Now-And Forecasting Unemployment from Google's Job-Search Activity

47 Pages Posted: 19 Sep 2017

Date Written: January 10, 2015

Abstract

Big data trends, have gained popularity among practitioners for its potential applications on accurate econometric prediction. This paper presents an application where unemployment job search indicators for the G7 countries are based on Google trends data. For each country, a set of google search keywords is identified, then a data reduction technique is applied to estimate our unemployment indicator which is considered a latent common trend. Finally the predictive performance of our indicators is assessed by an automatic stochastic specification with respect to unemployment levels and other key labour market outcomes.

Keywords: Google econometrics, unemployment rate, forecasting, factor analysis

JEL Classification: J64, C53

Suggested Citation

Dávalos, Jorge, Now-And Forecasting Unemployment from Google's Job-Search Activity (January 10, 2015). Available at SSRN: https://ssrn.com/abstract=3038007 or http://dx.doi.org/10.2139/ssrn.3038007

Jorge Dávalos (Contact Author)

Universidad del Pacifico ( email )

Av. Salaverry 2020
Región Metropolitana
Lima 18, Santiago Lima 11
Peru

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