Are foreign investors attracted to weak environmental regulations? Evaluating the evidence from China

ARE FOREIGN INVESTORS ATTRACTED TO WEAK ENVIRONMENTAL REGULATIONS? Evaluating the Evidence from China* Judith M. Dean** U.S. International Trade Commission Judith.Dean@usitc.gov Mary E. Lovely Department of Economics Syracuse University melovely@maxwell.syr.edu Hua Wang Development Research Group The World Bank hwang1@worldbank.org World Bank Policy Research Working Paper 3505, February 2005 The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org. *This paper is a revision of USITC Working Paper 2004-01-B. Partial funding for this research was provided by the World Bank. We would like to thank Xuepeng Liu for compiling the EJV data used in this study. Thanks are also due to Cory Davidson for research assistance and K.C. Fung, Meredith Crowley, Keith Head, Jan Ondrich, John List and Stuart Rosenthal for suggestions regarding data and estimation. We are also grateful for helpful comments from seminar participants at the American Economic Association meetings, Econometric Society Summer meetings, Midwest International Economics meetings, Northeast Universities Development Conference, Williams College, University of Minnesota, Cornell University, University of Maryland, UC Santa Barbara UNCTEE Workshop, and the World Bank Trade Seminar. **The views in this paper do not represent in any way the views of the U.S. International Trade Commission or any of its individual Commissioners.  ARE FOREIGN INVESTORS ATTRACTED TO WEAK ENVIRONMENTAL REGULATIONS? Evaluating the Evidence from China Judith M. Dean, U.S. International Trade Commission, Judith.Dean@usitc.gov Mary E. Lovely, Department of Economics, Syracuse University, melovely@maxwell.syr.edu Hua Wang, Development Research Group, The World Bank, hwang1@worldbank.org Abstract One of the most contentious debates today is whether pollution-intensive industries from rich countries relocate to poor countries with weaker environmental standards, turning them into "pollution havens." Empirical studies to date show little evidence to support the pollution haven hypothesis, but suffer potentially from omitted variable bias, specification, and measurement errors. This paper estimates the strength of pollution-haven behavior by examining the location choices of equity joint venture (EJV) projects in China. We derive a location choice model from a theoretical framework that incorporates the firm's production and abatement decision, agglomeration and factor abundance. We estimate conditional logit and nested logit models using new data sets containing information on a sample of EJV projects, effective environmental levies on water pollution, and estimates of Chinese pollution-intensity for 3-digit ISIC industries. Results from 2,886 manufacturing joint venture projects during 1993-96 show EJVs from all source countries go into provinces with high concentrations of foreign investment, relatively abundant stocks of skilled workers, concentrations of potential local suppliers, special incentives, and less state ownership. Environmental stringency does affect location choice, but not as expected. Low environmental levies are a significant attraction only for joint ventures in highly-polluting industries with partners from Hong Kong, Macao, and Taiwan. In contrast, joint ventures with partners from OECD sources are not attracted by low environmental levies, regardless of the pollution intensity of the industry. We discuss the likely role of technological differences in explaining these results.  ARE FOREIGN INVESTORS ATTRACTED TO WEAK ENVIRONMENTAL REGULATIONS? Evaluating the Evidence from China I. Introduction One of the most contentious issues debated today is whether inter-country differences in environmental regulations are turning poor countries into "pollution havens." The main argument is that stringent environmental standards in industrial countries drive firms to close plants at home and establish them instead in developing countries, where standards are relatively weaker. Since more pollution- intensive industries will have a larger incentive to move, a haven of such industries will build up in poor countries. A corollary is that developing countries may purposely undervalue environmental damage, in order to attract more foreign direct investment (FDI). This, in turn, could generate a "race to the bottom" with all countries lowering environmental standards in order to attract and retain investment. This study estimates the strength of pollution-haven-seeking behavior by foreign firms investing in China. We derive and estimate a model of FDI location choice in the presence of inter-provincial differences in environmental stringency. Our theoretical framework is built upon Copeland and Taylor's (2003) firm production and abatement decision model, amended to include agglomeration. From this model, we derive an econometric model which is estimated using two new and unique datasets. The first contains information on 2,886 manufacturing foreign equity joint venture (EJV) projects in China during 1993-96, including provincial location, industry classification, and whether the foreign partner is based in Macao, Taiwan or Hong Kong or in a non-ethnic-Chinese industrial (primarily OECD) economy. The second contains information from the annual Chinese environmental and economic censuses. The environmental data allow us to construct effective water pollution levy rates, by province and year, as a measure of provincial environmental stringency. They also include Chinese water-pollution intensities at the 3 digit ISIC industry level, as a measure of industrial pollution intensity. The economic data allow us to construct a rich set of provincial characteristics, including agglomeration, potential local suppliers, and labor skill shares. 