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The Privacy-Protected Gridded Environmental Impacts Frame
December 2024
Working Paper Number:
CES-24-74
This paper introduces the Gridded Environmental Impacts Frame (Gridded EIF), a novel privacy-protected dataset derived from the U.S. Census Bureau's confidential Environmental Impacts Frame (EIF) microdata infrastructure. The EIF combines comprehensive administrative records and survey data on the U.S. population with high-resolution geospatial information on environmental hazards. While access to the EIF is restricted due to the confidential nature of the underlying data, the Gridded EIF offers a broader research community the opportunity to glean insights from the data while preserving confidentiality. We describe the data and privacy protection process, and offer guidance on appropriate usage, presenting practical applications.
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Fighting Fire with Fire(fighting Foam): The Long Run Effects of PFAS Use at U.S. Military Installations
December 2024
Working Paper Number:
CES-24-72
Tens of millions of people in the U.S. may be exposed to drinking water contaminated with perand poly-fluoroalkyl chemicals (PFAS). We provide the first estimates of long-run economic costs from a major, early PFAS source: fire-fighting foam. We combine the timing of its adoption with variation in the presence of fire training areas at U.S. military installations in the 1970s to estimate exposure effects for millions of individuals using natality records and restricted administrative data. We document diminished birthweights, college attendance, and earnings, illustrating a pollution externality from military training and unregulated chemicals as a determinant of economic opportunity.
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The Census Historical Environmental Impacts Frame
October 2024
Working Paper Number:
CES-24-66
The Census Bureau's Environmental Impacts Frame (EIF) is a microdata infrastructure that combines individual-level information on residence, demographics, and economic characteristics with environmental amenities and hazards from 1999 through the present day. To better understand the long-run consequences and intergenerational effects of exposure to a changing environment, we expand the EIF by extending it backward to 1940. The Historical Environmental Impacts Frame (HEIF) combines the Census Bureau's historical administrative data, publicly available 1940 address information from the 1940 Decennial Census, and historical environmental data. This paper discusses the creation of the HEIF as well as the unique challenges that arise with using the Census Bureau's historical administrative data.
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Income, Wealth, and Environmental Inequality in the United States
October 2024
Working Paper Number:
CES-24-57
This paper explores the relationships between air pollution, income, wealth, and race by combining administrative data from U.S. tax returns between 1979'2016, various measures of air pollution, and sociodemographic information from linked survey and administrative data. In the first year of our data, the relationship between income and ambient pollution levels nationally is approximately zero for both non-Hispanic White and Black individuals. However, at every single percentile of the national income distribution, Black individuals are exposed to, on average, higher levels of pollution than White individuals. By 2016, the relationship between income and air pollution had steepened, primarily for Black individuals, driven by changes in where rich and poor Black individuals live. We utilize quasi-random shocks to income to examine the causal effect of changes in income and wealth on pollution exposure over a five year horizon, finding that these income'pollution elasticities map closely to the values implied by our descriptive patterns. We calculate that Black-White differences in income can explain ~10 percent of the observed gap in air pollution levels in 2016.
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The Changing Nature of Pollution, Income, and Environmental Inequality in the United States
January 2024
Working Paper Number:
CES-24-04
This paper uses administrative tax records linked to Census demographic data and high-resolution measures of fine small particulate (PM2.5) exposure to study the evolution of the Black-White pollution exposure gap over the past 40 years. In doing so, we focus on the various ways in which income may have contributed to these changes using a statistical decomposition. We decompose the overall change in the Black-White PM2.5 exposure gap into (1) components that stem from rank-preserving compression in the overall pollution distribution and (2) changes that stem from a reordering of Black and White households within the pollution distribution. We find a significant narrowing of the Black-White PM2.5 exposure gap over this time period that is overwhelmingly driven by rank-preserving changes rather than positional changes. However, the relative positions of Black and White households at the upper end of the pollution distribution have meaningfully shifted in the most recent years.
