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What Determined Conservative Success in the 2010 U.K. General Election? A Bayesian Spatial Econometric Analysis

Author

Listed:
  • Christa Jensen

    (Department of Economics, West Virginia University)

  • Donald Lacombe

    (Department of Economics, West Virginia University)

  • Stuart Mcintyre

    (Department of Economics, University of Strathclyde)

Abstract

The Conservative Party won the recent General Election in the United Kingdom (UK), gaining the most votes and seats of any single party. Conservatives simultaneously performed particularly well in some areas of the UK and poorly in others. In attempting to explain the variation in voting behaviour during this election, we consider an analysis involving an explicit accounting of geographic considerations. The spatial econometric analysis of voting behaviour is still quite rare in the literature, and analyses using a full suite of models, as employed here, are even rarer. We use data from various sources to examine the effects of a range of economic, socio-economic, and political variables on the percentage of the vote obtained by the Conservative Party in each UK constituency in the 2010 General Election. We employ recent advances in Bayesian spatial econometric modelling to determine the appropriate model for drawing these inferences. We find that there is significant spatial error dependence in a model of the percentage of the vote obtained by the Conservative Party in the 2010 UK General Election, justifying the use of spatial econometric methods for our analysis. By explicitly modelling this spatial phenomenon, we get better estimates of the impact of our chosen economic, socio-economic, and political explanatory variables. Results that seem contrary to our prior expectations when using a non-spatial regression model change when estimated using spatial econometric techniques.

Suggested Citation

  • Christa Jensen & Donald Lacombe & Stuart Mcintyre, 2010. "What Determined Conservative Success in the 2010 U.K. General Election? A Bayesian Spatial Econometric Analysis," Working Papers 1024, University of Strathclyde Business School, Department of Economics.
    • Handle: RePEc:str:wpaper:1024
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    References listed on IDEAS

    as
    1. Macallister, I. & Johnston, R. J. & Pattie, C. J. & Tunstall, H. & Dorling, D. F. L. & Rossiter, D. J., 2001. "Class Dealignment and the Neighbourhood Effect: Miller Revisited," British Journal of Political Science, Cambridge University Press, vol. 31(1), pages 41-59, January.
    2. Olivier Parent & James Lesage, 2005. "Bayesian Model Averaging for Spatial Econometric Models," Post-Print hal-00375489, HAL.
    3. James P. Lesage, 2008. "An Introduction to Spatial Econometrics," Revue d'économie industrielle, De Boeck Université, vol. 0(3), pages 19-44.
    4. R. Kelley Pace & James P. LeSage, 2004. "Spatial Statistics and Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 29(2), pages 147-148, September.
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    More about this item

    Keywords

    Bayesian spatial econometric analysis; spatial voting analysis; UK General Election 2010;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior

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