1  Early empirical studies suggested that environmental stringency had no discernible effect on location choice.1 Though FDI in pollution-intensive industries did occur, there was little evidence that it had been influenced by differing pollution abatement costs, or had flowed faster into developing countries relative to industrial countries.2 Recent econometric studies have adopted one of three approaches to investigate whether FDI flows have resulted in pollution havens: inter-state plant location choice; inter- industry FDI flows within a country; and inter-country FDI location choice. Results from these studies are mixed. In his review of four studies that use the first approach to study US plant location choice, Levinson (1996a) finds little evidence that inter-state differences in environmental regulations affect the location of plants in the US. Levinson (1996b) finds only one of six environmental stringency indicators has a significant impact on the location of new branch plants across US states, and its impact is small. However, controlling for unobserved state characteristics and adjusting their abatement cost measure for inter-state differences in industrial composition, Keller and Levinson (2003) find evidence that pollution costs have a moderate deterrent effect on foreign investment into US states. Eskeland and Harrison (2003) adopt the second approach, examining the pattern of foreign investment across industries within Mexico, Venezuela, Morocco, and Cote d'Ivoire. They find that abatement costs are not significant determinants of the distribution of foreign investment among manufacturing industries within a country. In addition, the relationship between FDI and pollution- intensity depends on the pollutant.3 Within an industry, foreign ownership is actually significantly and robustly associated with lower energy use (a proxy for lower pollution intensity). Smarzynska and Wei (2001) adopt the third approach, evaluating the foreign investment choices of multinational firms locating across Eastern Europe and the former Soviet Union. They emphasize the 1Reviews of the literature can be found in Dean (1992, 2001) and Copeland and Taylor (2004). 2Leonard (1988) found some evidence that governments used lenient environmental regulations to attract FDI in the 1970s, but he also found that incentives were not substantial enough to offset other determinants of location choice, particularly labor productivity, infrastructure and stability. 3While there is some evidence of a positive relation between FDI share and air pollution-intensity, there is a negative relation between FDI share and both water pollution and toxic-release intensity. 2  problem of omitted variable bias in previous work: corruption may deter FDI, but may be correlated with laxity of environmental controls. The authors control for the role of corruption, but find little support for the hypothesis that lower environmental standards attract investment, or for the hypothesis that lower standards are more attractive to pollution-intensive FDI. However, these results are sensitive to the measures chosen to proxy environmental stringency and pollution intensity.4 Our choice of theory, data, and method attempt to address five problems arising in the recent literature. First, as noted by Antweiler, Copeland, and Taylor (2001) most studies of openness and the environment have been loosely motivated by the theoretical literature on pollution emissions and abatement, potentially giving rise to specification error. In response, we use the Copeland and Taylor (2003) emission and abatement framework to derive a reduced form estimating equation. Second, the absence of relative factor abundance and agglomeration from many of these studies--critical determinants of FDI in China--may cause omitted variable bias. We draw on Zhang and Markusen (1999), Cheng and Kwan (2000), and Head and Ries (1996) to incorporate these features into the theoretical framework and resulting estimating equation. Third, as Smarzynska and Wei (2001) emphasize, many studies have had to rely on highly aggregated FDI data, and very broad proxies for environmental stringency or pollution intensity, potentially causing measurement error. In contrast, we have created a panel of FDI projects, allowing us to control for the pollution intensity of the activity and for the source of the foreign funding. The availability of provincial effective water pollution levy rates allows us to specify the stringency of regulations using a price-based policy instrument at the level of administration. We thereby avoid the use of national proxies (e.g. participation in environmental treaties), which may bear scant relation to actual practices, or average abatement costs, which are influenced by local production technologies, factor prices, and industry concentrations. 