Local participation and not unemployment explains the M5S result in the South

The abundance of economic data and the scarcity of social data with a comparable level of granularity is a problem for the quantitative analysis of social phenomena. I argue that this fundamental problem has misguided the analysis of the electoral results of the Five Star Movement (M5S) and its interpretation. In this article, I provide statistical evidence suggesting that — in the South — unemployment is not associated with the exceptional increase in the M5S support and that local participation is a stronger predictor of support than most of the demographics.

What happened

The 2018 Italian general elections (elections, since both the Chamber of Deputies and the Senate, were renewed) saw

  1. a significant increase in the number of votes for two parties, the Five Start Movement (M5S) and the League (formerly Northern League),

and

  1. an increase in the importance geography as an explanatory dimension for the distribution of votes.

The following two maps show where the M5S and the League have increased electoral support from 2013 to 2018. (Electoral data are always data for the election of the Chamber of Deputies).

Vote difference: 2018-2013 (a few communes have not reported all the results, notably Rome)

 

The geographic pattern is quite simple. The M5S has increased its support in the South and maintained its votes in the North, the League has significantly strengthened its support in the North but has also collected votes in the South, where it had virtually no support. The third and the fourth most voted parties, the Democratic Party (PD) and Berlusconi’s Forza Italia (FI), have lost votes almost everywhere. If we map the results of the four parties side-by-side with the same scale, the PD and FI almost faded into the background.

Votes in the 2018 General elections

Yet, major metropolitan areas do not always follow the national trend. If Naples unambiguously voted M5S, Turin, Milan and Rome did saw the Democratic Party as the most voted party in the wealthiest districts.

Votes in the 2018 General elections (Clock-wise from top-left: Turin, Milan, Naples, Rome)

The density of the distribution of results at the commune and sub-commune level in the macro regions indicates that if the M5S electorally dominates in the South and in the two major islands, the League is the most popular party in the North.

Distribution of votes at commune or sub-commune level

The territoriality of the results, especially along the North-South dimension, makes the analysis especially complicated. This because the strong result of the League in the North and of the M5S in the South might simplistically suggest that immigration (which is much stronger in the North) explains the League’s result in the North and unemployment and poverty (stronger in the South) explain the M5S’s result in the South. This reading is especially attractive since immigration and the M5S proposal to introduce a guaranteed minim income have dominated the campaign.

(more…)

Tuesday, 20 March 2018

tweets


Twitter: frbailo

links


blogroll


RSS r-bloggers.com

  • Model-Based Causal Forests for Heterogeneous Treatment Effects
    A new arXiv paper investigates which building blocks of random forests, especially causal forests and model-based forests, make them work for heterogeneous treatment effect estimation, both in randomized trials and observational studies. ... Continue reading: Model-Based Causal Forests for Heterogeneous Treatment Effects
  • A Major Contribution to Learning R
    Prominent statistician Frank Harrell has come out with a radically new R tutorial, rflow. The name is short for “R workflow,” but I call it “R in a box” –everything one needs for beginning serious usage of R, starting from little or no background. By serious usage I mean real ... Continue reading: A Major […]
  • Evaluating GitHub Activity for Contributors
    Say you have a bug report or feature request to make to a package. How can you use information on GitHub to manage your expectations (will there be a quick fix) and actions (should you go ahead and fork the repository)? In this post, we shall go over ... Continue reading: Evaluating GitHub Activity for […]
  • Developing React Applications in RStudio Workbench
    Introduction RStudio Workbench provides a development environment for R, Python, and many other languages. When developing a performant web application you may progress from Shiny towards tools li... Continue reading: Developing React Applications in RStudio Workbench
  • Food Crisis Analysis and, Forecasting with Neural Network Autoregression
    The war between Russia and Ukraine has affected the global food supply other than many vital things. Primarily cereal crop products have been affected the most because the imports have been provided to the world mainly through Ukraine and Russia. Let’s check the situation we’ve mentioned for G20 ... Continue reading: Food Crisis Analysis and, […]

RSS Simply Statistics

RSS Statistical Modeling, Causal Inference, and Social Science