(1995) still hold or should be updated. By synthesizing the evidence, we also hope to inform

the political debate concerning the economic impacts of environmental regulations.

Competitiveness concerns stem largely from differences in environmental regulations

across countries. Thus we focus primarily on studies that empirically examine cross-

country differences in environmental stringency. We also include some studies that examine

differences between smaller-scale jurisdictions (e.g., cross-county differences in the United

States). Importantly, our review covers only ex post evaluation studies, thus excluding ex ante

modeling studies, which have recently been reviewed by Carbone and Rivers (2017). We also

focus on environmental regulations that affect the manufacturing sector and target industrial

emissions, which are at the center of most competitiveness debates. 1

The article is organized as follows. We start by explaining how environmental regulation

causes competitiveness effects and how these effects are measured. We then review the ex-

isting evidence, first discussing the impact of relative environmental stringency on trade,

industry location, and employment, and then examining the effects on productivity and

innovation, which could also impact firms’ competitiveness. We conclude with a summary

and a discussion of priorities for future research.

How Does Environmental Regulation Affect Firms’ Competitiveness?

In the context of environmental policies, competitiveness 2

effects result from differences

or asymmetries in regulatory stringency 3

applied across entities (e.g., firms or sectors) that

1 We do not include regulations on fishing, agriculture, forestry, mining, or waste, which are sometimes directed explicitly at protecting the environment and human health.

2 Competitiveness is a term that is often used but ill-defined. In general, it refers to the ability of a firm or sector to survive competition in the marketplace, grow, and be profitable (Bristow 2005). Some concepts of competitiveness discussed in the literature include the ability to sell (which reflects the capacity to increase market share), ability to earn (the capacity to increase profit), ability to adjust, and ability to attract (see e.g., Berger [2008] for an overview).

3 We use the term policy stringency here to describe a general level of policy ambition. As we will discuss, in practice, measuring relative policy stringency across different forms of regulation and enforcement regimes is far from straightforward.

184 A. Dechezleprêtre and M. Sato

are competing in the same market. For example, some firms may be regulated while

others are exempt, some sectors may face stricter pollution standards than others, or

environmental stringency may vary across jurisdictions, as is the case with climate change

mitigation policies, where different regions are expected to take carbon mitigation action

at different speeds under the United Nations Framework Convention on Climate Change

Paris agreement. If two competing firms face identical regulation, then competitiveness

effects are not an issue. 4

Thus competitiveness effects can be distinguished from the

general effects of regulations on polluting firms’ economic outcomes, which are caused

by the policy itself rather than by differences in environmental policy faced by competing

polluting firms.

Asymmetric Environmental Regulations and Relative Production Costs

Environmental regulations generally require polluting facilities to undertake abatement

activities and may impose costs on businesses. Thus regulatory differences across firms,

sectors, or jurisdictions can cause changes in relative production costs. Such changes could

arise from differences in direct costs. For example, the European Union Emissions Trading

System (EU ETS), which regulates carbon emissions of approximately 12,000 installations

across Europe, is estimated to have increased average material costs (including fuel) for

regulated firms in the power, cement, and iron and steel sectors by 5 percent to 8 percent

(Chan, Li, and Zhang 2013). 5

Increases in relative costs could also result from higher indirect

costs caused by policy-induced changes to input costs. For example, even if they are not

directly regulated by the EU ETS, European consumers of electricity face higher electricity

costs due to the price on carbon emissions paid by electricity producers. Differences in

environmental regulations can thus alter the competition between firms by changing their

relative production costs.

Pasurka (2008) finds evidence that differences in environmental stringency across coun-

tries induce important differences in pollution abatement costs. Across nine countries in

Europe, North America, and Asia, the share of manufacturing capital expenditure assigned to

pollution abatement in 2000 ranged from 1 percent (Taiwan) to 5 percent (Canada). In terms

of sectoral variation, abatement costs are typically higher for pollution-intensive industries

such as pulp and paper, steel, and oil refining. In the United States, for example, in 2005 each

of these sectors spent approximately 1 percent of their turnover to comply with environmen-

tal regulations, while the average for all manufacturing plants was 0.4 percent (Ferris and

McGartland 2014). Importantly, differences in relative costs may arise not only from the

stringency of the regulation, but also from its nature and design (Iraldo et al. 2011), in

4 Note, moreover, that if there are no regulatory differences across companies, it is not possible to establish a counterfactual scenario (i.e., what would have happened had the policy not been implemented) against which to evaluate the impact of a given regulation.

5 In addition to affecting marginal and average costs of production, environmental regulations can affect entry and investment costs for companies. Ryan (2012) finds that the 1990 U.S. Clean Air Act Amendments (CAAA) had no effect on the cement industry’s marginal (variable) costs, but the average sunk costs of entry increased, with the costs of building a new, greenfield facility increasing by $5 million to $10 million due to the rigorous environmental certification and testing requirements of the CAAA.

Impacts of Environmental Regulations on Competitiveness 185

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particular because of the uncertainty associated with different types of instruments (Goulder

and Parry 2008).

As illustrated in table 1, asymmetric environmental policies induce changes to relative

production costs (the first-order effect) and trigger different responses by firms. Firms may

respond through decisions concerning pricing, output, or investment (second-order effects).

For example, in the case of pricing, firms may decide to absorb the increase in production

costs or pass it through to consumers. 6

These firm responses in turn influence outcomes

along various economic, technological, international, and environmental dimensions (third-

order effects). These effects are not uni-directional, rather there are multiple linkages and

dynamic feedbacks. Changes to technology outcomes, for example, may trigger cost impacts

or firm responses to change.

The Pollution Haven Hypothesis

There are two opposing views on the likely competitiveness effects arising from asymmetric

environmental policies worldwide, as noted earlier. The pollution haven hypothesis goes back

more than thirty years (e.g., McGuire 1982) and predicts that if competing companies differ

only in terms of the environmental policy stringency they face, then those facing relatively

stricter regulation will lose competitiveness.

