Verlag:
National Bureau of Economic Research, Cambridge, Mass
We use restricted-access, geocoded data on the near-universe of workers in 23 U.S. states in order to quantify the impact of wind energy development on local earnings and employment, by race, ethnicity, sex, and educational attainment. We find the...
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ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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We use restricted-access, geocoded data on the near-universe of workers in 23 U.S. states in order to quantify the impact of wind energy development on local earnings and employment, by race, ethnicity, sex, and educational attainment. We find the largest relative impacts for workers without a high school education, or workers with a college education, in addition to other systematic differences across sub-populations. We compare these results to estimates using county aggregates of the worker-level data, such as can be obtained using publicly available data. We find that (a) county-level estimates are dramatically dampened relative to geocoded worker-level estimates, and (b) the degree of bias differs by sub-population such that qualitative comparisons of impacts are not consistent using restricted-access data versus county-level data for most sub-populations. We discuss implications for achieving equity goals within energy transition policies
