Updated Forecasts of the Italian Legislative Election

As an update of our previous post, we ran some simulations including an additional "political" effect (voters' fatigue with the incumbent) and additional sources of uncertainty. While the simulations we reported last week were basically a rerun of the 2013 election, only with current economic conditions and immigration levels, and should therefore be considered a very rough baseline, these simulations are closer to a forecast of this election, as they take into account that the Prime Minister in office belongs to the Democratic Party.

Specifically, these plots display the results of new simulations that take into account the fact that usually the ruling party (i.e., the party of the Prime Minister) does worse in the election at the end of its tenure. We base the simulations on a plausible value of the magnitude of voters' fatigue with the incumbent, consistent with recent Italian legislative elections.

The red line is the mean prediction from our simulations, and the dashed lines identify the 95% credible interval.

Interestingly, this seems to be, to an extent, a case of the "why are campaign polls so variable if elections are so predictable" effect, documented in the U.S. case.

In particular, the Democratic Party polls seem to be converging to the prediction we make based on the economy and immigration, once the "fatigue" of voters with the incumbent is taken into account. If anything, maybe the Democratic Party, as of January, was polling a bit higher than the fundamentals and incumbency predict.

To an extent, the same is true also for the Five Star Movement, that was polling exceptionally well in the first half of 2017, but seems to be converging to the level we forecast based on the economy and immigration patterns.

On the other hand, the Center-Right coalition seems to be polling, as of January, quite higher than what one would otherwise expect based on fundamentals. This effect could be attributed to the return of Berlusconi, who, in 2013 (the election on which we base our forecast) was arguably quite less popular than he is now (and than he was prior to the crisis). Voters seem to have forgiven (or forgotten) Berlusconi's role in the debt crisis.

The mean of our predictions for the national vote share of the Center-Right coalition, plotted against the mean of surveys in each month going from January 2017 to January 2018. Dashed lines are 95% Bayesian credible intervals. The swing attributed to the incumbency disadvantage in each municipality is drawn from a normal distribution with mean -2.3, and standard deviation 6.7.

The mean of our predictions for the national vote share of the Democratic Party, plotted against the mean of surveys in each month going from January 2017 to January 2018. Dashed lines are 95% Bayesian credible intervals. The swing attributed to the incumbency disadvantage in each municipality is drawn from a normal distribution with mean -2.3 and standar deviation 6.7.

The mean of our predictions for the national vote share of the Five-Star Movement, plotted against the mean of surveys in each month going from January 2017 to January 2018. Dashed lines are 95% Bayesian credible intervals. The swing attributed to the incumbency disadvantage in each municipality is drawn from a normal distribution with mean -2.3 and standard deviation 6.7.

More technical information: The new forecasts are based on  simulations that include a (stochastic) swing reflecting a plausible "incumbency disadvantage". In general, at least since the beginning of the century, the party of the Prime Minister lost several percentage points over a term in office. This loss ranges from a maximum of almost 17 percentage points (People of Freedom, 2013 compared to 2008) to a minimum of 2.3 percentage points (Berlusconi's coalition, 2006 compared to 2001).

These simulations include a swing at the municipal level, normally distributed with mean -2.3 (the negative swing received by Berlusconi's camp between 2001 and 2006) and standard deviation 6.7 (the standard deviation, across municipalities, of the negative swing received by the Center-Left coalition between 2006 and 2008).

For each of the 1000 simulations of the election, we draw one incumbency shock for each municipality from the distribution and add it to the vote share of the Democratic Party. We then allocate the gain to the other three camps (Center-Right coalition, Five Star Movement, and "others") based on weights drawn from uniform distributions with expected value 1/3 and summing to one. In practice, this reflects our ignorance regarding who gains more from the incumbency disadvantage of the Democratic Party. We assume that, on average, the votes the Democratic Party loses due to this phenomenon benefit equally the Center-Right, the Five Star Movement, and other smaller parties (e.g., Free and Equal, the splinter party set up by a faction of the Democratic Party). At the same time, we incorporate in the simulations the uncertainty about how the gains are split: in each simulation and in each municipality the gains are split based on different draws of the weights.

Below are more conservative simulations, where we include an incumbency effect like that of 2006 vs 2001, including its (very large) observed standard deviation across municipalities (22 percentage points, as observed in the actual data in 2006). In these simulations, the confidence intervals are quite wider, and the polling average for the Five Star Movement and the Democratic Party fall within our 95% credible interval. The Center-Right coalition, though, is still polling higher than our forecasts.

The mean of our predictions for the national vote share of the Center-Right coalition, plotted against the mean of surveys in each month going from January 2017 to January 2018. Dashed lines are 95% Bayesian credible intervals. The swing attributed to the incumbency disadvantage in each municipality is drawn from a normal distribution with mean -2.3 and standard deviation 22. 

The mean of our predictions for the national vote share of the Democratic Party, plotted against the mean of surveys in each month going from January 2017 to January 2018. Dashed lines are 95% Bayesian credible intervals. The swing attributed to the incumbency disadvantage in each municipality is drawn from a normal distribution with mean -2.3 and standard deviation 22. 

The mean of our predictions for the national vote share of the Five-Star Movement, plotted against the mean of surveys in each month going from January 2017 to January 2018. Dashed lines are 95% Bayesian credible intervals. The swing attributed to the incumbency disadvantage in each municipality is drawn from a normal distribution with mean -2.3 and standard deviation 22. 

About the authors

Massimo Pulejo is a Pre-Doctoral Fellow at Bocconi University, Department of Policy Analysis and Public Management.

Piero Stanig is Assistant Professor of Political Science at Bocconi University, Department of Policy Analysis and Public Management, and a fellow of the Carlo F. Dondena Research Center. 

Thanks to Giovanni Da Fre' for excellent research assistance.