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The long memory model of political support: some further results

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  • David Byers
  • James Davidson
  • David Peel

Abstract

This article extends the results of Byers et al. (1997) on long memory in support for the Conservative and Labour Parties in the UK using longer samples and additional poll series. It finds continuing support for the ARFIMA(0, d, 0) model, though with somewhat smaller values of the long memory parameter. We find that the move to telephone polling in the mid-1990s had no apparent effect on the estimated value of d for either party. Finally, we find that we cannot reject the hypotheses that the parties share a common long memory parameter which we estimate at around 0.65.

Suggested Citation

  • David Byers & James Davidson & David Peel, 2007. "The long memory model of political support: some further results," Applied Economics, Taylor & Francis Journals, vol. 39(20), pages 2547-2552.
  • Handle: RePEc:taf:applec:v:39:y:2007:i:20:p:2547-2552
    DOI: 10.1080/00036840600707340
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    1. David Byers & James Davidson & David Peel, 2002. "Modelling political popularity: a correction," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(1), pages 187-189.
    2. David Byers & James Davidson & David Peel, 1997. "Modelling Political Popularity: an Analysis of Long-range Dependence in Opinion Poll Series," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 471-490.
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    Cited by:

    1. Maggie E. C. Jones & Morten Ørregaard Nielsen & Micha Ksawery Popiel, 2014. "A fractionally cointegrated VAR analysis of economic voting and political support," Canadian Journal of Economics, Canadian Economics Association, vol. 47(4), pages 1078-1130, November.
    2. Hassler, Uwe & Hosseinkouchack, Mehdi, 2014. "Effect of the order of fractional integration on impulse responses," Economics Letters, Elsevier, vol. 125(2), pages 311-314.
    3. Morten Ørregaard Nielsen & Sergei S. Shibaev, 2015. "Forecasting daily political opinion polls using the fractionally cointegrated VAR model," Working Papers 1340, Queen's University, Department of Economics.

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