Does the Private Sector Help or Hurt the Environment? Evidence from Carbon Dioxide Pollution in Developing Countries

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World Development Vol. 29, No. 5, pp. 827±840, 2001 Ó 2001 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0305-750X/01/$ - see front matter

PII: S0305-750X(01)00008-0

Does the Private Sector Help or Hurt the Environment? Evidence from Carbon Dioxide Pollution in Developing Countries DEBABRATA TALUKDAR School of Management, SUNY at Bu€alo, Bu€alo, NY, USA and CRAIG M. MEISNER * Development Economics Research Group, Infrastructure and Environment, The World Bank, Washington, DC, USA Summary. Ð How does the nature of enterprise ownership a€ect the environment in an economy? Conventional wisdom and theoretical conjectures are split on this important question. In this paper we estimate a reduced-form, random-e€ects model using data from 44 developing countries over nine years (1987±95) to study for any systematic empirical relationship between the relative level of private sector involvement in an economy and the environmental performance of the economy in terms of its emission of industrial carbon dioxide. We control for both observed and unobserved crosscountry heterogeneity along various institutional and structural dimensions such as the scope of ®nancial market, industrial sector composition and level of foreign direct investment. The regression results indicate that the higher the degree of private sector involvement in a developing economy, the lower is its environmental degradation. In addition, its environmental degradation is likely to be further reduced in presence of a well-functioning domestic capital market and through increased participation by developed economies in its private sector development. Ó 2001 Elsevier Science Ltd. All rights reserved. Key words Ð privatization, environment, global warming, carbon dioxide, developing countries

1. INTRODUCTION The last decade has seen a distinct change in opinion regarding the role of state and private enterprises in promoting economic growth. The prevailing view promotes a greater role for the private sector to achieve a more dynamic economic growth (Galal & Shirley, 1994; Lieberman, 1993; World Bank, 1991, 1995a,b). Underlying this view is the belief that resources will be used more productively if they are transferred to the private sector. A well-publicized element of this emphasis on private sector development has been the privatization of existing state-owned enterprises (SOEs). The other key element has been the existence of measures that encourage entry by new private operators. These two elements together account for the growing evidence of a 827

shift in the long-term balance of economic activities from the public to the private domain in many developing countries. For example, during 1980±95, private sector investment in developing countries increased from 15% to 18% of GDP while public sector investment declined from 9% to 6% of GDP (Bouton & Sumlinski, 1996). In absolute terms, net private capital ¯ows to developing

* The views expressed here are the authors' and do not

re¯ect those of the World Bank, its Executive Directors, or the countries they represent. The authors thank the two anonymous referees for their very helpful comments. The authors would also like to thank seminar participants at McGill University for their comments on an earlier version of the paper. Final revision accepted: 7 December 2000.

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countries reached US$240 billion in 1995, nearly ®ve times greater than in 1980. Another indication of the growing role of the private sector in developing economies has been the increase in private sector investment from 4.1% of gross domestic investment in 1990 to nearly 20% in 1996 (World Bank, 1997a,b). Along with the distinct trend toward a greater role for the private sector in economic activities, there has also been a growing concern about the adverse environmental impacts of economic growth (Blondell, 1996; Grove, 1992). This concern has led to a rich stream of research 1 on the notion of environmentally sustainable economic development that explores the tradeo€ between economic growth and environmental quality (Anderson, 1992; Dasgupta & Heal, 1979; van Marrewijk, van der Ploeg, & Verbeek, 1993; World Bank, 1992). The dominant view here is that the conventional tradeo€ between economic growth and environmental quality is not inevitable. In fact, it is possible to mitigate greatly or to even reverse the tradeo€ through appropriate policy interventions (Antle & Heidebrink, 1995; Grossman & Krueger, 1995; Selden & Song, 1994; Sha®k, 1994). This has now shifted the research focus on identifying ``environmental friendly'' policies that can spur economic growth at a least cost to the environment by encouraging substitution toward the technologies and practices for pollution prevention and control. The issue is particularly signi®cant for developing countries whoÐunder pressure to achieve accelerated economic growthÐface the danger of adopting economic policies that run contrary to the objective of their long-term environmental sustainability (Serageldin & Steer, 1994). As developing countries experience a marked shift in the involvement of the private sector in their economic activities, a pertinent policy question is whether such a shift helps or hurts the environment. In other words, does private investment (as opposed to public investment) lead to greater environmental degradation when market prices fail to recognize external costs and when property rights regimes are weak and/or not enforced? Conventional wisdom and theoretical conjectures are split about the environmental consequences of private sector development. One argument holds that the private sector's emphasis on economic eciency could lead to increased investment in newer and cleaner