Higher regulatory costs could, for example, crowd out productive investment in in-

novation or efficiency improvements and slow down productivity growth. If increased

regulatory costs are passed through to product prices in fiercely competitive product

markets, distortions in trade could occur, as product prices will increase more in coun-

tries with relatively strict regulation. Companies in countries with higher costs will then

lose market share to competitors in countries producing pollution-intensive exports

Table 1 Competitiveness Effects Due to Differences in the Stringency of Environmental Regulations

First-order

effect

Second-order

effect

Third-order effects

Cost impacts Firm

responses

Economic

outcomes

Technology

outcomes

International

outcomes

Environmental

outcomes

Changes to

relative costs

(direct and

indirect

costs)

– Production

volume

– Product prices

– Productive

investments

– Investment in

abatement

– Profitability

– Employment

– Market share

– Product innovation

– Process innovation

– Input-saving

technologies

– Total factor

productivity

(TFP)

– Trade flows

– Investment

location

– Foreign direct

investment

(FDI)

– Pollution levels

and intensity

– Pollution

leakage

Source: Authors.

6 In order to drive a demand-side switch toward cleaner products, it is both desirable and necessary to have product prices reflect pollution abatement costs. How firms respond to pricing has important distributional consequences.

186 A. Dechezleprêtre and M. Sato

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more cheaply. If environmental regulatory differences are expected to last, companies’

decisions regarding the location of new production facilities or foreign direct investment

may also be affected, with pollution-intensive sectors, and thus manufacturing employ-

ment, possibly gravitating toward countries with relatively lax policies and creating pol-

lution havens.

The Porter Hypothesis

The Porter hypothesis takes the more dynamic perspective that more stringent policies

should trigger greater investment in developing new pollution-saving technologies. If these

technologies induce input (e.g., energy) savings that would not have occurred without the

policy, they may offset part of the compliance costs. Porter and van der Linde (1995b) go

further, arguing that environmental regulations can actually “trigger innovation that may

more than fully offset the costs of complying with them,” i.e., lowering overall production

costs and boosting the competitiveness of firms. 7

This Porter hypothesis outcome may occur

if cleaner technologies lead to higher productivity, input savings, and innovations, which over

time offset regulatory costs (dynamic feedback to the first-order effect) and improve export

performance and market share. For example, the existence of learning externalities might

prevent the replacement of an old polluting technology by a new, cleaner and more produc-

tive technology because firms have a second-mover advantage if they wait for someone else to

adopt. In this situation, the introduction of an environmental regulation would induce firms

to switch to the new, cleaner technology, which improves environmental quality and even-

tually increases productivity (Mohr 2002). An argument that is related to the Porter hypoth-

esis postulates that a country can generate a first-mover advantage to domestic companies by

regulating pollution sooner than other countries, which leads domestic firms toward inter-

national leadership in clean technologies that are increasingly in demand globally (Porter and

van der Linde 1995a).

Measuring Competitiveness Effects Empirically

Since Jaffe et al. (1995), empirical analyses of the competitiveness effects of environmental

regulation have benefited from improvements in data availability, empirical methodology,

and policy stringency measurement. There is yet no single accepted test or measure of the

competitiveness effects of environmental regulation and the literature continues to use a

variety of outcome measures linked to competitiveness (summarized in table 1). 8

Estimates of

the effect of policies on these different outcomes are usually derived using reduced form

rather than structural equations. Despite some progress being made, there are still a number

7 See Ambec et al. (2013) for a discussion of the theoretical justifications for the Porter hypothesis that have been proposed in the literature.

8 Jaffe et al. (1995) argue that the ideal measure to study competitiveness would be the effect of relative policies on net exports. With aggregated sector-level data, this is a theoretical measure because it is impossible to measure the reduction in net exports “before” adjustments in the exchange rates, holding real wages and exchange rates constant. However, it is less of a problem when using data at a disaggregated level, because changes to trade of a single company are unlikely to affect exchange rates.

Impacts of Environmental Regulations on Competitiveness 187

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of challenges to conducting credible empirical analysis of the competitiveness impacts of

environmental regulations.

Solving Endogeneity Concerns Through Disaggregated Data

The greater availability of detailed data, in particular at the firm or facility level, over the last

couple of decades has been key to obtaining more robust evidence on competitiveness im-

pacts. Using country- or sector-level data can be problematic because it does not allow

researchers to distinguish between the production facilities that are covered or exempt and

the particular policy being evaluated, leading to aggregation bias (Levinson and Taylor 2008).

Moreover, an important challenge to empirically analyzing the competitiveness impacts of

environmental regulation is that the policies could be endogenous. This could be the case if

environmental policies are correlated with the unobserved determinants of the outcome

variable of interest, such as trade (e.g., supply chain linkages, other firm-specific factors,

political institutions, the stringency of other regulations). Governments could also set strin-

gency levels strategically, for example, by exempting key export sectors from environmental

regulations, suggesting the possibility of reverse causality when using sectorally aggregated

data. The recent economic geography literature also suggests the presence of bias if the

location of polluting firms is influenced by other firms in that location (e.g., Zeng and

Zhao 2009). Firm-level panel datasets over long time periods both before and after the

introduction of the policy and improved estimation methods can overcome these problems

by controlling for unobserved heterogeneity across firms. 9

However, numerous policies, in

particular in developing countries, can still not be the subject of rigorous evaluation, because

of the lack of high-quality data. Going forward, ensuring that data collection is built into the

design of policies from the outset will enable researchers to evaluate the impacts of the many

new environmental policies that are being implemented.

Measuring Environmental Stringency

To evaluate the impact of a given regulation, there needs to be an accurate measure of envi-

ronmental stringency so that a control group can be constructed that captures what happens in

the absence of a policy or in the event of a weaker policy. In within-country analyses, variation

in environmental regulatory stringency can arise if a policy is implemented in a random subset

of regions or if the rollout is staggered over time. For example, in the U.S. context, the federal

designation of counties into “attainment” or “nonattainment” status depends on local air

quality for various pollutants, thus providing a convenient source of exogenous variation.

Counties with nonattainment status then face much stricter environmental regulation. 10

In an international context, however, it is often the case that different policies need to be

compared. This is a difficult task due to the complex nature of environmental regulation.

9 Omitted variable bias can occur when firms’ unobserved characteristics may be correlated with both regulatory stringency and the outcome measure (e.g., productivity).

10 Being federally mandated, this status is unlikely to be related to differences in tastes, geographic attributes, or underlying economic conditions across counties. Moreover, local pollution levels depend heavily on weather patterns (in particular, wind and precipitation), which are unlikely to be systematically related to local manufacturing sector activity (Greenstone, List, and Syverson 2012).

188 A. Dechezleprêtre and M. Sato

Although the measurement of relative stringency is likely to be fraught with measurement

error, a number of approaches have been used in the literature. One popular option is to

proxy stringency using either the environmental outcome (pollution level) or measures of

compliance costs as a share of value added. The latter option has typically used data on

pollution abatement and control expenditures (PACE), which has been collected for the

United States since the 1970s and for Europe and Asia–Pacific countries since the 1990s.

