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英文文献：Forecasting daily political opinion polls using the fractionally cointegrated VAR model-使用小协整VAR模型预测每日政治民意调查
英文文献作者：Morten ?rregaard Nielsen,Sergei S. Shibaev
英文文献摘要：
We examine forecasting performance of the recent fractionally cointegrated vector autoregressive (FCVAR) model. We use daily polling data of political support in the United Kingdom for 2010-2015 and compare with popular competing models at several forecast horizons. Our findings show that the four variants of the FCVAR model considered are generally ranked as the top four models in terms of forecast accuracy, and the FCVAR model significantly outperforms both univariate fractional models and the standard cointegrated VAR (CVAR) model at all forecast horizons. The relative forecast improvement is higher at longer forecast horizons, where the root mean squared forecast error of the FCVAR model is up to 15% lower than that of the univariate fractional models and up to 20% lower than that of the CVAR model. In an empirical application to the 2015 UK general election, the estimated common stochastic trend from the model follows the vote share of the UKIP very closely, and we thus interpret it as a measure of Euro-skepticism in public opinion rather than an indicator of the more traditional left-right political spectrum. In terms of prediction of vote shares in the election, forecasts generated by the FCVAR model leading into the election appear to provide a more informative assessment of the current state of public opinion on electoral support than the hung parliament prediction of the opinion poll.
我们研究了最近的少量协整向量自回归(FCVAR)模型的预测性能。我们使用英国2010-2015年政治支持的每日民意调查数据，并将其与流行的竞争模型进行比较。我们的研究结果表明，就预测精度而言，FCVAR模型的四个变量通常排在前四位，而且FCVAR模型在所有预测范围内的表现都显著优于单变量分数模型和标准协整VAR (CVAR)模型。在更长的预测视野下，相对的预测改进程度更高，其中FCVAR模型的均方根预测误差比单变量分数模型低15%，比CVAR模型低20%。在实证应用2015年英国大选,估计常见的随机趋势从模型遵循英国独立党密切的投票份额,因此我们将其解读为衡量Euro-skepticism舆论而不是更传统的左右政治派别的一项指标。在选举中投票份额的预测方面，FCVAR模型对选举的预测似乎比民意调查中无多数议会的预测更能提供对选举支持现状的民意评估。
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