Journal of Environmental Economics and Management最新文献

The future of travel will be characterized by changes in weather patterns and changes in transportation technology. How will these forces interact? We explore this question by utilizing a unique randomized experiment with Uber riders in Cairo, Egypt. We consider how very hot days ($>$35 °C/95 °F) affect transportation choices, how a sizeable price decrease (simulating a future with autonomous vehicles and access to cheaper transportation) changes travel, and how the interaction of these two elements affects choices. We find that while travel will increase significantly in response to the price decrease, extreme weather dampens this effect by 21%. Individuals receiving subsidies also shift away from public transportation modes and towards private transportation modes, except when the public transit option is air-conditioned. These results provide important insights for policymakers when considering optimal travel policy in the face of climate change.

This paper estimates the mortality impacts of ozone pollution in China and the moderating effects of two possible adaptation strategies. Using an instrument variable constructed from ozone concentrations of nearby upwind cities, we find that ozone pollution significantly increases all-cause, cardiovascular, and respiratory mortality. Healthcare service provision significantly decreases the impacts of ozone pollution on all-cause and cardiovascular mortality, but does not moderate the impact on respiratory mortality. The impact of ozone on RES mortality declines after COVID-19. Healthcare service provision also reduces the distributional impact of ozone across the elderly and younger groups. Projection shows that climate change would induce mortality costs of 0.08% of China's GDP through increasing ozone pollution.

This paper estimates flexible demand systems for heterogeneous households in the United States and links the estimated parameters with an economy-wide model to assess their relative contributions to the social cost of regulation. We estimate elasticities for several final demand categories as well as labor-leisure elasticities that are important for calibrating the labor-leisure choice in the economy-wide model and find that estimated elasticities are relatively similar across regions but vary meaningfully by income. Using the estimated elasticities, we explore the implications of both the functional form and its parameterization in a simplified computable general equilibrium model for the social and distributional costs of illustrative policy scenarios. Model variants with less flexible consumer demand systems overestimate social costs across our entire range of scenarios. Furthermore, we find that parameterizing the model with elasticities that vary with household income is important for adequately characterizing the distributional implications of a policy.

Oil palm remains an important source of rural income in South East Asia. At the same time, Indonesia has become a hotspot for large-scale species extinction and a loss of biodiversity in favor of agricultural production. The present study sets out to assess the environmental performance of smallholder oil palm production with respect to biodiversity. Using a panel dataset that combines conventional farm data together with an account of plant diversity, we estimate a restricted hyperbolic environmental distance function. We integrate loss of biodiversity as an undesirable output into the production model which allows explaining shortfalls in environmental performance and the derivation of shadow prices of biodiversity conservation. We find a substantial environmental inefficiency, which is partly explained by both chemical and manual weeding practices, highlighting the potential for improvements in both the environmental and the economic dimension. Moreover, the value for conserving one species of the average biodiversity on a farmers plantation was 325 USD in 2018. Payments for ecosystem services schemes could be a viable policy response to conserve meaningful levels of biodiversity while simultaneously allowing smallholders to increase palm oil output. In general, addressing drivers of environmental performance in PES designs amplifies its effect without reducing output.

The damage function used to assess the economic impact of secular changes in temperature is one of the most speculative components of integrated assessment models of climate change. Existing work informing this debate is based on pooled empirical models incorporating limited non-linearity and giving little regard to dynamics. We use aggregate and agricultural data for 151 countries over the past six decades to estimate dynamic heterogeneous models which (a) allow the weather-output nexus to differ freely across countries, (b) help distinguish short-run from long-run effects, and (c) account for unobserved time-varying heterogeneity. Overall, we find that, in low-income or high-temperature countries, a permanent 1 °C rise in temperature is associated with a fall in income per capita of about 1.3% in the short-run and 8.5% in the long run. These long-run effects are substantially larger than those commonly suggested in the literature.

