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Empirical modeling of Pollution Abatement and Control Expenditure in new EU members countries: evidence from Romania

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Empirical modeling of Pollution Abatement and Control Expenditure in new EU members countries: evidence from Romania ROBERT SOVA 1 ANAMARIA SOVA 2 RAULT CHRISTOPHE 3 CES, Sorbonne University 1,2, Academy
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Empirical modeling of Pollution Abatement and Control Expenditure in new EU members countries: evidence from Romania ROBERT SOVA 1 ANAMARIA SOVA 2 RAULT CHRISTOPHE 3 CES, Sorbonne University 1,2, Academy of Economic Study 1, Economic & Business Research Center 2, LEO, University of Orleans and IZA 3 6, Romana Square, Bucharest ROMANIA Abstract: One of main area of environmental economics has studied the determinants of the pollution abatement effort. While hypotheses regarding the drivers that can affect the level of plant Pollution Abatement and Control Expenditure (PACE) have been proposed and tested using data from developed economies, a little empirical work particularly at the plant level - has been done to identify the most important factors in the conditions of transition economies. The transition economies are characterized by economic and institutional change which creates significant risks and uncertainty and this is particularly true for the Central and East European (CEE) countries. In addition, the eastern enlargement process of the European Union imposed the acquis communautaire adoption by the applicant countries which among many requirements suppose the improvement of environmental performances through an increase in PACE. Traditionally, the majority of the empirical literature has adopted several dimensions to explain plant PACE patterns i.e. plant, community, market and regulatory characteristics. To takes into account the selection bias problem a Heckman specification model is recommended. Thus, we can avoid inappropriate policy recommendations. Our results suggest that there are some significant differences in the factors influencing PACE in Romania relative to those found for developed countries. Key-Words: - Pollution Abatement and Control Expenditure, Transition Economy, Empirical Model 1 Introduction The basic economic processes are production and consumption; the firms transform natural resources, through the production process, into commodities demanded by the consumers. In physical terms, this conversion is never perfectly efficient: by-products (residuals) are produced. When residual has no economic value then it can be thought of as waste, which may lead to pollution. Thus, the firms impose a cost on other agent in society and these costs are not full compensated. This is the typical case of a negative externality i.e. the cost are outside or external to the market. These were situations where prices did not take account of damaging effects, means that the price failed to regulate the use of the environment. The price does not reflect full production costs to society. To correct this form of market failure is necessarily to internalize the externality. While the plants have a lack incentive to internalize the negative externality, these are subject of extern normative, coercive and mimetic factors that affect firm s decisions (DiMagio and Powell 2004). This pressure can be moderate by plant-level characteristics and organizational structure as well as industry effects. While each has provided a piece of puzzle, is desirable to examine the external and internal pressures that drive plants to regulatory compliance and so, to improve their environment performance. Since the Brundtland Report was published in 1987 as a result of World Commission on Environment and Development work, economist and business scholars have been conducting a wide research activity on corporative environmental concerns. Particularity a growing empirical evidence focus on environmental performance improvement through an increase in pollution abatement and control expenditure. Moreover, some research studies (Panayotou et al 1997, Ferraz and Seroa da Motta 2002, OECD 2001) consider environmental efforts most precisely capital expenditure as a proxi for the environmental performance. Even that the effort indicator it is not exactness evaluation for 454 ISSN: environmental performance, the literature has provide that are positive influence to the plant s environmental outcomes. The abatement and control of residuals from production processes can be done either by end-of-pipe technology attached to a given production process, or by changing the process itself. Investments in end-of-pipe technologies do not affect the production process itself, and the amount of pollution generated, instead they serve to treat pollution already generated. Investments in integrated technologies is synonymous with reducing the amount of potential pollutants at source, reducing the consumption of resources and energy, and recycling and utilization of residues and used products Some