Grandes datos, Google y desempleo/Big Data, Google and Unemployment

Raymundo M. Campos Vázquez and Sergio E. López-Araiza B.
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Raymundo M. Campos Vázquez: El Colegio de México, A.C.
Sergio E. López-Araiza B.: El Colegio de México, A.C.
Authors registered in the RePEc Author Service: Raymundo Miguel Campos-Vazquez

Estudios Económicos, 2020, vol. 35, issue 1, 125-151

Abstract: 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.

Keywords: Mexico; unemployment; Google; big data; machine learning; prediction (search for similar items in EconPapers)
JEL-codes: C52 C53 E24 J64 O54 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:emx:esteco:v:35:y:2020:i:1:p:125-151

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