Improving Truthful Reporting of Polluting Firms by Rotating Inspectors: Experimental Evidence from a Bribery Game

时间:2019-11-26浏览:20设置


ShanghaiTech SEM Working Paper No. 2019-005


Peiyao Shen 

ShanghaiTech University

Regina Betz

Zurich University of Applied Sciences

Andreas Ortmann

UNSW Australia

Rukai Gong

Donghua University

  

We consider a two-layered review system of environmental regulation where a polluting firm periodically self-reports its emissions to a regulatory authority. The system typically requires a third party to verify the firm’s report and, in addition, an official of the regulatory authority to spot-check. If there are potential gains from corruption, both the verifier and the official might be corruptible. Corruption is more likely in repeated-game situations, as suggested by the literature on corruption experiments. Our experimental design is motivated by the risk of under-reporting in emissions trading schemes where both the verifier and the official are corruptible and focuses on a situation with untruthful reporting and lax enforcement. Our test-bed is a three-player bribery game. We study how different types of rotation — a baseline of fixed matching, a complete rotation treatment, and two incomplete rotation treatments — affect untruthful reporting that requires collusion between three participants in a hierarchical structure. Our findings suggest that complete rotation improves significantly firms’ truthful reporting and verifiers’ truthful verification compared to situations where none is rotated, while incomplete rotation does not have such impact. In our experiment, none of the rotation treatments had a significant impact on the behavior of officials.hanghaiTech University


Keywords: truthful reporting, corruption, rotation, environmental regulation, experiment


Date Written: November, 2019


Available at SSRN: https://ssrn.com/abstract=3492819


Download this paper:  【No. 2019-005】Improving Truthful Reporting of Polluting Firms by Rotating Inspectors Experimental E.pdf












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