Hitotsubashi University
Institute of Innovation Research

Environmental regulation andinternational expansion of MNEs:
The moderating role of pollution reduction resources
and firm multinationality on location choice
Joel Malen
Junichi Yamanoi

IIR Working Paper WP#16-13

Dec. 2016

Institute of Innovation Research
Hitotsubashi University
Tokyo, Japan
http://www.iir.hit-u.ac.jp

Environmental regulation and international expansion of MNEs:
The moderating role of pollution reduction resources and firm multinationality on location choice
Working Paper: Comments Welcome
Please do not cite or circulate without permission

Joel Malen*
Institute of Innovation Research
Hitosubashi University
2-1 Naka, Kunitachi
Tokyo 186-8603
JAPAN
Tel +81 (42) 580-8425
Fax +81 (42) 580-8410
email: malen@iir.hit-u.ac.jp&
Junichi Yamanoi
School of Commerce
Waseda University
1-6-1 Nishiwaseda
Office 1213 Building 11
Tokyo 1698-050
JAPAN
Tel +81 (35) 286-2006
email: yamanoi@waseda.jp*Corresponding author. We would like to thank Akie Iriyama, Aseem Kaul, Paul Vaaler and seminar
participants at Waseda University, the 2016 ARCS Research Conference and 2016 GRONEN Research
Conference for valuable comments. All errors are ours.

1Environmental regulation and international expansion of MNEs:
The moderating role of pollution reduction resources and firm multinationality on location choice

ABSTRACT
We examine how stronger environmental regulations influence MNE international expansion decisions byattending to two sources of firm heterogeneity that moderate this effect: possession of pollution reduction
capabilities and firm multinationality. Empirical tests on 523 cases of international manufacturing
expansion into 49 potential host countries by 124 Japanese chemical industry firms between 2001 and2010 reveal that the market entry deterring effect of stronger environmental regulations is weaker forfirms possessing unique capabilities for pollution reduction and for more multinational firms. Moreover,because more multinational firms have greater incentives and skills for modifying capabilities to create
value in host-country environments, the positive moderating effect of PR-capabilities are strengthened yet
further for high multinationality firms.

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INTRODUCTION
Concern among politicians and business leaders that stronger environment regulations damage
competitiveness and discourage firms from maintaining or establishing domestic operations continues toensure that government efforts to improve environmental quality through regulation remain contentious.
Deeper understanding of how environmental regulations influence the global location patterns ofmultinational enterprises (MNEs) is therefore an issue of clear practical importance. Curiously, however,and despite long-standing attention from management scholars to issues of international location choice,the role of environmental regulations in influencing those decisions has been neglected in management
research (Christmann & Taylor, 2012; Madsen, 2009).
Addressing this gap is important in light of the fact that the bulk of academic studies on theimpact of environmental regulations have been conducted at the national level, focusing on outcomessuch as effects on overall productivity or economic growth (Jaffe, Peterson, Portney, & Stavins, 1995).
However, a country-level focus is likely to overlook two critical factors for understanding firm responses
to environmental regulation. The first is that heterogeneity among firms can engender substantiallydivergent responses to the same set of environmental regulations (Berrone, Fosfuri, Gelabert, & GomezMejia, 2013; Delmas & Toffel, 2008). The second is that while environmental regulation is almost
exclusively the purview of national (or sub-national) governments, the entities being regulated are
multinational. MNEs inherently operate across a range of regulatory environments of varying stringency interms of environmental performance requirements. Such institutional complexity substantially complicatesthe potential impact of regulations adopted by any one country (Kostova, Roth, & Dacin, 2008), creating
opportunities for firms to benefit from both weak (Surroca, Tribo, & Waddock, 2010) and strong(Sharfman, Shaft, & Tihanyi, 2004) environmental performance.
In this study, we combine an institutional perspective with Teece’s (2014) dynamic capabilitiesbased theory of the multinational enterprise to build on recent studies that have begun to highlight theimportance of considering firm heterogeneity when assessing the impact of environmental regulations onfirm behavior (Albrizio, Botta, Koźluk, & Zipperer, 2014; Berrone et al., 2013; Madsen, 2009).
Specifically, we take up the question of how more stringent national environmental regulations influence
the international expansion decisions of MNEs. We argue that while stronger environmental regulations
may increase the costs and challenges associated with entering a given host country, these disadvantages
are mitigated by the possession of valuable firm capabilities that reduce harmful environmental pollution
and by the experience and arbitrage advantages accumulated by firms with a more substantial global
footprint. Importantly, firm multinationality also shapes how firms develop and deploy resources globally.

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More multinational firms will not only have more occasion to find pollution reduction capabilities valuable
in multiple locations, the need to modify those capabilities across an increasing number of national
regulatory environments engenders experience that will ease any potential transition into a new host withstronger environmental regulations, further weakening any negative influence of stronger regulations on
potential host country attractiveness.
Empirical tests using a sample of 523 instances of foreign expansion for new manufacturing
facilities by 124 Japanese firms in the chemical industry between 2001 and 2010 provide support for ourarguments. These results prove robust to reasonable variation in model specification, sampling andestimation strategies.
This study makes several contributions to management research. First, we answer the call frominternational management (IM) scholars to capitalize upon the relative advantages of the IM perspective
for understanding how firm heterogeneity weighs on the relationship between environmental regulations
and location choice (Christmann & Taylor, 2012). Attending to firm differences allows for more granular
understanding of the phenomenon than has been provided by research focusing on national level
outcomes. Moreover, such an approach allows for better understanding of when stronger regulations
might have positive outcomes. Perspectives on the effects of stronger regulation can be broadly classified
into two viewpoints. One, the “race to the bottom” perspective argues that challenges associated withcomplying with stronger environmental regulations will increase the costs of conducting business, leading
firms to seek locations with less stringent and burdensome environmental requirements. Conversely, what
has come to be known as the Porter hypothesis, argues that stronger environmental regulations will
induce firms to innovate, in turn leading to the development of capabilities providing competitive
advantage over rivals from weaker environmental domains. However, by failing to attend to thedifferential impact of environmental regulation across firms, neither perspective considers the potential
for such regulations to be a net positive, at least for some firms, based on their extant (rather thanpotential future) environmental capabilities. The IM perspective adopted in the present study allows us toovercome these limitations and provide new insights on the phenomenon.
This study also contributes to management research on firm location choice where studies
considering how national regulation influences location choice have focused predominantly on the effects
of characteristics of the regulatory environment that create contractual hazards (e.g. Coeurderoy &Murray, 2008; Delios & Henisz, 2003; Holburn & Zelner, 2010). While attention to contractual hazards
follows logically from the importance of internalization theory to international management (IM) research4

(Buckley & Casson, 1976; Hennart, 1982), contractual hazards comprise only part of the story (Teece,
2014). As Teece (2014) articulates, the relevance of firm capabilities in a particular potential hostconstitute a relatively overlooked dimension of location choice. This oversight is particularly salient inlight of the fact that the value of resources is, to a substantial degree, externally determined (Barney, 1991;
Priem & Butler, 2001). To the extent that the policy choices influence the value of specific firm resources,
such as the pollution reduction technologies examined in this study, greater attention to the combinatorial
effects of regulatory content and firm resources on location choice is called for.
Empirically, our use of patents to measure firm-specific capabilities for pollution reduction
constitutes an advance on prior research. Patents provide a clearer, more objective indication of firm
capabilities than studies that rely on less precise and potentially biased survey measures (e.g. Christmann,
2004). They also better capture firm capabilities that are simultaneously rare, valuable and inimitable(Barney, 1991) than the use of ISO 14001 adoption (e.g. Delmas & Toffel, 2008; Madsen, 2009), which isoften adopted ceremonially, having minimal impact on actual firm operations (Boiral, 2007). The use ofpatents also represents an advance over studies that infer firm-level characteristics deriving from featuresof the home-country institutional environment, such as home-country regulatory stringency (e.g. Madsen,2009)—an important consideration in light of the failure of prior studies to find a relationship between
home-country conditions and pollution by foreign subsidiaries (King & Shaver, 2001).
Practically, our results allow us to weigh in on discussion between and among firm managers andpolicy makers regarding the effects that strengthening environmental regulatory regimes may have on firm
and national competitiveness.

