Gasoline Prices and Presidential Approval Ratings of the United States

Rangan Gupta, Christian Pierdzioch and Aviral Tiwari

No 202427, Working Papers from University of Pretoria, Department of Economics

Abstract: We use random forests, a machine-learning technique, to formally examine the link between real gasoline prices and presidential approval ratings of the United States (US). Random forests make it possible to study this link in a completely data-driven way, such that nonlinearities in the data can easily be detected and a large number of control variables, in line with the extant literature, can be considered. Our empirical findings show that the link between real gasoline prices and the presidential approval ratings is indeed nonlinear, and that the former even has predictive value in an out-of-sample exercise for the latter. We argue that our findings are in line with the so-called pocketbook mechanism, which stipulates that the presidential approval ratings depend on gasoline prices because the latter have sizable impact on personal economic situations of voters.

Keywords: Presidential approval ratings; Gasoline price; Random forests; Forecasting (search for similar items in EconPapers)
JEL-codes: C22 C53 Q40 Q43 (search for similar items in EconPapers)
Pages: 33 pages
Date: 2024-06
New Economics Papers: this item is included in nep-big, nep-cmp, nep-ene and nep-inv
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Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:202427

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