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Data on Google searches help predict the unemployment rate in the U.S. But the predictive power of Google searches is limited to short-term predictions, the value of Google data for forecasting purposes is episodic, and the improvements in forecasting accuracy are only modest. The results,...
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In this paper a Bayesian vector autoregressive model for nowcasting the seasonally non-adjusted unemployment rate in EU …
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There are over 3 billion searches globally on Google every day. This report examines whether Google search queries can be used to predict the present and the near future unemployment rate in Finland. Predicting the present and the near future is of interest, as the official records of the state...
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In this report we document the ETLAnow project. ETLAnow is a model for forecasting with big data. At the moment, it predicts the unemployment rate in the EU-28 countries using Google search data. This document is subject to updates as the ETLAnow project advances.
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nowcasting performance compared to an autoregressive model. Moreover, we find that the adoption of machine learning techniques … improves substantially the accuracy of our predictions in comparison to standard linear mod-els. While the average nowcasting …
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