THEORY AND HYPOTHESESInternational expansion and firm capabilities
Firm capabilities influence how firms expand and diversify (e.g. Chatterjee & Wernerfelt, 1991; Helfat &Lieberman, 2002). Firms are more likely to enter new lines of business in which extant capabilities can be
profitably deployed (Silverman, 1999). A similar logic applies to decisions regarding geographic expansion.
Because firm success in foreign markets derives largely from the ability to deploy valuable resources inways that competitors cannot imitate, firm capabilities constitute an important constraint on (and enablerof) market entry (Teece, 2014). At a minimum, the value of firm capabilities in a foreign market needs tocompensate for inherent liabilities of operating in different and unfamiliar environments (Hymer, 1976;

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Zaheer, 1995) in order to justify international expansion (Buckley & Casson, 1976; Dunning, 1988;
Hennart, 1982).
While some firm capabilities create value regardless of where they are deployed, others—
including valuable technologies and fundamental know-how underlying the ability to provide a particular
product or service—tend to be more specialized, creating heterogeneity in terms of the ability of resources
to create value across geographic locations (Helfat & Lieberman, 2002; Teece, 1986). Accordingly, therelevance of firm capabilities in a specific foreign market is an important influence on which countries
firms elect to enter (Teece, 2014). Further, to the extent that the value of firm capabilities is externallydetermined (Barney, 1991; Priem & Butler, 2001), differences in characteristics of national environments
can be expected to induce variation in the value of firm capabilities across potential host countries.
Below, we detail how national environmental regulations constitute one such source of variationin the value of firm capabilities across potential host countries. Because environmental regulations coverpollution that occurs within a country, our analysis concerns firm expansion decisions where theestablished subsidiaries are likely to generate pollution. Most pollution for which firms are directly
responsible is emitted during the manufacturing process. Consequently, environmental regulations are
more salient to decisions regarding the siting of manufacturing operations than, say, the siting ofsubsidiaries engaged in marketing or distribution of imported goods produced elsewhere. We therefore
focus our analysis on international expansion of manufacturing activities.

Environmental regulation and host-country attractiveness
Environmental regulations set the minimal acceptable environmental performance for firms operating
within a jurisdiction. Failure to comply with national environmental regulations can lead to the impositionof fines or other legal sanctions on a subsidiary’s activities, weakening its competitive position. Beyond
issues of legality, compliance also helps firms address challenges with establishing and maintaining theirlegitimacy in host nations (Kostova & Zaheer, 1999). Foreign firms can be targets of increased scrutiny
from the local public as well as regulators (Hymer, 1976). Such increased scrutiny is especially likely in thecontext of environmental issues, where the effects of pollution can have direct and drastic impacts on thehealth of the local population in addition to the natural environment. Failure to comply withenvironmental regulations can therefore precipitate social as well as legal sanctions (Deephouse, 1996).
Stronger environmental regulations set lower limits for various types of pollution that may bedischarged into the environment. Hart (1995) describes two general approaches for meeting such6

requirements. Firms can attempt to control their emissions directly through the use of pollution-control
equipment capable of trapping, storing, treating and disposing the pollutant. Alternatively, firms canattempt to prevent emissions through such means as the modification of existing or development of newprocesses, routines and technologies.
Pollution control approaches require the firm to purchase, install and operate new equipment.
Such an approach imposes costs—sometimes substantial—while failing to provide a means to improve
productivity and performance (Hart, 1995). Indeed, rather than improve productivity, adopting pollution
control measures can reduce incentives to scrutinize extant routines and processes for inefficiencies that
reduce waste and enhance productivity, weakening financial performance (King & Lenox, 2002). Further,
applying pollution control measures to extant firm processes and routines can interfere with theiroperation, thereby weakening the performance (and value) of current capabilities. For example, Klassen
and Whybark (1999) found that more extensive use of pollution control reduced firm manufacturingperformance.
The desire to avoid the drawbacks of adoption pollution control measures are particularly salientin the context of international expansion where, in addition to limiting the level of pollution emissions,stricter regulations often cover how firms comply with those limits as well. For example, national
governments may require the use specific technologies or the adoption of particular processes for
reducing various forms of pollution. Mandating specific approaches to compliance can create obstacles tomarket entry by foreign firms, a desirable outcome when, as often happens, environmental regulations areused to shelter domestic industry (Vogel, 1997; Vogel & Rugman, 1997). The costs associated with
pollution control decrease the potential value of firm resources in a given country, working to reduce its
attractiveness as a potential host.
In contrast to pollution control approaches, pollution reduction can precipitate financial
performance improvements (Hart, 1995; King & Lenox, 2002). Indeed, one of the preeminent arguments
for the case that stronger regulations benefit, rather than hurt firms, is that such regulations induce thedevelopment of new and valuable capabilities (Porter & van der Linde, 1995). However, managerial biases
and concerns about the time frames for payback to investments improving environmental performancelead firms to systematically underinvest in development of PR-capabilities (Berchicci & King, 2007;
Marcus, Geffen, & Sexton, 2002; McWilliams & Siegel, 2001). Managers desiring strategic flexibility andbiased against investments to improve environmental performance are unlikely to choose a market basedon the potential benefits of being forced by local regulations to develop new environmental capabilities.

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Rather, in the context of international expansion decisions, firms prefer countries where their existing
capabilities and resources already meet the resource requirements for successful market entry (Helfat &Lieberman, 2002).
Even in firms that possess PR-capabilities, it is the general competitive capabilities unrelated topollution reduction (non-PR-capabilities) that are central to competitive advantage (Kolk & Pinkse, 2008).
The stronger the environmental regulations of a potential host, the greater the likelihood that entry will
necessitate the implementation of pollution control or prevention measures that will diminish the net
benefits to the firm from deploying its present FSAs in the potential host. All things being equal, given the
choice between entering a country that requires supplementation to or modification of non-PR capabilities
or limits their value and one that does not, firms will prefer the latter.

Hypothesis 1: Stronger national environmental regulations discourage MNEs from entering a potential
host country.

Environmental regulation and pollution-reduction capabilities
Competitive performance is dictated by the possession of core capabilities which are only rarely explicitly
connected to environmental performance (Kolk & Pinkse, 2008). Nonetheless, for various reasons and tovarying degrees firms do develop capabilities designed to lessen the negative environmental impacts on
their activities. Such capabilities provide several important benefits when it comes to complying with hostcountry environmental regulations. To the extent that PR-capabilities enable compliance with the relevant
regulations, compliance and liability costs are mitigated. PR-capabilities may obviate the need to install
costly pollution control equipment and can precipitate direct costs savings through lowering the costs of
raw material inputs that would become waste pollution as well as the costs associated with disposal ofpollutants (Hart & Ahuja, 1996). Finally, PR-capabilities also spur improved efficiency of both material
input and firm asset use (Hart & Ahuja, 1996; Porter & van der Linde, 1995; Schmidheiny, 1992; Smart,1992) that can better position the firm competitively with respect to local competitors.
Firms with more extensive PR-capabilities are more likely to possess the requisite capabilities forcompliance with increasingly stringent levels of environmental regulation. Further, the ability to tout theuse of state-of-the art pollution reduction technology can also help to enhance local legitimacy. Even
where national environmental regulations contain provisions mandating the form of compliance approach,firms with more extensive PR-capabilities will be better positioned in terms of possessing the underlying

8

skills and knowledge necessary to meet those demands. Although the value of non-PR-capabilities in ahost may be weakened by stronger environmental regulation, those costs will be counter-balanced to atleast some extent by the possession of PR-capabilities that increase the ease and reduce the costs ofcompliance with national environmental regulatory regimes. Madsen (2009) has shown that generic, nonfirm specific environmental capabilities can mitigate the effects of stronger environmental regulation. Sucheffects can be expected to be stronger in the case of firm-specific PR-capabilities, which better position
firms to benefit competitively relative to rivals.
More extensive development of PR-capabilities also engenders a shift in managerial thinking
about environmental regulation. When firms develop experience in a particular area of technology, they
become better positioned to develop further innovations in the same domain (Fleming & Sorenson, 2001;
Teece, Pisano, & Shuen, 1997). Development of pollution reduction capabilities leads to the accumulationand dissemination of knowledge relevant to pollution reduction throughout the firm (Lapre, Mukherjee, &Van Wassenhove, 2000). Moreover, because the knowledge related to pollution reduction is tacit (and
often causally ambiguous), the accumulation of such knowledge among a firm’s employees leads to thedevelopment of yet more capabilities increasingly likely to be valuable, rare and difficult to imitate (Barney,
1991; Hart, 1995). As this process proceeds, competing based on environmental performance becomes anincreasingly viable strategic approach for improving overall firm performance.
As awareness among firm management regarding how pollution reduction efforts can improve
competitive performance accumulates, firms become increasingly active in seeking out opportunities toprofitably use PR-capabilities (Berchicci & King, 2007). From this perspective, stronger environmental
regulations can function as a type of strategic asset that complements existing PR-capabilities (Dunning,1998) allowing firms to extract more value from these assets, by increasing their potential cost andefficiency advantages vis-a-vis local competitors and decreasing legitimacy challenges associated with
operating in a foreign environment.
In sum, the development of more extensive PR-capabilities, not only helps to mitigate thenegative effects of environmental regulation on non-PR capabilities, but leads firms shift from perceiving
environmental regulation as a constraint to be avoided to being an opportunity to be sought out.