research has analyzed specific firms external factors that drive companies to adopt environmental responsibility and enhance environmentally performance such regulatory regime or government support, (Delmas, 2003; Chan & Wong, 2006; Rivera, 2004; Rivera & de Leon, 2004; Rivera, De Leon, & Koerber, 2006; Shin, 2005,), pressure from local wealthy stakeholders, civil society, and foreign customers in Europe and Japan (Neumayer & Perkins 2004) and industry pressure (Guler et al. 2002, Corbett & Kirsch, 2004; Viadiu et al., 2006) Other research has focused on the role of internal organizational factors such as organizational structure and culture. ( Zygliadopoulos 2002). Only a few works has begun integrating key organizational characteristics with institutional theory. This approach can yield new insights to understand differences between firms strategies.(seroa da Motta, 2006; Gunningham et al., 2003; Hoffman 2001) All these works was empirical quantitative studies and it was carry out in a significant proportion on the developed countries. The transition economies are characterized by economic and institutional change which creates significant risks and uncertainty. This is also true for the Central and East European (CEE) countries which, in addition, in this period, have adopted the acquis communautaire. Improving environmental performance poses a particular challenge for CEE countries in general and for Romania in particular. Under central planning, the wellknown bias towards heavy industry combined with a lack of incentives to economise on inputs created considerable waste and pollution. Thus, in the transition countries the production technologies are substantially lees efficient than in the developed countries, and therefore have higher emission per unit of output. In addition to facing severe environmental problems inherited from previous centrally-planned economies, the transition period has brought various other difficulties, including financial and economic hardship. Economic transition is a process of gradual adjustment from non-market equilibrium to market equilibrium. During the transition process, many variables such provision of public goods, willingness to pay, technology and capital markets and many other are in disequilibrium. The adjustment process creates both constraints and opportunities that may be unavailable to more settled economies. Ignoring them may lead to the misallocation of scarce resources in the provision of public goods, in pollution abatement, and in the financing of private environmental investments. The remainder of the paper is organized as follows. Section 2 presents an overview of the main features of analyses of the environmental performance and plant PACE in the particularly condition of Romanian economies. Section 3 reports the empirical investigation as well as the econometric results. Section 4 finally concludes. 2 Problem Formulation Romania, like other countries of Central and Eastern Europe, has made efforts of approximating its environmental legislation with the European Union. Thus it is probable that substantial and even fundamental changes will be required at the plant level as a result of this process. The compliance cost require that firms make efforts to adjust themselves to the norms and rules set in the regulation and so goes toward improving the environmental performance. These efforts are concretized in a two directions a capital expenditure and operating costs both associated with pollution abatement efforts. Early in the transition, Romania as all CEE countries experienced a decline in industrial production and as a consequence a decrease of pollution levels. As the transition progresses and Romania resume economic growth, pollution levels may significantly increase, unless concerted action is taken to more effectively enforce environmental policies and reduce pollution and energy intensities. Unfortunately, environmental efforts in most Romania face the twin obstacle of severe budgetary constraints and a legacy of poor practice in investment programming and project management. In this context, innovative and effective financing strategies for environmental protection need to be developed or strengthened, and steps must be taken to ensure that scarce financial resources are allocated efficiently to address priority issues. In the econometric framework a sample selection bias can arise where the dependent variable is only observed for a restricted, nonrandom sample. The solution to our problem is to use the Heckman selection model (Heckman 1976). 