Arbeitspapier

An exploratory study of populism: the municipality-level predictors of electoral outcomes in Italy

We present an exploratory machine learning analysis of populist votes at municipality level in the 2018 Italian general elections, in which populist parties gained almost 50% of the votes. Starting from a comprehensive set of local characteristics, we use an algorithm based on BIC to obtain a reduced set of predictors for each of the two populist parties (Five-Star Movement and Lega) and the two traditional ones (Democratic Party and Forza Italia). Differences and similarities between the sets of predictors further provide evidence on 1) heterogeneity in populisms, 2) if this heterogeneity is related to the traditional left/right divide. The Five-Star Movement is stronger in larger and unsafer municipalities, where people are younger, more unemployed and work more in services. On the contrary, Lega thrives in smaller and safer municipalities, where people are less educated and employed more in manufacturing and commerce. These differences do not correspond to differences between the Democratic Party and Forza Italia, providing evidence that heterogeneity in populisms does not correspond to a left/right divide. As robustness tests, we use an alternative machine learning technique (lasso) and apply our predictions to France as to confront them with candidates' actual votes in 2017 presidential elections.

Sprache
Englisch

Erschienen in
Series: GLO Discussion Paper ; No. 430

Klassifikation
Wirtschaft
Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
National Security; Economic Nationalism
Financial Crises
Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination
Technological Change: Choices and Consequences; Diffusion Processes
Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification
Thema
Voting
Populism
Economic insecurity
Political Economy

Ereignis
Geistige Schöpfung
(wer)
Levi, Eugenio
Patriarca, Fabrizio
Ereignis
Veröffentlichung
(wer)
Global Labor Organization (GLO)
(wo)
Essen
(wann)
2019

Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Levi, Eugenio
  • Patriarca, Fabrizio
  • Global Labor Organization (GLO)

Entstanden

  • 2019

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