technology, and thus to a better environment (Schmid & Rubin, 1995). The private sector also sees promoting foreign direct investment as a faster and cheaper way of acquiring technology for developing countries (Bloomstrom & Kokko, 1997; Gentry, 1998; Esty, 1995). The opposing argument holds that it is precisely this emphasis on economic eciency that could lead the private sector to compromise the environment by avoiding the potential costs of environmental expenditures (EII, 1990; Eiser, Reicher, & Podpadec, 1996). This latter argument has found particular resonance in developing countries apprehensive of being used as ``pollution havens'' by multinational enterprises (Eskeland & Harrison, 1997; Low & Yeats, 1992; Walter, 1982). Anecdotal empirical evidence appears to bolster both lines of argument. The wellpublicized pollution problems of SOEs in former Soviet-bloc countries in Eastern Europe are often cited as support for greater private sector activity. Similarly, proponents of the opposing argument point to conspicuous examples of environmental problems with the private sectorÐmost recently with the utility industry in the United States (Oliphant, 1999). Unfortunately, an almost exclusive focus of the extant research on the economic role of the private sector in promoting development provides little help in resolving the con¯icting arguments of the potential environmental consequences of private sector development. Apart from ambiguous anecdotal evidence, there is hardly any systematic empirical study on the long-term relationship between the nature of enterprise ownership and environmental performance of an economy (Anderson, 1995; Gentry & Fernandez, 1998a,b; Jasinski, 1996; Kikeri, Nellis, & Shirley, 1992). It is only very recently that some research has started to address this shortcoming by analyzing pollution data at the plant-level within a country. These few studies have found evidence that state-owned enterprises are likely to be more polluting than their privately-owned counterparts (Dasgupta, Wang, & Wheeler, 1997; Hartman, Huq, & Wheeler, 1997; Pargal & Wheeler, 1996). The contribution of this paper is to further extend this important stream of empirical research by investigating whether such ®ndings are generalizable to the longterm environmental performance of national economies at di€erent levels of private sector development.

DOES THE PRIVATE SECTOR HELP OR HURT THE ENVIRONMENT?

The paper uses panel data across 44 developing countries over nine years (1987±95) to study for any systematic empirical relationship between the relative level of private sector involvement in an economy and the environmental performance of the economy in terms of its emission of industrial carbon dioxide. We choose carbon dioxide …CO2 † emissions because of the increasing emphasis to reduce this particular greenhouse gas in the ongoing debate to combat global warming (Revkin, 2000). We also limit our focus to developing countries as the debate on the pace and level of private sector development is mostly pertinent in the context of developing economies. We use a reduced-form, random-e€ects regression model that controls for both observed and unobserved crosscountry heterogeneity along various institutional and structural dimensions such as the scope of ®nancial market, industrial sector composition and level of foreign direct investment. The regression results show a systematic relationship between the nature of enterprise ownership in an economy and its environmental quality in terms of CO2 emissions. The higher the degree of private sector involvement in a developing economy, the lower is its environmental degradation. Moreover, its environmental degradation is likely to be further reduced in presence of a well-functioning domestic capital market and through increased participation by developed economies in its private sector development. The paper is organized as follows. Section 2 brie¯y discusses the prevailing thoughts on the link between the nature of enterprise ownership and the environment. Section 3 presents the empirical study while Section 4 concludes with future research imperatives.

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2. ENTERPRISE OWNERSHIP AND THE ENVIRONMENT: PREVAILING THOUGHTS Anecdotal evidence suggests that both state and private enterprises have the impetus to, and frequently do, exploit any potential weaknesses in local environmental policies or property rights. Lacking any systematic empirical evidence, however, conventional wisdom and theoretical conjectures are split on the question as to whether a greater shift from public to private enterprises in an economy comes at a reduced or increased cost to the environment (Kikeri et al., 1992). Conceptually, the answer hinges on whether there are likely to be any di€erential economic incentives for the adoption of pollution abatement measures by private and public enterprises 2 (Figure 1). Arguments have been made to support either caseÐthat SOEs are likely to have fewer incentives than private enterprises and vice versa (Coequyt & Wiles, 1998; Coequyt, Wiles, & Campbell, 1999; Gentry, 1998; Kikeri et al., 1992; Kruszewska, 1993). Proponents in support of the ®rst case argue that private enterprises, with their emphasis on economic eciency, are more likely to invest in newer and cleaner technology and thus help the environment. As Kikeri et al. (1992) note: SOEs tend to use older, more-polluting technology than do private ®rms. Given most developing countries' inability to ®nance modernization investments and in light of the considerable evidence that a common e€ect of ownership change is increased investment, private sector development should be associated with less pollution as new private owners install cleaner technology.

Figure 1. Factors a€ecting the incentive for adoption of pollution abatement measures by private and public enterprises.