However, PACE is far from an ideal proxy for stringency. First, because the production level is

used as a denominator, it is unlikely to be exogenous. Second, because it is based on survey

data, PACE is not readily comparable across countries since the survey methodologies differ

across countries in terms of what should and should not be considered as abatement expen-

ditures. Third, PACE data do not account for how compliance costs may impact market

competition. Finally, PACE data are available only for surviving firms. Thus impacts on firms

that exit because of the environmental regulation would not be included in the measure.

Several alternative measures of stringency have been used in the literature, including en-

vironmental or energy tax revenue, renewable energy capacity, recycling rates, legislation

counts, and composite indicators. However, as discussed in Brunel and Levinson (2013) and

Sato et al. (2015b), all of these have shortcomings. For example, although price-based policies

such as emissions trading would appear to be easy to compare, they are complicated by

differences in the setup of systems (e.g., sectoral coverage) and exemption rules, such as

differences in free allowance allocation provisions, which not only affect the level of policy

stringency, but also alter incentives and influence the behavior of firms. 11

However, few

measures of stringency account for such provisions. Although these shortcomings do not

prevent analysis of the impacts of environmental policies, it is important to keep them in

mind when reviewing the available evidence, which we do in the next two sections.

Empirical Evidence: Impacts on Trade, Industry Location, and Employment

A central focus of the competitiveness debate has been the potential impact of environmental

regulation on international trade and the location of production and investment, as well as

the employment consequences of these effects. 12

In this section we examine the evidence

concerning these impacts.

Environmental Regulation and International Trade

Much of the early literature tested the pollution haven hypothesis 13

by examining the overall

effect of international trade on the quality of the environment. Grossman and Krueger

(1995), for example, asked how openness to trade affects the environment through its effects

11 For example, see Branger et al. (2015) for an analysis of the impact of the EU ETS free allocation rules on operational, investment, and trade decisions.

12 Related to this are political economy concerns about governments’ use of environmental policy as an implicit trade barrier to circumvent international free-trade agreements.

13 Some scholars also refer to a pollution haven effect, which occurs if asymmetric environmental policies, at the margin, influence firms’ trade and investment location decisions. See Copeland and Taylor (2004) for a detailed discussion of the pollution haven arguments.

Impacts of Environmental Regulations on Competitiveness 189

on the scale of economic activity, sector composition, and technology adoption, and found

limited empirical evidence that trade made developing countries dirtier. 14

In a study of 43

countries, Antweiler, Copeland, and Taylor (2001) find that international trade is in fact

beneficial to the environment (as measured by sulfur dioxide [SO2] concentration) be-

cause the increase in economic activity (scale effect) is offset by changes in both technol-

ogy and the composition of output in the economy. One explanation for this result is that

in low-income countries, the higher price of capital offsets their “advantage” of having lax

environmental policies because pollution intensive industries are also capital intensive.

Levinson (2010) instead examines the composition of U.S. imports following the adoption

of environmental regulation. Taking account of intermediate inputs, he finds that between

1972 and 2001, U.S. imports increasingly shifted away from pollution-intensive goods.

This, he argues, does not contradict the pollution haven hypothesis because the shift

toward less polluting imports may have been smaller without environmental regulations.

However, he suggests that if there was indeed a pollution haven effect, it was likely over-

whelmed by other forces such as availability and costs of raw materials, skilled labour

availability, transport costs, market structure, and fixed plant costs. Subsequent analyses

have found that international trade has a modest impact on pollution (e.g., McAusland

and Millimet 2013).

Several studies have more directly assessed whether environmental regulation causes

changes in trade flows. These studies use a variety of measures of relative environmental

stringency, with PACE being a popular choice. For example, Ederington and Minier (2003)

treat PACE as an endogenous variable 15

and, for a panel of U.S. manufacturing industries,

find that between 1978 and 1992, net imports rose with higher PACE, suggesting that differ-

ences in environmental regulation impact trade flows. Using the same data but taking ac-

count of factors that limit the geographic mobility of economic activity (e.g., transportation

costs, fixed plant costs, and agglomeration economies of an industry), Ederington, Levinson,

and Minier (2005) find that the pollution haven effect is difficult to detect in capital-intensive

industries. They note that quantifying average effects on competitiveness across all sectors

understates the effects of regulatory differences on “footloose” (i.e., geographically mobile)

sectors. Levinson and Taylor (2008) use a panel for 1977–1986 and find that a 1 percent

increase in PACE in the United States is associated with an increase in net imports of 0.4

percent from Mexico and 0.6 percent from Canada. 16

Levinson (2010), however, argues that

the result in Levinson and Taylor (2008) does not actually show that higher levels of PACE

cause higher imports; rather, it shows that imports are rising in sectors where the gap in the

stringency level across countries is increasing.

14 For a review of such earlier studies, see Jaffe et al. (1995) and Copeland and Taylor (2004).

15 The authors use political economy variables and factor intensities as instrumental variables for PACE. This analysis also finds that PACE is endogenous and suggests that policy stringency is determined strategically by governments.

16 They use a fixed effects model that accounts for unobserved sector characteristics that are correlated with regulation and trade, unobserved foreign pollution regulation levels, and aggregation bias in sectoral data (due to changes in industry composition). Because they use data from only one country, they can estimate the effects of environmental regulation on trade only by comparing sector-level net imports as a function of industry characteristics. The variation in pollution abatement expenditures across sectors may reflect unobserved heterogeneity rather than relative stringency.

