Support for Marine Le Pen in the French presidential election differed substantially across the country. Using data from the European Quality of Government Index, Nicholas Charron and Monika Bauhr show that Le Pen won a greater share of support in areas where citizens are dissatisfied with the delivery of public services.
Since at least 1789, stark ideological polarisation has constituted an important element of the political landscape of France. Yet French election results can also be explained by another, deep, cleavage in France between those that are largely satisfied with public services such as education and healthcare, and those that perceive these services to be plagued by particularism, unfairness and sometimes even outright corruption.
Using our recently published European Quality of Government Index Survey, we can see that regions voted for Macron when its citizens were largely satisfied with the quality, fairness and impartiality of their public services. Conversely, le Pen won in most regions where citizens are largely dissatisfied with the delivery of these public services.
The survey, collected at the beginning of 2021, provides responses from over 500 respondents in each of the NUTS 2 regions in France. Our findings indicate considerable within-country, regional variation, with roughly one-third or less of the vote going to Le Pen in regions such as Île de France, Bretagne and Pays-de-la-Loire, but a majority backing Le Pen in Nord-Pas-de-Calais, Champagne-Ardenne, Corse and the overseas territories.
Figure 1 shows scatterplots for our perceptions index for the French NUTS 2 (left side) and NUTS 3 levels (right side). We observe strikingly high correlations in both cases; -0.93 and -0.58 respectively, with the capital region, Île de France, highlighted with red triangles as a unique outlier.
Figure 1: Relationship between higher perceived quality of government and Le Pen vote share in NUTS 2 and NUTS 3 regions
Note: The figure shows the vote share for Le Pen in the second round by region on the y-axis, and European Quality of Government Index (EQI, Charron et al 2021) on the x-axis. Higher values in the European Quality of Government Index imply lower perceptions of corruption, higher perceptions of impartiality and fairness, and better quality of services. EQI figures standardised (0-1) for the French sample.
Yet how does this simple correlation stand up when we account for other factors? First, we test the effect of the European Quality of Government Index on the Le Pen vote share for the 2022 sample at the NUTS 2 (Regions) and NUTS 3 (Department) level. We control for several other possible confounding factors, such as unemployment, GDP per capita, population, the average perceived health worry of Covid-19, whether a region is located on the mainland or overseas, and the second round vote share for Le Pen in the 2017 election.
Figure 2 summarises the two models by order of variable importance. Among the regions sample, the European Quality of Government Index explains the most variance of the 2022 second round vote share for Le Pen, with an increase of one standard deviation in the index predicting around a six per cent decrease in Le Pen’s vote share. Le Pen’s 2017 vote share, the size of the population, overseas region status, and GDP per capita all significantly explain variation in the 2022 Le Pen vote share in the expected direction, while unemployment and concern about Covid-19 were statistically insignificant.
Looking at the Le Pen vote share among French departments, we find that again, the European Quality of Government Index is a significant and negative predictor, yet the 2017 vote share, overseas status, and population are more relevant in this model. One reason for this discrepancy could be that the European Quality of Government Index survey samples at the NUTS 2 level, and therefore the NUTS 3 estimates, which rely on far fewer respondents, could be less reliable. In any case, we take this as evidence that citizen perceptions of institutions explain more variation in vote share than do more common explanations such as GDP per capita, unemployment, or concern about Covid-19.
Figure 2: Predictors of the Le Pen vote share in French regions and departments
Note: Absolute effects of a one standard deviation increase in each variable shown, with direction of effect indicated (- or +). Paris is excluded due to it being an extreme outlier on several variables. Population and GDP per capita are logged and taken from Eurostat. Unemployment rate for 20-64 taken from Eurostat (unavailable for NUTS 3). Covid-19 threat from the 2021 EQI survey is the aggregate response to ‘how worried are you for your health due to Covid-19’ (1-4, not at all worried to very worried). R² = 0.94 and 0.86 in left and right-hand side models respectively. Black bars = p<0.05, dark grey bars = p<0.10, light grey bars = statistically insignificant.
While Le Pen managed to increase her vote share in all regions compared with 2017, there were significant differences in the amount by which her vote share increased. For instance, she increased support by just 4.3% in Lorraine, but by 39.6% in Guadeloupe. Accounting for the initial levels of the variables in 2017, how much do changes in our variables between 2017 and 2022 account for the change in regional support for Le Pen? While the European Quality of Government Index did not indicate the NUTS 3 level in 2017, we can look at this question for the NUTS 2, regions level.
In Figure 3, we observe a significant effect of the European Quality of Government Index. A one standard deviation of improved perceptions of regional governance since 2017 reduced the change in support for Le Pen by nearly 4%. Neither changes in GDP per capita nor unemployment rates explain changes in Le Pen support when accounting for the European Quality of Government Index. The 2017 levels show that initially wealthier regions had greater increases in Le Pen vote share on average, while regions with better perceived institutional quality, more urban and already stronger support for Le Pen saw smaller increases in her vote share, all things being equal. This demonstrates stronger, potentially causal evidence of the effect of perceived institutional quality on lower support for right-wing populism.
Figure 3: Changes in key variables since 2017 and change in regional support for Le Pen (2017 to 2022)
Note: The dependent variable is the change in Le Pen support from 2022 to 2017. ‘Δ’ indicates change from 2017 to 2022. R² = 0.93. See note in Figure 2 for more details.
Emmanuel Macron’s time in office has been plagued by multiple crises, from the ‘yellow vest’ protests against his fuel tax, the Covid-19 pandemic and currently inflation, and the war waged by Russia against Ukraine. The “can’t stand the other guy” effect on election results is of course important: many citizens choose Le Pen to protest against Macron (and vice versa). Others in particular from the left, could not even hold their nose and vote for either of these candidates and simply abstained.
This could at least partly explain Le Pen’s stronger performance in some regions where she previously performed poorly. While economic concerns and unemployment are generally promoted in the media as causes of support for right-wing populism, improving such factors may not quell support for right wing populists. Further, Le Pen performed poorly in urban areas with greater immigrant populations. Although the ideological differences between Le Pen and la gauche is stark, they seem to be united by one thing: the perception that public services are plagued by inequality, discrimination, and biases, and that they are seen to benefit the few and well connected at the expense of the many. This factor is undoubtedly a political force with the potential to change the electoral landscape in a decisive way and should receive greater attention by journalists and researchers alike.