Testing Predicitive Ability of Business Cycle Indicators for the Euro Area
Christina Ziegler
Abstract
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Christina Ziegler
Abstract
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We analyze the predictive power of seven leading indicators for economic activity in the Euro Area developed by different banks, institutions and research centers. Our comparison is conducted in a bivariate vector autoregressive framework. Indicators are compared by means of an in-sample and an out-of-sample forecasting experiment. Predictive accuracy is compared by recently proposed tests for superior predictive ability. Our results suggest that nearly all indicators have good in-sample properties and that a majority of them is able to outperform a naive univariate autoregressive model out-of-sample. Additionally, we find that indicators perform better in boom periods than in recessions. The OECD and FAZ indicators are both composite indicators and deliver the most accurate forecasts.
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We analyze the predictive power of seven leading indicators for economic activity in the Euro Area developed by different banks, institutions and research centers. Our comparison is conducted in a bivariate vector autoregressive framework. Indicators are compared by means of an in-sample and an out-of-sample forecasting experiment. Predictive accuracy is compared by recently proposed tests for superior predictive ability. Our results suggest that nearly all indicators have good in-sample properties and that a majority of them is able to outperform a naive univariate autoregressive model out-of-sample. Additionally, we find that indicators perform better in boom periods than in recessions. The OECD and FAZ indicators are both composite indicators and deliver the most accurate forecasts.
Key concepts: Bivariate analysis, Autoregressive model, Predictive power, Univariate, Econometrics, Business cycle, Economic indicator, Sample (material)