4 Measuring stringency and pollution-intensity by participation in international treaties and an emissions index, the authors find dirty projects more likely to locate in areas with low stringency. However, this result is not robust to alternative measures such as actual standards and an abatement index. 3  Fourth, Keller and Levinson (2002) note that unobservable features of a location, such as natural resources or sector-specific tax subsidies, may be correlated with both regulatory stringency and investment and lead to omitted variable bias. The direction of the bias cannot be predicted, but it may account for the failure of previous studies to find a negative relationship between environmental stringency and investment inflows. We use a number of methods to control for observed and unobserved provincial characteristics: a rich set of control variables; a nested logit procedure to allow for similarities among provinces in the same region; and robustness tests incorporating regional and provincial fixed effects. Finally, Ederington, Levinson, and Minier (2003), argue that certain features of an industry allow it to respond to greater stringency more dramatically than others. We expect that firms will respond more strongly to inter-provincial differences in pollution taxes, when these taxes represent a significant cost. Moreover, we expect that these differences in sensitivity will occur both between and within industries, if abatement efficiency varies across firms. Accordingly, we estimate the deterrent effect of regulatory stringency by the pollution intensity of the industry and by the source of the foreign investment. Results from our sample of joint venture projects suggest an important linkage between technology and pollution-haven behavior. For the sample of projects from OECD source countries, we find no evidence of pollution-haven-seeking behavior by investors, regardless of the pollution intensity of the industry. In contrast, projects in highly polluting industries from Chinese sources (Hong Kong, Macao, and Taiwan) are significantly deterred by pollution taxes. One possible explanation for this finding, supported by other studies, is that investment from advanced countries embodies newer technology, implying lower costs for abatement and a higher probability that a given plant will meet standards and avoid taxation. Our evidence provides some support for the idea that firms from developing countries may be attracted by weak environmental regulations. Thus, the attraction may be contingent on lack of access to advanced technology. In the next section, we describe FDI flows into China and China's pollution levy system. In the third section, we present a model of location choice, incorporating the firm's endogenous response to 4  pollution taxes, local factor prices, and local market conditions. We specify a profit function and we derive a proposition that forms the basis for our empirical work. In the fourth section, we describe our econometric approach and describe the data. Next, we present the results of the conditional and nested multinomial logit analysis. Finally, we interpret our results and suggest some likely explanations for the differences we find in firm behavior. 5  II. FDI Flows and Environmental Stringency in China In many ways, China is an ideal site for a study of pollution-haven behavior. China has been the largest recipient of FDI in the developing world since 1990 (Broadman and Sun, 1997; Henley, et al., 1999). During the period we will examine, 1993-96, FDI inflows surged dramatically across most of the country. This surge followed the 1992 liberalization in trade and foreign exchange regimes, which included some new favorable terms for FDI (Shuguang, et al., 1998). Yet the distribution of investment within China is highly uneven, raising obvious questions about the factors that attract capital inflows. Henley et al. report that 80% of cumulative FDI inflows have located in one of China's ten eastern provinces. This distribution clearly reflects the influence of special incentive programs,5 and the policy of gradual opening pursued before the new guidelines issued in 1992.6 However, as Huang (2003) notes, in comparison to investment flows to other countries at similar stages of development, the inflows to China were remarkable for their wide distribution among industries and provinces. Of the 28 manufacturing industries included in the 1995 Industrial Census, none had received more than 10 percent of total FDI.7 Moreover, while the interior regions of China received only about 13 % of cumulative FDI flows between 5In 1979, the Chinese national government began accepting foreign investment and in 1980 established four special economic zones (SEZs) within Guangdong and Fujian provinces. In 1984, fourteen coastal cities received special incentive programs for FDI. Additional zones have been established since to encourage development of interior locations. As Head and Ries (1996) note, however, after the issue in 1986 of a new legal framework governing foreign investment, certain incentives were available anywhere in China to foreign enterprises that produced for export or introduced advanced technology. 