THE 2007–2008 U.S. RECESSION: WHAT DID THE REAL-TIME GOOGLE TRENDS DATA TELL THE UNITED STATES?

Tao Chen, Erin Pik Ki So, Liang Wu and Isabel Kit Ming Yan

Contemporary Economic Policy, 2015, vol. 33, issue 2, 395-403

Abstract: type="main" xml:id="coep12074-abs-0001"> In the extant literature of business cycle predictions, the signals for business cycle turning points are generally issued with a lag of at least 5 months. In this paper, we make use of a novel and timely indicator—the Google search volume data—to help to improve the timeliness of business cycle turning point identification. We identify multiple query terms to capture the real-time public concern on the aggregate economy, the credit market, and the labor market condition. We incorporate the query indices in a Markov-switching framework and successfully “nowcast” the peak date within a month that the turning occurred. (JEL E37, G17)

Date: 2015
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