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WORLD DEVELOPMENT

They also contend that the public sector may more easily avoid compliance with pollution controls because they have less of an adversarial relationship with the state regulation authority. The high levels of pollution in the centrally planned economies in Eastern Europe and the former USSR suggest that SOEs are accountable to a much lesser extent than private enterprises. Moreover, unlike private enterprises, SOEs are not under ``informal regulatory'' pressure from the private ®nancial and capital market for compliance with environmental regulations. Further, SOEs have tended to bene®t from protection and, like other protected industries in developing countries, have tended to be more materials-intensive, more energy-intensive, and thus more pollution-intensive than private enterprises. Finally, many SOEs receive exemptions from the pollution regulations of their owners, the state. In the United States publicly-owned water treatment plants have been the most consistent violators of pollution regulations. The opposing school of thought holds that the environment will in fact be under greater threat from private enterprises. With the pressure of competition, as well as of performance expectations in ®nancial markets, private enterprises may have more of an incentive to undertake polluting activities than complacent SOEs that do not have to worry if they incur losses (Gentry, 1998). Often SOEs leave valuable assets idle that traditionally private owners would exploit (i.e., land). In addition, private enterprises are more likely to bribe regulators in order to evade pollution controls, since they are more likely to have the money than SOEs, and they may not have the scruples of the publicly employed manager (Kikeri et al., 1992). Finally, private enterprises may be better able to withhold information from the government than SOEs; making enforcement more dicult for regulators. While circumstantial evidence can and has been used to support either line of argument, the question remains as to whether there is any generalized empirical regularity in terms of evidence one way or the other. In the next section, we attempt to answer that question through a systematic empirical study. 3. EMPIRICAL STUDY The primary objective of this empirical study is to investigate whether greater involvement of

the private sector in an economy helps or hurts the environment. We limit our focus to developing countries as the debate on the pace and level of private sector development is mostly pertinent in the context of developing economies. We use CO2 emissions as the environmental pollution measure for several reasons. 3 CO2 emissionsÐonce thought to be a harmless by-product of combustionÐare now believed to be the primary greenhouse gas responsible for the problem of global warming (IPCC, 1996, p. 13). Regulating and monitoring anthropogenic emissions of CO2 from various economic activities has become a central issue in the ongoing negotiation for an international treaty on global warming (Cline, 1992; IPCC, 1996; Revkin, 2000; UN, 1992). Moreover, the scope of its spatial impact makes CO2 pollution more suitable for country level aggregate studies. Last but not the least, a consistent and reasonably reliable time series on CO2 emissions is now available for most countries from the Carbon Dioxide Information Analysis Center at the Oak Ridge National Laboratory (ORNL), USA. 4 (a) Empirical model To test whether the degree of private sector involvement has a systematic relationship with the level of CO2 emissions in a country, we adopt the standard reduced-form modeling approach used in the existing Environmental Kuznets Curve (EKC) literature. 5 To account for country speci®c unobserved heterogeneity, we use the following random-e€ects speci®cation for the regression model (Hsiao, 1986): 6 Eit ˆ a ‡ b1 …GNPPCit † ‡ b2 …GNPPCit †2 n X ‡ cj …SECTORijt † ‡ b3 …AGRit † jˆ1

‡ b4 …TIMEt † ‡ b5 …PSIit † ‡ b6 …CMDit † ‡ b7 …FDIit † ‡ b8 …TRADEit † ‡ mi ‡ it

…3:1†

where Eit is the CO2 emission per capita in country i at time t; GNPPCit the GNP per capita in country i at time t; SECTORijt the valueadded share (% of GDP) of industrial sector j in country i at time t; AGRit the value-added share (% of GDP) of agricultural sector in country i at time t; TIMEt the time trend variable at time t; PSIit the degree of private sector involvement

DOES THE PRIVATE SECTOR HELP OR HURT THE ENVIRONMENT?

in country i at time t; CMDit the degree of capital market development in country i at time t; FDIit the degree of foreign direct investment in country i at time t; TRADEit the degree of international trade in country i at time t; mi the country speci®c ``random e€ect'' term; and eit is the random error term. The rationale for the inclusion of each explanatory variable in the model is discussed below. (i) Scale of the economy Consistent with the practice in the EKC literature, our model allows for both the scale and composition of a country's economy to in¯uence the CO2 emission level. It uses the traditional GNP per capita measure, GNPPC, to estimate the scale impact of a country's economy on the level of CO2 emissions per capita. It also includes a squared GNP per capita term to test for a possible inverted-U relationship between economic growth and CO2 emissions in a country. Several studies have found evidence of such a relationship for a number of environmental indicators (e.g., deforestation and sulfur dioxide emissions), suggesting the existence of an ``environmental Kuznets curve'' where environmental quality actually begins to improve beyond a certain ``turning point'' of economic development (Antle & Heidebrink, 1995; Grossman & Krueger, 1991, 1995; Selden & Song, 1994). 7 As in many of the existing studies, we use purchasing power parity 8 adjusted values (in 1987 constant international dollars) for GNP per capita. (ii) Composition of the economy The existence of a relationship between the structure of a country's economy and its environment is well documented in the literature (Hettige, Mani, & Wheeler, 1998; Panayotou, 1997; Torvanger, 1991; Westbrook, 1995). For example, Panayotou (1997) decomposes economic activity into three categories broadly de®ned as the primary (agriculture, ®sheries, forestry and mining), secondary (industry) and tertiary (services) sectors. He argues that although each may have their own relative contribution to overall environmental degradation, it is the secondary sector that is the most pollution-intensive and thus includes the share of industry in GDP as an indicator of structural change in economic growth. Torvanger (1991), building upon an earlier analysis of industry structure and

