Can Technology Solve the Principal-Agent Problem? Evidence from ChinaÂ’s War on Air Pollution
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.
We thank Christoper Knittel, Liguo Lin, Alberto Salvo, Shaoda Wang, Bing Zhang, Junjie Zhang, and seminar participants at CIFAR, LSE, MIT, Nanjing University, NBER, and Peking University for their comments. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
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Michael Greenstone & Guojun He & Ruixue Jia & Tong Liu, 2022. "Can Technology Solve the Principal-Agent Problem? Evidence from China's War on Air Pollution," American Economic Review: Insights, American Economic Association, vol. 4(1), pages 54-70, March. citation courtesy of