Andrei Kirilenko
ABSTRACT
We propose a tool called RegRank that can be used to measure and test whether government regulatory agencies adjust aspects of final rules in response to comments received from the public. The algorithm, which combines customized dictionaries with LDA topic models, is used 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. A key finding based on the available data is that the government adjusts its final rules in the direction of public comments.
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Digital Library
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Index Terms
- Do U.S. Regulators Listen to the Public? Testing the Regulatory Process with the RegRank Algorithm
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