831

energy intensity by Howarth, Shipper, Duerr, and Strùm (1991), selects six manufacturing subsectors known to be associated with high energy use and attempts to determine the major drivers of CO2 intensity (de®ned as CO2 emissions/$ value-added). In another interesting panel exercise for 56 developing countries, Westbrook (1995) regresses the log of CO2 emissions per capita on GNP per capita, its square and the shares of GNP in agriculture and services. Her estimates indicate a negative relationship exists with pollution, re¯ecting the lower emissions of agriculture and services relative to the industrial sector. To the extent that these sectors are highly correlated with emissions, we explicitly control for both the size of the agricultural sector as well as composition of the industrial sector in terms of their respective value-added 9 shares of national GDP through the variables AGR and SECTOR, respectively. We use threedigit SIC codes for classifying industrial sectors and include seven top polluting sectors 10 (food products, paper products, industrial chemicals, petroleum re®neries, iron and steel, other nonmetallic mineral products, 11 and power generation) in terms of air pollution. It should be noted that the variables AGR and SECTOR in our modelcontrol for the in¯uence of only the output structure of the economy on the CO2 emissions in a country. Arguably, cross country variations in CO2 emissions are also driven by di€erences in the input structure of the economy. Unfortunately, reliable measures for the input structure of an economy, which are expected to vary both temporally and spatially, are extremely dicult to compile for large-scale panel studies such as this one. Moreover, such an analysis would be more appropriate in a microeconomic setting rather than the macroeconomic framework presented here. As such, we use two ``proxy'' variables in our model to partially capture the variation in the input structure of economies over time and across countries (Holtz-Eakin & Selden, 1995). First, we use the time-trend variable, TIME, to control for temporal changes in the input structure of economies. We assume a linear trend for such change and measure the variable, TIME, in terms of the annual time period. 12 Second, the random-effects speci®cation of our regression model allows us to control for some of the unobserved cross country di€erences in input structures of economies through the time invariant, country speci®c term, mi .

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WORLD DEVELOPMENT

In addition to the scale and structure of the economy, several other general macroeconomic policy-related factors are likely to in¯uence the environmental quality in a country (Sha®k, 1994). Accordingly, we use insights from the existing literature to include four such control variables in our regression model: private sector involvement; capital market development; foreign direct investment; and international trade. The control variable of our primary interest is of course the degree of private sector involvement, PSI, in a country. (iii) Private sector involvement As noted earlier, while the existing literature acknowledges the potential relationship between private sector involvement and the environment in a country, it is split on the exact nature of such a relationship. Arguably, there is no single measure in which to capture such a variable (Bouton & Sumlinski, 1996). In order to check the robustness of our results for the variable of primary interest, multiple measures are used. We run three sets of regressions with our estimation modelÐeach with a di€erent measure to capture the relative degree of private sector involvement in a country's economy. For the ®rst two regressions, we measure the degree of private sector involvement in a country in terms of private sector investment as a percentage share of total domestic investment and of national GDP, respectively. The third regression measures the degree of private sector involvement in a country in terms of private sector output as a percentage share of national GDP. Thus, we capture the degree of private sector involvement in terms of both investment and output from the private sector relative to the size of the economy. (iv) Capital market development Several studies have found evidence suggesting that ®nancial capital markets ``reward'' ®rms with superior environmental performance through a higher valuation of ®rms' equities (Hamilton, 1995; Klassen & McLaughlin, 1996; Lanoie & Laplante, 1994; Lanoie, Laplante, & Roy, 1998). Such evidence has led to the argument that a country with a more developed ®nancial capital market is likely to enjoy a better environmental quality than a country with a less developed capital market (Dasgupta, Laplante, & Mamingi, 1998). Our model tests this argument in the context of CO2 emissions by controlling for the degree of CMD across

