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Sentiment and Uncertainty about Regulation

Tara Sinclair and Zhoudan Xie ()

No 2021-004, Working Papers from The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting

Abstract: Regulatory policy can create economic and social benets, but poorly designed or excessive regulation may generate substantial adverse effects on the economy. In this paper, we present measures of sentiment and uncertainty about regulation in the U.S. over time and examine their relationships with macroeconomic performance. We construct the measures using lexicon-based sentiment analysis of an original news corpus, which covers 493,418 news articles related to regulation from seven leading U.S. newspapers. As a result, we build monthly indexes of sentiment and uncertainty about regulation and categorical indexes for 14 regulatory policy areas from January 1985 to August 2020. Impulse response functions indicate that a negative shock to sentiment about regulation is associated with large, persistent drops in future output and employment, while increased regulatory uncertainty overall reduces output and employment temporarily. These results suggest that sentiment about regulation plays a more important economic role than uncertainty about regulation. Furthermore, economic outcomes are particularly sensitive to sentiment around transportation regulation and to uncertainty around labor regulation.

Keywords: Regulation; text analysis; NLP; sentiment analysis; uncertainty (search for similar items in EconPapers)
JEL-codes: E2 E3 K2 O4 (search for similar items in EconPapers)
Pages: 80 pages
Date: 2021-06
New Economics Papers: this item is included in nep-big, nep-law and nep-mac
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https://www2.gwu.edu/~forcpgm/2021-004.pdf First version, 2021 (application/pdf)

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