Hypothesis 2: Firm capabilities for reducing pollution will positively moderate the effect of national
environmental regulations such that the entry-deterring effect of stricter protections is weaker for firms
with more extensive PR-capabilities.

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Environmental regulation and firm multinationality
In addition to PR-capabilities, firm multinationality represents another source of firm heterogeneity thatwill condition how firms perceive environmental regulations when considering international expansion.
The negative influence of stronger environmental regulations on host country attractiveness is likely to beless significant in firms with a more extensive global presence for several reasons. First, international
expansion engenders experiential learning that enables firms to reduce costs associated with newness andforeignness when they make subsequent new market entries (Hymer, 1976). As firms gain experienceestablishing subsidiaries in new locations, they become better attuned to salient features of new
institutional environments likely to bear on their operations (Lu & Beamish, 2004). More multinationalfirms are therefore not only more likely to recognize local conditions likely to influence firm performance,
but have the experience in modifying and localizing capabilities to address those conditions. Accordingly,
the negative influence on the value of non-PR capabilities will be offset to some extent by experience withnew country entry.
More multinational firms also operate in more diverse national institutional environments. This
increases the likelihood firms will have experience operating in an institutional environment at least similar
to that of a potential host country, working to lower the institutional distance and the associatedchallenges such distance creates for market entry (Ghemawat, 2007; Madsen, 2009). As Henisz (2003)
describes, even when the institutional environments of subsidiary host countries are not identical, more
extensive international experience enables firms to develop general routines for managing regulatory
challenges. Such experience will mitigate the entry-deterring effect of stronger environmental regulations
on market entry.
Finally, operating across a more extensive diversity of environments opens up possibilities forfirms to engage in institutional arbitrage (Ghemawat, 2007; Hennart, 2011). Operating in a greater numberof countries exposes an MNE to weaker as well as stronger environmental regulatory regimes. To theextent an MNE conducts operations in a host with a more permissive regulatory environment, it may beable to concentrate, in that host, activities that would conflict with environmental regulations elsewhere.
For example, Surroca and colleagues (2010) found that stakeholder pressure in one country induced
MNEs to transfer socially irresponsible practices from that country to its foreign subsidiaries. To theextent an MNE’s global footprint allows it to enter a potential host nation without conducting activities

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that conflict with local environmental regulations, such regulations will bear less strongly on international
location decisions.

Hypothesis 3: Firm multinationality will positively moderate the effect of national environmental
regulations such that the entry-deterring effect of stricter protections is weaker for more multinationalfirms.

Pollution-reduction capabilities and firm multinationality
Firm multinationality will also influence the nature of PR-capability development and deployment. The
attractiveness of a potential host country is shaped not only by the relevance of its capabilities in thatmarket but by the challenges associated with transferring a firm’s capabilities to the host as well as (Teece,
2014). In this regard, two characteristics of more multinational firms will facilitate the ability of firms tocreate value from PR-capabilities in foreign markets, further weakening the entry-deterring effect ofstronger environmental regulation.
First, more multinational firms are more likely to develop what Rugman and Verbeke (2001) term
“nonlocation-bound” PR-capabilities—that is, capabilities that “can be exploited globally” (Rugman &Verbeke, 2001: 241). Firms with a larger international footprint find it more beneficial to develop
nonlocation bound PR-capabilities as a means to reduce the inherent complexity and uncertainty ofoperating in multiple institutional environments (Aragon-Correa & Sharma, 2003; Sharfman et al., 2004).
More multinational firms are increasingly at risk to confront pressure from both home- and host-country
stakeholders to comply with environmental performance expectations (Sharfman et al., 2004).
Standardizing PR-capabilities at a high level can help firms to manage those demands while simultaneously
confronting the inherent challenges of maintaining legitimacy across divergent institutional contexts(Kostova & Zaheer, 1999). Accordingly, researchers have documented how more multinational firms are
more likely to have uniform environmental practices across their global operations (Christmann, 2004;
Dowell, Hart, & Yeung, 2000). The tendency toward development of nonlocation-bound PR-capabilities
means that such capabilities align with the requirements of any particular host, rendering stronger
environmental regulations in any specific host less relevant to location choice.
PR-capabilities are frequently incentivized through government regulations (Jaffe, Newell, &Stavins, 2005; Marcus, 1980). Accordingly, many PR-capabilities are initially location-bound. Difficulties
of adapting pollution reduction technologies to the unique demands of foreign environments (King &11

Shaver, 2001), can lead PR-capabilities remain location-bound (Kolk & Pinkse, 2008). However, even PRcapabilities originally developed for a specific country only remain location-bound over time underrelatively unique circumstances. In particular, it must remain true that restricting the use of a PR-capability
to a single (or limited number of) location(s) does not have a negative impact on firm performance(Rugman & Verbeke, 2001)—that is, there are no opportunities to beneficially deploy the capability inother locations. As firms expand their operations into more countries, such conditions become less likely
to hold. Firms with a larger international footprint operate in an increasingly diverse range ofenvironmental regulatory environments and are therefore more likely to find PR-capabilities to be of use
beyond a single location when it comes to compliance with local environmental regulations (Sharfman etal., 2004).
A second mechanism by which firm multinationality enhances the benefits of PRcapabilities is that more multinational firms possess more experience in modifying thesecapabilities to unique requirements across countries. Given that using a PR-capability in a new
country is likely to require at least some degree of modification (King & Shaver, 2001), firms
develop experience in adapting their PR-capabilities to unique country circumstances, with such
experience accumulating more extensively as firms extent operations abroad. Characteristics ofthe knowledge underlying the capabilities (Jensen & Szulanski, 2004; Kogut & Zander, 1993),
institutional barriers to capability transfer (Cuervo-Cazurra, Maloney, & Manrakhan, 2007) anddifferences in the level of infrastructure development (Tsai & Child, 1997) can all increase thedifficulty of capability transfer and necessitate modification or adaptation. The challenges
associated with capability transfer are particularly acute in the context of transferring PRcapabilities (Kolk & Pinkse, 2008). More multinational firms will therefore possess skills thatfacilitate deployment of PR-capabilities in new contexts. By contrast, PR-capabilities developed in
one country are less likely to be relevant elsewhere when MNEs operate in a limited number offoreign environments. In any event, such firms will have less experience in modifying PRcapabilities for foreign environments. These considerations suggest our final hypothesis.

Hypothesis 4: The positive moderating effect of pollution-reduction capabilities on the entry-deterring
effect of stricter national environmental regulations is stronger in more multinational firms.

