Predicting Instability

Razzak, Weshah (2010): Predicting Instability.

Abstract

Unanticipated shocks could lead to instability, which is reflected in statistically significant changes in distributions of independent Gaussian 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 to predicting statistically significant sudden and large shifts in the conditional variance of a vector of correlated macroeconomic variables. Central banks can incorporate the framework in the policy making process.

• Item Type: MPRA Paper
• Language: English
• Keywords: Sample Generalized Variance, Conditional Variance, Sudden and Large Shifts in the Moments
• Subjects: E - Macroeconomics and Monetary Economics > E6 - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook > E66 - General Outlook and Conditions; C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General

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