Measuring Contagion with a Bayesian Time-Varying Coefficient Model

We propose using a Bayesian time-varying coefficient model estimated with Markov chain-Monte Carlo methods to measure contagion empirically. The proposed measure works in the joint presence of heteroskedasticity and omitted variables and does not require knowledge of the timing of the crisis. It distinguishes contagion not only from interdependence but also from structural breaks and can be used to investigate positive as well as negative contagion. The proposed measure appears to work well using both simulated and actual data.
Publication date: September 2003
ISBN: 9781451858525
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Finance , Finance , contagion , Gibbs sampling , heteroskedasticity , omitted variable bias , time-varying coefficient models , correlation , covariance , parameter vector , correlations , Bayesian Analysis , Simulation Methods , Open Economy Macroeconomics , International Policy Coordination and T

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