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Predicting unemployment in short samples with internet job search query data

Francesco, D'Amuri

MPRA Paper from University Library of Munich, Germany

Abstract: This article tests the power of a novel indicator based on job search related web queries in predicting quarterly unemployment rates in short samples. Augmenting standard time series specifications with this indicator definitely improves out-of-sample forecasting performance at nearly all in-sample interval lengths and forecast horizons, both when compared with models estimated on the same or on a much longer time series interval.

Keywords: Google econometrics; Forecast comparison; Keyword search; Unemployment; Time series models. (search for similar items in EconPapers)
JEL-codes: C53 E27 J60 J64 C22 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-for, nep-lab and nep-ore
Date: 2009-10-30
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