Abstract not found

For the last ten years environmentalists and the trade policy community have engaged in a heated debate over the environmental consequences of liberalized trade. The debate was originally fueled by negotiations over the North American Free Trade Agreement and the Uruguay round of GATT negotiations, both of which occurred at a time when concerns over global warming, species extinction and industrial pollution were rising. Recently it has been intensified by the creation of the World Trade Organization (WTO) and proposals for future rounds of trade negotiations. The debate has often been unproductive. It has been hampered by the lack of a common language and also suffered from little recourse to economic theory and empirical evidence. The purpose of this essay is set out what we currently know about the environmental consequences of economic growth and international trade. We critically review both theory and empirical work to answer three basic questions. What do we know about the relationship between international trade, economic growth and the environment? How can this evidence help us evaluate ongoing policy debates? Where do we go from here?

Because the enormous health consequences of its degradation do matter for households, indoor air quality offers a natural setting in which use of household data can avoid difficulties that plague aggregate estimation of income effects that underlie environmental Kuznets curves (EKCs). Such micro-level evidence is new to the literature, and also provides the empirical underpinning for working from household preferences through to voting and the environmental regulations linked to EKCs. Relevant income effects are obtained from Engel curves for the fuel choices that determine indoor air quality. Using the World Bank’s LSMS data set for Pakistan, and in keeping with our household modeling (Pfaff, Chaudhuri and Nye (2001), we estimate ‘traditional ’ and ‘modern ’ fuels-usage regressions and simulate the implied relationship between income and indoor air quality. Under a range of plausible fuel-emissions assumptions, we find a U-shaped relationship.

What determines the relationship between pollution and growth? Are the forces that explain the behavior over time of these quantities potentially useful to understand more generally the relationship between policies and growth? In this paper, we make a first attempt to analyze the equilibrium behavior of two quantities—the level of pollution and the level of income—in a setting in which societies choose, via voting, how much to regulate pollution. Our major finding is that, consistent with the evidence, the relationship between pollution and growth need not be monotone and that the precise equilibrium nature of the relationship between the two variables depends on whether individuals vote over effluent charges or directly restrict the choice of technology. Moreover, our analysis of the pollution problem suggests that, more generally, endogenous policy choices should be taken seriously as potential sources of heterogeneity when studying cross country differences in economic performance.

By now the observation that some pollutants appear to increase and then decrease with economic development has become a widely accepted stylized fact. This paper argues that the fundamental insight of the empirical literature is merely that pollution does not necessarily increase with economic growth, and that the fundamental insight of the theoretical literature is that the observed inverse-U-shaped pollution-income relationship is neither necessary nor sufficient for Pareto-efficient environmental policies. Furthermore, the inverse-U-shaped path is not unique to environmental phenomenon, and may exist wherever a desirable good generates an undesirable side-effect. Finally, all of these points can be made without most of the econometric or theoretical mechanics that fill this literature.

This paper introduces endogenous and directed technical change in a growth model with environmental constraints and limited resources. A unique final good is produced by combining inputs from two sectors. One of these sectors uses “dirty ” machines and thus creates environmental degradation. Research can be directed to improving the technology of machines in either sector. We characterize dynamic tax policies that achieve sustainable growth or maximize intertemporal welfare, as a function of the degree of substitutability between clean and dirty inputs, environmental and resource stocks, and cross-country technological spillovers. We show that: (i) in the case where the inputs are suffi-ciently substitutable, sustainable long-run growth can be achieved with temporary taxation of dirty innovation and production; (ii) optimal policy involves both “carbon taxes ” and research subsidies, so that excessive use of carbon taxes is avoided; (iii) delay in intervention is costly: the sooner and the stronger is the policy response, the shorter is the slow growth transition phase; (iv) the use of an exhaustible resource in dirty input production helps the switch to clean innovation under laissez-faire when the two inputs are substitutes. Under reasonable parameter values (corresponding to those used in existing models with exogenous technology) and with suffi cient substitutability between inputs, it is

We contrast effects of taxing non-renewable resources with the effects of traditional capital taxes and investment subsidies in an endogenous growth model. In a simple framework we demonstrate that when non-renewable resources are a necessary input in the sector where growth is ultimately generated, interest income taxes and investment subsidies can no longer affect the long-run growth rate, whereas resource tax instruments are decisive for growth. The results stand out both against observations in the literature from the 1970’s on non-renewable resources and taxation -observations which were not based on general equilibrium considerations- and against the general view in the newer literature on taxes and endogenous growth which ignores the role of non-renewable resources in the “growth engine”.

The exact specification and motivation of the Environmental Kuznets Curve (EKC) is the subject of a vast literature in environmental economics. A remarkably diverse set of econometric approaches has been employed to support or reject a specific relationship between environmental quality and pollution. Nevertheless, methods employed to date have not addressed the issue of model uncertainty, given that a sizable number of competing theories exist that can explain the income/pollution relationship. We introduce Bayesian Model Averaging to the EKC analysis to examine a) whether a sulphur dioxide EKC exists, and if so, b) which income/pollution specification is most strongly supported by the data. We find only weak support for an EKC, which disappears altogether when we address oversampling issues in the data. In contrast, our results highlight the relative importance of political economy and site-specific variables in explaining pollution outcomes. Trade is also shown to play an important indirect role. It moderates the influence of the composition effect on pollution. Our findings run contrary to the deterministic view of the income/pollution relationship that is persistent in the literature.

The paper analytically explores the optimal policy mix between mitigation and environmental adaptation against climate change at a macroeconomic level. The constructed economicenvironmental model is formulated as a social planner problem with the adaptation and abatement investments as separate decision variables. The authors prove the existence of a unique steady state and provide a comparative static analysis of the optimal investment. It leads to essential implications for associated long-term environmental policies. In particular, the dependence of the optimal ratio between abatement and adaptation investments on economic efficiency appears to have an inverted U-shape. Data calibration and numerical simulation are provided to illustrate theoretical outcomes.

The literature that tests for U-shaped relationships using panel data, such as those between pollution and income or inequality and growth, reports widely divergent (parametric and non-parametric) empirical findings. We explain why lack of identification lies at the root of these differences. To deal with this lack of identification, we propose an identification strategy that explicitly distinguishes between what can be identified on the basis of the data and what is a consequence of subjective choices due to a lack of identification. We apply our methodology to the pollution-income relationship of both CO2 and SO2 emissions. Interestingly, our approach yields estimates of both income (scale) and time (composition and/or technology) effects for these reduced-form relationships that are insensitive to the required subjective