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Measuring Contagion with a Bayesian Time-Varying Coefficient Model

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  • Alessandro Rebucci
  • Matteo Ciccarelli

Abstract

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.

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Bibliographic Info

Paper provided by International Monetary Fund in its series IMF Working Papers with number 03/171.

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Length: 32
Date of creation: 01 Sep 2003
Date of revision:
Handle: RePEc:imf:imfwpa:03/171

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Keywords: Economic models; contagion; correlation; covariance; parameter vector; correlations; sampling; estimation procedure; dummy variables; probability; time series; outliers; statistics; econometrics; empirical model; statistical significance; crisis country; standard deviation; linear regression; forecasting; equations; skewness; equation; normal distribution; descriptive statistics; markov chain; explanatory power; random walk; stochastic processes; confidence interval; random variables; algebra; observable variable; correlation analysis; probability density function; predictability; simultaneous equations; independent variable; financial contagion; instrumental variable; financial crises; linear regression model; prediction; factor analysis; probability density; constant term; monte carlo simulation; monte carlo methods; survey; polynomial; conditional expectation; number of variables; surveys; kurtosis; numerical integration; experimental data; linear model; estimation bias;

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References

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  1. Roberto Rigobón & Kristin Forbes, 2001. "Contagion in Latin America: Definitions, Measurement, and Policy Implications," JOURNAL OF LACEA ECONOMIA, LACEA - LATIN AMERICAN AND CARIBBEAN ECONOMIC ASSOCIATION.
  2. King, Mervyn A & Wadhwani, Sushil, 1990. "Transmission of Volatility between Stock Markets," Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 5-33.
  3. Fabio Canova & Matteo Ciccarelli, 2000. "Forecasting And Turning Point Predictions In A Bayesian Panel Var Model," Working Papers. Serie AD 2000-05, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  4. Marcello Pericoli & Massimo Sbracia, 2001. "A Primer on Financial Contagion," Temi di discussione (Economic working papers) 407, Bank of Italy, Economic Research and International Relations Area.
  5. Manmohan S. Kumar & Avinash Persaud, 2001. "Pure Contagion and Investors Shifting Risk Appetite," IMF Working Papers 01/134, International Monetary Fund.
  6. Toni Gravelle & Maral Kichian & James Morley, 2003. "Shift Contagion in Asset Markets," Working Papers 03-5, Bank of Canada.
  7. Roberto Rigobon, 2001. "Contagion: How to Measure It?," NBER Working Papers 8118, National Bureau of Economic Research, Inc.
  8. Canova, Fabio, 1993. "Modelling and forecasting exchange rates with a Bayesian time-varying coefficient model," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 233-261.
  9. Favero, Carlo A. & Giavazzi, Francesco, 2002. "Is the international propagation of financial shocks non-linear?: Evidence from the ERM," Journal of International Economics, Elsevier, vol. 57(1), pages 231-246, June.
  10. Matteo Ciccarelli & Alessandro Rebucci, 2001. "The Transmission Mechanism of European Monetary Policy: Is There Heterogeneity? Is It Changing Over Time?," Banco de Espa�a Working Papers 0115, Banco de Espa�a.
  11. Timothy Cogley & Thomas Sargent, . "Drifts and Volatilities: Monetary Policies and Outcomes in the Post WWII US," Working Papers 2133503, Department of Economics, W. P. Carey School of Business, Arizona State University.
  12. Corsetti, Giancarlo & Pericoli, Marcello & Sbracia, Massimo, 2005. "'Some contagion, some interdependence': More pitfalls in tests of financial contagion," Journal of International Money and Finance, Elsevier, vol. 24(8), pages 1177-1199, December.
  13. Matteo Ciccarelli & Alessandro Rebucci, 2002. "The Transmission Mechanism of European Monetary Policy," IMF Working Papers 02/54, International Monetary Fund.
  14. Taimur Baig & Ilan Goldfajn, 2000. "The Russian Default and the Contagion to Brazil," IMF Working Papers 00/160, International Monetary Fund.
  15. Chib, Siddhartha & Greenberg, Edward, 1995. "Hierarchical analysis of SUR models with extensions to correlated serial errors and time-varying parameter models," Journal of Econometrics, Elsevier, vol. 68(2), pages 339-360, August.
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Citations

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Cited by:
  1. Fabio Canova & Matteo Ciccarelli, 2007. "Estimating Multi-country VAR models," Discussion Papers 7_2007, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.
  2. Cappiello, Lorenzo & Gérard, Bruno & Manganelli, Simone, 2005. "Measuring comovements by regression quantiles," Working Paper Series 0501, European Central Bank.
  3. Simone Manganelli & Lorenzo Cappiello & Bruno Gerard, 2004. "The Contagion Box: Measuring Co-Movements in Financial Markets by Regression Quantiles," Econometric Society 2004 Latin American Meetings 77, Econometric Society.
  4. Ascari, Guido & Rankin, Neil, 2004. "Perpetual youth and endogenous labour supply: a problem and a possible solution," Working Paper Series 0346, European Central Bank.
  5. Baele, Lieven & Inghelbrecht, Koen, 2010. "Time-varying integration, interdependence and contagion," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 791-818, September.
  6. Juan F. Rubio-Ramirez & Daniel Waggoner & Tao Zha, 2006. "Markov-Switching Structural Vector Autoregressions: Theory and Application," Computing in Economics and Finance 2006 69, Society for Computational Economics.
  7. Gropp, Reint & Moerman, Gerard, 2003. "Measurement of contagion in banks' equity prices," Working Paper Series 0297, European Central Bank.

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