Nowcasting With Google Trends in an Emerging Market
AbstractMost economic variables are released with a lag, making it difficult for policy-makers to make an accurate assessment of current conditions. This paper explores whether observing Internet browsing habits can inform practitioners about real-time aggregate consumer behavior in an emerging market. Using data on Google search queries, we introduce a simple index of interest in automobile purchases in Chile and test whether it improves the fit and efficiency of nowcasting models for automobile sales. We also examine to what extent our index helps us identify turning points in sales data. Despite relatively low rates of Internet usage among the population, we find that models incorporating our Google Trends Automotive Index outperform benchmark specifications in both in-sample and outof- sample nowcasts while providing substantial gains in information delivery times.
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Bibliographic InfoPaper provided by Central Bank of Chile in its series Working Papers Central Bank of Chile with number 588.
Date of creation: Jul 2010
Date of revision:
Other versions of this item:
- Yan Carrière‐Swallow & Felipe Labbé, 2013. "Nowcasting with Google Trends in an Emerging Market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(4), pages 289-298, 07.
- NEP-ALL-2011-04-23 (All new papers)
- NEP-FOR-2011-04-23 (Forecasting)
- NEP-ICT-2011-04-23 (Information & Communication Technologies)
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