Krilenko et al.: Do U.S. Regulators Listen to the Public? Testing the Regulatory Process with the RegRank Algorithm

Professor Dr. Andrei A. Kirilenko of MIT, Professor Dr. Shawn Mankad of the University of Maryland, and Professor Dr. George Michailidis of the University of Michigan, have posted Do U.S. Regulators Listen to the Public?: Testing the Regulatory Process with the RegRank Algorithm .

Here is the abstract:

According to the U.S. Constitution, the government cannot harm a single individual without “the due process of the law.” Things are different, however, if a government action affects multiple individuals. The U.S. Supreme Court ruled that the government can issue a regulation that can greatly harm many businesses and individuals “without giving them a chance to be heard.” A federal statute called the Administrative Procedure Act mandates that federal regulatory agencies give the public a chance to comment on proposed regulations before they become final. We propose a new analytical tool called RegRank that can be used to measure and test whether government regulatory agencies actually adjust final rules in response to comments received from the public. We use RegRank to analyze the text of public rulemaking documents of the Commodity Futures Trading Commission (CFTC) – a federal regulatory agency in charge of implementing parts of the Dodd-Frank Wall Street Reform and Consumer Protection Act. We then test whether the regulatory agency adjusts final rules in the direction of sentiment expressed in public comments. We find strong evidence that it does.

Filed under: Articles and papers, Research findings Tagged: Andrei A. Kirilenko, Citizens' influence on regulations, Citizens' legal communication, Citizens' participation in erulemaking, Citizens' participation in lawmaking, Citizens' participation in rulemaking, erulemaking, erulemaking systems, George Michailidis, Legal communication, Legal sentiment analysis, Legal text analysis, RegRand algorithm, RegRank, Regulatory communication systems, Regulatory information systems, Sentiment analysis, Sentiment analysis about regulations, Sentiment analysis algoritms, Shawn Mankad, SSRN



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