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Measuring “State-Level” Economic Policy Uncertainty

Published online by Cambridge University Press:  13 June 2023

Redouane Elkamhi ,
Chanik Jo Open the ORCID record for Chanik Jo [Opens in a new window]  and
Marco Salerno
Redouane Elkamhi
Affiliation:
University of Toronto, Rotman School of Management redouane.elkamhi@rotman.utoronto.ca
Chanik Jo*
Affiliation:
The Chinese University of Hong Kong, CUHK Business School
Marco Salerno
Affiliation:
Healthcare of Ontario Pension Plan Trust Fund msalerno@hoopp.com
*
chanikjo@cuhk.edu.hk (corresponding author)
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Abstract

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We develop 50 indices of state-level economic policy uncertainty (SEPU) based on newspaper coverage frequency using 204 million newspaper articles from Mar. 1984 to Dec. 2019. We assess the validity of our measures. Our SEPU indices vary counter-cyclically with respect to state-specific economic conditions, rise before close gubernatorial elections, and exhibit a large cross-sectional variation. We demonstrate that SEPU indices are associated with the cross-sectional variation in state-level GDP, employment, income as well as industry investment decisions. Our findings highlight the importance of economic policy uncertainty at the state level in addition to the nationwide level.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , First View , pp. 1 - 37
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

Footnotes

We thank Pat Akey, Hendrik Bessembinder (the editor), Jonathan Brogaard and Art Durnev (the referees), Charles Martineau, and Tom McCurdy as well as seminar participants at the University of Toronto for helpful comments and suggestions. We are grateful to Jad Izgua, Jingkai Xu, and Lorna Zhong for their excellent research assistance. Any errors or omissions are our own responsibility. Our indices are available on Chanik Jo’s website at https://chanikjo.github.io/Research.

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