countries. We use the total value of stocks traded in capital markets as a percentage of national GDP as the measure of the relative degree of capital market development, CMD, across countries. (v) Trade and foreign direct investment While there is widespread acknowledgment in the existing literature about the environmental impact on developing countries from international trade and foreign direct investment, opinions and evidence are split about the nature of such impact (Chua, 1999; Birdsall & Wheeler, 1992; Eskeland & Harrison, 1997; Hettige, Lucas, & Wheeler, 1992; Low & Yeats, 1992; Rock, 1996; Stern, 1998; Walter, 1982). Opinions of a negative environmental impact are based on arguments that by raising output, trade intensi®es pollution in developing countries (the ``scale e€ect''). In addition, lax environmental standards and enforcement in developing countries intensify pollution further by attracting investment in pollution-intensive industries from developed countries (the ``pollution haven'' hypothesis). Opposing opinions of a positive environmental impact are based on the rationale that a more ``outward-oriented'' developing economy in the form of higher trade and foreign investment will have greater access to new, cleaner environmental technologies (which will force pre-existing industries to ``clean-up'' their production processes). We include both trade and foreign direct investment variables in our regression model to test which of the two opposing arguments are supported in the context of CO2 emissions. We use incoming foreign direct investment as a percentage of gross domestic investment as the measure of the relative degree of foreign direct investment, FDI, across countries. The relative degree of international trade, TRADE, across countries is measured as the total value of exports and imports as a percentage of national GDP. Finally, we believe that our regression model includes a much larger set of relevant explanatory variables for crosscountry CO2 variation than most other existing studies in the EKC literature. Even then, partly because relevant data (especially for developing countries) are scarce and partly because some of the factors are extremely dicult to quantify, the model excludes some potentially relevant variables (e.g., energy policies, energy prices, environmental ``consciousness,'' informal regulations, etc.). A few observations are in order regarding

DOES THE PRIVATE SECTOR HELP OR HURT THE ENVIRONMENT?

this problem of ``missing variables'' in any reduced-form modeling approach (Grossman & Krueger, 1995). From a methodological point of view, this problem is not a critical issue for several reasons. First, without any formal abatement policies in place in developing countries, GNP per capita is likely to be the predominant determinant of long-run carbon dioxide emissions, and factors such as environmental ``consciousness'' and informal regulations are expected to be systematically correlated with GNP per capita (Pargal & Wheeler, 1996). Second, the presence of the countryspeci®c random-e€ect term and the time-trend variable in our model further alleviate the problem by capturing some of these e€ects on emissions (Holtz-Eakin & Selden, 1995). Finally, the objective of this research is not to develop a short-run predictive model of carbon dioxide emissions, but to test for any systematic empirical relationship between the nature of enterprise ownership and carbon dioxide emissions in an economy. (b) Data We use annual data for 44 developing countries over nine years (1987±95) for the variables speci®ed in the estimation model (3.1) above. The countries in the data represent a wide range of developing countries from all over the world (see Appendix A). The data for all the explanatory variables except for the valueadded shares of the selected industrial sectors were collected from various data bases and publications of the World Bank (Bouton & Sumlinski, 1995, 1996; World Bank, 1991, 1995a,b, 1997a,b, 1999). The data for the valueadded shares of the industrial sectors are from the International Labor Organization (ILO) and United Nations Industrial Development Organization (UNIDO) databases. 13 As noted earlier, the Carbon Dioxide Information Analysis Center at the Oak Ridge National Laboratory (ORNL), USA, maintains a large database of annual carbon dioxide emissions since 1960 for a large number of countries. The data include emissions from aggregate fossil fuel consumption and cement manufacture (for the computational details, refer to Boden, Marland, & Andres, 1995). Unfortunately, it excludes emissions from activities such as the burning of fuel wood and dung in the informal sector of a developing economy. But, in the absence of any other reliable data source, this studyÐas in most other previous studies on

833

CO2 emissionsÐuse the data from the ORNL (Moomaw & Unruh, 1997). 14 (c) Estimation results We use the generalized estimating equation (GEE) technique 15 to estimate the regression model (3.1) with our panel data. The technique allows for heteroskedasticity 16 and ``within group'' (intra-country) serial correlation 17 in the error term. Our results are presented in Table 1 for the three sets of regressions corresponding to the three di€erent measures of private sector involvement. Very similar results across all the three sets of regressions indicate that our ®ndings are quite robust to the measure used for the degree of private sector involvement. The signi®cantly positive value for coecient b1 and statistically insigni®cant negative value for coecient b2 suggest that CO2 emissions increase monotonically with economic growth, rather than decreasing beyond a particular ``turning point'' as hypothesized by the environmental Kuznets curve. The EKC literature does not, however, postulate the ``turning point'' to be inevitable, but rather to be policy induced (Grossman & Krueger, 1995; Moomaw & Unruh, 1997). In other words, it is policy that is instrumental in reversing the conventional tradeo€ between economic growth and environmental degradation. Therefore, in the absence of any meaningful current policies to abate carbon dioxide in our sample countries, the ®nding of an adverse impact of economic growth on carbon dioxide emissions is hardly surprising (Holtz-Eakin & Selden, 1995; Roberts & Grimes, 1997; Selden & Song, 1994; Sha®k, 1994). A similar conclusion would also be true for other pollutants such as particulate matter, lead in fuels, and a range of water and air pollutants in the industrialized countries until the early 1990s when speci®c pollution control and abatement policies were instituted. Our results also show that the structural composition of the economy a€ects carbon dioxide emissions in the expected way with accentuating and mitigating pressures from industrial and agricultural sectors, respectively (Panayoutou, 1997; Torvanger, 1991; Westbrook, 1995). The coecient b4 for the timetrend variable is found to be negative and signi®cant. The ®nding is consistent with some evidence that developing countriesÐalthough without any speci®c policy to abate CO2 in

