U.S. presidential approval and the macroeconomy: 1960–2022

Abstract

U.S. presidential approval is a topic that has long attracted the interest of political pundits, journalists, candidates, and academics. This study focuses on quarterly U.S. presidential approval and measures of the U.S. macroeconomy. This research will expand, update and reinvestigate this relationship using new data, additional variables and the IVX predictive regression model of Kostakis, et al. (2015), specifically developed for time series data with mixed orders of integration such as we have here. We found that (as measured by Gallup data) U.S. presidential approval is a stationary mean-reverting variable with a long-term mean of approximately 50%. Our results also suggest that presidential party and the business cycle have no impact on the mean of quarterly presidential approval as standalone variables. However, using a comprehensive set of macroeconomic variables in a single study, we found that macroeconomic variables make a difference in applying predictive regression models to indicate significance. Specifically, before and after controlling for other macroeconomic variables, political party and the business cycle, more immediate “pocketbook issues” like gasoline prices and inflation expectations are important issues to American voters' presidential approval rating. Simply put, our regression results suggest rising prices and the expectation of rising prices consistently lower presidential approval in our sample data. This is a result that will likely interest political practitioners and academics alike.