6See Tseng and Zebregs (2002). In 1992, the Chinese government significantly liberalized its FDI regime. As Lardy (1994) reports, it removed a number of sectoral and regional restrictions on FDI and decentralized approval from the central government to local governments. New rules introduced in 1995 grouped investment into three categories. "Encouraged" investment includes new agricultural technology; construction of energy, communications, and raw materials projects for local industry; projects that enhance exports; projects that use renewable resources or involve new technology or equipment for pollution control or prevention; and investments developing the central and western parts of China. "Restricted" investment includes projects already developed, where the technology has already been imported and capacity can meet demand; projects in industries where the state is experimenting with foreign investment while a state monopoly still exists; exploration and/or extraction of minerals; and projects in industries requiring central planning. "Prohibited" investment includes dangerous, polluting, or wasteful processes. See Henley, et al. (1999). 7See Huang (2003), Table 1.4. 6  1992 and 1998, its total value was $31.5 billion, exceeding the entire FDI inflow to India during the same period.8 China also offers the opportunity to study the response of investors to the Chinese water pollution levy system--the broadest application of a price-based mechanism in the developing world (see Appendix A). We know of no previous study that estimates the strength of environmental regulation in shaping foreign investment flows within China.9 The Chinese water discharge levy depends upon both concentration and volume. For each plant, a pollutant-specific discharge factor is calculated, based on both total waste water discharge and the degree to which pollutant concentration exceeds the standard for each water pollutant. Concentration standards are set jointly at the national and provincial level, and vary across provinces and across pollutants. If a pollutant concentration is more than (less than or equal to) the standard, a charge (no charge) is applied.10 These charges, which are set at the national level, vary by pollutant but not by industry. For each plant, the potential levy is calculated for each pollutant. The final levy imposed on the plant is the greatest of these potential levies. Another important feature of FDI in China which is relevant for testing the pollution haven hypothesis is differences across source countries. According to Henley, et al. (1999) between 1985 and 1996, 66.4% of FDI into China came from Hong Kong, Macao, and Taiwan. (An unknown proportion of this investment originated in mainland China and found its way back to China in a practice known as `roundtripping.') While dispersed throughout China, FDI from these sources, especially from Hong Kong, concentrated in the southern coastal provinces. Much of this investment involved labor-intensive processing of imported inputs for re-export. During the same time period, only 8% of FDI came from the United States and 8% from Japan.11 Investments from Japan and the West tended to be undertaken by 8Figures provided by Huang (2003), page 28. 9Levinson (1996a, 1996b) and Keller and Levinson (2002) perform such studies using US state-level abatement costs. Because state rules and implementation differ, they are able to identify the impact of controls on firm location. Henderson (1996) and Kahn (1997) use county-level variation in compliance with national air quality standards. The US does not rely primarily on a price-based system, however, and it is difficult to relate these measures to actual regulatory instruments. 10Beginning in 1993, a fee was imposed on all wastewater. See appendix A for details. 11No other country provided more than 3% of total FDI into China during 1985-96. See Henley, et al., Table 7. 