TY - JOUR
T1 - The mortality and medical costs of air pollution
T2 - Evidence from changes in wind direction
AU - Deryugina, Tatyana
AU - Heutel, Garth
AU - Miller, Nolan H.
AU - Molitor, David
AU - Reif, Julian
N1 - Funding Information:
* Deryugina: Gies College of Business, University of Illinois, 340 Wohlers Hall, 1206 S. Sixth Street, Champaign, IL 61820 (email: [email protected]); Heutel: Department of Economics, Georgia State University, PO Box 3992, Atlanta, GA 30302 (email: [email protected]); Miller: Gies College of Business, University of Illinois, 340 Wohlers Hall, 1206 S. Sixth Street, Champaign, IL 61820 (email: [email protected]); Molitor: Gies College of Business, University of Illinois, 340 Wohlers Hall, 1206 S. Sixth Street, Champaign, IL 61820 (email: [email protected]); Reif: Gies College of Business, University of Illinois, 340 Wohlers Hall, 1206 S. Sixth Street, Champaign, IL 61820 (email: [email protected]). Thomas Lemieux was the coeditor for this article. We thank Alan Barreca, Allen C. Basala, Shuai Chen, Mert Demirer, Alex Hollingsworth, Pierre Léger, Feng Liang, Christos Makridis, Mar Reguant, and seminar participants at the AERE Summer Conference, Cornell University, Georgia Tech, IGPA, the IZA Conference on Labor Market Effects of Environmental Policies, the Midwestern Health Economics Conference, Purdue University, the Research Triangle Institute, the Southern Economics Association Conference, the University of Illinois Research Lunch, the University of Iowa, and the WCERE for helpful comments. Dominik Mockus, Isabel Ferraz Musse, and Eric Zou provided excellent research assistance. We thank Jean Roth for assistance with the Medicare data and Daniel Feenberg and Mohan Ramanujan for system administration. Research reported in this publication was supported by the National Institute on Aging of the National Institutes of Health under Award Number R01AG053350. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Funding Information:
Thomas Lemieux was the coeditor for this article. We thank Alan Barreca, Allen C. Basala, Shuai Chen, Mert Demirer, Alex Hollingsworth, Pierre L?ger, Feng Liang, Christos Makridis, Mar Reguant, and seminar participants at the AERE Summer Conference, Cornell University, Georgia Tech, IGPA, the IZA Conference on Labor Market Effects of Environmental Policies, the Midwestern Health Economics Conference, Purdue University, the Research Triangle Institute, the Southern Economics Association Conference, the University of Illinois Research Lunch, the University of Iowa, and the WCERE for helpful comments. Dominik Mockus, Isabel Ferraz Musse, and Eric Zou provided excellent research assistance. We thank Jean Roth for assistance with the Medicare data and Daniel Feenberg and Mohan Ramanujan for system administration. Research reported in this publication was supported by the National Institute on Aging of the National Institutes of Health under Award Number R01AG053350. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Publisher Copyright:
© 2019 American Economic Association. All rights reserved.
PY - 2019/12
Y1 - 2019/12
N2 - We estimate the causal effects of acute fine particulate matter exposure on mortality, health care use, and medical costs among the US elderly using Medicare data. We instrument for air pollution using changes in local wind direction and develop a new approach that uses machine learning to estimate the life-years lost due to pollution exposure. Finally, we characterize treatment effect heterogeneity using both life expectancy and generic machine learning inference. Both approaches find that mortality effects are concentrated in about 25 percent of the elderly population.
AB - We estimate the causal effects of acute fine particulate matter exposure on mortality, health care use, and medical costs among the US elderly using Medicare data. We instrument for air pollution using changes in local wind direction and develop a new approach that uses machine learning to estimate the life-years lost due to pollution exposure. Finally, we characterize treatment effect heterogeneity using both life expectancy and generic machine learning inference. Both approaches find that mortality effects are concentrated in about 25 percent of the elderly population.
UR - http://www.scopus.com/inward/record.url?scp=85076021903&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85076021903&partnerID=8YFLogxK
U2 - 10.1257/aer.20180279
DO - 10.1257/aer.20180279
M3 - Article
C2 - 32189719
AN - SCOPUS:85076021903
SN - 0002-8282
VL - 109
SP - 4178
EP - 4219
JO - American Economic Review
JF - American Economic Review
IS - 12
ER -