This paper extends previous analyses of aggregate political popularity (partisanship) data by Box-Steffensmeier and Smith (Box-Steffensmeier, J.M., Smith, R.M., 1996. The dynamics of aggregate partisanship. American Political Science Review 90 (September), 567–580) for the US, and Byers et al. (Byers, D., Davidson, J., Peel, D.A., 1997. Modelling political popularity: an analysis of long-range dependence in opinion poll series. Journal of the Royal Statistical Society Series A, 160, 471–490) for the UK. These studies independently found that the time series of poll ratings are well modelled by fractionally integrated processes. Here, the analysis is conducted for 26 political parties in eight different countries, and the results obtained are on the whole closely in line with the ones cited above. As in the earlier studies, we find in many of our cases that the estimated fractional integration parameter d is close to 0.7. This implies that popularity is highly persistent and a nonstationary process, but that it is also mean-reverting eventually. Most of the time series are also found to be pure fractional noise, effectively uncorrelated after fractional differencing, so that the d parameter alone accounts for the dependence. As well as offering added support for theories of political allegiance based on a certain distribution of the attributes of commitment and pragmatism in the voting population, these findings have important implications for the explanation of political support using time series data.
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