By Using a machine-learning algorithm based on BIC, we set up a reduced set of best predictors for Italian populist parties using data on the 2018 general elections at municipality level. Two different and clear patterns emerge, which provide partial support to theories on economic insecurity, cultural backlash, and political detachment. 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. In a second step, by using our best predictors we predict the vote of the Italian parties in France, Spain, and United Kingdom, and confront them with those countries’ actual electoral outcomes. Results confirm that our models are able to catch some common features of the ongoing reshaping of the political arena. In conclusion, our analysis suggests that populist parties are re-grouping votes astray from the previous left/right cleavage.

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

Levi E;
2020-01-01

Abstract

By Using a machine-learning algorithm based on BIC, we set up a reduced set of best predictors for Italian populist parties using data on the 2018 general elections at municipality level. Two different and clear patterns emerge, which provide partial support to theories on economic insecurity, cultural backlash, and political detachment. 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. In a second step, by using our best predictors we predict the vote of the Italian parties in France, Spain, and United Kingdom, and confront them with those countries’ actual electoral outcomes. Results confirm that our models are able to catch some common features of the ongoing reshaping of the political arena. In conclusion, our analysis suggests that populist parties are re-grouping votes astray from the previous left/right cleavage.
2020
Populism, Italy, Predictors, Machine-learning
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14085/21416
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