190 A. Dechezleprêtre and M. Sato

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While carbon pricing policies are relatively new and coverage is limited, a number of recent

studies conduct ex post analysis on their trade impacts. 17

Branger, Quirion, and Chevallier

(2016) examine the impact of the EU ETS—to date the world’s largest carbon market—using

a time-series analysis for the period 2004–2012. They test whether carbon prices increased net

EU imports of cement and steel, but they find limited evidence. Two studies use an alternative

approach—exploiting the historic variation in energy prices to estimate the effect of carbon

price differences on trade—thus taking advantage of the fact that carbon prices essentially

work by increasing energy prices. In the first study, Aldy and Pizer (2015) use U.S. state-level

variation in industrial energy prices and fuel composition to estimate how production and

net imports changed in response to energy prices between 1974 and 2005. 18

When averaging

across all sectors, they find that the effect of energy price on net imports is statistically

indistinguishable from zero. However, they find evidence that both net imports and produc-

tion are more sensitive to energy prices in more energy-intensive sectors, including iron and

steel, chemicals, paper, aluminum, cement, and bulk glass, but that the magnitude of the

effect is small (a 0.1–0.8 percent increase in net imports from a hypothetical $15 per ton CO2 price). In the second study, Sato and Dechezleprêtre (2015) examine the influence of an

energy price gap between two trading partners on bilateral trade flows for 42 countries and 62

manufacturing sectors between 1996 and 2011. On average, they find that a 10 percent in-

crease in the energy price gap increases bilateral imports by 0.2 percent and that overall,

energy price differences explain 0.01 percent of the variation in trade flows. 19

To summarize, the recent evidence appears to offer broad support for the existence of a

pollution haven effect, with imports of pollution- or energy-intensive goods increasing in

response to tighter regulation. However, the effects tend to be small and concentrated in a few

sectors. Overall, the effect of relative stringency on trade flows is overwhelmed by other

determinants of trade.

Environmental Regulation and Production and Investment Location

Addressing concerns that trade liberalization is creating a “race to the bottom,” in which

governments competing for FDI are strategically undercutting each others’ environmental

standards, another active area of empirical investigation has been exploration of the effects of

environmental regulation on investment location as evidence of pollution havens.

This literature broadly examines two distinct questions: first, whether relatively lax policies

are a pull factor in attracting incoming manufacturing investments and second, whether

stringent policies are a push factor that influences the decision on outward investment flows

or relocation decisions.

17 There is a substantial literature on carbon leakage that explores the potential environmental consequences of the trade effects of regulatory differences (see Branger and Quirion [2014] for a review). However, this literature mostly uses ex ante modeling and is thus excluded from our review. The carbon leakage literature can be distinguished from the literature on trade-embodied carbon (e.g., Peters et al. 2011), which includes all embodied emissions in trade regardless of whether they are induced by asymmetric policies or other underlying economic factors that influence trade patterns.

18 They use a detailed panel of state-level manufacturing production data covering 450 sectors.

19 The more recent time frame of these two studies means we can interpret the results in the post-2000 context, which saw rapid growth in global trade, particularly between industrialized countries and emerg- ing economies such as China, as well as an increase in competitiveness concerns.

Impacts of Environmental Regulations on Competitiveness 191

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Location choice of new and relocating domestic firms

A number of studies use the variation in environmental standards across U.S. states and counties

to examine its effect on manufacturing plant location. Using establishment-level data for 1982

from the Census of Manufacturers and six different measures of environmental stringency,

Levinson (1996) finds that interstate differences in environmental regulations do not system-

atically influence the location choice of new manufacturing plants. Using the Levinson index of

environmental regulatory stringency, 20

Henderson and Millimet (2005) examine the impact of

environmental policy between 1977 and 1986 and find no effect on state-level aggregate output.

In contrast, studies that used more disaggregated data for New York State find that between 1980

and 1990, county-level differences in the regulatory status of the 1997 Clean Air Act

Amendments (CAAA) had very large statistically significant effects. More specifically, relative

to an “attainment” county, being a strictly regulated “nonattainment” county decreases the

inflow of relocating plants by nearly 63 percent (List et al. 2003) and decreases the expected

inflow of new dirty plants by 44–61 percent or 150–600 percent, depending on the estimator

used (List, McHone, and Millimet 2004). A comparison of these inter- and intrastate studies of

the United States suggests that studies with a smaller geographic scope tend to find stronger

effects, possibly because smaller areas tend to have less variation in the other determinants of

production location. Indeed, also using the dataset for New York State, Millimet and List (2004)

finds that the effect of stricter regulation is spatially heterogeneous and varies systematically with

location-specific attributes such as unemployment levels.

Impacts on inward FDI location

A number of studies use the within-country variation in environmental stringency and find incon-

clusive evidence on its impact on inward FDI location. List, McHone, and Millimet (2004)

use U.S. data and find that environmental stringency has very strong effects on new plant

births for domestic companies’ plants, but no effect on locational choice for foreign-owned

pollution-intensive plants. Dean, Lovely, and Wang (2009) examine inward FDI in China

between 1993 and 1996 and find that equity joint ventures in polluting industries are gen-

erally not attracted by weak environmental standards. In contrast, using U.S. state-level data,

Keller and Levinson (2002) find that between 1977 and 1994, a 10 percent increase in relative

manufacturing pollution abatement cost is associated with a 0.79 percent decrease in

manufacturing FDI and, more specifically, a 1.98 percent decrease in FDI in the chemical

industry. Fredriksson, List, and Millimet (2003) and Millimet and Roy (2016) also find that

environmental regulation plays a role in the location outcome of FDI into the United States,

and both studies highlight the importance of treating environmental regulation as endoge-

nous, because the influx of FDI can lead to a change in environmental regulation.

With international studies, determining whether countries use environmental regulation

strategically to attract FDI faces the major challenge of accurately measuring relative envi-

ronmental stringency across countries. Xing and Kolstad (2002) studied 22 countries

between 1985 and 1990 using SO2 emissions. 21

The authors find a significant effect for

20 This is a state- and year-level industry-adjusted index of environmental stringency based on pollution abatement costs.

21 This approach captures only one component of environmental stringency, namely the regulation of coal combustion, which likely biases estimates towards energy-intensive industries.

192 A. Dechezleprêtre and M. Sato

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two of the six sectors studied – with a 1 percent decrease in SO2 emissions associated with

0.27 and 0.20 million dollar increases, respectively, in new investments from U.S. multina-

tional companies in the chemicals and primary metals sectors. However, this effect is small

relative to the total outflow of U.S. FDI (e.g., $4 billion in 1991 in the chemicals sector).

Wagner and Timmins (2009) use the World Economic Forum (WEF) index of environ-

mental stringency and enforcement, which is based on interviews with business executives,

to study the effect of relative environmental stringency on German FDI destinations across

163 countries and 23 industrial sectors. They find that in the chemicals sector, if a country

reduces its environmental stringency by one standard deviation, 22

German FDI to that

country would increase by e122,000 per year, which corresponds to almost two-thirds of

the standard deviation of annual investment flows in the chemical industry. However, they

find no effects for other sectors. Kellenberg (2009) also uses the WEF index and finds strong

evidence that countries with lax environmental policy enforcement (rather than lax strin-

gency) attracted more U.S. multinational firms’ production. 23

In contrast, although

Raspiller and Riedinger (2008) and Ben-Kheder and Zugravu (2012) experiment with a

number of different measures of stringency, they find no systematic evidence concerning

French firms’ FDI location choice.

