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Spatial modelling of the two-party preferred vote in Australian federal elections: 2001-2016

Author

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  • Jeremy Forbes
  • Dianne Cook
  • Rob J Hyndman

Abstract

We examine the relationships between electoral socio-demographic characteristics and two-party preference in the six Australian federal elections held between 2001 to 2016. Socio-demographic information is derived from the Australian Census, which occurs every five years. Since a Census is not directly available for each election, spatio-temporal imputation is employed to estimate Census data for the electorates at the time of each election. This accounts for both spatial and temporal changes in electoral characteristics between Censuses. To capture any spatial heterogeneity, a spatial error model is estimated for each election, which incorporates a spatially structured random effect vector that can be thought of as the unobserved political climate in each electorate. Over time, the impact of most socio-demographic characteristics that affect electoral two-party preference do not vary, with industry of work, incomes, household mobility and de facto relationships having strong effects in each of the six elections. Education and unemployment are amongst those that have varying effects. It is also found that between 2004 and 2013, the spatial effect was insignificant, meaning that electorates voted effectively independently. All data featured in this study has been contributed to the eechidna R package (available on CRAN).

Suggested Citation

  • Jeremy Forbes & Dianne Cook & Rob J Hyndman, 2019. "Spatial modelling of the two-party preferred vote in Australian federal elections: 2001-2016," Monash Econometrics and Business Statistics Working Papers 8/19, Monash University, Department of Econometrics and Business Statistics.
    • Handle: RePEc:msh:ebswps:2019-8
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    File URL: https://www.monash.edu/business/ebs/research/publications/ebs/wp08-2019.pdf
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    References listed on IDEAS

    as
    1. M F Goodchild & L Anselin & U Deichmann, 1993. "A Framework for the Areal Interpolation of Socioeconomic Data," Environment and Planning A, , vol. 25(3), pages 383-397, March.
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    More about this item

    Keywords

    Federal election; census; Australia; spatial modelling; imputation; data science; socio-demographics; electorates; R; eechidna.;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior

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