7  transnational corporations that produced goods for the Chinese market.12 Investors based in Macao, Hong Kong, or Taiwan are likely to have family or business interests in neighboring provinces. These links may be very close, and as Head and Ries (1996) emphasize, an unobserved share of the investment from Chinese sources is `roundtripping' and its location choice decision influenced by the location of mainland connections.13 The fact that Chinese investment is largely for export, while transnational corporations generally target the local market , suggests that the two types of projects may be of substantially different character. Fung, Iizaka, and Parker (2002) find that investment from Japan and the U.S. is sensitive to provincial labor quality, while investment from Hong Kong and Taiwan is, in contrast, not sensitive to labor quality but to labor costs.14 Head and Ries (1996) find evidence that previous foreign investment, high labor productivity, good transportation, and a large pool of local suppliers make a city more attractive to non-Chinese investors, but that low industrial wages have no significant influence. It is also likely that EJVs from high-income countries use cleaner technologies than do Chinese EJVs. Since industrial countries generally have relatively stringent standards compared to Hong Kong, Taiwan, or Macao, they are more likely to develop and use cleaner technologies. Lanjouw and Mody (1996) report that the United States, Japan, and Germany were the most important sources of environmental innovation and diffusion during the 1970s and 1980s and that the share of these innovations related to water pollution control increased dramatically over time, as detailed emissions standards and technology specification became common. In addition, firms from high-standard countries report high costs to installing and maintaining older vintage technology in new plants, even when these plants are located in countries with weaker standards. Survey data on EJVs in China collected and reported by Loren Brandt and Susan Zhu indicate important technological differences among foreign 12While some authors describe investment from ethnic-Chinese economies as smaller scale, Huang (2003) reports that the average size of individual FDI projects from Japan, Korea, the United States, and Thailand are not substantially larger than those from Chinese sources. 13For this reason, Head and Ries (1996) exclude projects with partners from Hong Kong, Macao, and Singapore from their analysis of FDI flows to Chinese cities in 1984-1991. 14Similar results are found in Fung, Iizaka, Lin, and Siu (2002) and Gao (2002), who use more comprehensive measures of labor quality. 8  parents.15 While performance requirements were common among joint ventures initiated during 1987- 1993, Brandt and Zhu report that only about one-third of joint ventures from Hong Kong were required to transfer advanced technology from the parent firm, while about three-fourths of joint ventures from industrial country investors were required to do so.16 This technological difference is even more likely if Chinese EJVs actually represent round-tripping. Thus, it is likely that Chinese and foreign EJVs have access to different pollution control technologies and we investigate separately the strength of each type of investor's attraction to provinces with weak standards. Table 1 shows the percent of national FDI inflows (actually utilized17) locating in high, medium, and low-income provinces, based on income averages throughout the period.18 In 1987, nearly 80% of foreign investment located in provinces with relatively high GDP per capita, while only 8% located in one of the lowest-income provinces. A similarly large gap is found in 1995, with high-income provinces receiving 64% of FDI while the lowest-income provinces only received 9%. A closer look, however, reveals that the rich-province share declines fairly steadily throughout the period. Flows into the low- income group appear stagnant, while the share of FDI flowing to the moderate-income group nearly doubles. The relationship between FDI inflows and two indicators of environmental stringency are also shown in Table 1. Provinces are first grouped by average effective water pollution levy during the period. It is clear that the highest shares of FDI inflows are found in provinces with the most stringent environmental regulations. The differential is quite large, and holds for every year in the period. Provinces are also grouped by average discharge intensity (tons of COD discharge per million yuan 15Our thanks to Susan Zhu for making this information available. 16 Brandt and Zhu (undated) write: For the joint ventures that have investors from Hong Kong, only 35% were required to transfer advanced technology from foreign parent and 5% were required to transfer a patent from foreign parent. For the joint ventures having investors from developed countries, 76% were required to transfer advanced technology and 29% were required to transfer a patent from foreign parent. Only 6% of the firms having partners from Hong Kong were required to manufacture certain components or final products in China, while 42% of the firms with partners from developed countries had this requirement. From this we may infer that the technology flow will be larger for the joint ventures that have foreign parents from developed countries. (p. 7) 17FDI inflow in a given year is not necessarily utilized immediately, since its use requires approval. 