DATA AND METHODS

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Sample and Data
To assess how environmental regulations influence international expansion decisions, we employ datafrom the Kaigai Shinshutu Kigyou Souran database (Overseas Japanese companies) provided by Toyo Keizai(OJC). The OJC database provides information on each foreign subsidiary, including its parent firm,
location, business scope, industry, and foundation year. We limit our sample to firms from the chemicalindustry (Japan SIC between 1600 and 1699). Important differences exist across industries in terms ofboth the relative propensity to (and importance of) patent(ing) new technologies. The extent to whichfirm operations create pollution and to which environmental regulations are likely to bear on those
activities can also vary substantially across industries. Focusing on the chemical industry limits the sample
to firms for which patenting is prominent and for which environmental regulations are salient. Moreover,international investment tends to be prominent in the chemical industry, accounting for roughly 12% of
all greenfield FDI projects in manufacturing over the decade through 2012 (UNCTAD, 2015).
Because our research question concerns where firms choose to locate as opposed to whether theyelect to make a foreign investment, we limit the sample to years in which firms establish a new foreign
manufacturing subsidiary. The final sample comprises 357 firm-expansion-years in which a Japanesechemical firm established at least one new foreign manufacturing subsidiary. In some cases, firms
established new manufacturing facilities in more than one host country in a given year. In total, the sample
comprises 534 instances where one of 124 Japanese chemical industry firms in the OJC established a newforeign manufacturing subsidiary. For each firm-expansion-year, the base choice set of potential locations
for establishment of a new manufacturing subsidiary comprises all countries hosting at least one
manufacturing subsidiary of at least one Japanese chemical firm in our sample over the ten-year (20012010) sample period. There were 49 such countries in our sample for which data were available.1

Measures
Dependent variable. Country Entry is a binary indicator set to one when a firm establishes a new
manufacturing subsidiary in a host country (zero, otherwise). We identified manufacturing subsidiaries byreferring to the description of the business scope of each subsidiary provided in the OJC. We then1

The 49 countries: Australia, Austria, Bangladesh, Belgium, Brazil, Brunei, Canada, China, Colombia, Czech
Republic, Denmark, Finland, France, Germany, Greece, Hungary, India, Indonesia, Ireland, Israel, Jordan,
Luxembourg, Malaysia, Mexico, Netherlands, New Zealand, Pakistan, Philippines, Poland, Portugal, Russia, Saudi
Arabia, Singapore, Slovak Republic, South Africa, South Korea, Spain, Sri Lanka, Sweden, Switzerland, Tanzania,
Thailand, Turkey, United Arab Emirates, United Kingdom, United States, Venezuela, Vietnam

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employed structured content analysis (Jauch, Osborn, & Martin, 1980; Yu & Cannella, 2007). First, 1,000
foreign subsidiaries were randomly selected for the identification of foreign subsidiary activities. Second,
the authors read all the descriptions of the business scope of these foreign subsidiaries and generated a listof keywords that are likely to indicate manufacturing-related activities. These keywords were generated
based on interviews conducted with Japanese practitioners with experience working abroad. The set of
keywords was then applied to the complete list of business scope descriptions in the OJC through a
combination of computer aided and human coding to identify which subsidiaries were engaged in
manufacturing activities.
Independent variable. Direct measurement of environmental regulations over time and acrosscountries is challenging (Albrizio et al., 2014). Within countries, myriad laws cover environmental
protection. Relevant laws can vary across industries and types of pollution. Typically, both the content oflaws and extent of enforcement evolve and change over time. Across countries, the set of relevant
environmental laws differs substantially in both form and substance. Further complicating measures ofenvironmental regulatory stringency is the fact that even when protective laws exist “on the books,” weak
enforcement can limit their effectiveness in practice. Esty and Porter (2005) provide evidence that thestringency of a country’s environmental regulatory regime is closely related to cross-national differences inenvironmental performance. We therefore turned to measures of national environmental performance toserve as an indicator of environmental regulatory stringency. Looking at environmental performanceoutcomes provides the additional advantage of accounting for the extent to which environmental
regulations are actually enforced, better capturing their influence on firm behavior.
One of the most comprehensive efforts to measure national environmental performance across alarge number of countries is the Environmental Performance Index (EPI) developed by the Yale Center
for Environmental Law and Policy and Columbia University Center for International Earth Science
Information Network, Columbia University in collaboration with the World Economic Forum and Joint
Research Centre of the European Commission (Emerson et al., 2012). The 2012 EPI tracks 22
environmental performance indicators across a range of policy categories measuring the effects pollution
on human and ecosystem health for 132 countries. The 2012 EPI also provides historical annual
indicators of environmental performance going back to 2000. We use a country’s overall EPI score as ourmeasure national environmental regulatory stringency—EPI.
Moderating variables. We measure PR-capabilities by referencing firm patents. To measure firm
pollution reducing patents we first obtain the set of patents granted by the Japan Patent Office (JPO) to14

the sample firms using the Institute of Intellectual Property (IIP) Patent Database (Goto & Motohashi,2007). To identify which of the granted patents in the IIP database are related to pollution reduction we
use the CleanTech PatentEdge (CTPE) database provided by IP Checkups—a private research firm. The
CTPE database provides a comprehensive description of patents filed at major global patent offices(including JPO) covering technologies that mitigate negative environmental externalities and has beenused by other scholars investigating similar issues, such as the development of renewable energy
technologies (e.g. Nanda, Younge, & Fleming, 2013). We define pollution reduction patents as those
identified by IP Checkups to reduce air or water pollution, improve waste treatment or improve
manufacturing and industrial processes. Pollution Reduction Patents is a count of the number of pollution
reduction patents granted to the sample firm over the previous four years—based on prior research toaccount for the greater relevance of more recent patents.2
We define firm multinationality based the number of counties in which a firm operates (Lu &Beamish, 2004; Tallman & Li, 1996). Country Scope is count of the number of countries in which a sample
firm has manufacturing subsidiaries in a given year.
Control Variables. In addition to the stringency of national environmental regulations, the degree of
economic and institutional development also weigh on a country’s environmental performance (Esty &Porter, 2005). Because these factors simultaneously play a role in shaping the relative attractiveness of hostcountries, it is necessary to control for their influence. We therefore include a measure of GDP per capita(constant US dollars) to capture the overall level of economic development. To control for the level of
institutional development we include a measure of Government Effectiveness developed by Kaufman andcolleagues (2009; 2000) from the World Bank’s Governance Matters database. This measure captures“perceptions of the quality of public services, the quality of the civil service and the degree of its
independence from political pressures, the quality of policy formulation and implementation, and thecredibility of the government's commitment to such policies” (Kaufmann et al., 2009: 6).
We control for three measures of host-country attractiveness. Host country GDP (constant billion
US dollars) is included as a measure of overall market size. The annual percentage change in GDP Growthaccounts for recent trends in economic conditions. Total net inflows of foreign direct investment (FDI)(constant billion US dollars) control for general market attractiveness and openness to foreign investment.
These three variables and GDP per capita come from the World Development Indicators Databaseprovided by the World Bank. As a final country-level control, we include the Geographic Distance
2 Results are robust to varying this measure from three and five years

15(kilometers) from Japan to account for dimensions of market attractiveness stemming from proximity to
the home market. This measure is taken from the GeoDist database provided by the Centre d’Etudes
Prospectives et d’Informations Internationales.
At the firm-level, we control for two characteristics that may influence both location decisions
and pollution reduction technology development. Size is a measure of annual sales (10 billion Japanese
Yen). R&D Intensity—measured as annual firm R&D expenditure divided by annual sales—captures theextent to which firms emphasize technological competition and prioritize development of newtechnological resources. Data for both measures come from Nikkei Financial Quest. To account for the
potential influence that current operations in a potential host country may have on the relative
attractiveness of the host, we include an annual count of the total number of firm subsidiaries in eachpotential host country (Number Country Subsidiaries). Data for this measure come form the OJC database.
Finally, to account for general time effects we include a set of year dummy variables. All right-hand-side
variables are lagged by one year.

Estimation Strategy
As described above, our data are structured to examine where firms choose to expand internationally,
conditional on the decision to establish a foreign manufacturing subsidiary. Because we employ a discrete
dependent variable to indicate which host countries firms select for foreign manufacturing expansion, alogit model is appropriate for testing our hypotheses. In order to account for the fact that observations
within firms are not independent, we cluster standard errors at the firm-level.
This study is centrally concerned with the moderating effects of PR-capabilities and firm
multinationality on the influence of environmental regulations. Because coefficient estimates do not
represent marginal effects in non-linear models, care must be taken when interpreting estimation results(Hoetker, 2007; Shaver, 2007). Accordingly, we assess the moderating relationships in two ways. First, wefollow Zelner and Holburn (2010) who employ a simulation-based approach developed by King andcolleagues (2000) to plot, and test for the significance of, the difference in predicted probabilities ofcountry entry across levels of environmental regulatory stringency in firms with high and low levels of,respectively, PR-capabilities and multinationality. Second, we follow Hoetker (2007) and split the sample
at meaningful levels of the moderating variables and compare the average marginal effect (AME) ofenvironmental regulatory stringency across the subsamples. We defer additional description of theseapproaches to the results section.

