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Forecasting Spanish unemployment with Google Trends and dimension reduction techniques



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Mulero, Rodrigo and Garcia Hiernaux, Alfredo (2020) Forecasting Spanish unemployment with Google Trends and dimension reduction techniques. pp. 1-24. (Unpublished)




This paper presents a method to improve the one-step-ahead forecasts of the Spanish unemployment monthly series. To do so, we use a large number of potential explanatory variables extracted from searches in Google (Google Trends tool). Two different dimension reduction techniques are implemented to decide how to combine the explanatory variables or which ones to use. The results reveal an increase in predictive accuracy of 10-25%, depending on the dimension reduction method employed. A deep robustness analysis confirms this findings, as well as the relevance of using a large amount of Google queries together with a dimension reduction technique, when no prior information on which are the most informative queries is available.

Item Type:Article
Uncontrolled Keywords:Unemployment; Forecasting; Google Trends; Dimensionality reduction; RMSE
Subjects:Social sciences > Economics
Social sciences > Economics > Econometrics
Social sciences > Economics > Economic indicators
JEL:C32, C52, C53
ID Code:61298
Deposited On:03 Jul 2020 09:32
Last Modified:03 Jul 2020 11:39

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