Impacts on outward FDI location

Whether stringent environmental policies encourage firms to increase foreign assets also

remains empirically unresolved. Using energy intensity as a proxy, Eskeland and Harrison

(2003) find little evidence that stringent regulation in the United States encourages outbound

investment to Mexico, Cote d’Ivoire, Morocco, and Venezuela. Manderson and Kneller

(2012) use UK firm-level data to explicitly account for heterogeneous firm behavior, and

also find no evidence that firms with high environmental compliance costs are more likely to

establish foreign subsidiaries than those with low environmental compliance costs. Hanna

(2010) also uses firm-level data to examine whether exogenous changes in regulatory status

under the CAAA caused U.S. multinational firms to increase their foreign assets and foreign

output in the 1980s and 1990s. 24

She finds that for “nonattainment” counties, their resident

multinational firms increased their foreign assets by 5.3 percent and their foreign output by 9

percent.

Overall, the empirical evidence suggests that the existence of a pollution haven effect for

foreign investment remains unclear. In a meta-analysis of eleven studies on the impact of

environmental regulations on new plant location, Jeppesen, List, and Folmer (2002) find that

the estimates are highly sensitive to the empirical specification, the data, the definition of the

regulatory variable, the control variables, and geographic coverage. Our updated review of the

new plant and FDI location literature here suggests that this conclusion still holds.

22 To give an idea of magnitude, this is exemplified by the difference in environmental stringency between Austria and neighbouring Slovakia.

23 More specifically, they find that for countries in the top twentieth percentile in terms of the value added of U.S. multinational affiliates from 1999 to 2003, 8.6 percent of the value added growth was attributed to lower environmental policy stringency.

24 The use of disaggregated data allows Hanna (2010) to avoid reverse causality issues, control for unobserved heterogeneity at the firm level, and industry trends, thus going a long way toward avoiding the problem of omitted variable bias.

Impacts of Environmental Regulations on Competitiveness 193

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Environmental Regulation and Employment

Given that the offshoring of pollution-intensive production corresponds to the offshoring of

pollution-intensive jobs, debates about the impacts of environmental regulations on com-

petitiveness are often framed in terms of “jobs versus the environment” (Morgenstern, Pizer,

and Shih 2002), particularly in regions where declining manufacturing employment has

become a contentious political issue. 25

Hafstead and Williams (2016) show that at the mac-

roeconomic level, in the long run, environmental regulations might simply induce a substi-

tution between polluting and nonpolluting activities, with the impact on net employment

impossible to determine a priori but likely small because of general equilibrium effects.

However, at the microeconomic level and in the short-run, the available evidence shows

that the effects of environmental regulations on employment in energy- and pollution-

intensive sectors are small but statistically significant.

Unfortunately, the evidence to date is based exclusively on within-country differences in

environmental stringency across subnational jurisdictions. This suggests that if relocation

barriers are assumed to be higher across than within countries, then it is reasonable to con-

sider the results we will present here as being upper bounds on the likely effect of an equivalent

cross-border difference in environmental stringency.

Sectoral studies

Using PACE as a proxy for environmental stringency, Morgenstern, Pizer, and Shih (2002)

find that stricter environmental regulation generally does not have a statistically significant

effect on employment. In fact, they even find statistically significant and positive employment

effects in two industries (plastics and petroleum), although the total number of affected jobs

remains quite small. More specifically, they find that environmental regulation accounted for

at most 2 percent of the observed decline in employment from 1984 to 1994. Similarly, in one

of the very few non-U.S. studies, Cole and Elliott (2007) find no evidence that environmental

regulations reduced employment in 27 industries in the UK.

Plant- and firm-level studies

Studies using sector-level data cannot capture job reallocation within firms, industries, or

regions. However, a few studies have used plant- or firm-level data and can thus account for

these impacts. For example, Berman and Bui (2001a) compare petroleum refineries in the Los

Angeles area, which are subject to some of the strictest air pollution regulations in the United

States, to all other refineries in the country. They find no evidence that environmental reg-

ulation decreased labor demand, even when allowing for induced plant exit and discouraged

plant entry. They actually find weak evidence that the strict environmental regulations in Los

Angeles may have resulted in a small net increase in employment, possibly because more labor

is required for pollution control activities. This finding is similar to Morgenstern, Pizer, and

Shih (2002), with the lower bound of the Berman and Bui (2001a) estimates implying that

25 For example, in the United States, aggregate manufacturing jobs declined by 35 percent between 1998 and 2009, while total manufacturing sector production grew by 21 percent (Kahn and Mansur 2013).

194 A. Dechezleprêtre and M. Sato

over a 12-year period, fewer than 3,500 jobs were lost due to regulation (and the upper bound

implying 11,700 jobs were gained).

By combining large micro datasets with long panels, Kahn (1997) and Greenstone (2002)

are able to provide the most compelling evidence to date on the impact of the U.S. CAAA on

employment. Kahn (1997) finds that the growth rate in manufacturing employment over the

1982–1988 period is 9 percent lower in nonattainment counties that have more stringent air

pollution regulations than in attainment counties. However, the magnitude of this effect

differs across sectors, with the impact of differences in relative stringency ranging from not

statistically significant (but negative) in half of the sectors examined to more than a 10 percent

slower growth rate in the chemicals, primary metals, industrial machinery, and instruments

sectors. Interestingly, plants in nonattainment areas are less likely to close but, conditional on

staying open, grow more slowly than their counterparts in attainment counties. A possible

explanation for this finding is that strict environmental regulation of new sources in these

counties conveys some monopoly power to the incumbents. Using a longer panel of plant-

level data (1972–1987), Greenstone (2002) estimates that the CAAA of the 1970s resulted in a

loss of around 590,000 jobs in nonattainment counties. This represents 3.4 percent of

manufacturing employment in the United States and less than 0.5 percent of total employ-

ment. However, Greenstone (2002) cannot reject the hypothesis (even at the 10 percent level)

that the pollutant regulation effects are equal across industries. Clearly, part of the lost activity

in nonattainment counties may have simply moved to attainment counties. This suggests that

the net national effect of the CAAA on employment is likely to be smaller, but from a cross-

country perspective, and assuming the same effects of environmental regulation, the jobs

would have been lost to foreign competitors. In a study of the employment effects of phase I of

the Title IV cap-and-trade program for SO2 emissions implemented under the 1990 CAAA,

Ferris and McGartland (2014) provide evidence suggesting that the impact of environmental

regulations on employment may be only temporary. Using a small panel dataset of 61 reg-

ulated and 109 unregulated plants, they find that employment is significantly lower in reg-

ulated plants than in nonregulated plants, but only in the first year of compliance.