16

RESULTSCore results
Table 1 reports descriptive statistics and pair-wise correlations. The bivariate correlation of 0.83 between
GDP per capita and Government Effectiveness stands out. Conceptually, this correlation is intuitive as economic
and institutional development tend to go hand-in-hand (North, 1981). Multicollinearity diagnostic tests
reveal that the largest individual variance inflation factor (VIF) is 3.79, and the average VIF is 1.82, bothsufficiently below threshold levels where multicollinearity becomes a concern (Belsley, Kuh, & Welsch,1980).3———Insert Table 1 around here———Results of logistic regression estimations are reported in Table 2. Column 1 reports results forcontrol variables only. Results align with intuition. Firms are more likely to locate manufacturingsubsidiaries in countries with larger markets, stronger economic growth and better regulation that are
more geographically proximate. At the firm level, firms are more likely to establish new manufacturing
facilities in countries where they already have an established presence. Column 2 adds EPI and the twomoderating variables—Pollution Reduction Patents and Country Scope. Here, we do not find support for
Hypothesis 1, which argued that stronger environmental regulation discouraged market entry. Not only is
the coefficient estimate not significant, it is positive, opposite the prediction. This results comports withextant research examining the influence of environmental regulation on FDI (Madsen, 2009) and suggests
the importance of investigating contingencies through which EPI may be relevant to international location
decisions.

———Insert Table 2 around here———3

Nonetheless, because economic and institutional development are so tightly linked, we reestimate our main
specifications: 1. without GDP per capita 2. without Government Effectiveness 3. with neither measure 4. with a single
factor variable combining the two created using the principal-component factor method. In all cases, coefficientestimates for the interaction terms between EPI and Pollution Reduction Patents and EPI and Country Scope remain fully
consistent with reported results.

17

Columns 3-5 of Table 2 add the interaction term between EPI and the two moderating variables.
In Column 3, the coefficient for the interaction term between EPI and Pollution Reduction Patents is positiveand significant (0.002, p<0.001), in line with the Hypothesis 2, which argued that possession of PRcapabilities would positively moderate the relationship between environmental regulation and host country
attractiveness. Similarly, the coefficient for the interaction term between EPI and Country Scope is also
positive and significant (0.004, p<0.01) in Column 4, as predicted by Hypothesis 3. Column 5 displays
results of the main specification where both interaction terms are included. Results here are consistent
with those in Columns 3 and 4.
To facilitate interpretation of the interaction terms, we employ the “intgph” procedure for Statadeveloped by Zelner (2009). Setting all right-hand-side (RHS) variables—other than the two in theinteraction term—to their sample means (modes for binary variables), Figure 1 simulates how the
likelihood of selecting a country to host a new manufacturing subsidiary changes as environmental
regulatory stringency of that country increases for three different firms: Firm A, possessing the sample
median level of pollution reduction patents (1 patent), Firm B, with one standard deviation (approximately
10 patents) above the sample median of pollution reduction patents (11 patents) and, Firm C, at the 90th
percentile for pollution reduction patents (16 patents). The trend lines Figure 1, plots the likelihood of
selecting a particular host nation for a new manufacturing subsidiary as a function of increasing levels ofenvironmental regulatory stringency (EPI). The hollow circles indicate regions where there is a statisticallysignificant difference in the expected likelihood of country entry between Firms A and B and Firms B andC, respectively.
———Insert Figure 1around here———The trend line in Figure 1 representing Firm A, slopes downward to the right, indicating that
MNEs at or below the median level of pollution reduction patents become increasingly less likely to entera potential host country as environmental regulatory stringency increases. The trend line for Firm B, whilestill negative, is considerably more shallow than for that of Firm A, consistent with the argument,
articulated in Hypothesis 2, that the entry deterring effect of stronger environmental regulations will be
weaker in firms with more extensive PR-capabilities. Perhaps more interesting is the trend line for Firm C
where, in contrast to Firms A and B, the slope moves upward to the right. MNEs with the most extensive
PR-capabilities (above the 90th percentile) become more, not less, likely to enter a country as its
environmental regulatory stringency increases.

18

Whereas the likelihood Firm A would enter a country at the weakest levels of sample EPI (33.67)
is 1.85 percent, the likelihood would be only 1.33 percent for Firm B and 1.13 percent for Firm C,
decreases of approximately 28 and 39 percent, respectively. The hollow circles in Figure 1 indicate that thelower likelihood entry of Firms B and C as compared to Firm A are statistically significant (at the 5
percent level) with respect to countries with EPI values below 44.5. Conversely, Firms B and C are more
likely than Firm A to enter countries with higher EPI levels—these differences are statistically significant
for countries whose EPI is greater than 67.5. For example, while the likelihood of Firm A entering acountry with the most stringent environmental regulations (EPI of 77.99) is only 0.79 percent, thelikelihood is 1.11 percent for Firm B and 1.33 percent for Firm B. That is, Firms B and C are, respectively,
40 and 68 percent more likely to enter. A test of whether the difference in the predicted likelihood ofentry between Firm A and Firm B with respect to the weakest sample level of environmental regulatory
stringency and the same difference with respect to the highest level of regulatory stringency rejects the null
hypothesis that the two differences are the same (p<0.01). The trends displayed in Figure 1 are consistent
with Hypothesis 2, providing evidence that the influence of an MNE’s PR-capabilities on the relationshipbetween environmental regulatory stringency and international location decision-making is both
statistically significant and practically meaningful.
Figure 2 plots the predicted likelihood of country entry as a function of EPI for two firms: one at
the median level of multinationality (Country Scope is six countries) and one at one standard deviation(approximately 5 countries) above the median level of multinationality (Country Scope is 11 countries).
Indeed, whereas the weak downward slope of the trend line for low multinationality firms suggests
become slightly less likely to enter a country as its environmental stringency increases, the effect ofstronger environmental regulations is opposite for high multinationality firms, as indicated by the
positively sloping trend line. Importantly, however, the difference between the two lines is only statisticallysignificant (at the 5 percent level) with respect to the likelihood of entry into countries with low
environmental regulatory stringency—EPI values below 45.7. The likelihood of entry into a country at thelow end of the EPI range is 1.25 percent for the low multinationality firm, but only 0.92 percent for thehigh multinationality firm. The high multinational firm is 25% less likely to enter. Figure 2, therefore,
provides support for Hypothesis 3, which argued that the influence of environmental regulatory
stringency on the likelihood of country entry would be positively moderated by firm multinationality.

———Insert Figure 2 around here———19

Hypothesis 4, argued that the positive moderating effect of PR-capabilities on the relationshipbetween environmental regulatory stringency and international expansion will be stronger for more
multinational firms. To facilitate testing and interpretation of this three-way interaction, we compare themoderating effect of PR-capabilities on the environmental regulatory stringency-international expansion
relationship in firms with high to low levels of multinationality. Because separate estimation for eachgroup is preferable to including a dummy variable in non-linear models (Hoetker, 2007), we split the
sample at the sample mean level of multinationality and separately estimate the main specification for highand low multinationality MNEs. Results for the high-multinationality sub-sample are reported in Column
6, where the coefficient for the interaction term between EPI and Pollution Reduction Patents is positive andsignificant (0.001, p<0.001). By contrast, the coefficient estimate for the same interaction in low
multinationality firms, reported in Column 7, is not significant (-0.0003, p=0.890). Taken together, thecombination of the significant and non-significant estimates in Columns 6 and 7, provide support for
Hypothesis 4 (Hoetker, 2007). Possession of PR-capabilities positively moderates the relationship between
environmental regulatory stringency and international location choice for high-, but not low-,multinationality MNEs.
To interpret these results we again plot the predicted likelihood of country entry as a function of
EPI. Figure 3a plots the relationship for two high-multinationality MNEs (Country Scope above 7
countries): one possessing the median level of PR-capabilities (1 Pollution Reduction Patent) and one with one
standard deviation above the median level of PR-capabilities (11 Pollution Reduction Patents). Figure 3b plots
the same relationship, but for two low-multinationality MNEs. Figure 3a reveals that compared to firms
with the median level of PR-capabilities, firms with high PR-capabilities are less likely to enter countries
with EPI levels below 47.1 and more likely to enter countries with EPI above 69.5. The likelihood a firmwith median PR-capabilities will enter a country at the low end of the EPI range is 4.17 percent, comparedto 2.93 percent for the firm with high PR-capabilities. At the high end of the EPI range, the high PRcapabilities firm is 40 percent more likely to enter (1.91 percent vs. 1.36 percent). A test for whether thedifference in probability of country between high-and low-PR-capability MNEs at the low and high endsof the EPI range rejects the null hypothesis that the differences are equal (p<0.05).
By contrast, the trend lines for the high- and low-PR-capability MNEs are nearly identical for the
low-multinationality subsample depicted in Figure 3b. Further, at no point is the difference between thetwo groups statistically significant. That PR-capabilities do not moderate the relationship between

20environmental regulatory stringency and international expansion for low multinationality MNEs is
consistent with the arguments laid out in Hypothesis 4. PR-capabilities are more likely to be location
bound in low multinationality MNEs. At the same time, a lack of experience in modifying PR-capabilities
for foreign environments suggests that the challenges associated with deploying such capabilities in new
institutional environments are likely more daunting, working to discourage market entry.

