Forecasting multiparty by-elections using Dirichlet regression

Chris Hanretty

International Journal of Forecasting, 2021, vol. 37, issue 4, 1666-1676

Abstract: By-elections, or special elections, play an important role in many democracies – but whilst there are multiple forecasting models for national elections, there are no such models for multiparty by-elections. Multiparty by-elections present particular analytic problems related to the compositional character of the data and structural zeros where parties fail to stand. I model party vote shares using Dirichlet regression, a technique suited for compositional data analysis. After identifying predictor variables from a broader set of candidate variables, I estimate a Dirichlet regression model using data from all post-war by-elections in the UK (n=468). The cross-validated error of the model is comparable to the error of costly and infrequent by-election polls (MAE: 4.0 compared to 3.6 for polls). The steps taken in the analysis are in principle applicable to any system that uses by-elections to fill legislative vacancies.

Keywords: Dirichlet regression; By-elections; Special elections; Election forecasting; Compositional data; Polling (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:37:y:2021:i:4:p:1666-1676

DOI: 10.1016/j.ijforecast.2021.03.007

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