AbstractUnanticipated 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 to 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.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 52463.
Date of creation: 07 Nov 2012
Date of revision:
Generalized Variance; Conditional Variance;
Other versions of this item:
- 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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