Walker (2013) finds that the labor transition costs associated with reallocating workers to

other sectors because of the CAAA are large, estimating that the average worker in a regulated

sector experienced a total earnings loss equivalent to 20 percent of the worker’s preregulatory

earnings. In aggregate, workers in newly regulated plants experienced more than $5.4 billion

in forgone earnings for the years after the change in policy, with almost all of the estimated

earnings losses driven by unemployment. 26

Impacts of energy price levels

A few recent studies have examined the impact of differences in energy price levels on

employment, providing insights into the effect of carbon tax differentials on jobs. Using

within-state variation in electricity prices in the United States, Deschenes (2011) finds that

employment rates are weakly related to electricity prices: a 1 percent increase in electricity

prices leads to a change in full-time equivalent employment that ranges from �0.16 percent to �0.10 percent. Kahn and Mansur (2013) examine variations in energy prices and

26 However, earnings losses also depend on the strength of the local labor market, suggesting that policy- induced labor market reallocation may be more costly in periods of high unemployment.

Impacts of Environmental Regulations on Competitiveness 195

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Deleted Text: that is

environmental regulations among adjacent counties from 1998 to 2009 and find evidence

that energy-intensive sectors tend to locate in low electricity price areas and that polluting

sectors seek out low regulation areas, thus reducing employment in high regulation areas.

Although the effects are modest and only weakly significant for the typical manufacturing

industry, the most electricity-intensive industry—primary metals—has an implied price

elasticity of employment of�1.65, which means that a 10 percent increase in the price of electricity leads to a 16.5 percent decrease in employment in that sector. Based on these

estimation results, Kahn and Mansur (2013) predict that the employment effect of a hypo-

thetical $15 per ton carbon tax would affect employment very differently across states, ac-

cording to the carbon intensity of electricity production and the energy intensity of the

industry, ranging from a 3.8 percent decline in employment in Ohio to a 0.3 percent decline

in California.

Role of policy design

Importantly, the effects of relative environmental stringency on employment levels and dis-

tribution depend on the policy design. In an econometric analysis of the impact of British

Columbia’s unilateral revenue-neutral carbon tax, Yamazaki (2017) finds that the carbon tax

generated a small but statistically significant 2 percent increase in employment in British

Columbia relative to other (free of carbon taxes) provinces over the 2007–2013 period, but

that the magnitude of the effect differs according to the sector’s carbon intensity and trade

exposure. For example, with a carbon tax of CAD10 per tonne of CO2 equivalent, the basic

chemical manufacturing sector, one of the most emissions-intensive and trade-exposed in-

dustries, experiences the largest decline in employment (30 percent), 27

while the health care

industry experiences a 16 percent increase in employment, which the author attributes to the

positive demand shock induced by the redistribution of tax revenues to residents of British

Columbia. Thus Yamazaki (2017) finds that while there are clearly winners and losers, a

revenue-neutral carbon tax may not adversely affect aggregate employment.

In summary, the most rigorous studies that use installation or county-level data from the

United States and long panels provide evidence of a pollution haven effect within the United

States. More specifically, they find that environmental regulations have negative effects on

employment in pollution-intensive sectors. This suggests that—in the United States at

least—differences in environmental regulations between states or counties have led to small

negative effects on employment in polluting sectors. However, it is important to keep in mind

that employment effects might be larger within national boundaries (where relocation bar-

riers are lower) than across countries.

Empirical Evidence: Impacts on Productivity, Innovation, and Competitiveness

Environmental regulation may also alter firms’ decisions concerning the volume, type, or

timing of their investments, whether in adopting cleaner technologies through plant refur-

bishment or replacement or in the development of innovative production technologies or

27 The 95% confidence interval ranges from -15 percent to -48 percent.

196 A. Dechezleprêtre and M. Sato

Deleted Text: /

Deleted Text: ,

Deleted Text: –

products. Environmental policies can thus affect firms’ long-term competitiveness through

these channels.

Environmental Regulations and Productivity

By lowering firms’ marginal production costs (and hence product prices in competitive

markets), increased productivity can enhance the competitiveness of firms that operate in

international markets, thus boosting exports and market share. 28

However, because invest-

ment in pollution control diverts resources away from production, economic theory suggests

that environmental regulation will hamper productivity growth.

Evidence that environmental regulation hampers productivity

Early studies of the relationship between environmental regulation and productivity did find

empirical evidence to support this theory, at least for some sectors of the economy. For

example, Gollop and Roberts (1983) found that SO2 regulations in the United States reduced

productivity growth in 56 fossil-fuelled electricity utilities by an estimated 44 percent during

the 1973–1979 period. More recently, Gray and Shadbegian (2003) found a link between

higher pollution-abatement operating costs and lower productivity in 116 pulp and paper

plants. However, most of these early studies used small samples.

Thus far, Greenstone, List, and Syverson (2012) have conducted the largest plant-level

study, with 1.2 million plant observations from the 1972–1993 Annual Survey of

Manufacturers. This large data set allows them to control for many confounding factors

that may affect both productivity and regulation. Specifically, Greenstone, List, and

Syverson (2012) investigate the economic costs of the 1970 CAAA using nonattainment

designation as a measure of regulation. They find that total factor productivity (TFP) declines

by 4.8 percent for polluting plants in strictly regulated counties relative to weakly or unregu-

lated counties. Almost all of the effect occurs in the first year of nonattainment status, sug-

gesting that capital investments in pollution abatement have only a short-term impact on

productivity.

Variation across pollutants and industries

The evidence also suggests that the impacts of the relative stringency of environmental reg-

ulations on productivity vary across pollutants and industries and can sometimes be positive.

