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Long-range dependence in Spanish political opinion poll series

  • Laura Mayoral

    (Dept of Economics and Business, Universidad Pompeu Fabra, Spain)

  • Juan J. Dolado

    (Dept of Economics, Universidad Carlos III de Madrid, Spain)

  • Jes�s Gonzalo

    (Dept of Statistics and Econometrics, Universidad Carlos III de Madrid, Spain)

This paper investigates the time series properties of partisanship for five political parties in Spain. It is found that pure fractional processes with a degree of integration, d, between 0.6 and 0.8 fit the time-series behaviour of aggregate opinion polls for mainstream parties quite well, whereas values of d in the range of 0.3 to 0.6 are obtained for opinion polls related to smaller regional parties. Those results are in agreement with theories of political allegiance based on aggregation of heterogeneous voters with different degrees of commitment and pragmatism. Further, those models are found to be useful in forecasting the results of the last general elections in Spain. As a further contribution, new econometric techniques for estimation and testing of ARFIMA model are used to provide the previous evidence. Copyright © 2003 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/jae.700
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File URL: http://qed.econ.queensu.ca:80/jae/2003-v18.2/
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 18 (2003)
Issue (Month): 2 ()
Pages: 137-155

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Handle: RePEc:jae:japmet:v:18:y:2003:i:2:p:137-155
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  1. Eisinga, Rob & Franses, Philip Hans & Ooms, Marius, 1999. "Forecasting long memory left-right political orientations," International Journal of Forecasting, Elsevier, vol. 15(2), pages 185-199, April.
  2. Chrystal, K Alec & Peel, David A, 1986. "What Can Economics Learn from Political Science, and Vice Versa?," American Economic Review, American Economic Association, vol. 76(2), pages 62-65, May.
  3. Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188.
  4. 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.
  5. Tieslau, Margie A. & Schmidt, Peter & Baillie, Richard T., 1996. "A minimum distance estimator for long-memory processes," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 249-264.
  6. Cheung, Yin-Wong, 1993. "Long Memory in Foreign-Exchange Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 93-101, January.
  7. 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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