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Predicting instability

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  • W. A. Razzak

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.

Suggested Citation

  • W. A. Razzak, 2013. "Predicting instability," Applied Economics, Taylor & Francis Journals, vol. 45(23), pages 3305-3315, August.
    • Handle: RePEc:taf:applec:v:45:y:2013:i:23:p:3305-3315
    DOI: 10.1080/00036846.2012.707775
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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