Environmental policies and productivity growth: Evidence across industries and firms

This paper investigates the impact of changes in environmental policy stringency on industry- and firm-level productivity growth in a panel of OECD countries. To test the strong version of the Porter Hypothesis (PH), we extend a neo-Schumpeterian productivity model to allow for effects of environmental policies. We use a new environmental policy stringency (EPS) index and let the effect of countries׳ environmental policies vary with the pollution intensity of the industry and with the countries’ and firms’ technological advancement. A tightening of environmental policy is associated with a short-term increase in industry-level productivity growth in the most technologically-advanced countries. This effect diminishes with the distance to the global productivity frontier, eventually becoming insignificant. For the average firm, no evidence of PH is found. However, the most productive firms see a temporary boost in productivity growth, while the less productive ones experience a productivity slowdown.     

Is a voluntary approach an effective environmental policy instrument?: A case for environmental management systems

Using Japanese facility-level data from an OECD survey, we estimate the effects of implementation of ISO14001 and publication of environmental reports on the facilities’ environmental performance. While most previous studies focused on an index of emissions toxicity, this study examines three areas of impacts, none of which have been explored in the literature: natural resource use, solid waste generation, and wastewater effluent. The study is also unique in that the effectiveness of ISO14001 is considered in relation to environmental regulations. Our findings are summarized as follows. First, both ISO14001 and report publication help reduce all three impacts; the former appears more effective in all areas except wastewater. Second, environmental regulations do not weaken the effect of ISO14001. Third, assistance programs offered by local governments—a voluntary approach—promote facilities’ adoption of ISO14001. These findings suggest that governments can use command-and-control and voluntary approaches concurrently.     

Is ISO 14001 a gateway to more advanced voluntary action? The case of green supply chain management

Using Japanese facility-level data, we estimate the effects of ISO 14001 certification on the promotion of more advanced practices, namely green supply chain management (GSCM). Our results show that ISO 14001 promotes GSCM practices. Facilities with environmental management systems (EMS) certified to ISO 14001 are 40% more likely to assess their suppliers' environmental performance and 50% more likely to require that their suppliers undertake specific environmental practices. Further, government programs that encourage voluntary EMS adoption indirectly promote GSCM practices. These programs increase the probabilities that facilities will assess their suppliers' environmental performance and require suppliers to undertake specific environmental practices by 7% and 8%, respectively. Combined, these findings suggest that there may be significant but previously unnoticed spillover effects of ISO 14001 and government promotion of voluntary action.     

Measurement of agricultural total factor productivity growth incorporating environmental factors: A nutrients balance approach

This article proposes to use nutrient-orientated environmental efficiency (EE) measures to construct a nutrient total factor productivity index (NTFP). Since nutrient-orientated EE measures are consistent with the materials balance principle, NTFP index is superior to other existing TFP indexes. An empirical study on the environmental performance of an agricultural sector in 30 OECD countries from 1990 to 2003 yielded several important findings. First, these countries should be able to produce current outputs with at least 50% less aggregate eutrophying power, implying that they should have been able to substantially reduce the potential for eutrophication. Second, traditional TFP has grown by 1.6% per annum due to technical progress; however, there are lags in the responses of several countries to this technical progress. Third, environmental TFP has grown at a slower rate than traditional TFP growth due to reductions in nutrient-orientated allocative efficiency. Finally, changes in input combinations could have significantly improved environmental efficiency and productivity. These findings favor policy interventions and faster technological transfer to improve environmental performance.     

From data and theory to environmental models and indices formation

A prerequisite for environmental indices is that they represent environmental pressure, and the state of, and impact on environmental conditions. In other words, they should capture as much as possible of the cause-effect chains they represent and relate pressure and effect to criteria of environmental quality. The approach proposed in the article attempts to link the pressure–state–impact–response framework of indicators to the integrated environmental model, based on the method of response function (MRF). The MRF allows to construct purposeful, credible models from data and prior knowledge or information. The data are usually time series observations of system inputs and outputs, and sometimes of internal states. The output of such models is presented with highly aggregated environmental indices, reflecting the main pressure–state–impact–response cause-effect chains. The proposed approach is illustrated with the example of soil erosion indices.     

