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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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    References listed on IDEAS

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    1. 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, September.
    2. 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, February.
    3. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
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    1. Maggie E. C. Jones & Morten Ørregaard Nielsen & Michał Ksawery Popiel, 2014. "A fractionally cointegrated VAR analysis of economic voting and political support," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, 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 Paper 1340, Economics Department, Queen's University.
    4. Javier Hualde & Morten {O}rregaard Nielsen, 2022. "Fractional integration and cointegration," Papers 2211.10235, arXiv.org.
    5. Alexander Boca Saravia & Gabriel Rodríguez, 2022. "Presidential approval in Peru: an empirical analysis using a fractionally cointegrated VAR," Economic Change and Restructuring, Springer, vol. 55(3), pages 1973-2010, August.

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