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Suite of Statistical Models Forecasting Latvian GDP

机译:一套预测拉脱维亚国内生产总值的统计模型

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We develop a suite of statistical models to forecast Latvian GDP. We employ various univariate and multivariate econometric techniques to obtain short-term GDP projections and to assess the performance of the models. We also comprise the information contained in components of GDP and obtain short-term GDP projections from disaggregated perspective. We run out-of-sample forecasting procedures to evaluate GDP projections and to assess forecasting accuracy of all individual statistical models. We conclude that factor and bridge models are among the best individually performing models in the suite. Forecasting accuracy obtained using disaggregated models of factor and bridge models is noteworthy and might be considered as a good alternative to aggregated ones. Furthermore, weighted combination of the forecasts of the statistical models allows obtaining robust and accurate forecasts which leads to a reduction of forecasted errors.
机译:我们开发了一套统计模型来预测拉脱维亚的GDP。我们采用各种单变量和多元计量经济学技术来获得短期GDP预测并评估模型的性能。我们还包含GDP组成部分中包含的信息,并从分类的角度获得短期GDP预测。我们执行样本外预测程序来评估GDP预测并评估所有单个统计模型的预测准确性。我们得出结论,因子模型和桥梁模型是套件中性能最佳的模型之一。使用因子模型和桥梁模型的分解模型获得的预测准确性是值得注意的,并且可以被认为是聚合模型的良好替代方案。此外,统计模型的预测的加权组合允许获得鲁棒且准确的预测,从而减少了预测误差。

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