I exploit a panel data set on United States for the time span 1990–2013 to evaluate the causal impact of government regulation on bureaucratic corruption. Despite the stylized fact that corruption and regulation are positively correlated, there is a lack of empirical evidence to substantiate a causal relationship. Using novel data on federal regulation of industries (Al-Ubaydli and McLaughlin [2015], Regulation and Governance, 11, 109–123), and convictions of public officials from the Public Integrity Section, I apply a stochastic frontier approach to account for one-sided measurement error in bureaucratic corruption and the Lewbel [2012, Journal of Business and Economic Statistics, 30, 67–80] identification strategy to control for potential endogeneity of regulation. Results are striking. Based on the preferred model, there is evidence of endogeneity of regulation and absence of a causal link between regulation and corruption. However, if any of the above two econometric issues are ignored, evidence of a spurious relationship between corruption and regulation is found.

中文翻译：

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监管与腐败：来自美国的证据*

我利用 1990 年至 2013 年期间美国的面板数据集来评估政府监管对官僚腐败的因果影响。尽管腐败与监管呈正相关这一典型事实，但缺乏实证证据来证实因果关系。使用有关联邦行业监管的新数据（Al-Ubaydli 和 McLaughlin [2015]，Regulation and Governance , 11 , 109-123）以及公共诚信科对公职人员的定罪，我应用了一种随机前沿方法来解释一个官僚腐败和 Lewbel 的侧面测量误差 [2012, Journal of Business and Economic Statistics , 30, 67-80] 识别策略来控制潜在的内生性调控。结果是惊人的。根据首选模型，有证据表明监管具有内生性，监管与腐败之间不存在因果关系。但是，如果忽略上述两个计量经济学问题中的任何一个，就会发现腐败与监管之间存在虚假关系的证据。