Predicting instability

Weshah Razzak

Applied Economics, 2013, vol. 45, issue 23, 3305-3315

Abstract: Unanticipated shocks could lead to instability, which is reflected in statistically significant changes in distributions of random variables. Changes in the conditional moments of stationary variables are predictable. We provide a framework based on a statistic for the sample generalized variance , which is useful for interrogating real time data and for predicting statistically significant sudden and large shifts in the conditional variance of a vector of correlated macroeconomic and financial variables. It is a test for a market-wide instability. Central banks can incorporate the framework in the policymaking process.

Date: 2013
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Working Paper: Predicting Instability (2012)
Working Paper: Predicting Instability (2010)
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DOI: 10.1080/00036846.2012.707775

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