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Political-Economic Polarization

González-Rostani, Valentina (2024) Political-Economic Polarization. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

The political landscape in post-industrial democracies is increasingly turbulent and polarized, driven by structural economic changes, especially production automation since the mid-1990s. This dissertation explores how economic polarization (a disappearing middle class) fuels political polarization (declining moderate parties, candidates, and voters). It introduces the concept of “political-economic polarization" to explain the interplay between economic change and party system shifts. This theory provides insights into the political economy of job automation, examining its impact on political attitudes, partisan politics, and the interplay of economic, cultural, and institutional factors, drawing on political economy, institutions, party politics, and political psychology.

Structural economic changes create vulnerabilities among workers that political parties exploit strategically. Whether a party can appeal to these workers depends on its status as part of the establishment or an outsider and is critically dependent on a country's electoral institutions and party systems, which shape the mechanisms sustaining political polarization. In majoritarian systems, right-wing populists focus on tax and transfer policies to win the support of at-risk workers in marginal districts. In proportional representation systems with trichotomous multipartism (PRITM), right-wing populists emphasize identity-related issues rather than material transfers to attract dissatisfied voters. On the demand side of political representation, this dissertation proposes two channels explaining why at-risk workers shift to radical right instead of left parties and candidates. First, at-risk workers experience increased cultural grievances, including feelings of marginalization and nostalgia. Second, declining political efficacy among workers leads to political alienation, paving the way for radicalization. This work employs a multi-method approach, integrating formal modeling, time-series cross-sectional analysis, panel data analysis, survey experiments, and text-analysis techniques.

Despite the overall increase in political polarization, the strategies of outsider parties and leaders to mobilize support vary significantly. This research is among the first to consider how political-institutional contexts moderate economic polarization's effects on elections. It also explains why at-risk workers turn to right-wing populism. Methodologically, it advances political communication studies by utilizing cutting-edge natural language processing techniques to measure populism and identify issues. On the demand side, it employs a survey experiment with double randomization to identify causal mechanisms between automation exposure and politics.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
González-Rostani, Valentinamag384@pitt.edumag3840000-0003-1316-1009
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairHays, Judejch61@pitt.edujch610000-0003-2069-3038
Committee MemberOwen, Ericaeop3@pitt.edueop3
Committee MemberAklin, Michaëlmichael.aklin@epfl.ch0000-0001-9487-9359
Committee MemberGoplerud, Maxmgoplerud@austin.utexas.edumhg230000-0002-3179-251X
Date: 27 August 2024
Date Type: Publication
Defense Date: 19 June 2024
Approval Date: 27 August 2024
Submission Date: 8 July 2024
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 413
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Political Science
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Automation, technological change, economic polarization, political polarization, populism, survey experiment, text-as-data
Date Deposited: 27 Aug 2024 13:40
Last Modified: 27 Aug 2024 13:40
URI: http://d-scholarship.pitt.edu/id/eprint/46658

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