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

Cloé Garnache, Arijit Ghosh and Garreth Gibney

No 113, I4R Discussion Paper Series from The Institute for Replication (I4R)

Abstract: Greenstone et al. examine the effect of the introduction of automatic air pollution monitoring on the reporting of local air pollution in China. Using 654 regression discontinuity designs (RDDs) based on city-level variation in the day that monitoring was automated, they find an immediate and lasting increase of 35 percent in reported PM10 concentrations post-automation. Moreover, they find that automation's introduction increases online searches for face masks and air filters by 200 percent and 28 percent, respectively, using an RDD. Results are consistent when using an event study design. First, we were able to computationally replicate the results. Second, we find that results are robust to more flexible specifications of the weather variables, to re-constructed weather variables using the same matching procedure as the authors (i.e., closest station) and meteorological data with additional weather stations, to alternative construction of the weather variables using an inverse distance weighted approach of the surrounding weather stations, and to more flexible choices of fixed effects (up to the city level). Finally, we find limited evidence of discontinuity in objective measures of ground pollution (i.e., AOD) for a sub-sample using alternative weather variables. The estimate, however, is economically insignificant. Moreover, no discontinuity is observed in the full sample. Therefore, we believe this result does not invalidate the original study's findings.

JEL-codes: D82 O13 P28 Q53 Q55 Q58 (search for similar items in EconPapers)
Date: 2024
New Economics Papers: this item is included in nep-cna, nep-ene and nep-env
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