Resumen

CAMPOS VAZQUEZ, Raymundo M.  y  LOPEZ-ARAIZA B., Sergio E.. Big data, Google and unemployment. Estud. Econ. (México, D.F.) [online]. 2020, vol.35, n.1, pp.125-151.  Epub 15-Jun-2020. ISSN 0186-7202.

We use Google Trends data for employment opportunities related reply in order to forecast the unemployment rate in Mexico. We begin by discussing the literature related to big data and nowcasting in which user generated data is used to forecast unemployment. Afterwards, we explain the basics of several machine learning algorithms. Finally, we implement such algorithms in order to find the best model to predict unemployment using both Google Trends queries and unemployment lags. From a public policy perspective, we believe that both user generated data and new statistical methods may provide great tools for the design of policy interventions.

Palabras llave : unemployment; Google; big data; machine learning; prediction; C52; C53; E24; J64; O54.

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