It is widely known that pre-electoral polls often suffer from non-sampling errors which pollsters try to compensate in final estimates by means of diverse ad hoc adjustments, thus leading to the well-known house effects. We analyze vote share predictions from election polls in Italy in 2006, 2008 and 2013 in order to investigate the relative role of house effects on their variability. We are able to confirm that the variability due to house effect is the most important source of variation

A hierarchical Bayesian model for house effects in pre-electoral polls

PAULI, FRANCESCO;DE STEFANO, DOMENICO;TORELLI, Nicola
2013-01-01

Abstract

It is widely known that pre-electoral polls often suffer from non-sampling errors which pollsters try to compensate in final estimates by means of diverse ad hoc adjustments, thus leading to the well-known house effects. We analyze vote share predictions from election polls in Italy in 2006, 2008 and 2013 in order to investigate the relative role of house effects on their variability. We are able to confirm that the variability due to house effect is the most important source of variation
97888-6493-019-0
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2707881
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact