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Abstract

Do different economic shocks favor different types of political leadership? Using a survey experiment conducted on 3500 American respondents, we offer causal evidence for an unexpected relation between different types of economic shocks and a demand for a radical political response. First, we show that individuals believe politicians have a role in preventing layoffs due to both offshoring and automation, compared to run-of-the-mill bankruptcies. Second, we find strong evidence that economic shocks due to offshoring lead to greater demands for leaders who display authoritarian traits, with no equivalent effect for layoffs due to automation. When presented with news of an offshoring event, respondents favor leaders who claim to be more willing to flout the rule of law, to implement divisive policies, and to employ force. By contrast, traits commonly associated with populism, such as siding with “the people” or preferring political outsiders, see no association with either offshoring or automation shocks. Our findings support the view that some economic shocks provide a greater opportunity for political candidates willing to turn to radical political solutions.

Keywords

Automation offshoring populism authoritarianism United States

Introduction

What economic shocks generate demand for radical political measures and the leaders who promise to deliver them? By contrast, which shocks are dismissed as part of the natural course of economic activity? As uneven growth and losses in manufacturing employment have coincided with a wave of right-wing populism across industrialized democracies, few questions have garnered as much scholarly attention. Studies from both economics and political science (Colantone and Stanig 2018; Di Tella and Rodrik 2020; Jensen et al., 2017; Mutz 2018; Norris and Inglehart 2019; Rickard 2022; Walter 2010) have taken to explaining the various ways that economic shocks and political upsets might be linked.

Considerable scholarly study has been devoted to the study of economic shocks and their effects on individuals’ political views (Ahlquist et al., 2020; Margalit 2013, 2019). Yet for all the attention it has garnered, the backlash against globalization and the outsourcing of production tasks to countries with lower labor costs that it allows, remains puzzling. Indeed, the number of layoffs due to technology is significantly greater than those due to globalization; yet it is trade and offshoring that have borne the brunt of the political condemnation (Wu 2022). Meanwhile, automation may in fact have a greater political impact than anecdotal evidence would suggest, with a number of findings linking automation to the election of populist candidates on both sides of the Atlantic (Anelli et al., 2021; Milner 2021), in a claim encapsulated by Edsall’s (2018) view that “robots can’t vote, but they helped elect Donald Trump.” Yet because most of the underlying findings are based on observational evidence, it remains difficult to tease out the effect of automation from that of globalization.

To shine a light on the causal relation between different economic shocks and political demands, we conduct an original survey experiment covering more than 3500 US respondents. The main analysis involves a vignette experiment in which respondents are randomly assigned to two treatments: (i) layoffs due to automation; and (ii) layoffs due to offshoring. The control group is exposed to layoffs due to run-of-the-mill bankruptcy. Respondents are then asked two questions: first, should political leaders prevent layoffs of this type? And second, what type of leader would be best placed to do so? Respondents then choose from a set of leadership characteristics. Some of these seek to capture commonly perceived aspects of populism: “political outsiders” who “listen to the people.” Others seek to capture authoritarian traits: politicians who understand that “using force is sometimes required to bring about positive change,” appear “unconstrained by the rules,” and are willing to implement divisive policies that benefit their local constituents, “even if it upsets other people in the country.” In this way, our research design focuses on the type of leader, and the approach to political rule that individuals view as effective and desirable in the wake of different types of economic shocks. Building on previous work (Borwein et al., 2024; Di Tella and Rodrik 2020), we attempt to causally identify the effect of automation versus offshoring events on demand for political leaders displaying populist and authoritarian traits.

The experimental evidence delivers three main findings. First, we find evidence that layoffs due to both automation and offshoring are viewed through a political lens, in ways that layoffs due to bankruptcy are not. Contrarily to a commonly held view that sees technological progress as an unstoppable structural force outside of the political ambit, respondents believe that “it is the role of political leaders to prevent layoffs due to new technology replacing human workers,” while those exposed to layoffs due to run-of-the-mill bankruptcies see these as non-political events, requiring no political intervention. This finding is all the more notable because our survey was run shortly before the advent of generative large language models in November 2022. This development has been seen as contributing to demands for intervention in the face of technological change¹; our findings show that such demand existed before recent advances in AI. While layoffs due to both offshoring and automation trigger significantly greater demands for government intervention than those due to bankruptcy, the effect is almost twice as large for offshoring than automation. This is consistent with the anecdotal observation that policymakers appear to make more political hay out of offshoring than technology-induced layoffs.

