Economics, COVID, Election Forecasting: Did Trump Escape Blame?

• Published date: 01 September 2023
• DOI: http://doi.org/10.1177/1532673X231168584
• Author: Charles Tien,Michael S. Lewis-Beck
• Date: 01 September 2023
• Subject Matter: Articles

Article

American Politics Research

2023, Vol. 51(5) 619–632

© The Author(s) 2023

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DOI: 10.1177/1532673X231168584

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Economics, COVID, Election Forecasting: Did

Trump Escape Blame?

Charles Tien, Ph.D.

1

and Michael S. Lewis-Beck

2

Abstract

Given Trump’s provocative personal prof‌ile, coupled with boasts of his political prowess, one might expect that the electorate

would not allocate praise or blame at the ballot box in the usual reward and punishment way. They might blame him more than

other candidates or, indeed, they might blame him less. Utilizing election forecasting as a benchmark, in particular the structural

model of political economy, we assess whether voters blamed him less for his faltering performance with respect to leading

policy issues, particularly the economy and COVID-19. Our f‌indings suggest that, contrary to claims from supporters, voter s

punished him at least as much as they punished past presidents, when confronted with similar issue contexts. The Trump image

of a leader with superior powers has the character of f‌iction, rather than fact.

Keywords

economic voting, election forecasting, 2020 US presidential election

The start of an American presidential election year turns a

spotlight on the question: Who will win the November

contest? Different popular forecasting approaches offer an-

swers, foremostly from polls, markets, or models. While all

these strategies rely for their accuracy on scientif‌ic tech-

niques, modeling rests on the classic tradition of theory

building and equation estimation. These structural models, as

they are sometimes called, argue that fundamental determi-

nants of voting behavior shape the electoral outcome. Vir-

tually always, the economy presents itself as one of these

fundamental causes. The pervasiveness of the economic

variable, e.g., economic growth, appears unsurprising, given

the intuitive appeal of the reward-punishment theory behind

it, namely, good economic performance delivers votes to the

president’s party, while bad economic performance delivers

votes to the opposition. The predictive power of the reward-

punishment explanation has often been taken as axiomatic,

something that all presidential candidates are subject to.

However, the exceptional character of Trump’s candidacy,

and his presidency, cast doubt on the axiom. In 2016, did

Trump win despite a positive economy under Obama? In the

2018 congressional mid-terms, did Trump and the Repub-

licans gain more seats than expected? In 2020, did Trump

“almost”win, by def‌lecting responsibility for the consider-

able economic damage accompanying COVID-19?

We examine the role of the economy in shaping the results

of these three contests, with an eye to seeing, ex ante, whether

Trump was punished too little or rewarded too much for

economic conditions heading into the elections. In other

words, with respect to the economy, was he able to escape

blame or magnify praise, because of his unique leadership

traits? Or did the vicissitudes of the economy impact upon

him pretty much as they have done on past presidential

candidates? We look f‌irst at economic and election data,

aggregate and individual, from the 2016 presidential election,

before turning to the 2018 congressional contests and, f‌inally,

to the 2020 presidential race. As we shall see, Trump, despite

the super-hero claims of himself and many followers, ex-

perienced economic reward or punishment to essentially the

same degree as past contenders. His extraordinary powers, in

this respect, then, remain mythical.

Trump is Different

Donald Trumpbroke so many political expectationsand norms

that it is hard to try to cataloguethem all. There were plenty of

media and political science examples that documented

Trump’s differences. For example, he lied so often that The

Washington Post had to tally them and counted 30,573 lies

over four plus years (Kessler et al., 2021). Journalists call him

the real “Tef‌lon Don”as they marvel at his abilityto escape the

1

Department of Political Science, Hunter College & The Graduate Center,

New York, NY, USA

2

Department of Political Science, The University of Iowa, IA, USA

Corresponding Author:

Charles Tien, Department of Political Science, Hunter College, 695 Park

Avenue, New York, NY 10065, USA.

Email: ctien@hunter.cuny.edu