The general argument presented by Arrow et al. runs as follows: government regulation might improve on free market outcomes, since markets sometimes misallocate resources. However, the costs of regulations need to be assessed against their presumed benefits. Benefit-cost analysis is a valuable technique for making such an assessment, even though it was developed for the appraisal of physical investment projects. However, since the technique is not perfect, it should not provide the only input into the process, but rather be part of an array of evidence.

Considerable interest has focused on the possible existence of an environmental Kuznets curve, whereby pollution first increases but later falls with increasing income. Empirical studies have concentrated on a wide spectrum of countries and run into inevitable problems of data comparability and quality. We avoid these problems by looking at seven types of air emissions across the 50 US states and find all seven pollutants decrease with increasing per capita income. We also find strong evidence of heteroscedasticity with respect to the income–emissions relationship: lower-income states display much greater variability in per capita emission levels than higher-income states. Additionally, we look at the best measured of these emissions, air toxics, for the period 1988–94. Using a simple sign test, we find support for the notion that an increase in income is associated with a decrease in per capita emissions. However, the change in emissions appears to be unrelated to the magnitude of the change in income. We do find, though, that the reduction in per capita emissions is increasing both in terms of the 1988 level of per capita emissions and income. Possible implications of these results for the development process are discussed.

Environmental Kuznets curve (EKC) analysis links changes in environmental quality to national economic growth. The reduced form models, however, do not provide insight into the underlying processes that generate these changes. We compare EKC models to structural transition models of per capita CO2 emissions and per capita GDP, and find that, for the 16 countries which have undergone such a transition, the initiation of the transition correlates not with income levels but with historic events related to the oil price shocks of the 1970s and the policies that followed them. In contrast to previous EKC studies of CO2 the transition away from positive emissions elasticities for these 16 countries is found to occur as a sudden, discontinuous transition rather than as a gradual change. We also demonstrate that the third order polynomial 'N' dependence of emissions on income is the result of data aggregation. We conclude that neither the 'U'- nor the 'N'-shaped relationship between CO2 emissions and income provide a reliable indication of future behaviour.

The growing impact of regulations on the economy has led both Congress and the Administration to search for new ways of reforming the regulatory process. Many of these initiatives call for greater reliance on the use of economic analysis in the development and evaluation of regulations. One specific approach being advocated is benefit-cost analysis, an economic tool for comparing the desirable and undesirable impacts of proposed policies.

The reduced-form approach to the income–environment relationship has been a useful first step towards answering the question of how economic growth affects the environment. However, without an explicit consideration of the underlying determinants of environmental quality, the scope for policy intervention is unduly circumscribed. In this paper a modest attempt is made to incorporate explicit policy considerations into the income–environment relationship and to explore its determinants as a step towards a better understanding of this relationship and its potential as a policy tool. The role of the rate of economic growth and population density is also explored. A main finding is that at least in the case of ambient SO2 levels, policies and institutions can significantly reduce environmental degradation at low income levels and speed up improvements at higher income levels, thereby flattening the EKC and reducing the environmental price of economic growth.

The thrust of the principles enunciated in Arrow et al. is that economic benefits and costs can be a great help in organizing disparate concerns, in identifying issues, and in designing regulatory policies and individual projects with environmental impact. While this true, I must disagree with the authors that 'formal benefit-cost analysis should not be viewed as either necessary or sufficient for designing sensible public policy' (p. 201). At least there can be little doubt that cost-benefit analysis is necessary for sensible policy. I comment below from the perspective of devloping countries.

Environmental Kuznets curves have been estimated using a simple reduced-form model that gives no information on the mechanisms underlying the estimated inverted U-shaped relationship between some pollutants and income. Various intuitive appealing explanations for the observed patterns have been offered, such as structural changes and environmental policy, but these have rarely been empirically investigated. Expanding the reduced-form model with explanatory variables may introduce serious multicollinearity problems, a reason why decomposition analysis is a preferable alternative for investigating the origins of change in emissions. Applying decomposition analysis fails to find evidence for structural changes as an important determinant of the impressive reductions in SO2 emissions of developed economies during the 1980s. Environmental policy, fostered by international agreements, gives a better explanation why pollution curbs downward at high income levels. Besides the level of income, the present state of the environment seems an important, but often neglected, variable that explains the ambition of environmental policy.

Arrow et al. revisit the case for using benefit-cost analysis in a developed country, the USA, where markets work reasonably efficiently and where the capacity to implement such studies is undoubted. Their recommendations deserve wholehearted support in that context, particularly their recommendation 1 calling for a comparison of gains and losses from regulatory actions. Those who have not worked in government will recognise that most decisions are not in fact made with any form of calculus that we might describe as 'cost benefit thinking'. Indeed, the whole process of policy priority setting is all too often ad hoc, reactive, crisis-based and over-responsive to often ill-informed pressure groups (of all kinds).

This paper extends previous empirical studies of the environmental Kuznets curve by examining the role of rising incomes in promoting development of new technologies directed toward environmental improvements. The main result, based on an analysis of data from 19 OECD countries for the period 1980–94, shows that the income elasticity of public research and development funding for environmental protection is positive, and may be close to unity. This finding suggests that emissions of at least some pollutants may decline with income after a threshold level of income is reached. However, this should be interpreted cautiously in light of: (1) the small size of public research and development funding relative to overall spending on environmental protection, (2) the ability of a country to substitute between public and private research and development expenditures, as well as among alternative policy instruments, and (3) the possibility that public research and development funding may be a form of industrial subsidy in some countries.

Can benefit-cost analysis (BCA) be used in the developing world in the same way in which it is used in developed market economies? The paper by Arrow et al. makes a good case for employing BCA to evaluate environmental, health, and safety regulations in the United States. It offers a number of principles to guide the use of benefit-cost analyses, some of which can be applied to developing countries. Conservation policies in the tropics can help illustrate the relevance of BCA for evaluating regulations in less industrialized countries. I use a set of studies on the Mantadia National Park to show in practical terms how and when BCA can serve as an effective evaluative tool.

Among the tools of the economic trade, cost-benefit analysis is the most widely used in policy circles. Asking whether there is a role for cost-benefit analysis is like asking whether there is a role for the weatherman. Of course there is.