Secondly, we find no evidence that either technology-induced layoffs or layoffs due to offshoring trigger significantly greater demand for some of the main leadership traits associated with populism. Despite several observational findings linking globalization to the emergence of populism, our results suggest that offshoring is no different in this respect than either technological change or run-of-the-mill bankruptcies: respondents exposed to these different shocks do not vary in their demand for leaders who are “political outsiders” who embrace “the people.”

Third, layoffs due to offshoring are causally related to demands for leaders who display authoritarian traits: individuals respond to news of offshoring by demanding leaders who are more willing to employ force when necessary to bring about positive change, who appear unconstrained by the rules, and who are inclined to adopt nationally divisive policies. By comparison, automation layoffs appear no different in this respect from run-of-the-mill bankruptcies.

Economic shocks and political effects

While automation is widely thought to be a greater source of labor dislocation than trade and offshoring, it has been the target of less political opprobrium.² Yet the relationship between automation and political outcomes remains unclear. Frey et al. (2018) argue that automation contributed to Trump’s victory in the 2016 presidential elections. In Europe, both automation and trade shocks have been associated with increased support for nationalist and radical-right parties (Anelli et al., 2021; Colantone and Stanig 2018; Im et al., 2019; Milner 2021). The adoption of industrial robots, in particular, has coincided with a rise in anti-immigrant sentiment, which in turn brought populist leaders to power across Europe.

These findings are based on observational evidence, making it difficult to tease apart the effect of automation from that of globalization, especially since these interact in various ways. For one, the geographic distribution of labor-saving technology matches the geographically concentrated aspect of trade exposure: industrial robots have their greatest displacement effects in manufacturing-dependent commuting zones that are also vulnerable to import competition and task offshoring (Acemoglu and Restrepo 2018). And technological advances may themselves facilitate offshoring by reducing the skills required to carry out specific tasks (Goos et al., 2014). On the other hand, automation reduces the wage differential between countries and economizes on transportation costs, affecting incentives to offshore jobs in the first place (Bonfiglioli et al., 2021). Many firms thus view the two as substitute means of cutting costs (Owen 2020).

Meanwhile, several studies have tried to account for why automation would be a less appealing political target than offshoring. Automation in general, and digitalization in particular, generate a large set of winners among voters, who are in turn likely to have political preferences in line with the status quo (Gallego et al., 2022). Some look to the nature of the shock itself: offshoring may be more visible (Wu 2022), as entire factories close down and move abroad, while robots can gradually replace tasks previously performed by humans without raising attention. Automation also brings to mind progress and innovation. In capital-rich countries, it may be seen as bolstering an existing comparative advantage in capital-intensive goods, whereas offshoring underscores their comparative disadvantage in labor (Chaudoin and Mangini 2024). Or it may be that technological change is seen as an unstoppable force, operating entirely outside of any political process (Lee 2021). The question is thus, do voters view some economic shocks as more inherently political, while dismissing others as the natural course of economic events?

Existing work argues that offshoring is different from other types of layoff events. For instance, Di Tella and Rodrik (2020) show that offshoring leads to greater calls for trade protectionism, as compared with technology and demand shocks. This is perhaps not altogether surprising, since offshoring is a trade activity: production is transferred abroad and the product is reimported into the country. As such, it can be tackled more readily through protectionism than a technological shock.

We are ultimately interested in a distinct question: do voters view different economic shocks as requiring different types of political leaders? Rather than ask respondents about government measures—like trade protection or compensation—we test whether the type of shock has differential effects on the type of leader respondents think is best suited to preventing these layoffs. Without denying the importance of policies and political parties, there is growing evidence of a personalization of politics (Rahat and Kenig 2018). Our focus on leaders makes particular sense in the US, where leaders are significantly more polarizing than parties (Reiljan et al., 2024). In short, preferences for leaders are more salient than preferences for specific policies, such as trade measures, which remain second-order concerns for the average American voter.

While we are principally interested in showing how the sources of economic shocks differ in their political effects, it is worth briefly considering why this could be the case. A first reason may have to do with the type of intervention that would be required to prevent or remedy the shock in each case. In attempting to tackle structural forces like offshoring and technological change, policymakers have limited options. They can try to cushion the labor transition following layoffs, using government transfers. But preventing private companies from moving production abroad, or from adopting new labor-saving technology, is politically difficult, and requires radical measures. In the past, politicians have thus threatened to forcefully nationalize companies that did not stay in the country.³ In the US, Donald Trump famously threatened specific companies like Carrier, Toyota, and Harley Davidson with direct (but highly indeterminate) “consequences” if they moved their US production offshore.⁴ In the case of automation, policymakers on both sides of the Atlantic have proposed adopting a “robot tax” that would make the use of labor-reducing technology more costly.⁵ For this reason, the threat of large structural forces may lead to calls for radical measures that would seem out of step with strictly economic events.

A second possibility is that economic shocks have different implications for different identity groups. When economic facts are refracted through the lens of group identity, who the “culprit” is also determines individual beliefs over who bears the greatest harm. The focus on identity may account for a puzzling aspect of the recent populist backlash: an individual’s own material condition may be unchanged, yet they may nonetheless worry that the fortunes of their group are declining, and demand that politicians take action in response (Jardina 2019; Sides et al., 2018). In this view, the key distinction between the two shocks we consider, offshoring and automation, is that the first benefits an identifiable out-group—foreign workers—while the second does not. The resulting grievance is of a type that the recent wave of populist leaders is especially well suited to exploit (Müller 2016).

A third possibility is that individuals’ responses to external economic shocks may come down less to instrumental demands for specific policies, and more to an attempt at reasserting control in settings where individuals feel deprived of it. A large literature in social psychology, from Fromm (2014) to Adorno (2019) and more recently Altemeyer (2007), attests to how individuals become more inclined to seek out and support strong, controlling leaders who promise order and stability in the face of external threats, and who are willing to use any means required to secure these (Ballard-Rosa et al., 2022). Similarly, individuals may rally behind leaders who articulate their fears and offer what are often simplistic solutions to complex problems.

Whether out of a belief that only radical measures can help in the face of structural forces like offshoring, or out of a need to reassert control in settings where individuals feel deprived of it, an authoritarian approach to political rule may be especially likely to garner support in the face of external threats, like competition from foreign workers, that appear unstoppable.

This reasoning leads us to distinguish leadership traits associated with authoritarianism to other commonly held aspects of populism. In particular, the core claim of populist leaders is that “only some of the people are really the people” (Müller 2016), and they will represent them. Another common trait of populist leaders is their claim to being political outsiders, unsullied by the political establishment (Guriev and Papaioannou 2022). We test the extent to which different economic shocks lead to specific demands for these two leadership traits. We acknowledge that some real-world leaders, such as President Trump, embody both traits. Our main goal is exactly to assess whether some shocks breed more tolerance for one trait (i.e., authoritarianism) than another (i.e., populism). In sum, in response to findings that link economic shocks, broadly held, to populism, broadly conceived (Benczes and Szabó 2023; Guiso et al., 2017), our analysis teases apart the various components of these concepts.

Research design

We conducted an original survey on 3500 US adults, representing a quota-valid sample in terms of age, employment status, sex, and region, conducted from December 9, 2021 to January 7, 2022.⁶ The key part of the survey involves a vignette experiment, shown in Table 1. We employ simple random assignment for this between-subjects pre-registered experimental design to elicit the type of leader most favored to tackle different economic shocks.⁷

Table 1.

The wording of the vignette experiment.

Imagine the following event: 1000 employees of a company in your area are being laid off because:

[randomized order, one scenario out of three]

• The company is moving its production abroad

• New technology is replacing human workers

• The company is going bankrupt

How much do you agree with the following statement (0 - Completely disagree, 10 - Completely agree):

It is the role of political leaders to prevent layoffs due to:

• A company moving its production abroad?

• New technology replacing human workers?

• A company going bankrupt?

[one scenario, matching the randomly assigned scenario]

On a scale where 0 means the worst and 10 means the best, which leader would be best at preventing layoffs like these?

[randomized order]

• A politician who listens to the people

• A political outsider

• A politician who does not feel constrained by the rules to serve people’s needs

• A politician who understands that using force is sometimes required to bring about positive change

• A politician who does whatever it takes to help their local constituents, even if it upsets other people in the country

Outcome variables

We explore three outcome variables. First, we ask whether respondents believe that some layoffs demand more political attention than others. We ask all respondents, “How much do you agree with the following statement: It is the role of political leaders to prevent layoffs due to a company moving its production abroad/ new technology replacing human workers/ a company going bankrupt?” This Prevent Layoffs variable is measured on a 0–10 scale, with higher values indicating greater demand for political action. In this way, we test whether the perceived responsibility of politicians depends on the cause of the economic disruption, holding its magnitude constant. Does attributing layoffs to offshoring or automation—as opposed to a generic bankruptcy—move an economic event into the political realm?

We then ask respondents about the leadership traits most apt to preventing the randomized layoff. A second variable, Populism, measures the extent to which respondents seek: (i) “a politician who listens to the people” and (ii) “a political outsider,” and takes the average of these two items.⁸

A third outcome variable, Authoritarianism, captures aggressive policy measures (Ballard-Rosa et al., 2022) suggestive of anti-democratic attitudes. To measure respondents’ support for such authoritarian measures, we measure their combined support for: (i) “a politician who does not feel constrained by the rules to serve people’s needs”; (ii) “a politician who understands that using force is sometimes required to bring about positive change”; and (iii) “a politician who does whatever it takes to help their local constituents, even if it upsets other people in the country.”

Empirical strategy

We estimate the following model:

Y_{i} = α_{0} + β_{1} {A u t o m a t i o n}_{i} + β_{2} {O ff s h o r i n g}_{i} + β_{3} X_{i} + ϵ_{i},

(1)

where the outcome variable Y_i is one of the three variables outlined above, observed for each respondent i. Automation_i and Offshoring_i are randomized treatments, which vary across respondents. The baseline category is the scenario of layoffs due to run-of-the-mill “bankruptcy.” X_i is a set of individual-level pre-treatment controls: Age, sex, region, education, residence type, race, occupational status, ideology, political interest, partisanship, and vote in the 2020 US presidential elections.⁹ We estimate OLS regressions with robust standard errors and we account for multiple comparisons.¹⁰

Findings

We report our main findings in Table 2, where we uncover three main causal effects. First, both automation and offshoring are more likely to trigger a demand for government intervention than bankruptcy and both effects are significant (Model 1). This finding may not be too surprising, since bankruptcies are typically seen as market-driven, that is, inevitable, more so than layoffs due to automation and offshoring. However, the most important result for us is that the coefficient for Offshoring is about twice as large as for Automation. The difference of coefficients’ size is significant (p < .001). Being exposed to the offshoring condition makes the respondents 14 percentage points more likely to demand political action than those in the bankruptcy treatment, compared to nine points for automation. Comparatively, the effect of Offshoring is more than twice as large as the effect of partisanship.

Table 2.

The political Impact of Offshoring and Automation.

	PreventLayoffs(1)	Populism(2)	Authoritarianism(3)
Offshoring	1.423***	0.066	0.230**
	(0.110)	(0.071)	(0.082)
	[0.000]	[1.000]	[0.044]
Automation	0.850***	0.064	0.059
	(0.107)	(0.071)	(0.080)
	[0.000]	[1.000]	[1.000]
Constant	5.263***	6.354***	5.296***
Constant	(0.344)	(0.211)	(0.241)
p (β_Offshoring = β_Automation)	0.000	0.97	0.03
Controls	Yes	Yes	Yes
Observations	3505	3505	3505

Note. ^***p < .01,^**p < .05, ^*p < .1. OLS estimations with robust standard errors in parentheses. Bonferroni-adjusted p-values are shown in square brackets. Dependent variables (0–10): Politicians should prevent these layoffs - model 1; Populism - model 2; Authoritarianism - model 3. The bankruptcy vignette is the reference category.

Second, automation and offshoring appear no more likely to trigger a demand for populism than bankruptcy (Model 2). The coefficients of Offshoring and Automation remain positive across all our specifications, but fall short of statistical significance throughout. A possible explanation is that the mean value of populism for the baseline bankruptcy condition is high (6.3 on a 0–10 scale) and especially high for the “listens to the people” component (7.7). In other words, populist attitudes may be so high on average that it becomes difficult to observably move respondents on this dimension. This is in line with previous research showing that populist attitudes are highly prevalent among American voters (Bonikowski and Gidron 2016). Moreover, it confirms other findings about the valence (rather than the positional nature) of populism (Neuner and Wratil 2022, 559).¹¹

Third, and most striking, offshoring appears significantly more likely to trigger a demand for authoritarianism than either automation or bankruptcy (Model 3).¹² The coefficient of Offshoring is large and significant, while the effect for Automation shows no effect; the difference between these two coefficients is statistically significant (p = .03). Compared to the bankruptcy scenario, the Offshoring treatment makes respondents more favorable to authoritarian traits by about 5%. The effect of Offshoring is comparable in magnitude to both having a high school degree (relative to being a college graduate, the reference category) and exhibiting high political interest.

In sum, our experimental analysis offers evidence that offshoring has a strong causal effect on authoritarianism attitudes, compared to automation or run-of-the-mill bankruptcies. By contrast, neither offshoring nor automation appears to drive calls for populist leaders. Given the difficulty of preventing either offshoring or automation, respondents appear to view leaders who do not shy away from radical political actions as more effective in preventing companies from relying on either.

Additional evidence

We report additional tests in Appendix E. In particular, we show that (i) the demand for leaders more willing to employ force and to adopt divisive policies drives our main result (Appendix E.1); (ii) results are substantively similar with a binary operationalization of outcomes, based on the midpoint of the scale (Appendix E.2); and (iii) results are not driven by pre-treatment attitudes towards globalization and redistribution (Appendix E.3). We find little impact of key moderating variables—sex, race, education, rural residence, partisanship, and vote for Trump—on the demand for radical political action (Appendix E.4). Furthermore, economic vulnerability does not mediate our main effects (Appendices E.5–E.7).

Conclusion

In this research note, we seek to provide causal evidence for what is prima facie an unexpected relation between different types of economic shocks and a demand for radical political leaders. The findings are striking. First, respondents appear to believe that both automation and offshoring are events that require a political response, and that politicians thus have a role in preventing these. Yet this call for political action is almost twice as large for offshoring than for automation.

Most sobering is the type of political response individuals call for. We find strong evidence that economic shocks due to offshoring lead to greater demands for a specifically authoritarian approach. When presented with news of layoffs due to offshoring, respondents turn to leaders who claim to be more willing to employ force, to flout the rule of law, and to implement divisive policies. By contrast, we find no significant evidence of increased support for typically populist stances, such as an embrace of “the people” or of political “outsiders.”

Automation and offshoring are both difficult to prevent through policy means. As long as labor costs outside the US costs are lower, firms have an incentive to outsource and automate production. In response, some political leaders have made direct threats aimed at specific companies, or hinted at unprecedented taxes or forced nationalization. Political audiences may thus reason that only a radical response can prevent layoffs caused by these structural forces. If so, the willingness to resort to force and break extant norms may serve as a proxy for the ability to act with sufficient resolve.

Supplemental Material

Supplemental Material - The source of economic shocks matters for their political outcomes

Supplemental Material for The source of economic shocks matters for their political outcomes by Leonardo Baccini, Costin Ciobanu, and Krzysztof Pelc in Research & Politics

Footnotes

Acknowledgments

We thank Francesco Amodio, Elissa Berwick, Aengus Bridgman, Aaron Erlich, Diana Mutz, Thomas Sattler, Joost van Spanje, and Stephen Weymouth for suggestions on the survey experiment. We also thank participants to Princeton’s Niehaus Center “The Backlash: What’s Next” Workshop (2022) and to the 2022 APSA Annual Meeting for their feedback. Sean Nossek provided outstanding research assistance. The usual disclaimers apply. Ethics approval for the survey experiment was obtained from McGill University (REB #21-01-034, January 21, 2021). The pre-analysis plan registered with EGAP is available here: .

ORCID iDs

Leonardo Baccini

Costin Ciobanu

Krzysztof Pelc

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Funding for this research was provided by the SSHRC Insight Development Grant, Canada (Grant agreement 430-2018-1145) and the FQRSC Team Grant (Grant agreement 243479 2017-SE-196451).

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Carnegie Corporation of New York Grant

This publication was made possible (in part) by a grant from the Carnegie Corporation of New York. The statements made and views expressed are solely the responsibility of the authors.

Supplemental Material

Supplemental material for this article is available online.

The replication files are available at: .

Notes

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