Urban heat stress poses a major risk to public health. Case studies of individual cities suggest that heat exposure, like other environmental stressors, may be unequally distributed across income groups. There is little evidence, however, as to whether such disparities are pervasive. We combine surface urban heat island (SUHI) data, a proxy for isolating the urban contribution to additional heat exposure in built environments, with census tract-level demographic data to answer these questions for summer days, when heat exposure is likely to be at a maximum. We find that the average person of color lives in a census tract with higher SUHI intensity than non-Hispanic whites in all but 6 of the 175 largest urbanized areas in the continental United States. A similar pattern emerges for people living in households below the poverty line relative to those at more than two times the poverty line.

Africa is likely to experience warming and increased climate variability by the late 21st century. Climate extremes have been linked to adverse economic outcomes. Hence, adaptation is a key component of the United Nations Framework Convention on Climate Change agreements and development assistance. Effective climate adaptation policy requires an understanding of how temperature and rainfall variability affect migration patterns. Yet, how individuals in developing countries manage climate variation is poorly understood, especially in Africa. Combining high-resolution climate data with panel micro-data on migration, labor participation, and demographics, we employ regression analysis to assess temporary migration responses to local temperature and precipitation anomalies in four East African countries. We find that climate impacts are most pronounced in urban areas, with a standard deviation temperature increase and rainfall decrease leading to respective 10 and 12 percent declines in out-migration relative to mean values. Evidence from other labor market outcomes suggests that urban out-migration is not associated with reduced local employment opportunities. Instead, declines in urban out-migration appear to coincide with negative local climate employment impacts. These results challenge the narrative that temporary out-migration serves as a safety valve during climate extremes and that climate change will most strongly affect out-migration rates from rural areas in developing countries.

Economists have long been interested in measuring distributional impacts of policy interventions. As environmental justice (EJ) emerged as an ethical issue in the 1970s, the academic literature has provided statistical analyses of the incidence and causes of various environmental outcomes as they relate to race, income, and other demographic variables. In the context of regulatory impacts, however, there is a lack of consensus regarding what information is relevant for EJ analysis, and how best to present it. This paper helps frame the discussion by suggesting a set of questions fundamental to regulatory EJ analysis, reviewing past approaches to quantifying distributional equity, and discussing the potential for adapting existing tools to the regulatory context.

Inequality indexes have long been used to analyze distributions of income. Studies have recently begun to use these tools to evaluate the equity of distributions of environmental harm. In response, issues have been raised regarding the appropriateness of using income‐based measures in the context of undesirable outcomes. We begin from first principles, identifying a theoretical preference structure under which income‐based tools can be appropriate for ranking distributions of “bads.” While some critiques of existing applications are valid, they are not a justification for rejecting the approach altogether. Instead, we show how standard income‐based measures can be adjusted to accommodate bad outcomes. Rather than inequality indexes, we argue that equally distributed equivalents (EDEs) are well‐suited for this purpose since they account for levels and dispersion of outcome distributions. The Kolm–Pollak EDE is particularly useful, having the advantage of consistently evaluating both bads and their complementary goods (e.g., mortality risk and survival probability). As an illustration, we show how these tools can inform an environmental justice analysis of a proposed Environmental Protection Agency (EPA) rule addressing indoor air pollution.

We examine fossil-fuel power plant employment impacts of new nitrogen oxides (NOx) provisions under Title I of the 1990 Clean Air Act Amendments (CAAAs). These provisions required installation of reasonably available control technology (RACT) for NOx emissions for major stationary sources in the Ozone Transport Region and in more stringently classified ozone nonattainment areas. Standard approaches using nonattainment designation to identify regulatory impacts abstract from important implementation aspects such as when regulatory changes occur, where regulations are in effect, and which specific regulations apply. Omitting these factors can introduce bias by contaminating the control group, leading to underestimation of historical employment impacts and overestimation of projected impacts from tightening regulations. Our results indicate that the new NOx RACT requirements negatively impacted power plant employment. We find no significant impacts on generation, suggesting that installation of pollution controls may have contributed to labor-saving technical change at affected units.