Working Papers

The Role of People vs. Places in Individual Carbon Emissions

Under Revision for the American Economic Review

There is substantial spatial heterogeneity in household carbon emissions across the US, and a strong association between emissions and local amenities such as density, transportation infrastructure, and housing characteristics. I estimate what share of this heterogeneity in carbon emissions is attributable to places themselves, and what share reflects individual preferences and taste-based sorting. To do this, I construct a longitudinal panel of residential energy use and commute characteristics for over a million individuals from two decades of administrative Decennial Census and American Community Survey data. I use movers in my data to estimate place effects – the amount by which carbon emissions change for the same individual living in different places – for almost 1,000 labor markets and roughly 60,500 neighborhoods across the US. I find that place effects explain about 15-25% of overall variation in carbon emissions, but more than half of the variation between places. My estimates suggest that decreasing neighborhood-level place effects from one standard deviation above the mean to one standard deviation below the mean would decrease household carbon emissions from residential energy use and commuting by about 40%.

The Race Gap in Residential Energy Expenditures

Black households have higher residential energy expenditures than white households in the US. This residential energy expenditure gap persists after controlling for income, household size, home-owner status, and city of residence. It decreased but did not disappear between 2010 and 2017, and it is fairly stable in levels across the income distribution, except at the top. Controlling for home type or vintage does not eliminate the gap, but survey evidence on housing characteristics and available appliances is consistent with the gap being driven at least in part by differences in housing stock and related energy efficiency investments.

Ongoing work expands this analysis using administrative data in the state of California.

Building the Prototype Census Environmental Impacts Frame

with John Voorheis, Jonathan Colmer, Kendall Houghton, Mary Munro, Cameron Scalera, and Jennifer Withrow

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.

Work in Progress

Nice Work if You Can Get it: The Distribution of Employment and Earnings During the Early Years of the Clean Energy Transition

with Jonathan Colmer, John Voorheis, and Kyle Addison.

Transitional Dynamics and the Decline of Coal: Worker-Level Evidence

with Jonathan Colmer, Eleanor Krause, and John Voorheis.

Why is Industrial Energy Efficiency Improving?

with Will Rafey, Joe Shapiro, and Reed Walker.


Regulating Mismeasured Pollution: Implications of Firm Heterogeneity for Environmental Policy

With Joe Shapiro and Reed Walker. AEA Papers and Proceedings (2018)

This paper provides the first estimates of within-industry heterogeneity in energy and CO2 productivity for the entire U.S. manufacturing sector. We measure energy and CO2 productivity as output per dollar energy input or per ton CO2 emitted. Three findings emerge. First, within narrowly defined industries, heterogeneity in energy and CO2 productivity across plants is enormous. Second, heterogeneity in energy and CO2 productivity exceeds heterogeneity in most other productivity measures, like labor or total factor productivity. Third, heterogeneity in energy and CO2 productivity has important implications for environmental policies targeting industries rather than plants, including technology standards and carbon border adjustments.