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Modelling Political Popularity: an Analysis of Long‐range Dependence in Opinion Poll Series
Author(s) -
Byers David,
Davidson James,
Peel David
Publication year - 1997
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.1111/j.1467-985x.1997.00075.x
Subject(s) - popularity , voting , politics , opinion poll , sample (material) , econometrics , event (particle physics) , series (stratigraphy) , public opinion , noise (video) , range (aeronautics) , positive economics , psychology , political science , economics , social psychology , computer science , law , artificial intelligence , image (mathematics) , paleontology , chemistry , physics , materials science , chromatography , quantum mechanics , composite material , biology
A simple model of political popularity, as recorded by opinion polls of voting intentions, is proposed. We show that, as a consequence of aggregating heterogeneous poll responses under certain assumptions about the evolution of individual opinions, the time series of poll data should exhibit long memory characteristics. In an analysis of the monthly Gallup data on party support in the UK, we confirm that the series have long memory and further show them to be virtually pure ‘fractional noise’ processes. An explanation of the latter result is offered. We study the role of economic indicators in predicting swings in support, perform event analyses and use our estimates to generate post‐sample forecasts to April 1997.