Nutrient criteria for lakes,ponds, and reservoirs: A Bayesian TREED model approach

We develop regional-scale eutrophication models for lakes, ponds, and reservoirs to investigate the link between nutrients and chlorophyll-a. The Bayesian TREED (BTREED) model approach allows association of multiple environmental stressors with biological responses, and quantification of uncertainty sources in the empirical water quality model. Nutrient data for lakes, ponds, and reservoirs across the United States were obtained from the Environmental Protection Agency (EPA) National Nutrient Criteria Database. The nutrient data consist of measurements for both stressor variables (such as total nitrogen and total phosphorus), and response variables (such as chlorophyll-a), used in the BTREED model. Markov chain Monte Carlo (McMC) posterior exploration guides a stochastic search through a rich suite of candidate trees toward models that better fit the data. The Bayes factor provides a goodness of fit criterion for comparison of resultant models. We randomly split the data into training and test sets; the training data were used in model estimation, and the test data were used to evaluate out-of-sample predictive performance of the model. An average relative efficiency of 1.02 between the training and test data for the four highest log-likelihood models suggests good out-of-sample predictive performance. Reduced model uncertainty relative to over-parameterized alternative models makes the BTREED models useful for nutrient criteria development, providing the link between nutrient stressors and meaningful eutrophication response.     

Pollution and Capital Markets in Developing Countries

It is said that firms in developing countries do not have incentives to invest in pollution control because of weak implementation of environmental regulations. This argument assumes that the regulator is the only agent that can create incentives for pollution control, and ignores that capital markets, if properly informed, may provide the appropriate financial and reputational incentives. We show that capital markets in Argentina, Chile, Mexico, and the Philippines do react to announcements of environmental events, such as those of superior environmental performance or citizens' complaints. A policy implication is that environmental regulators in developing countries may explicitly harness those market forces by introducing structured programs of information release pertaining to firms' environmental performance: public disclosure mechanisms in developing countries may be a useful model to consider given limited government enforcement resources.     

Good news for environmental self-regulation? Finding the right link

We investigate the stock market response to firm disclosure of positive environmental information and the link from that information to environmental outcomes. We classify environmental media releases by informational content and value relevance, and assess the abnormal stock returns of each type of event. While announcements of future environmental activities lead to the largest favorable stock market reactions, there is no guaranteed link from this type of information to environmental outcomes. Further analysis of the abnormal returns shows that the magnitude of the stock market reaction depends on firm financial characteristics across all event types rather than on firm environmental performance. Our results indicate that the ability for voluntary environmental information disclosure to induce environmental self-regulation is limited to the extent that firms are able to follow through with their announcements of planned environmental activities.     

A weight-adjusted Peto’s test when cause of death is not assigned

A new statistical testing approach using a weighted logrank statistic is developed for rodent tumorigenicity assays that have a single terminal sacrifice but not cause-of-death data. Instead of using cause-of-death assignment by pathologists, the number of fatal tumors is estimated by a constrained nonparametric maximum likelihood estimation method. For data lacking cause-of-death information, the Peto test is modified with estimated numbers of fatal tumors and a Fleming–Harrington-type weight, which is based on an estimated tumor survival function. A bootstrap resampling method is used to estimate the weight function. The proposed testing method with the weight adjustment appears to improve the performance in various situations of single-sacrifice animal experiments. A Monte Carlo simulation study for the proposed test is conducted to assess size and power of the test. This testing approach is illustrated using a real data set.     

Competitive investment in clean technology and uninformed green consumers

In a market where consumers and the regulatory authorities are not fully informed about the actual production technology or environmental performance of firms that engage in strategic competition, I study the effect of environmental consciousness of consumers on firms׳ incentive to invest in cleaner technology. Firms compete in prices and may signal their environmental performance to uninformed consumers through prices. I also analyze the effect of an expected liability on firms in this setting. Compared to full information, incomplete information generates higher strategic incentive to invest in cleaner technology particularly when consciousness and/or expected liability are not too high. Requiring mandatory disclosure of technology or environmental performance may discourage such investment. Even though consumers and the regulator are uninformed, competition has a positive effect (relative to monopoly) on the incentive to invest.     

Experimental and environmental factors affect spurious detection of ecological thresholds

Threshold detection methods are increasingly popular for assessing nonlinear responses to environmental change, but their statistical performance remains poorly understood. We simulated linear change in stream benthic macroinvertebrate communities and evaluated the performance of commonly used threshold detection methods based on model fitting (piecewise quantile regression [PQR]), data partitioning (nonparametric change point analysis [NCPA]), and a hybrid approach (significant zero crossings [SiZer]). We demonstrated that false detection of ecological thresholds (type I errors) and inferences on threshold locations are influenced by sample size, rate of linear change, and frequency of observations across the environmental gradient (i.e., sample-environment distribution, SED). However, the relative importance of these factors varied among statistical methods and between inference types. False detection rates were influenced primarily by user-selected parameters for PQR (tau) and SiZer (bandwidth) and secondarily by sample size (for PQR) and SED (for SiZer). In contrast, the location of reported thresholds was influenced primarily by SED. Bootstrapped confidence intervals for NCPA threshold locations revealed strong correspondence to SED. We conclude that the choice of statistical methods for threshold detection should be matched to experimental and environmental constraints to minimize false detection rates and avoid spurious inferences regarding threshold location.     

Cap-and-trade, taxes, and distributional conflict

Enacting market-based environmental regulation, such as emissions taxes and cap-and-trade programs, often create rents that are contested by agents. In this paper, we create a framework that compares social welfare from alternative market-based environmental policy instruments under the presence of rent seeking. We show that, contrary to the commonly held view, non-revenue-raising instruments (NRRIs) are in many cases preferable over revenue-raising instruments (RRIs). We find that the choice of instrument depends on the size of a potential revenue-recycling effect and the level of preassigned rents.     

Double-dipping in environmental markets

There is an increasing tendency to use markets to induce the provision of environmental services. As such markets increase in scope, potential market participants might sell multiple environmental services. The question we consider here is whether participants in such markets should be allowed to sell credits in more than one market simultaneously. Some have argued in favor of such “double-dipping”, because it would make the provision of environmental services more profitable. In practice however, most programs do not allow double-dipping. We show that if the optimal level of pollution abatement is sought, then double-dipping maximizes societal net benefits. However, if pollution policies are set in a piecemeal fashion, then the caps for each market are unlikely to be optimal and, in this second-best setting, a policy prohibiting double-dipping can lead to greater social net benefits. We explore conditions under which a single-market policy is preferred, or equivalently, where piecemeal policies are likely to yield particularly inefficient outcomes.     

Investigating potential for effects of environmental endocrine disrupters on wild populations of amphibians in UK and Japan: status of historical databases and review of methods.

Concern over global declines among amphibians has resulted in increased interest in the effects of environmental contaminants on amphibian populations, and more recently, this has stimulated research on the potential adverse effects of environmental endocrine disrupters in amphibians. Laboratory studies of the effects of single chemicals on endocrine-relevant endpoints in amphibian, mainly anuran, models are valuable in characterizing sensitivity at the individual level and may yield useful bioassays for screening chemicals for endocrine toxicity (for example, thyroid disrupting activity). Nevertheless, in the UK and Japan as in many other countries, it has yet to be demonstrated unequivocally that the exposure of native amphibians to endocrine disrupting environmental contaminants results in adverse effects at the population level. Assessing the potential of such effects is likely to require an ecoepidemiological approach to investigate associations between predicted or actual exposure of amphibians to (endocrine disrupting) environmental contaminants and biologically meaningful responses at the population level. In turn, this demands recent but relatively long-term population trend data. We review two potential sources of such data for widespread UK anurans that could be used in such investigations: records for common frogs and common toads in several databases maintained by the Biological Records Centre (UK Government Centre for Ecology and Hydrology), and adult toad count data from 'Toads on Roads' schemes registered with the UK wildlife charity 'Froglife'. There were little abundance data in the BRC databases that could be used for this purpose, while count data from the Toads on Roads schemes is potentially confounded by the effects of local topology on the detection probabilities and operation of nonchemical anthropogenic stressors. For Japan, local and regional surveys of amphibians and national ecological censuses gathering amphibian data were reviewed to compile survey methodologies and these were compared with methods used in the UK and other countries. Substantial consensus exists in amphibian survey methodologies and this should be exploited in the initiation of coordinated monitoring programs for widespread and common anuran amphibians in Japan and the UK to generate long-term robust and standardized population trend data. Such data would support comparative ecoepidemiological assessments of the impact of environmental endocrine disrupters in these two cooperating countries.     

A Revealed Preference Approach to Estimating Supply Curves for Ecosystem Services: Use of Auctions to Set Payments for Soil Erosion Control in Indonesia

Abstract:  To supply ecosystem services, private landholders incur costs. Knowledge of these costs is critical for the design of conservation-payment programs. Estimating these costs accurately is difficult because the minimum acceptable payment to a potential supplier is private information. We describe how an auction of payment contracts can be designed to elicit this information during the design phase of a conservation-payment program. With an estimate of the ecosystem-service supply curve from a pilot auction, conservation planners can explore the financial, ecological, and socioeconomic consequences of alternative scaled-up programs. We demonstrate the potential of our approach in Indonesia, where soil erosion on coffee farms generates downstream ecological and economic costs. Bid data from a small-scale, uniform-price auction for soil-conservation contracts allowed estimates of the costs of a scaled-up program, the gain from integrating biophysical and economic data to target contracts, and the trade-offs between poverty alleviation and supply of ecosystem services. Our study illustrates an auction-based approach to revealing private information about the costs of supplying ecosystem services. Such information can improve the design of programs devised to protect and enhance ecosystem services.     

