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Predicting US bank failures with internet search volume data


Schaffner, Florian (2015). Predicting US bank failures with internet search volume data. Working paper series / Department of Economics 214, University of Zurich.

Abstract

This study investigates how well weekly Google search volumes track and predict bank failures in the United States between 2007 and 2012, contributing to the expanding literature that exploits internet data for the prediction of events. Different duration models with time-varying covariates are estimated. Higher Google search volumes go hand in hand with higher failure rates, and the coefficients for the Google volume growth index are highly significant. However, Google’s predictive power quickly dissipates for future failure rates.

This study investigates how well weekly Google search volumes track and predict bank failures in the United States between 2007 and 2012, contributing to the expanding literature that exploits internet data for the prediction of events. Different duration models with time-varying covariates are estimated. Higher Google search volumes go hand in hand with higher failure rates, and the coefficients for the Google volume growth index are highly significant. However, Google’s predictive power quickly dissipates for future failure rates.

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Additional indexing

Item Type:Working Paper
Communities & Collections:03 Faculty of Economics > Department of Economics
Working Paper Series > Department of Economics
Dewey Decimal Classification:330 Economics
JEL Classification:G170, G180, G190, G210, G280
Uncontrolled Keywords:Bank failures, internet, financial crisis, Google, survival analysis
Language:English
Date:December 2015
Deposited On:05 Jan 2016 16:42
Last Modified:28 Jun 2016 10:33
Series Name:Working paper series / Department of Economics
Number of Pages:32
ISSN:1664-7041
Official URL:http://www.econ.uzh.ch/static/wp/econwp214.pdf
Related URLs:http://www.econ.uzh.ch/static/workingpapers-new.php
Permanent URL: https://doi.org/10.5167/uzh-118268

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