———Insert Figures 3a and 3b around here———Robustness analyses
These core results prove robust to several reasonable variations in model specification, sampling andestimation strategies. An alternative approach to including an interaction term when testing moderating
hypotheses is to split the sample at meaningful levels of the independent variables and compare thecoefficient estimates for the moderated independent variable(s) across the sub-groups (Hoetker, 2007). A
comparison of AMEs across the groups can further facilitate interpretation. To provide additional
interpretation of our moderating hypotheses and test the robustness of our results, we therefore, follow
this approach, splitting the sample into high and low levels of Pollution Reduction Patents and Country Scope atsample mean values and comparing the effect of EPI across the sub-groups. Columns 1 and 2 of Table 3
report the results for logit estimation of the effect of EPI on the likelihood of country entry for high andlow levels, respectively, of Pollution Reduction Patents. Whereas the coefficient estimate for EPI is positiveand significant for firms with high levels of Pollution Reduction Patents in Column 1 (0.033, p<0.01), it is notstatistically significant in Column 2 (0.001, p=0.924). To interpret this effect, we can compare the AME of
EPI across the two groups. For MNEs with high PR-capabilities, a 1-unit increase in EPI (a relatively
modest increase in context of the overall sample range of 44.3) increases the likelihood of country entry
by roughly 0.09 percentage point. Compared to the overall sample mean likelihood of entry of 3.09
percent, this would represent a 2.79 percent increase in the likelihood of entry. These results are consistent
with the positive moderating effect of PR-capabilities on the relationship between EPI and the likelihoodof country entry reported in Table 2. By contrast, the same 1-unit increase in EPI has essentially no effecton the likelihood of country entry for MNEs with low PR-capabilities. These results lend additional
support to Hypothesis 2.
Columns 3 and 4 of Table 3 report results for firms with high and low levels of multinationality.
According to Hypothesis 3, the effect of EPI should be more positive (less negative) in the former than in21

the latter. However, coefficient estimates for EPI are nearly identical in both columns and, in any event,not statistically significant in either case. These results fail to provide additional support for Hypothesis 3
and suggest that the support for the positive moderating effects of firm multinationality detailed above
need to be interpreted cautiously.
Columns 5-8 of Table 3 report results for four sample subgroups based on levels of both Pollution
Reduction Patents and Country Scope. Column 5 reports results for firms above sample mean levels of bothmeasures. The coefficient estimate for EPI is positive and significant for firms with high PR-capabilities
and high multinationality (0.040 p<0.01). The AME of a 1-unit increase in EPI is a 0.11 percentage point
increase in the likelihood of country entry, an increase of 3.58 percent as compared to the sample mean.
Columns 6-8 report results for the high PR-capabilities/low multinationality, low PR-capabilities/highmultinationality and low PR-capabilities/low multinationality, subsamples respectively. Coefficientestimates for EPI are in all cases smaller in magnitude than the estimate reported in Column 5 and, in any
event, not statistically significant for any of the remaining subgroups. These results indicate that thepositive moderating effect of PR-capabilities on the relationship between environmental regulatory
stringency and the likelihood of country entry relationship is strongest for, and, indeed, only significant
with respect to, high multinationality firms, providing additional support for Hypothesis 4.
A second alternative estimation strategy addresses the fact that among the 17,283 sample
observations (over 357 firm-expansion years) in the sample, there are only 534 positive outcomes(instances of new foreign subsidiary establishment). To address the potential for small-sample bias inmaximum likelihood logit estimation, we conduct a supplementary analysis using penalized maximum
likelihood estimation. The coefficients on the terms representing the interaction between EPI and Pollution
Reduction Patents and that between EPI and Country Scope are positive and statistically significant in Column
1 of Table 4 in line with Hypotheses 2 and 3, respectively. The interaction between EPI and Pollution
Reduction Patents is significant for sub-sample of high-multinationality MNEs (Column 2) but not lowmultinationality MNEs (Column 3), again consistent with Hypothesis 4.
Our sample contains only firm-years for which firms elected to establish a new foreign
manufacturing subsidiary. However, to the extent that the decision to engage in international expansion ina given year may be influenced by firm characteristics, such as global footprint or its technologicalinitiatives to develop pollution reduction technologies, results reported in Table 2 may suffer from sample
selection bias. To address this possibility, we reestimate the main specification using a maximumlikelihood probit model that accounts for sample selection. We include all firm-level RHS variables, a set

22

of firm-dummies and a set of year dummies in the selection equation, relying on the nonlinear functional
form for identification. Results for the outcome equation are reported in Columns 4-6 of Table 4. Results,
reported in Columns 4-6 of Table 4 are again fully consistent with those reported in Columns 3-5 of Table
2.
In addition to the above alternative estimation strategies we also estimated several alternativemodel specifications. While we control for several country- and firm-level factors that may influenceinternational expansion decisions, it is possible that country- or firm-level influences we are unable tomeasure may be salient to our analysis. We therefore reestimate the main specification and the high- andlow-multinational sub-sample estimations in three ways: first, including a set of dummy variables for the
49 countries in the sample and, second, including a set of firm dummy variables for the 124 sample firms
and, finally, including a set of firm-year dummies for all 357 firm-expansion years. Results for all nineestimations are fully consistent with the respective estimations reported in Columns 3-5 of Table 2.4
Another modification replaces the environmental regulatory stringency measure based on a positive
indication of the quality of a country’s environmental performance (EPI), with a negative measure based on
the extent of pollution. Specifically we divide the total amount of carbon dioxide (CO2) emissions frommanufacturing (in metric tons) by the country’s total value added in the manufacturing sector (in constant
US dollars). We then log this value to account for the increasing difficulty of reducing CO2 emissions. This
negative approach to regulatory stringency measurement is similar to that used in prior management
studies into the role of environmental regulation on FDI (Madsen, 2009). Results are unchanged fromthose reported in Table 2. To address the concern that patent counts provide an inaccurate measure of thevalue of firm resources, we replace our four-year patent count measure with a four-year count of thenumber of forward citations to the patent (Hall, Jaffe, & Trajtenberg, 2005). Again, results align with thosereported in Table 2.
Finally, we address the possibility of auto-correlation in expansion decisions that is not fully
controlled for by controlling for the number of firm subsidiaries in a host. We reestimate the main
specifications using a restricted sample where countries hosting any firm subsidiaries in a given firmexpansion year are removed from the firm-expansion year choice set. Results are again fully consistent
with those reported in Table 2.