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WORLD DEVELOPMENT Table 1. Regression results for the random-e€ects model Dependent variable: CO2 emissions per capita

Independent variable Regression coecient (GNPPC) (GNPPC)

b1 2

Industry sector Food products

b2

c1

Paper

c2

Industrial chemicals

c3

Petroleum products

c4

Non-metallic mineral products

c5

Iron and steel

c6

Power

c7

AGR

b3

TIME TREND

b4

PSI

b5

CMD

b6

FDI

b7

TRADE

b8

Adj. R2 Number of Observations

Regression 1a

Regression 2b

Regression 3c

7.5 ´10 4 (2.321)d )2.99 ´ 10 ()1.406)

7.6 ´ 10 4  (2.208) )3.04  10 8 ()1.277)

7.9 10 4 (2.446) )3.21 10 8 ()1.403)

 8

9.878 (1.298) 50.094 (1.677) 8.101 (2.344) 6.027 (2.342) 0.076 (1.668) 0.551 (2.249) 0.244 (2.277)

9.989 (1.385) 49.649 (1.444) 8.033 (2.461) 6.024 (2.311) 0.074 (1.543) 0.553 (2.267) 0.239 (2.386)

11.041 (0.892) 52.232 (1.854) 7.854 (0.896) 5.987 (2.422) 0.073 (1.466) 0.547 (2.668) 0.242 (2.237)

)0.033 ()2.704) )0.012 ()2.318) )0.002 ()3.146) )0.035 ()2.349) )0.018 ()2.272) 0.016 (1.488)

)0.034 ()2.868) )0.012 ()2.377) )0.002 ()3.109) )0.037 ()2.139) )0.019 ()2.208) 0.014 (1.558)

)0.037 ()2.191) )0.014 ()2.021) )0.003 ()2.496) )0.033 ()2.801) )0.016 ()2.244) 0.020 (1.601)

0.59 396

0.57 396

0.54 308

a Uses private sector investment as a percentage of total domestic investment as the measure for the degree of private sector involvement (PSI) in a country's economy. b Uses private sector investment as a percentage of national GDP as the measure for the degree of PSI in a country's economy. c Uses the value of output from the private sector as a percentage of national GDP as the measure for the degree of PSI in a country's economy. d t-values of coecient estimates are in parenthesis. ** Coecient is statistically signi®cant at 0.05 level.

placeÐare showing a stronger general environmental regulatory (both formal and informal) trend that encourages the adoption of small scale energy eciency policies through input substitution or savings (Dasgupta et al., 1997; Pargal & Wheeler, 1996). A negative value with high statistical signi®cance for the coecient b5 of the variable of primary interest indicates that greater private sector involvement in an economy leads to a

positive environmental spillover in terms of reduced carbon dioxide emissions. Further, the negative values for the coecients b6 and b7 suggest that both foreign direct investments and the presence of a well-functioning domestic ®nancial capital market in an economy are likely to have positive impacts on the environment. Our ®ndings thus support the argument that foreign direct investments in developing countries are more likely to act as ``conduits''

DOES THE PRIVATE SECTOR HELP OR HURT THE ENVIRONMENT?

for advanced, cleaner environmental technologies than as ``pollution havens'' for dirty industries from developed countries (Chua, 1999; Bloomstrom & Wang, 1989; Bloomstrom, 1991; Esty, 1995). Given the lingering debate on the economic welfare e€ects of private sector development and foreign direct investment, our study provides one additional environmental rationale for promoting private sector development through foreign participation (Brada, 1996; Perotti, 1995). It is also consistent with the ``incentive hypothesis'' that a ®rm's environmental performance is likely to be ``rewarded'' by capital markets (Klassen & McLaughlin, 1996; Lanoie et al., 1998). Unfortunately, the statistically insigni®cant coecient b8 of the trade variable fails to shed any additional insight into the ongoing debate about the environmental consequences of open trade policies for developing countries. 4. CONCLUSION Major changes in the world political landscape at the turn of this decade led to a renewed scrutiny of the relationship between the nature of enterprise ownership and growth in an economic system. The repercussions of this have been an increased emphasis on private sector development based on grounds of economic eciency. At the same time, rising concerns about the environmental consequences of economic growth have sought to answer the question: How does the nature of enterprise ownership a€ect the environment in an economy? Conventional wisdom and theoretical conjectures are split in their answer as is the anecdotal evidence. Unfortunately, the existing literature is conspicuous for its near absence of any systematic empirical study on the long-term relationship between the nature of enterprise ownership and environmental performance of an economy. Given an almost exclusive focus of the existing research on the economic rather than environmental consequences of the nature of enterprise ownership, that is not entirely surprising. It is only very recently that some research has started to address this shortcoming by systematic empirical analysis of pollution data at the plant-level within a country. These few studies have found evidence that state-owned enterprises are likely to be more polluting than their privately-owned counterparts. This paper further extends this important stream of empirical research by