455 ISSN: 3 Problem Solution 3.1 Model specification If pollution control expenditures were observed for everyone in the population, we would proceed in a standard regression framework. However, a potential sample selection problem arises because environmental investment is observed only for firm who adopt an environmental behavior. We assume that the plants engage in pollution abatement have an environmental behavior. In the general case, the sample selection rule that determines that determines the availability of data has serious consequences. Sample selection bias may arise because there may be self selection by individuals being investigated. Since the data on corporate pollution control investments reveal the existence of positive expenditures, this suggests that some plants may have decided to participate in environmental behavior. The amount that a firm invests is a censored variable in the sense that it cannot take negative value. Heckman (1979) and Amemiya (1985) makes it clear that in such circumstances, OLS regression using the selected sample (the firms which invest) generally leads to both biased and inconsistent estimation of model parameters. Heckman (1979) suggested that the presence of selection bias can be viewed as an omitted variable problem in the selected sample and proposed a two-stage method (heckit) that eliminates the specification error for the case of censored samples. The first stage estimates a probit model, with the dependent variable equal to 1 if the firm makes a participation decision and 0 otherwise. This permits recovery of the invers mills ratio which is included as an instrument in the second stage estimation of the truncated regression of the expenditure. Using the unobserved effects unbalanced panel data context Wooldridge (1995) extend Heckman s (1976) model, and suggested that the structure of the econometric model is: y X c u, it 1 = β1 it1 + i1 + it1 t = 1,..., T [ X + c + v 0] s δ, it2 = 1 2 it i2 it2 vit 2 ( xi, ci 1, ci2) Normal(0,1) where y it1 is observed only if the binary selection indicator, s it2, is unity, X it denote all exogenous variable at time t and c i the unobserved individual effects. Identification of the model require that X it1 is a subset of X it, means that X it contain at least one element not present in X it1. The inverse Mills ratio λ it2 was obtained for estimating selection equation by pooled probit across i and t. Wooldridge (2002) suggest that using λ it2 and FE in the structural equation not produce consistent estimators. The procedure has same advantage over alternative estimation techniques for censored samples. Thus unlike Tobit model, it allows variables to have asymmetric effects on participation and expenditures. Also in contrast to more sophisticated double-hurdle how assume that neither hurdle dominates the other in determining investment patterns, the approach involves first hurdle dominance in the sense that non-expenditure may only arise as an outcome of the participation decision. Given that the analysis period consist of intensive regulation of the environmental domain as the result of the European acquis adoption, it is more plausible to interpret non-expenditures as the outcome of a decision to not participate in environmental behavior that it is to interpret is as being outcome of binding expenditure constraints. Hence the structure of the econometric model reveals two parts: the participation equation and the expenditure equation. The expenditure equation and the participation equation are therefore specified as follows: P ( PACE 0) = f ( Plant, Market, Comm, Re g) and PACE = f ( Plant, Market, Comm, Re g, Lambda) Where: Plant - Plant characteristics, Market Market incentives Comm - Community characteristics, Reg - Regulatory intensity, Lambda - inverse Mills ratio. The binary dependent variable in the participation equation was constructed from the continuous data on corporate environmental investment. The dummy variable indicates whether a firm has an environmental behavior (whereupon the variable = 1) or not (when the variable = 0). The dependent variable in the expenditure equation is the level of pollution abatement expenditures made by the plants. We hypothesize that the plant decision for an environmental behavior and environmental investment level can be affected by their own characteristics, substantial regulatory actions (sanction aspects) as formal pressure and market incentives and community aspects as informal pressure. However, the Heckman estimator is appropriate only when at least one explanatory variable influence selection and not the dependent variable in the structural equation. The reason is that the extra explanatory variable in selection equation is necessarily for the model identification and so can provides the information necessary to distinguish the effects of the independent variables on selection from their effects on the later outcome of interest. As a 456 ISSN: technical point, we do not need an exclusion restriction if the regression function is correctly specified. The non existence of the exclusion restriction can introduce severe collinearity among the repressors in the structural regression. Hence in practice, usually an exclusion restriction is imposed on Heckman two-stage estimator to tell the genuine selection bias from a regression function misspecification (Lee, 2002). Of course, a trivial solution is to can simply exclude an explanatory variable that is implied by theory but this creates specification error and can bias results as well. It also important to emphasize that for sample selectivity models, normality and