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Unemployment Rates Forecasts – Unobserved Component Models Versus SARIMA Models In Central And Eastern European Countries

机译:失业率预测–中欧和东欧国家的未观测成分模型与SARIMA模型

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In this paper we compare the accuracy of unemployment rates forecasts of eight Central and Eastern European countries. The unobserved component models and seasonal ARIMA models are used within a rolling short-term forecast experiment as an out-of-sample test of forecast accuracy. We find that unemployment rates present clear unconditional asymmetry in three out of eight countries. Half the cases there is no difference between forecasting accuracy of the methods used in the study. In the remaining, a proper specification of seasonal ARIMA model allows to generate better forecasts than from unobserved component models. The forecasting accuracy deteriorates in periods of rapid upward and downward movement and improves in periods of gradual change in the unemployment rates.
机译:在本文中,我们比较了八个中东欧国家的失业率预测的准确性。滚动短期预测实验中使用了未观察到的分量模型和季节性ARIMA模型作为预测准确性的样本外测试。我们发现,八分之三的国家中失业率呈现出明显的无条件不对称性。在一半的情况下,研究中使用的方法的预测准确性之间没有差异。在剩下的部分中,适当的季节性ARIMA模型规范可以产生比未观察到的组件模型更好的预测。预测准确度在快速向上和向下移动期间会恶化,而在失业率逐渐变化的时期会有所改善。

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