For example, Greenstone, List, and Syverson (2012) find that while nonattainment of ozone

concentrations negatively affects productivity, nonattainment of carbon monoxide concen-

trations leads to statistically significant increases in productivity. However, the authors do not

discuss reasons for these differences in outcomes across pollutants. Similarly, Alpay,

Kerkvliet, and Buccola (2002) find that the productivity of the Mexican food processing

industry increased with more stringent local environmental regulation and that pollution

28 See the seminal article by Melitz (2003), who shows that only firms that are sufficiently productive can become exporters (as being more productive allows firms to secure a market share that is large enough to cover the fixed cost of exporting) and that trade increases average productivity by forcing the least pro- ductive firms to exit. See Balistreri and Rutherford (2012) for a discussion of the consequences of using the Melitz model for competitiveness in a computable general equilibrium (CGE) setting.

Impacts of Environmental Regulations on Competitiveness 197

Deleted Text: , respectively

regulations in the United States had no negative impact on the profitability or productivity of

its domestic food manufacturing industry.

Short-term impacts

Berman and Bui (2001b) find that although refineries located in the Los Angeles (South Coast)

Air Basin area experience a short-run decrease in productivity due to increased regulatory

stringency between 1979 and 1992, this effect appears to be temporary; after a few years they

enjoy significantly higher productivity than other refineries in the United States despite the

more stringent air pollution regulations. Similarly, Lanoie, Patry, and Lajeunesse (2008) find

that the negative short-run effects of regulation on the Quebec manufacturing sector are

outweighed by subsequent positive effects on multifactor productivity (MFP) growth.

In one of the few European studies to date, Rubashkina et al. (2015) find that environmental

regulation (as proxied by PACE) negatively affects TFP, but the effects dissipate within 2 years.

In a multilevel analysis using a dataset covering 60,000 companies across 23 Organization for

Economic Cooperation and Development countries, 22 manufacturing sectors, and 21 years,

Albrizio, Kozluk, and Zipperer (2014) find no evidence that a tightening of environmental

policy has any permanent effects on MFP growth at either the country or industry level. In fact,

they find that an increase in environmental stringency is associated with a short-run increase in

productivity growth, which translates into permanently higher MFP levels. However, all effects

tend to fade away within less than 5 years. Albrizio, Kozluk, and Zipperer (2014) also find that

the most productive industries and firms experience the highest gains in productivity, while less

productive firms see negative effects, possibly because highly productive firms are better able to

profit from changes required by environmental regulations.

In sum, the evidence indicates that environmental regulation has both negative, short-term

impacts on productivity in some sectors and for some pollutants and positive productivity

impacts in others. 29

However, more research is needed to investigate the longer run produc-

tivity impacts of environmental regulations.

Environmental Regulations and Innovation

From an economic perspective, it is critical for environmental regulations to provide incen-

tives for technological change because new technologies may substantially reduce the long-

run cost of abatement (Jaffe, Newell, and Stavins 2003). From a political perspective, such

policy-induced innovation may also improve the acceptability of environmental policies.

Indeed, in today’s knowledge-based economy, firms’ competitiveness depends largely on

innovation, which is considered to be a key component of productivity growth (Aghion

and Howitt 1992). Thus there is growing literature that seeks to quantify the link between

environmental regulations and technological innovation. 30

The “induced innovation hy-

pothesis,” dating back to Hicks (1932), suggests that when regulated firms face a higher price

on polluting emissions relative to other costs of production, these firms have an incentive to

develop new emissions-reducing technologies. Many studies have clearly shown that envi-

ronmental regulations can indeed encourage the development of pollution-reducing

29 See Kozluk and Zipperer (2013) for a review specifically focused on productivity.

30 For recent surveys, see Carraro et al. (2010), Popp, Newell, and Jaffe (2010), and Ambec et al. (2013).

198 A. Dechezleprêtre and M. Sato

technologies. For example, Jaffe and Palmer (1997) and Brunnermeier and Cohen (2003)

show that stricter regulation (proxied by higher pollution control expenditures) leads to

higher research and development expenditures and more environment-related patents.

Similarly, higher energy prices have been shown to induce the development of energy-effi-

cient technologies (Newell, Jaffe, and Stavins 1999; Popp 2002). These results are confirmed

in recent studies that use firm-level data, which allows them to control for macroeconomic

factors that might affect both environmental regulation and innovation at the sector level. For

example, using data on approximately 3,000 firms in the car industry, Aghion et al. (2016)

show that firms tend to innovate more in clean technologies (electric, hybrid, and hydrogen

cars) in response to higher road fuel prices. Calel and Dechezleprêtre (2016) find that the EU

ETS has increased innovation activity in low-carbon technologies among regulated compa-

nies by 30 percent relative to a control group.

From a policy perspective, an important issue is determining which regulatory instruments

provide the strongest incentives for innovation. The theoretical literature suggests that

market-based instruments provide stronger incentives for innovation than technology man-

dates and performance standards, and that among market-based instruments, emissions

taxes and auctioned emission permits encourage more innovation than freely allocated emis-

sion permits (Milliman and Prince 1989; Fischer, Parry, and Pizer 2003; Parry, Pizer, and

Fischer 2003). However, the handful of empirical studies on this issue appear to at least partly

contradict the hypothesis that market-based policies encourage more innovation than

command-and-control regulations. For example, Popp (2003) shows that following passage

of the 1990 CAAA, which replaced command-and-control regulation with permit trading,

innovation activity actually decreased in intensity. Taylor (2012) shows that for both the U.S.

SO2 emissions cap-and-trade program and the U.S. Ozone Transport Commission NOx Budget Program, patenting activity collapsed when traditional regulation was replaced by

cap-and-trade. Thus further research is needed on this issue.

Induced Innovation and Firms’ Competitiveness

Can innovation induced by environmental regulations more than fully offset the costs of

complying with them (Porter and van der Linde, 1995b) and enhance firms’ competitiveness?

While there is evidence that the actual cost of achieving an environmental objective is usually

smaller than anticipated because of induced innovation (see, e.g., Harrington, Morgenstern,

and Nelson 2000, 2010; Simpson 2014), the literature to date does not provide much empir-

ical support for the Porter hypothesis in its so-called strong version. 31

Thus there is currently

no empirical evidence that environmental regulation leads to an increase in firm competi-

tiveness through its effect on innovation.

In theory, environmental regulation can increase productivity growth (and hence com-

petitiveness) if it leads to a permanent increase in the rate of innovation. There is some

emerging evidence, however, that regulation-induced environmental innovations tend to

replace other innovations, leaving the overall level of innovation unchanged. For example,

31 The “weak” version of the Porter hypothesis postulates that properly designed environmental regulation may spur innovation. The “strong” version of the Porter hypothesis goes further, asserting that in many cases this innovation more than offsets any additional regulatory costs—in other words, environmental regulation can lead to an increase in firm competitiveness (Ambec et al. 2013).