In a trade model with endogenous emissions abatement, we investigate the impact of three policy instruments aimed at mitigating carbon leakage: free emission allowances, a Carbon Border Adjustment Mechanism (CBAM), and a CBAM with export rebates. We show that providing free allowances does not alter the incentives to abate carbon emissions, but, instead fosters the entry of more carbon intensive producers. This “levels the playing field” both domestically and internationally, and may even reverse carbon leakage. In contrast, a CBAM only levels the playing field domestically, and may lead to an autarky equilibrium. To reverse carbon leakage, a CBAM must be complemented with export rebates. We further show that a CBAM and export rebates improve welfare for any carbon price, and we identify the optimal share of free allowances with or without a CBAM. Finally, we perform a calibration exercise on cement and steel sectors to simulate the effects of the CBAM recently adopted by the European Union. Our model predicts a scenario with reverse carbon leakage and significant welfare gains for both sectors.

The application of quasiexperimental impact evaluation to remotely sensed measures of deforestation has yielded important evidence detailing the effectiveness of conservation policies. However, researchers have paid insufficient attention to the binary and nonrepeatable structure of most deforestation datasets. Using analytical proofs and simulations, we demonstrate that many commonly employed econometric approaches are biased when applied to binary and nonrepeatable outcomes. The significance, magnitude and even direction of estimated effects from many studies are likely incorrect, threatening to undermine the evidence base that underpins conservation policy adoption and design. To address these concerns, we provide guidance and new strategies for the design of panel econometric models that yield more reliable estimates of the impacts of forest conservation policies.

Climate policy needs to set incentives for investors who face imperfect, distorted markets and large uncertainties about the costs and benefits of abatement. These investors decide on uncertain investments according to their expected return and risk (carbon beta). We study carbon pricing and financial incentives in a consumption-based asset pricing model distorted by technology spillovers and time-inconsistency. We find that both distortions reduce the equilibrium asset return and delay investment in abatement. However, their effect on the carbon beta and the risk premium for abatement can be decreasing (when innovation spillovers are not anticipated) or increasing (when climate policy is not credible). We show that the distortions can be overcome by modified carbon pricing by a regulator, or by financial incentives, implemented in our model by a long-term investment fund. The fund pays a subsidy to reduce technology costs or offers financial contracts to boost investment returns to complement the carbon price. The investment fund can thus pave the way for carbon pricing in later periods by preventing a capital misallocation that would be too expensive to correct, thus improving the feasibility of ambitious carbon pricing.

Short-term weather forecasts, a common and popular public good in the modern world, affect labor decisions regarding time allocations. This study uses a novel dataset of city-level day-ahead weather forecasts in China, collected through video transcriptions of the country’s popular TV program spanning over 2000 days since 2010. I estimate the number of hours laborers worked in a day as flexible functions of the daily maximum temperature forecast under different historical levels of forecast accuracy (represented by half-year rolling daily maximum temperature forecast root-mean-squared-error, $RMSE$). The results suggest large-magnitude (up to 4.5 and 1.2 h per day) labor decreases under uncomfortable temperature forecasts (extreme heat above $30{}^{\circ }C$ and medium cold $15{}^{\circ }C\text{–}25{}^{\circ }C$), but only when forecasts are accurate ($RMSE\approx 1{}^{\circ }C$). The economic value of accurate weather forecasts is assessed by modeling this labor adaptation to forecasts. Specifically, 930 Yuan (148 USD, in 2015 currency) is gained per worker per year, with each $1{}^{\circ }C$ decrease in the city forecast $RMSE$. For the entire country, an average 3.9% increase in city-level forecast accuracy for 2011–2015 generates a considerable social benefit of 25.3 billion Yuan (4.03 billion USD) annually from the labor sector alone, nearly covering the annual cost of the national weather forecasting system.

Many renewable natural resources have been extracted beyond sustainable levels. While some resource stocks have recovered, others are still over-extracted, causing substantial economic losses. This paper develops a model motivated by empirical facts about resource use and regulation to understand these patterns. The model is a dynamic model of a dual economy with technological progress, structural change, and costly resource regulation. Based on this model, we show that technological progress explains the initial increase in resource use. Technological progress also induces structural change and a decline in resource users. While the declining number of resource users does not directly lead to resource recovery, it does reduce regulatory costs, paving the way for resource regulation and recovery. Our results show that although technological progress can contribute to resource degradation, it also helps resource recovery through reduced regulatory costs. Our results suggest further that a temporal use beyond sustainable levels can be socially optimal until regulatory costs fall below the benefits of regulation.