18Hainan and Tibet are excluded due to lack of data. 9  output (1990 yuan)) over the period. To the extent that discharge intensity is an indicator of laxity of standards and/or concentration of pollution-intensive industries, it appears that neither of these factors attracts FDI. Most FDI flows to provinces with relatively low discharge intensity. Since per capita income and pollution levies are strongly correlated (Dean, 2002; Wang and Wheeler 2003, 2005), it is not clear from this evidence the extent to which each of these characteristics influences location choice. It is clear that FDI is not flowing to provinces with the least stringent regulations. Over time, however, there is a reduction in the share of FDI going to provinces with high pollution levies (low discharge intensity), and an increase in the share going to the group with moderate pollution levies (moderate discharge intensity). Since provinces show increased levies over time, the trends in Table 1 could indicate that FDI moves in response to stricter environmental regulations. 10  III. Theoretical Model A Model of Production and Emissions Like Smarzynska and Wei (2001) we consider a multinational firm that wants to invest one unit of capital to produce somewhere in a given region.19 We assume that China has been chosen because it is the lowest-cost region in which to produce. Therefore, the decision for the firm is to choose the host province within China that produces the highest profit. We treat foreign firms as price takers with respect to pollution taxes. Local variations in enforcement raise the possibility that firms may negotiate over pollution levies with local authorities. However, as explained in Appendix A, such negotiations occur after production and emissions decisions have been made by the firm, following an inspection by local authorities. We assume, therefore, that at the time that a location decision is made by the firm, the exact levy rate it will be charged is unknown but that the firm has information on the effective rate per unit that provincial regulators have actually charged local firms in the past. As this rate is influenced both by the statutory rate and by enforcement practices, we use this effective rate as the firm's indicator of provincial environmental regulatory stringency. Our treatment of production follows Copeland and Taylor (2003). We consider a firm that jointly produces two outputs, good X and emissions Z, using variable inputs of unskilled labor, skilled labor, and intermediate (locally-provided) services. The capital input is embodied in the original investment and is fixed in the short run. Abatement of emissions is possible, so emission intensity is a choice for the firm. We assume that the firm can allocate an endogenous fraction, , of its inputs to abatement activity. This implies that abatement and production use factors in the same proportion. If = 0 , there is no abatement and, by choice of units, each unit of output generates one unit of pollution. The joint production technology is given by: 19We take the decision to produce abroad, as well as the region in which the project will be located, as made in a prior stage. Zhang and Markusen (1999) consider the firm's choice of producing at home and exporting or producing abroad. 11  X = (1- )F Lx ,Hx ,Ix(s) , ( ) , (1) Z = ( )F Lx ,Hx ,Ix(s) , ( ) where L is unskilled labor, H is skilled labor, and s is a vector of locally provided services. The function Ix(s) aggregates these local service varieties into an intermediate input for the foreign firm. We assume that F is increasing and concave, and0 1,(0) = 1,(1) = 0. To aid our ability to derive an estimating equation, we follow Copeland and Taylor (2003) and assume that the relation between abatement activity and emissions is given by () = (1-)1/ , (2) where 0 1.Using this form, we can eliminate theta and invert the joint production technology to obtain a net production function in which emissions is treated as an input: X = Zx [F(Lx, Hx, Ix(s))](1 . -) (3) If we assume that the production function is generalized Cobb-Douglas, F(Lx, Hx, Ix) = ALbxHx (Ix(s))e, d (4) where b, d, and e are constants, and A is a measure of Hicks neutral technological progress, the net production function becomes X = Zx A (1-) Lx Hx (Ix(s)) , (5) where = b(1-), = d(1-), and = e(1-) . We note that , , , are factor shares and in particular that is the share of pollution taxes in the value of output. Profit maximization implies cost minimization. Let be the emissions tax rate, u the wage for unskilled labor, h the wage for skilled labor, and ps a price index for locally-provided services. Using ~ the net production function, the cost of producing X units in province j is -(1-) 1 1 CX ( ,uj,hj, %sj, X ) = KA p p (6) j j wj hj %j X = KcX(wr )X , j 12  where = + + + <1 and the vector w = ( ,u,h, %s r p ) . To begin, we assume that the firm produces only for export to a third market, so the price of the final good produced by the project, p f , does not vary by province. The maximum profit earned on fixed capital investment in any province j is given by the profit function: Xj(pf ,wr ) = 1- -1- pf 1- 1 1 1 1- . j KcX r (7) (wj) This profit function is multiplicative and, therefore, linear in logs. Using (7), we can explore how an increase in the emissions tax rate changes the maximum profit r that an