Can Technology Solve the Principal-Agent Problem? Evidence from China’s War on Air Pollution

47 Pages Posted: 1 Jul 2020

See all articles by Michael Greenstone

Michael Greenstone

University of Chicago - Department of Economics; Becker Friedman Institute for Economics; National Bureau of Economic Research (NBER)

Guojun He

Hong Kong University of Science and Technology

Ruixue Jia

University of California, San Diego (UCSD)

Tong Liu

Hong Kong University of Science & Technology

Date Written: June 29, 2020

Abstract

We examine the introduction of automatic air pollution monitoring, which is a central feature of China’s “war on pollution.” Exploiting 654 regression discontinuity designs based on city-level variation in the day that monitoring was automated, we find that reported PM10 concentrations increased by 35% immediately post–automation and were sustained. City-level variation in underreporting is negatively correlated with income per capita and positively correlated with true pre-automation PM10 concentrations. Further, automation’s introduction increased online searches for face masks and air filters, suggesting that the biased and imperfect pre-automation information imposed welfare costs by leading to suboptimal purchases of protective goods.

Keywords: Technology, Automation, Air Pollution, China, Monitoring and Surveillance, Moral Hazard, Data Quality

Suggested Citation

Greenstone, Michael and He, Guojun and Jia, Ruixue and Liu, Tong, Can Technology Solve the Principal-Agent Problem? Evidence from China’s War on Air Pollution (June 29, 2020). University of Chicago, Becker Friedman Institute for Economics Working Paper No. 2019-87, Available at SSRN: https://ssrn.com/abstract=3638591

Michael Greenstone (Contact Author)

University of Chicago - Department of Economics

1126 East 59th Street
Chicago, IL 60637
United States

Becker Friedman Institute for Economics ( email )

Chicago, IL 60637
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Guojun He

Hong Kong University of Science and Technology ( email )

Division of Social Science
HKUST
Clear Water Bay, Kowloon
Hong Kong

Ruixue Jia

University of California, San Diego (UCSD) ( email )

9500 Gilman Drive
Mail Code 0502
La Jolla, CA 92093-0112
United States

Tong Liu

Hong Kong University of Science & Technology ( email )

Division of Social Science
Kowloon
Hong Kong, Hong Kong
China

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