Temperature and temperament: Evidence from Twitter

Patrick Baylis

Journal of Public Economics, 2020, vol. 184, issue C

Abstract: How do people value their climate? This paper demonstrates a new approach to estimating preferences for nonmarket goods using social media data. I combine more than a billion Twitter updates with natural language processing algorithms to construct a rich panel dataset of expressed sentiment for the United States and six other English-speaking countries around the world. In the U.S., I find consistent and statistically significant declines in expressed sentiment from both hot and cold temperatures. To better understand how preferences may adapt, I document heterogeneity in both regional and seasonal responses. I complete the U.S. analysis with a suite of validation exercises to understand the magnitude of these effects and two methods to estimate willingness-to-pay for climate amenities. Finally, I document similar relationships between temperature and expressed sentiment for four out of the six non-U.S. countries I examine.

Date: 2020
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Citations: View citations in EconPapers (35)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:pubeco:v:184:y:2020:i:c:s0047272720300256

DOI: 10.1016/j.jpubeco.2020.104161

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