“Google it!”Forecasting the US Unemployment Rate with a Google Job Search index

Francesco D’Amuri and Juri Marcucci
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Francesco D’Amuri: Economic Research Department
Authors registered in the RePEc Author Service: Francesco D'Amuri

No 2010.31, Working Papers from Fondazione Eni Enrico Mattei

Abstract: We suggest the use of an Internet job-search indicator (the Google Index, GI) as the best leading indicator to predict the US unemployment rate. We perform a deep out-of-sample forecasting comparison analyzing many models that adopt both our preferred leading indicator (GI), the more standard initial claims or combinations of both. We find that models augmented with the GI outperform the traditional ones in predicting the monthly unemployment rate, even in most state-level forecasts and in comparison with the Survey of Professional Forecasters.

Keywords: Google Econometrics; Forecast Comparison; Keyword search; US Unemployment; Time Series Models (search for similar items in EconPapers)
JEL-codes: C22 C53 E27 E37 J60 J64 (search for similar items in EconPapers)
Date: 2010-03
New Economics Papers: this item is included in nep-for and nep-lab
References: Add references at CitEc
Citations: View citations in EconPapers (35)

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Related works:
Working Paper: ‘Google it!’ Forecasting the US unemployment rate with a Google job search index (2009)
Working Paper: "Google it!" Forecasting the US unemployment rate with a Google job search index (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:fem:femwpa:2010.31

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