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),


  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.


Tuesday, 20 March 2018


Twitter: frbailo



RSS r-bloggers.com

  • Why R? 2018 Conference – Registration and Call for Papers Opened
    The first edition of Polish R Users Conferences called Why R? took place on 27-29 September at Warsaw University of Technology - Faculty of Mathematics and Information Science. The event was so successful that we’ve decided to launch a second edition of the conference. About the Why R? 2018 conference Important dates Keynotes Programme Pre-meetings […]
  • Amsterdam in an R leaflet nutshell
    The municipal services of Amsterdam (The Netherlands) is providing open panorama images. See here and here. A camera car has driven around in the city, and now you can download these images. Per neighborhood of Amsterdam  I randomly sampled 20 … Continue reading →
  • Data Science For Business: Course Launch In 5 Days!!!
    Last November, our data science team embarked on a journey to build the ultimate Data Science For Business (DS4B) learning platform. We saw a problem: A gap exists in organizations between the data science team and the business. To bridge this gap, we’ve created Business Science University, an online learning platform that teaches DS4B, using […]
  • Big changes behind the scenes in R 3.5.0
    A major update to R is now available. The R Core group has announced the release of R 3.5.0, and binary versions for Windows and Linux are now available from the primary CRAN mirror. (The Mac release is forthcoming.) Probably the biggest change in R 3.5.0 will be invisible to most users — except by […]
  • The current state of the Stan ecosystem in R
    This post is by Jonah. Last week I posted here about the release of version 2.0.0 of the loo R package, but there have been a few other recent releases and updates worth mentioning. At the end of the post I also include some general thoughts on R package development with Stan and the growing number of […]

RSS Simply Statistics

  • What can we learn from data analysis failures?
    Back in February, I gave a talk at the Walter and Eliza Hall Research Institute in Melbourne titled “Lessons in Disaster: What Can We Learn from Data Analysis Failures?” This talk was quite different from talks that I usually give on computing or environmental health and I’m guessing it probably showed. It was nevertheless a […]
  • Process versus outcome productivity
    Several times over the last few weeks my hatred of Doodle polls has come up in meetings. I think the polling technology is great, but I’m still frustrated by the polls. Someone asked what I’d rather have happen and I said: “set the meeting, then let me know when it is, if I can come […]
  • What is a Successful Data Analysis?
    Defining success in data analysis has eluded me for quite some time now. About two years ago I tried to explore this question in my Dean’s Lecture, but ultimately I think I missed the mark. In that talk I tried to identify standards (I called them “aesthetics”) by which we could universally evaluate the quality […]

RSS Statistical Modeling, Causal Inference, and Social Science

  • Proposed new EPA rules requiring open data and reproducibility
    Tom Daula points to this news article by Heidi Vogt, “EPA Wants New Rules to Rely Solely on Public Data,” with subtitle, “Agency says proposal means transparency; scientists see public-health risk.” Vogt writes: The Environmental Protection Agency plans to restrict research used in developing regulations, the agency said Tuesday . . . The new proposal […]
  • The current state of the Stan ecosystem in R
    This post is by Jonah. Last week I posted here about the release of version 2.0.0 of the loo R package, but there have been a few other recent releases and updates worth mentioning. At the end of the post I also include some general thoughts on R package development with Stan and the growing number of […]
  • A few words on a few words on Twitter’s 280 experiment.
    Gur Huberman points us to this post by Joshua Gans, “A few words on Twitter’s 280 experiment.” I hate twitter but I took a look anyway, and I’m glad I did, as Gans makes some good points and some bad points, and it’s all interesting. Gans starts with some intriguing background: Twitter have decided to […]