835

investigating whether such ®ndings are generalizable to the long-term environmental performance of national economies at di€erent levels of private sector development. Using panel data across 44 developing countries over nine years (1987±95), we estimate a random-e€ects model to study for any systematic empirical relationship between the degree of private sector involvement in an economy and the environmental performance of that economy. The paper speci®cally looks into the impact of private sector involvement on emissions of industrial carbon dioxideÐthe primary greenhouse gas believed to be responsible for global warming. The speci®cation of the estimation model controls for unobserved as well as observed heterogeneity across countries along several institutional and structural dimensions. Our study shows a signi®cantly negative relationship between the degree of private sector involvement in an economy and the CO2 emission level. It thus lends empirical support to the notion that an increased role by the private sector in economic activities is more likely to help the environment of a country. We also ®nd that both foreign direct investments and domestic ®nancial capital markets in an economy are likely to have positive impacts on the environment. Thus a country which allows greater private sector involvement and foreign direct investment in its economic activities and possesses a well-developed ®nancial capital market is likely to enjoy a better environmental quality at any stage of its economic development. Our ®ndings are consistent with the argument that business enterprises, in their own self-serving pursuit for economic eciency, may help the environment by seeking and adopting more ecient and cleaner production technologies (Carrington, 1992; Feltes & Fink, 1996; Montes, 1995; Mullin & Sissell, 1996). It is important to acknowledge several limitations of the current study. Like other existing studies that use the carbon dioxide emission data from ORNL, our study also fails to account for the informal sector emissions from wood burning in developing countries. As such, our ®ndings are essentially limited to understanding the impact of private sector development on carbon dioxide emissions from the burning of fossil fuels. In addition, although quite relevant in the context of the globalwarming problem, carbon dioxide emissions are still a relatively low priority for developing countries. Local problems such as unsafe water,

836

WORLD DEVELOPMENT

urban air pollution, soil erosion and degradation are far more pressing in developing countries than globally-bounded problems such as CO2 . Thus, while we believe that the general conclusion of our ®ndings is likely to hold, future research needs to undertake similar studies for local and regional environmental pollutants. Finally, as with any empirical study, our ®ndings re¯ect the historical trend speci®c

to our sample data and analysis period. Again, while we feel that our ®ndings can be generalized to other developing as well as developed countries, future research needs to further check its validityÐespecially in the context of mature economies where the scope of additional gain in economic eciency from the reduction of pollution waste is more limited.

NOTES 1. Such research has assumed added signi®cance in the wake of the proposed international treaty on greenhouse gas emissions to combat global warming. A key issue of the proposed treaty is the extent of tradeo€s between the environmental and economic consequences of any restriction on greenhouse gas emissions (Manne & Richels, 1992; Munasinghe, Meier, Hoel, Hong, & Aaheim, 1995). 2. It should be noted that while formal environmental policies are crucial in theory to generate economic incentives for adoption of pollution abatement measures, the prevalence of such policies in practice is by no means uniform across countries and pollutants. For example, in contrast to the case of most other pollutants, few countriesÐand certainly no developing countries so farÐhave a formal policy to abate carbon dioxide (aside from some small-scale energy eciency policies). As Figure 1 indicates, however, enterprises may still have other sources of incentives to adopt voluntary measures that result in pollution abatement. For example, incentives for higher economic eciency through lower production cost may lead enterprises to voluntary input substitution and/or saving. 3. As noted earlier, no developing country has any formal policy in place to abate carbon dioxide emissions. Thus, CO2 emissions would not be a good choice if the focus of the study were to investigate the impact of direct CO2 abatement or control policies. But, the primary objective of the study is to investigate whether general macroeconomic policies (such as private sector development policy) in¯uence the incentives of private enterprises for input substitution and/or saving with or without the presence of formal abatement policies. 4. An attempt was made to collect data on alternative indicators of environmental pollution (i.e., United Nations GEMs Air/Water); however, neither reliable time-series nor country-level aggregates were available. In the case of GEMs, these data are collected at the city