investor can earn in a given province. The emissions tax rate enters the cost function, cX (w),so using Shepard's lemma and denoting proportionate changes with a "", ^Xj = -1- 1 ZX (pf ,wr ) j j = -1- < 0. ^j (8) 1 cX (wj)X (p f ,wj) r r The maximum profit that can be earned in province j falls in response to a 1 percent increase in the emissions tax. Additionally, this effect is proportional to the share of pollution taxes in total variable costs when the firm chooses inputs optimally. Equation (8) leads to the following proposition. PROPOSITION 1: The effect of a higher pollution levy on potential profits: (a) is larger for industries in which variable costs are a larger relative cost share; (b) is larger for firms within an industry that are less efficient in their ability to abate pollution. PROOF: This proposition follows directly from the properties of the profit function. Part a can be easily proved by comparing two industries that have the same abatement efficiency (the same value for ) but different values for the sum of b, d, and e. The industry with the larger sum has a larger variable cost 13  share (a larger value for ). Statement (a) then follows from equation (8): the effect of a levy increase on potential profits is larger for industries that have higher variable costs relative to total cost. For part b, we note that the efficiency of a firm in abating pollution is governed by the abatement function (2). A less efficient firm has a higher value, but the same factor shares b, d, and e as other firms in the same industry. Therefore, using equation (8), an increase in the pollution tax has a larger effect on the potential profits of the less efficient firm. This proposition provides us with the basis for testable hypotheses about location choice. Part a of the proposition leads to the hypothesis that industries with highly polluting production technology will be more sensitive than low-polluting industries to pollution levy differences across provinces. Part b suggests the hypothesis that, within an industry, firms with less efficient abatement technologies will be more sensitive to differences in levy rates. Foreign Investment and Local Suppliers Previous research by Head and Ries (1996) suggests that firms have higher profits when they locate in areas where other foreign firms have located. We incorporate agglomeration into our model using the derivation in Head and Ries. The function, I(s), aggregates local service varieties, si, into a composite intermediate good. It is assumed to take a constant elasticity of substitution form with the substitution elasticity given by . Positing a standard monopolistic competition framework for the market for local services, Head and Ries assume that all service providers face the same unit cost function, r cS (w). If the number of suppliers is large, each firm faces an iso-elastic demand curve and sets the price Ps = cs(w)/. Given this symmetry, each service provider sets the same price and produces the r same quantity. Moreover, final goods producers use the same amount of each variety, leading to the aggregated service input, I(s) = Ns s where s is the common quantity of each service variety. 1/ We now develop an intermediates price index, which appears in the profit function and which measures the price per effective service unit. Note that the total amount paid by a final-good producer for 14  intermediates is PsNss, while the number of effective units is given by I(s). Dividing the total amount paid by effective units provides the price index, %sp = PsNs ( -1)/ . This price index is decreasing in the number of service providers, which reflects the notion that effective costs may be lowered by an increase in the number of varieties, as well as by a reduction in the price of a representative variety. Head and Ries derive the equilibrium number of local service providers by assuming that they must invest in costly upgrading in order to serve foreign-invested firms. The net profits obtained by an entrant into the intermediates sector depend on the direct costs of upgrading to satisfy foreign quality requirements and on the value of any foregone opportunity. The total cost of upgrading is assumed to vary across potential entrants. Within this context, Head and Ries show that the number of local service firms is a function of local factor prices (because profits fall as costs rise), the final goods price, Pf , and the number of foreign-invested firms producing final goods, N f, (because profits rise with a higher demand for intermediates from final-goods producers), and the number of potential suppliers, Ns (which implies a larger number of local firms that can profitably upgrade).20 Thus, in equilibrium, Ns = (w, P f , N , Ns), r f (9) where the function ( ) is multiplicative. Assuming that intermediates are produced with skilled and unskilled labor in a Cobb-Douglas technology and adopting the Head and Ries assumption that upgrading costs are uniformly distributed among potential entrants, it can be shown that the price index takes the form r r % ps = cs(w) f ( -1)/ f (w,Pf ,N ,Ns) = K2u