Can Google Search Data Help Predict Macroeconomic Series?

Robin Niesert, Jochem Oorschot, Chris Veldhuisen, Kester Brons and Rutger-Jan Lange
Additional contact information
Jochem Oorschot: Econometric Institute, Erasmus University

No 19-021/III, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: We use Google search data with the aim of predicting unemployment, CPI and consumer confidence for the US, UK, Canada, Germany and Japan. Google search queries have previously proven valuable in predicting macroeconomic variables in an in-sample context. To our knowledge, the more challenging question of whether such data have out-of-sample predictive value has not yet been satisfactorily answered. We focus on out-of-sample nowcasting, and extend the Bayesian Structural Time Series model using the Hamiltonian sampler for variable selection. We find that the search data retain their value in an out- of-sample predictive context for unemployment, but not for CPI and consumer confidence. It may be that online search behaviour is a relatively reliable gauge of an individual's personal situation (employment status), but less reliable when it comes to variables that are unknown to the individual (CPI) or too general to be linked to specific search terms (consumer confidence).

Keywords: Bayesian methods; forecasting practice; Kalman filter; macroeconomic forecasting; state space models; nowcasting; spike-and-slab; Hamiltonian sampler (search for similar items in EconPapers)
JEL-codes: C11 C53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-big and nep-for
References: Add references at CitEc
Citations:

Downloads: (external link)
https://papers.tinbergen.nl/19021.pdf (application/pdf)

Related works:
Journal Article: Can Google search data help predict macroeconomic series? (2020)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20190021

Access Statistics for this paper

More papers in Tinbergen Institute Discussion Papers from Tinbergen Institute Contact information at EDIRC.
Bibliographic data for series maintained by Tinbergen Office +31 (0)10-4088900 ().