DISCUSSION AND CONCLUSION
4These and all other unreported results are available from the authors

23

In this study we set out to better understand how environmental regulations influence firm international
expansion decisions. Building on Teece’s (2014) dynamic capabilities-based theory of the multinational
enterprise we argued that while the costs and constraints imposed by stronger national environmental
regulations would, on balance, tend to decrease the attractiveness of a potential host country for
expansion of manufacturing operations, this effect would be weaker for firms possessing uniquecapabilities for pollution reduction. At the same time, experience with establishing new foreignsubsidiaries and arbitrage advantages associated with a larger global footprint would also mitigate theentry-deterring effect of stronger environmental regulations. Finally, because more multinational firms
would have greater incentives and skills for modifying capabilities to work in new host-country
environments, the positive moderating effect of PR-capabilities would be strengthened yet further forhigh multinationality firms.
We tested our arguments using data on 523 instances of international manufacturing expansion
into 49 potential host countries by 124 Japanese chemical industry firms between 2001 and 2010
confirmed our findings. By using firm pollution reduction patents to measure PR-capabilities, ourmethodological approach offered an advance on prior research which has relied on less objective data that
may not effectively distinguish between general and firm-specific advantages. Empirical tests, provided
both statistically significant and practically meaningful support for our arguments.
These findings build on the findings of recent studies that have drawn attention to theimportance of understanding firm heterogeneity when assessing the impact of environmental regulation(Albrizio et al., 2014; Madsen, 2009). While our results confirmed the findings common to much priorresearch that stronger environmental regulations do not have an overall negative impact on host country
investment, we also found that the effects are, in fact, meaningful when firm heterogeneity is taken into
account, with some evidence that both camps—those arguing that the influence is detrimental and thosethat it is beneficial—being correct. Although we did find some indication that firms with low levels ofcapabilities for reducing pollution do seem to be discouraged from entering markets with more stringent
environmental regulation, the effect is almost disappears in firms with PR-capabilities. At the same time,
we found that stronger regulations work to increase host-country attractiveness for firms whose capabilities
position them to benefit from stronger regulations.
Our study makes an important contribution to prior research highlighting the importance of
paying attention to the multinational character of MNEs and considering the impact the aggregate global
footprint can have on how and where firms locate activities (Madsen, 2009; Surroca et al., 2010). Although24capabilities are important, the potential and incentives to design environmental technologies to suit only
local environments may lead to such advantages becoming stranded in individual locales. Firms with moreglobal operations have the incentives and experience to ensure that such capabilities are exploited more
fully—an important societal benefit in light of the potential to increase environmental as well as economic
well-being. The source of such incentives may be overlooked if analyses rely solely on measures of dyadic
distance between home- and host-countries.
Results of our study also hold implications for managers, who can obtain a better perspective on
where competition may originate in response to environmental regulatory changes in a country where they
conduct business. It also suggests the importance of being open minded to the possibilities of stricter
regulation providing profitable opportunities as well as potential performance challenges. Such thinking
will also be of relevance to policy makers concerned about the potential consequences of strengthening
their environmental regulatory regimes.
The implications of our results for policy makers are particularly salient when considering thedesire among government officials to use regulation to enhance national competitiveness. Building on thework of Porter and Van der Linde (1995) scholars have argued that stronger national regulation act tospur domestic firms to innovate, in turn developing capabilities placing them ahead of foreign rivals
lacking such institutional incentives to improve environmental performance. However, the results here
highlight the potential for such regulations to attract stronger foreign incumbents. Accordingly, dependingon the level of regulatory stringency, the capabilities of domestic firms vis-à-vis foreign rivals and theextent to which increased foreign competition may act as an incentive or disincentive for environmental
innovation, the outcome of stronger regulations may have the opposite effect of the hoped for effect. This
problem is likely to be especially acute in courtiers with lower environmental stringency seeking tostrengthen their environmental regulatory regimes. Stronger regulations may attract stronger foreign rivals,
hurting domestic industry. However, as Dowell and colleagues (2000) note, intentionally maintaining weakregulations may end up attracting poor quality and less competitive firms.

Limitations and future directions
Although our results were robust to several reasonable changes in equation terms, sampling andestimation strategy, there were of course limitations to our analysis. Perhaps most apparent is the need torely on an indirect measure of environmental regulation. The inherent challenges of developing a timevarying measure of environmental regulation that is comparable across a large number of countries have25

forced the reliance on such proxy measures. Recently, Albrizio and colleagues at the OECD (2014), havemade important efforts to address this problem, developing a measure of environmental policy stringency.
Unfortunately, their measure only covers 24 OECD countries, less than half of those in our sample,
resulting in a substantial loss of variation in our main independent variable and a loss of nearly 2/3 of
instances of international manufacturing expansion that prohibited its use for our study. Although therelatively high bivariate correlation of roughly 0.60 with the EPI values for the same 24 countries suggests
we are picking up much of the same factors, future research would undoubtedly benefit from the use of
more direct measures.
The manner in which firm multinationality influences how firms choose to deploy existing PRcapabilities suggests a natural follow-up question. Namely, how does such multinationality influence thedevelopment of pollution reduction capabilities. Berrone and colleagues (2013) found that differences inregulation across US states influenced the development of PR-capabilities. Future research might build on
their findings by studying how the global footprint of an MNE, which is likely to have both substantiallygreater variation in regulatory stringency and more opportunities for institutional arbitrage (Surroca et al.,2010) than jurisdictions within a single country.
When assessing the impact of environmental regulation on business activity, the assumptions are
all too often approached from a negative perspective. By contrast, this study demonstrates that stronger
regulations actually encourage market entry by the most environmentally capable firms. This evidence runs
against a common perception that MNEs are responsible for worsening global environmental
degradation. Sharfman and colleagues (2004), in laying a convincing case for why MNEs will often havesuperior environmental performance, note that this perception as the MNE as vehicle for environmental
destruction persists. These findings provide further evidence of the careful need to assess the positive role
MNEs may play in diffusing state-of-the-art environmental technologies around the globe.

26

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29

TABLES AND FIGURES
Table 1. Descriptive statistics and pair-wise correlations

1. GDP per capita
2. GDP
3. GDP Growth
4. Geographic Distance
5. Government Effectiveness6. FDI
7. Number Country Subsidiaries
8. Firm Sales
9. Firm R&D Intensity
10. Country Scope
11. Pollution Reduction Patents
12. Environmental Performance Index

Mean
S.D.
Min
Max
1
2
3
4
5
6
7
8
9
10 11
20539.99 18206.15 361.97 87772.69 788.92 1864.02
8.84 13682.00 0.23
3.52
3.46
-8.86
18.29 -0.33 -0.09 8581.02 3201.42 1156.67 18549.61 0.14 0.11 -0.25 0.81
0.92
-1.11
2.43
0.83 0.19 -0.31 0.07 23.53
52.92-29.68734.01 0.26 0.58 -0.03 0.06 0.23 0.38
1.30
0.00
41.00 0.00 0.39 0.10 -0.17 0.05 0.28 23.23
24.99
0.42
124.62 0.00 0.00 0.02 0.00 0.00 0.03 0.17 0.05
0.05
0.00
0.34
0.01 0.00 -0.03 0.00 0.00 0.04 0.00 0.00 7.05
4.60
1.00
21.00 0.01 0.00 0.00 0.00 0.00 0.02 0.24 0.59 -0.11 5.37
9.96
0.00
75.00 0.00 0.00 -0.04 0.00 0.00 0.01 0.08 0.33 -0.05 0.27 56.01
9.42
33.66
77.99 0.66 0.06 -0.36 0.17 0.63 0.12 -0.04 0.01 0.02 0.01 0.01

30

Table 2. Core logistic regression results

GDP per capita
GDP
GDP GrowthGeographic Distance
Government Effectiveness
FDI
Number Country Subsidiaries
Firm Sales
Firm R&D Intensity
Pollution Reduction Patents
Country Scope
Environmental Performance Index

1
Controls

2
Main Effects

3
Interaction:
PR Pats

4
Interaction:
Country
Scope-0.000***(0.000)0.000***(0.000)0.102***(0.021)-0.000***(0.000)0.688***(0.133)0.004***(0.001)0.132***(0.023)0.006*(0.003)-0.816(0.797)-0.000***(0.000)0.000***(0.000)0.111***(0.024)-0.000***(0.000)0.635***(0.161)0.004***(0.001)0.132***(0.023)0.006*(0.003)-0.836(0.804)-0.002(0.009)-0.004(0.013)0.009(0.010)-0.000***(0.000)0.000***(0.000)0.113***(0.023)-0.000***(0.000)0.643***(0.161)0.004***(0.001)0.135***(0.024)0.006*(0.003)-0.89(0.810)-0.103***(0.019)-0.005(0.013)-0.001(0.011)0.002***(0.000)-0.000***(0.000)0.000***(0.000)0.112***(0.024)-0.000***(0.000)0.629***(0.159)0.004***(0.001)0.141***(0.022)0.006*(0.003)-0.812(0.802)-0.002(0.009)-0.223**(0.069)-0.020†(0.012)-0.005(0.013)

EPI x Pollution Reduction Patents
EPI x Country Scope
Constant-2.989***(0.300)-3.522***(0.714)-3.013***(0.715)0.004**(0.001)-1.973**(0.756)

Year Dummies
Firm Expansion Years
Observations
Robust standard errors in parentheses*** p<0.001, ** p<0.01, * p<0.05, † p<0.1