homoskedasticity are crucial assumption. Thus we suggest that the ISO certification explain only the decision of participation and it has not effect on the investment amount. In fact, conforming to ISO does not require any specific environmental action. All it really requires is that a company establish an environmental management system which refers to that part of the overall management system which includes organizational structure, planning activities, responsibilities, practices, procedures, processes and resources for developing, implementing, achieving, reviewing and maintaining the environmental policy. ISO is a management system standard, not a performance standard. ISO does not constitute or guarantee compliance with legal requirements and will not in any way prevent the governments from taking enforcement actions where appropriate. In addition, some fear that the ISO series could be used by certified firms as proof of commitment to environmental protection, without requiring concrete improvements in environmental performance. Dahlström et al s (2003) study was unable to confirm the link of the effect of Environmental Management System (EMS) with legal compliance of environmental regulation. The study - which is one of the few analyses that draw on a comprehensive set of independent performance assessments - found that EMS sites have a better procedural performance (as assessed by the regulator) but did not find a significant correlation between EMS and the likelihood of incidents, complaints and noncompliance events. Hertin et al (2004), based on data collected during the MEPI research project, conclude that at the firm-level and plant-level analysis, some correlations between EMS and performance were found, but in general correlations were weak, sometimes ambiguous and usually not statistically significant. The econometric specification used is the following: - participation equation InvDec it =β 0 +β 1 Product it +β 2 Debt it +β 3 Turnover it + β 4 Mark it + +β 5 PollSect it +β 6 EnvTx it +β 7 EnvSub it +β 8 UnEmp it +β 9 EnvNGO it + β 10 EnvGuard tt + β 11 Iso it + Dt + u it (1) - structural equation PACE it =β 0 +β 1 Product it +β 2 Debt it +β 3 Turnover it +β 4 Mark it + β 5 PollSect it + β 6 EnvTx it + β 7 EnvSub it + β 8 UnEmp it + β 9 EnvNGO it + β 10 EnvGuard tt + mills + Dt+ u it (2) 3.2 Data The exercise has been carried out for Romania in the period Data are taken from yearly survey of plant pollution abatement effort, managed by the Romanian National Institute of Statistic. Regarding to the dependent variable, we use plant environmental pollution expenditure. Table 1 provides a list of variable definitions and a summary of the hypothesized effects, from the literature, of the variables on participation (1) and PACE (2) Table 1 Variables Explanations (1) (2) Product plant productivity which + + approximate the economic performance Debt debt ratio a measure of a - - company's financial leverage Turnover plant activity size defined + + as turnover UnEmp unemployment proxy for - - the population welfare Iso ISO certification, + proving environmental management adoption Mark listing on Bucharest Stock + + Exchange proxy for the firm s visibility PollSect dummy variable which + + take value 1 for the pollution sectors and 0 otherwise EnvGuard environmental penalties, + + proxy for the regulatory pressure to adopt an environmental behavior EnvNGO number of environmental + + non-governmental organizations; proxy for population reactivity EnvTx environmental taxes proxy + + for the economic incentives to adopt an environmental behavior EnvSub environmental subsidies policy instruments to promote plant environmental behavior + + The data consist of a panel of environmental and financial information at establishment-level and the 457 ISSN: community characteristics and regulation intensity data at the counties level for the period The sample contain 4230 plants in 2002, 4159 plants in 2003, 4661 plants in 2004 and 4466 plants in 2005 covering almost all industrial sectors. Reported pollution abatement and control expenditure, was extracted from an annually survey 1. The survey inquires about capital expenditures and operating cost associated with pollution abatement efforts. Data from survey are tabulated by industry and type of cost. The explanatory variables are cluster it in several dimensions plant characteristics, market incentive, communities characteristics and regulation intensity. The establishment characteristics, refer to the economical and financial information, were extracted from plant financial reports. Also we identified the firms who were traded on the capital market mean listed at Bucharest Stock Exchange and the firms certified ISO 14001, information obtained from Romanian Accreditation Association. The community characteristics were obtained from National Institute of Statistic except for the number of the environmental ONG which come from Ministry of Environment. Using the information from Environmental Guard we constructed the proxy variable which
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