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Is Air Pollution Regulation Too Lenient? Evidence from US Offset Markets
June 2023
Working Paper Number:
CES-23-27R
This paper describes a framework to estimate the marginal cost of air pollution regulation, then applies it to assess whether a large set of existing U.S. air pollution regulations have marginal benefits exceeding their marginal costs. The approach utilizes an important yet under-explored provision of the Clean Air Act requiring new or expanding plants to pay incumbents in the same or neighboring counties to reduce their pollution emissions. These "offset" regulations create several hundred decentralized, local markets for pollution that differ by pollutant and location. Economic theory and empirical tests suggest these market prices reveal information about the marginal cost of abatement for new or expanding firms. We compare estimates of the marginal benefit of abatement from leading air quality models to offset prices. We find that, for most regions and pollutants, the marginal benefits of pollution abatement exceed mean offset prices more than ten-fold. In at least one market, however, estimated marginal benefits are below offset prices.
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Building the Prototype Census Environmental Impacts Frame
April 2023
Working Paper Number:
CES-23-20
The natural environment is central to all aspects of life, but efforts to quantify its influence have been hindered by data availability and measurement constraints. To mitigate some of these challenges, we introduce a new prototype of a microdata infras tructure: the Census Environmental Impacts Frame (EIF). The EIF provides detailed individual-level information on demographics, economic characteristics, and address level histories ' linked to spatially and temporally resolved estimates of environmental conditions for each individual ' for almost every resident in the United States over the past two decades. This linked microdata infrastructure provides a unique platform for advancing our understanding about the distribution of environmental amenities and hazards, when, how, and why exposures have evolved over time, and the consequences of environmental inequality and changing environmental conditions. We describe the construction of the EIF, explore issues of coverage and data quality, document patterns and trends in individual exposure to two correlated but distinct air pollutants as an application of the EIF, and discuss implications and opportunities for future research.
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Some Open Questions on Multiple-Source Extensions of Adaptive-Survey Design Concepts and Methods
February 2023
Working Paper Number:
CES-23-03
Adaptive survey design is a framework for making data-driven decisions about survey data collection operations. This paper discusses open questions related to the extension of adaptive principles and capabilities when capturing data from multiple data sources. Here, the concept of 'design' encompasses the focused allocation of resources required for the production of high-quality statistical information in a sustainable and cost-effective way. This conceptual framework leads to a discussion of six groups of issues including: (i) the goals for improvement through adaptation; (ii) the design features that are available for adaptation; (iii) the auxiliary data that may be available for informing adaptation; (iv) the decision rules that could guide adaptation; (v) the necessary systems to operationalize adaptation; and (vi) the quality, cost, and risk profiles of the proposed adaptations (and how to evaluate them). A multiple data source environment creates significant opportunities, but also introduces complexities that are a challenge in the production of high-quality statistical information.
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The Grandkids Aren't Alright: The Intergenerational Effects of Prenatal Pollution Exposure
November 2020
Working Paper Number:
CES-20-36
Evidence shows that environmental quality shapes human capital at birth with long-run effects on health and welfare. Do these effects, in turn, affect the economic opportunities of future generations? Using newly linked survey and administrative data, providing more than 150 million parent/child links, we show that regulation-induced improvements in air quality that an individual experienced in the womb increase the likelihood that their children, the second generation, attend college 40-50 years later. Intergenerational transmission appears to arise from greater parental resources and investments, rather than heritable, biological channels. Our findings suggest that within-generation estimates of marginal damages substantially underestimate the total welfare effects of improving environmental quality and point to the empirical relevance of environmental quality as a contributor to economic opportunity in the United States.
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What Caused Racial Disparities in Particulate Exposure to Fall? New Evidence from the Clean Air Act and Satellite-Based Measures of Air Quality
January 2020
Working Paper Number:
CES-20-02
Racial differences in exposure to ambient air pollution have declined significantly in the United States over the past 20 years. This project links restricted-access Census Bureau microdata to newly available, spatially continuous high resolution measures of ambient particulate pollution (PM2.5) to examine the underlying causes and consequences of differences in black-white pollution exposures. We begin by decomposing differences in pollution exposure into components explained by observable population characteristics (e.g., income) versus those that remain unexplained. We then use quantile regression methods to show that a significant portion of the 'unexplained' convergence in black-white pollution exposure can be attributed to differential impacts of the Clean Air Act (CAA) in non-Hispanic African American and non-Hispanic white communities. Areas with larger black populations saw greater CAA-related declines in PM2.5 exposure. We show that the CAA has been the single largest contributor to racial convergence in PM2.5 pollution exposure in the U.S. since 2000 accounting for over 60 percent of the reduction.
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