Yes
357
17,283Yes
357
17,283Yes
357
17,283Yes
357
17,283

5
Interaction:
PR Pats &Country
Scope-0.000***(0.000)0.000***(0.000)0.113***(0.024)-0.000***(0.000)0.638***(0.160)0.004***(0.001)0.140***(0.023)0.006*(0.003)-0.861(0.810)-0.085***(0.020)-0.174*(0.078)-0.022†(0.012)0.002***(0.000)0.003*(0.002)-1.905*(0.760)Yes
357
17,283

6
7
Interaction: Interaction:
PR Pats (high PR Pats (lowcountry
country
scope)
scope)-0.000**-0.000***(0.000)(0.000)0.000***
0.000***(0.000)(0.000)0.092**
0.113**(0.029)(0.040)-0.000***-0.000***(0.000)(0.000)0.419*
1.037***(0.195)(0.242)0.004***
0.003(0.001)(0.002)0.174***
0.215***(0.026)(0.053)0.005†
0.007(0.002)(0.007)-0.975-1.366(1.252)(1.070)-0.086***0.018(0.018)(0.116)-0.176-0.584(0.166)(0.382)-0.028-0.027(0.036)(0.028)0.001***-0.000(0.000)(0.002)0.002
0.011(0.003)(0.007)-1.088-1.351(2.010)(1.522)
Yes
174
8,433

Yes
183
8850

31

Table 3. Alternative estimation of core logistic regression results employing sub-samples created by splitting at meaningful levels of independent variables

GDP per capita
GDP
GDP GrowthGeographic Distance
Government Effectiveness
FDI
Number Country Subsidiaries
Firm Sales
Firm R&D Intensity
Country Scope
Pollution Reduction Patents
Environmental Performance Index
Constant
EPI AMEEPI AME/Mean Entry

1
High Patents

2
Low Patents

3High MN

4
Low MN-0.000**(0.000)0.000***(0.000)0.105*(0.042)-0.000***(0.000)0.381*(0.160)0.005***(0.001)0.120***(0.023)0.007(0.008)13.299***(3.984)-0.011(0.033)-0.013(0.010)0.033**(0.011)-5.199***(0.807)-0.000***(0.000)0.000***(0.000)0.115***(0.028)-0.000***(0.000)0.739***(0.215)0.004***(0.001)0.146***(0.041)0.006*(0.003)-1.670*(0.784)-0.001(0.012)0.002(0.025)0.001(0.013)-3.090***(0.843)-0.000**(0.000)0.000***(0.000)0.090**(0.029)-0.000***(0.000)0.414*(0.194)0.004***(0.001)0.170***(0.026)0.005†(0.002)-0.875(1.231)-0.045*(0.020)-0.004(0.008)0.008(0.014)-3.046**(0.951)-0.000***(0.000)0.000***(0.000)0.109**(0.040)-0.000***(0.000)1.046***(0.244)0.003(0.002)0.215***(0.053)0.007(0.008)-1.392(1.061)-0.023(0.029)0.001(0.011)0.009(0.016)-3.135**(1.002)

0.09%
2.79%

0.00%
0.10%

0.02%
0.77%

0.02%
0.57%

0.11%
3.58%

Yes
174
8,433

Yes
183
8,850

Yes
55
2,671

Year Dummies
Yes
Yes
Firm Expansion Years
88
269
Observations
4,267
13,016
Robust standard errors in parentheses. *** p<0.001, ** p<0.01, * p<0.05, † p<0.1

5
6High Patents / High Patents /High MN
Low MN-0.000*-0.000†(0.000)(0.000)0.000***
0.000**(0.000)(0.000)0.134**
0.051(0.051)(0.088)-0.000**-0.000***(0.000)(0.000)0.388†
0.608(0.215)(0.428)0.005***
0.002(0.001)(0.003)0.118***
0.263**(0.021)(0.093)0.001
0.041***(0.010)(0.010)18.831***
4.839(3.601)(5.866)-0.0440.042(0.038)(0.081)-0.013-0.048**(0.011)(0.016)0.040**
0.017(0.014)(0.026)-5.541***-4.146*(0.907)(2.036)

7
Low Patents /High MN-0.000†(0.000)0.000***(0.000)0.069†(0.036)-0.000***(0.000)0.41(0.298)0.002***(0.001)0.211***(0.057)0.004(0.003)-1.966†(1.179)-0.053**(0.018)-0.041(0.044)-0.01(0.019)-1.626(1.377)

8
Low Patents /Low MN-0.000***(0.000)0.000***(0.000)0.122**(0.044)-0.000***(0.000)1.088***(0.253)0.004†(0.002)0.216***(0.064)0.004(0.006)-1.323(1.087)-0.041†(0.023)0.055*(0.025)0.013(0.016)-3.717***(1.050)

0.04%
1.25%

-0.03%-0.98%

0.02%
0.79%

Yes
33
1,596

Yes
98
4,751

Yes
171
8,265

32

Table 4. Robustness Analyses

GDP per capita
GDP
GDP GrowthGeographic Distance
Government Effectiveness
FDI
Number Country Subsidiaries
Firm Sales
Firm R&D Intensity
Country Scope
Pollution Reduction Patents
Environmental Performance
Index

1
Penalized MLE

2Penalized MLE

3Penalized MLE

Interaction: PR Pats &Country Scope-0.000***(0.000)0.000***(0.000)0.112***(0.023)-0.000***(0.000)0.633***(0.141)0.004***(0.001)0.138***(0.024)0.006**(0.002)-0.808(1.100)-0.174*(0.069)-0.085**(0.030)-0.022†

Interaction: PR Pats
(high country scope)-0.000**(0.000)0.000***(0.000)0.091**(0.029)-0.000***(0.000)0.412*(0.172)0.004***(0.001)0.171***(0.029)0.005*(0.002)-0.863(1.338)-0.177(0.129)-0.086**(0.031)-0.029(0.013)(0.028)0.002**
0.001**(0.001)(0.001)
EPI x Country Scope
0.003*
0.002(0.001)(0.002)
Constant-1.879*-1.044(0.779)(1.561)
Year Dummies
Yes
Yes
Firm Expansion Years
357
174
Observations
17283
8433
Robust standard errors in parentheses *** p<0.001, ** p<0.01, * p<0.05, † p<0.1
EPI x Pollution Reduction Patents

Interaction: PR Pats
(low country scope)-0.000***(0.000)0.000***(0.000)0.110**(0.041)-0.000***(0.000)1.027***(0.251)0.003†(0.002)0.208***(0.061)0.008(0.010)-1.283(1.984)-0.578†(0.321)
0.016(0.117)-0.0274
Sample Selection ML
ProbitInteraction: Country
Scope-0.000***(0.000)0.000***(0.000)0.054***(0.010)-0.000***(0.000)0.255***(0.065)0.002***(0.000)0.089***(0.014)0.001(0.001)-0.053(0.425)-0.076*(0.031)-0.038***(0.009)-0.009†5
Sample Selection ML
ProbitInteraction: PR Pats
(high country scope)-0.000**(0.000)0.000***(0.000)0.045***(0.012)-0.000***(0.000)0.164*(0.080)0.002***(0.000)0.104***(0.015)0.001(0.001)-0.110(0.616)-0.086(0.071)-0.039***(0.009)-0.014

6
Sample Selection ML
ProbitInteraction: PR Pats
(low country scope)-0.000***(0.000)0.000***(0.000)0.055**(0.018)-0.000***(0.000)0.408***(0.097)0.002***(0.001)0.146***(0.029)0.003(0.003)-0.822(0.523)-0.207(0.163)0.001(0.049)-0.008(0.024)0.000(0.002)0.011†(0.006)-1.288(1.427)
Yes
183
8850

(0.005)0.001***(0.000)0.001*(0.001)-0.862*(0.354)
Yes
357
17283

(0.016)0.001***(0.000)0.001(0.001)-0.577(0.920)
Yes
174
8433

(0.012)0.000(0.001)
0.004(0.003)-0.734(0.694)
Yes
183
8850

33

Figure 1. Effect of stronger environmental regulation on likelihood of country entry for firms with high and low
levels of pollution reduction capabilities

Figure 2. Effect of stronger environmental regulation on likelihood of country entry for firms with high and low
levels of multinationality

34

Figure 3a. Effect of stronger environmental regulation on likelihood of country entry in high multinationality
firms with high versus low levels of pollution reduction patents

Figure 3b. Effect of stronger environmental regulation on likelihood of country entry in low multinationality
firms with high versus low levels of pollution reduction patents

35