Measuring Contagion with a Bayesian Time-Varying Coefficient Model

By Alessandro Rebucci, Matteo Ciccarelli

September 1, 2003

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Alessandro Rebucci, and Matteo Ciccarelli. Measuring Contagion with a Bayesian Time-Varying Coefficient Model, (USA: International Monetary Fund, 2003) accessed December 26, 2024

Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate

Summary

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.

Subject: Currencies, Currency markets, Exchange rates, Expenditure, Financial markets, Foreign exchange, Metal prices, Money, Prices, Public expenditure review

Keywords: Chilean peso, Contagion, Correlation coefficient, Cross-market correlation, Cross-market linkage, Currencies, Currency markets, Estimation procedure, Exchange rates, Foreign exchange market reaction, Gibbs sampling, Global, Heteroskedasticity, Metal prices, OLS estimate, Omitted variable bias, Public expenditure review, Time-varying coefficient models, U.S. dollar, WP

Publication Details

Pages:

32
Volume:

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DOI:

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Issue:

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Series:

Working Paper No. 2003/171
Stock No:

WPIEA1712003
ISBN:

9781451858525
ISSN:

1018-5941

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