Impacts of Environmental Regulations on Competitiveness 199

in their study of paper mills in the United States, Gray and Shadbegian (1998) found that

more stringent air and water regulations improved environmental innovation, but that the

increased investment in emissions and water abatement technologies came at the cost of other

types of productivity-improving innovation. Popp and Newell (2012) find that alternative

energy patenting crowds out other types of patenting at the firm level. There seems to be a

larger crowding out effect for small firms that are credit constrained (Hottenrott and

Rexh€auser 2013). Aghion et al. (2016) show that innovations in clean cars (electric, hybrid,

and hydrogen) occur almost completely at the expense of innovation in dirty vehicles (com-

bustion engines). In contrast, Noailly and Smeet (2015) and Calel and Dechezleprêtre (2016)

find no evidence of such substitution effects at the firm level, suggesting that some environ-

mental regulations may raise the overall rate of innovation of regulated firms rather than

simply redirecting innovation toward clean and away from polluting technologies. 32

Several studies have examined the causality chain implied by the Porter hypothesis—from

regulation to innovation to profitability—and find that the positive effect of innovation on

business performance does not outweigh the negative effect of the regulation itself (Lanoie

et al. 2011). Thus environmental regulation is costly, but it is less costly than if one were to

consider only the direct costs of the regulation itself and ignore the ability of innovation to

mitigate those costs. This is because, over time, regulation-induced innovations that improve

a firm’s resource efficiency in terms of material or energy consumption have a positive impact

on profitability (Rexh€auser and Rammer 2014).

Porter and van der Linde (1995a) also argue that countries that take early action in envi-

ronmental protection will induce higher costs for domestic firms in the short run, but that the

induced innovation will generate economic benefits in the long run by giving domestic firms a

competitive advantage over foreign firms, which will be constrained by the same regulation

later on. However, to our knowledge, no study has empirically analyzed whether this first-

mover advantage actually leads to competitiveness improvements in the long run.

While there is no evidence that regulated firms’ competitiveness will increase due to policy-

induced environmental innovation activities, global benefits appear to be more likely. Popp

and Newell (2012) find that the social value of renewable energy patents, as measured by

patent citations, is higher than the social value of patents in conventional fossil fuel technol-

ogies that are crowded out. Dechezleprêtre, Martin, and Mohnen (2014) confirm this finding

in a comparison of knowledge spillovers from clean and dirty technologies in the transpor-

tation and energy production sectors. Thus regulation-induced innovation in clean technol-

ogies might increase the innovation activity (and possibly the competitiveness) of some

unregulated companies through knowledge spillovers. This would improve the net social

benefit (or reduce the net cost) of the regulation without cancelling out the competitiveness

effects on regulated companies.

Conclusions and Priorities for Future Research

Some 20 years ago, in their review of the literature on the competitiveness impacts of envi-

ronmental regulation in the United States, Jaffe et al. (1995) concluded that “there is relatively

32 To our knowledge, crowding out between firms, which could occur because the number of inventors in the economy is somewhat fixed in the short run, has not been analyzed.

200 A. Dechezleprêtre and M. Sato

little evidence to support the hypothesis that environmental regulations have had a large

adverse effect on competitiveness.” Since then, through hundreds of studies that have used

ever larger datasets with increasingly fine levels of disaggregation, employing up-to-date

econometric techniques, and covering a wider set of countries, this conclusion has only

become more robust.

This article has reviewed the recent empirical literature on the impacts of environmental

regulations on firms’ competitiveness, as measured by trade, industry location, employment,

productivity, and innovation. The cost burden of environmental policies has often been

found to be very small. The recent evidence shows that taking the lead in implementing

ambitious environmental policies can lead to small, statistically significant adverse effects on

trade, employment, plant location, and productivity in the short run, particularly in pollu-

tion- and energy-intensive sectors. However, the scale of these impacts is small compared

with other determinants of trade and investment location choices such as transport costs,

proximity to demand, quality of local workers, availability of raw materials, sunk capital

costs, and agglomeration. Moreover, the effects tend to be concentrated on a subset of sectors

for which environmental and energy regulatory costs are significant—a small group of basic

industrial sectors characterized by very energy-intensive production processes, limited ability

to fully pass through pollution abatement costs to consumers (whether due to regulation or

international competition), and a lack of innovation and investment capacity to advance new

production processes (Sato et al., 2015a). For these subsectors, where pollution leakage and

competitiveness issues represent a genuine risk, a critical avenue for future research is to

assess and evaluate the various policy options available to prevent adverse impacts on trade

and investment without dampening the incentives to develop cleaner processes and products

(Martin et al. 2014; Branger et al. 2015).

This article has also shown that there is strong evidence that environmental regulations

induce innovation activity in cleaner technologies. Thus far the benefits from these innova-

tions do not appear to be large enough to outweigh the costs of regulations for the regulated

entities. Of course, this does not preclude the ability of environmental regulations to foster

the development of global leaders in innovation, but it does suggest that the evidence for the

most controversial interpretation of the Porter hypothesis (i.e., that environmental regula-

tions can lead to an increase in firms’ competitiveness) is lacking. As regulatory designs and

combinations continue to be explored, further research will be needed to identify the com-

binations of research and development and environmental policies that best encourage in-

novation in green technologies (Burke et al. 2016).

This review raises the question of why the effects of environmental regulations on inter-

national industry relocation have been found to be so small and narrow given the strong

concerns about competitiveness in public policy circles. One explanation could be that reg-

ulated companies have an incentive to overstate the potential competitiveness impacts of

regulations as a strategy to lobby against stringent policies by attributing unpopular off-

shoring decisions to public policy rather than to underlying economic factors such as the

shifting locus of supply and demand in global manufacturing or decreasing transport costs.

An alternative explanation for the lack of empirical support for the large pollution haven

effects discussed in the literature is that environmental policy is endogenous, i.e., governments

strategically set stringency levels to be low (high) where there is a high (low) risk of

Impacts of Environmental Regulations on Competitiveness 201

Deleted Text: falling

Deleted Text: i.e.

competitiveness distortions. This argument suggests that competitiveness concerns could

trigger a “race to the bottom” in global environmental protection efforts. To avoid such an

outcome, further research is needed to accurately measure and monitor the competitiveness

effects of environmental regulations to help ensure that policy is based on robust evidence.

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