level and thus would not suce for a crosscountry analysis. 5. The reduced-form modeling approach, as opposed to the structural-form modeling approach, has several advantages in terms of data requirements and estimation, and is widely used to determine long-term relationships between economic growth and environmental quality (Antle & Heidebrink, 1995; Grossman & Krueger, 1995; Selden & Song, 1994; Sha®k, 1994). 6. An alternative speci®cation would have been ®xede€ects. The ®xed-e€ects approach takes mi to be a country-speci®c constant term in the regression model. In contrast, the random-e€ects approach speci®es that mi is a country speci®c disturbance, similar to eit except that for each country, there is a single draw that enters the regression identically in each time period. As our study uses only a sample subset of all the developing countries as cross-sectional units for the regression analysis, a random-e€ects speci®cation is considered more appropriate. But, a necessary assumption under the randome€ects speci®cation is that the country speci®c e€ects are uncorrelated with the other regressors in the model. We test this assumption using the Hausman test for our regression model (Hausman, 1978). Based on the value of the test statistic …v2…df ˆ15† ˆ 7:47; p > 0:1†, we fail to reject the hypothesis that country speci®c e€ects are uncorrelated with the other regressors. The Hausman test thus supports the random-e€ects speci®cation over the ®xed-e€ects speci®cation. 7. A signi®cant body of literature has been written on the subject and researchers continue to explore the relationship between environmental degradation and economic growth (see also special issues by Environment and Development Economics, 1997 and Ecological Economics, 1998). 8. Many studies in this area use per capita values based on purchasing power parity (PPP) to allow

DOES THE PRIVATE SECTOR HELP OR HURT THE ENVIRONMENT? for crosscountry comparisons with estimates free from the volatility of exchange rates of currency (Stern, 1998). 9. We have selected value-added as the output indicator instead of gross output, since employing gross output would lead to double counting problems due to the production and use of intermediate products, and since value-added data are comparable over countries. 10. With the exception of the food products sector, the other six sectors were identi®ed in Howarth et al. (1991) and Torvanger (1991) as major energy-intensive sectors. The food products sector is also included as it has been generally recognized as both a major air and water polluter (Rothman, 1998). 11. ``Other non-metallic mineral products'' includes the Pottery, china and earthenware, Glass and glass products, Structural clay products, Cement, lime and plaster and Nonmetallic mineral products (n.e.c.) industries. 12. The linear trend assumption seems reasonable, as the change in the input structure of economies is more likely to follow a continuous rather than a discrete or discontinuous path. Since our data span the nine-year period 1987±95, the TIMEt variable takes the value of one (for the year 1987) to nine (for the year 1995). 13. The UNIDO National Accounts Statistics Database is based on data provided by the World Bank, OECD, IMF, UN Statistics Division, UNECE, regional development banks, and estimates made by UNIDO; UN Population Division; UNIDO Industrial Statistics Database; and estimates derived from the UN Commodity Trade database. Manufacturing value-added data, in US dollars, for all the sectors other than the power generation sector were computed by using period

837

average market exchange rates as published in International Financial Statistics (IMF publication) and other sources. In the absence of value-added data, we use electricity production from coal, natural gas and oil sources as a percentage share of total electricity production in a country as the measure for the power generation sector. 14. One exception to the use of the ORNL data is by Galeotti and Lanza (1999) who use data from the International Energy Agency. Even their data do not, however, capture informal sector CO2 emissions from such activities as the burning of fuel wood or dung. 15. The GEE technique estimates general linear models for panel data. The GEE estimator is asymptotically equivalent to the weighted-generalized least square estimator and maximum-likelihood estimator. The GEE technique is considered more ¯exible, however, because of its ability to accommodate a variety of error distributions in addition to the common normal (Gaussian) distribution. It also allows for a richer correlation and covariance error structure. For a very good discussion of the GEE technique for panel data, see Liang and Zeger (1986). 16. To account for heteroskedasticity, the GEE technique generates robust variance estimators that go by various names: Huber/White/Sandwich estimators corrected for heteroskedasticity (MacKinnon & White, 1985). 17. The within-country serial correlation coecient of the residuals is estimated to be 0.247. The correlation structure corresponds to an ``exchangeable'' structure where the within-country serial correlation of the residuals remains constant with the time lag (as opposed to diminishing with the time lag in an ``auto-regressive'' structure).

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APPENDIX A Table 2. List of developing countries used for model estimationa Sub-Saharan Africa

Latin America and Caribbean

Middle-East and North Africa

Asia

East Europe

C^ ote d'Ivoire Ghana Kenya Mauritius Namibia Nigeria South Africa Zimbabwe

Argentina Barbados Bolivia Brazil Chile Colombia Costa Rica Ecuador Guatemala Honduras Mexico Panama Paraguay Peru Trinidad and Tobago Uruguay Venezuela

Egypt Jordan Morocco Tunisia Turkey

Bangladesh China India Indonesia Iran Malaysia Nepal Pakistan Philippines South Korea Sri Lanka Thailand

Bulgaria Poland

a

Note: Grouped according to the World Bank's Regional Classi®cation (Bouton & Sumlinski, 1996).