Nowcasting with Google Trends in an Emerging Market

Despite relatively low rates of Internet usage among the population, it is found that models incorporating the Google Trends Automotive Index outperform benchmark specifications in both in-sample and out-of- sample nowcasts while providing substantial gains in information delivery times.

Abstract

ABSTRACT Most 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 aggregate consumer behavior in an emerging market. Using data on Google search queries, we introduce an index of online interest in automobile purchases in Chile and test whether it improves the fit and efficiency of nowcasting models for automobile sales. 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 out‐of‐sample nowcasts, provide substantial gains in information delivery times, and are better at identifying turning points in the sales data. Copyright © 2011 John Wiley & Sons, Ltd.