Environmental public health tracking: piloting methods for surveillance of environmentally related diseases in England and Wales

An effective environmental public health tracking system integrates data and intelligence on environmental hazards, exposures, and health outcomes to focus interventions on reducing the impact of environmental contamination on public health. Most work in this area in the UK has focused on assessing data on hazards that are relatively easy to obtain. However, most hazards will present no actual risk and information on exposure is required to make an effective risk assessment. Obtaining exposure data is technically challenging, expensive, and potentially raises ethical concerns. Consequently, the Health Protection Agency is exploring methods for targeting geographical zones for efficient detailed environmental assessment (including exposure assessment). This paper describes and assesses three methods (indirect standardization, statistical process control (SPC) and kernel density contouring) for the surveillance of potentially environmentally related diseases for this purpose. While the evaluation demonstrates the utility of the three methods, particularly SPC, the comparison was limited due to ethical approval issues.     

Differentiated impacts of environmental policies on the Colombian Frontier: coercive conservation and containment of illicit activities in the Pacific and the Ariari region

ABSTRACT

This article, through the use of political ecology perspectives on coercive conservation, aims to explain how in two separate Colombian Natural Parks and buffer zones, environmental policies designed to (re)take control of the frontier, have produced a similar territorial differentiation in the contention of illicit activities. Los Farallones in the Colombian Pacific and La Macarena/Puerto Rico in the Ariari region have experienced different stages of the armed conflict and are at the center of this analysis. I argue that in the contexts of both conflict escalation (1998–2007) and conflict de-escalation (2008–2016), the State in its attempt to control the frontier has not only had military intervention in areas of conservation but has also reinforced environmental programs that attack illegal mining and coca, producing both a territorially differentiated containment of illicit activities and an uneven progression of the illicit frontier.     

Comparison of six correlative models in predictive vegetation mapping on a local scale

A variety of statistical techniques has been used in predictive vegetation modelling (PVM) that attempt to predict occurrence of a given community or species in respect to environmental conditions. We compared the performance of three profile models, BIOCLIM, GARP and MAXENT with three nonparametric models of group discrimination techniques, MARS, NPMR and LRT. The two latter models are relatively new statistical techniques that have just entered the field of PVM. We ran all models on a local scale for a given grassland community (Teucrio-Seslerietum) using the same input data to examine their performance. Model accuracy was evaluated both by Cohen’s kappa statistics (κ) and by area under receiver operating characteristics curve based both on resubstitution of training data and on an independent test data set. MAXENT of profile models and MARS of group discrimination techniques achieved the best prediction.     

Composite likelihood approach to the regression analysis of spatial multivariate ordinal data and spatial compositional data with exact zero values

In many environmental and ecological studies, it is of interest to model compositional data. One approach is to consider positive random vectors that are subject to a unit-sum constraint. In landscape ecological studies, it is common that compositional data are also sampled in space with some elements of the composition absent at certain sampling sites. In this paper, we first propose a practical spatial multivariate ordered probit model for multivariate ordinal data, where the response variables can be viewed as the discretized non-negative compositions without the unit-sum constraint. We then propose a novel two-stage spatial mixture Dirichlet regression model. The first stage models the spatial dependence and the presence of exact zero values, and the second stage models all the non-zero compositional data. A maximum composite likelihood approach is developed for parameter estimation and inference in both the spatial multivariate ordered probit model and the two-stage spatial mixture Dirichlet regression model. The standard errors of the parameter estimates are computed by an estimate of the Godambe information matrix. A simulation study is conducted to evaluate the performance of the proposed models and methods. A land cover data example in landscape ecology further illustrates that accounting for spatial dependence can improve the accuracy in the prediction of presence/absence of different land covers as well as the magnitude of land cover compositions.     

Voluntary environmental regulation in developing countries: Mexico’s Clean Industry Program

Because conventional command-and-control environmental regulation often performs poorly in developing countries, policymakers are increasingly experimenting with alternatives, including voluntary regulatory programs. Research in industrialized countries suggests that such programs are sometimes ineffective, because they mainly attract relatively clean participants free-riding on unrelated pollution control investments. We use plant-level data on more than 100,000 facilities to analyze the Clean Industry Program, Mexico’s flagship voluntary regulatory initiative. We seek to identify the drivers of participation and to determine whether the program improves participants’ environmental performance. Using data from the program’s first decade, we find that plants recently fined by environmental regulators were more likely to participate, but that after graduating from the program, participants were not fined at a substantially lower rate than nonparticipants. These results suggest that although the Clean Industry Program attracted dirty plants under pressure from regulators, it did not have a large, lasting impact on their environmental performance.