Polling and political behavior : explaining inaccuracy in Italian polling

The use of polls during election campaigns has become increasingly commonplace, its main purpose being to predict elections results. Some literature highlights evidence that pre-electoral polls increase their predictive accuracy as the time between the interview and Election Day decreases. Understanding why some polls get it right and others get it wrong is important to better ascertain the evolution of election campaigns and voting intentions across time. A considerable literature shows how the quality of poll predictions is affected by a variety of methodological decisions taken by pollsters. This raises the question that underlies this thesis: under what conditions are polls inaccurate as predictors of voters’ behaviour? In order to answer this question, we analyze the last three Italian general elections. The aim of this thesis is to estimate what has the greatest impact on inaccuracy in Italian polling between the house effect and voters sentiment change. To do that, we firstly revise the well-established accuracy measures used so far in order to fit the Italian case and the new accuracy measure proposed for multi-party systems (Bw). Then, we estimate the house effect using OLS and multivariate regression models, where the days and polling houses and the methodologies employed by pollsters are the explanatory variables respectively. To estimate the extent of voters sentiment change in Italian voters, we apply the autoregressive model. The evidence provided by the accuracy measures shows a high presence of inaccuracy in Italian polling. Moreover, the OLS models provide strong evidence of the house effect, whereas the autoregressive model does not confirm the hypothesis of voters sentiment change across time. Therefore, the greater cause of inaccuracy in Italian polling is the house effect rather than any movement in voting intentions in the last three general elections.

Level dc:type.qualificationlevel

Doctoral (Level 8)

Year dc:date.issued

2026

Author dc:creator

• Castro, G

Language dc:language

en

Identifier

oai:salford-repository.worktribe.com:1410276

OAI identifier oai:identifier

oai:salford-repository.worktribe.com:1410276