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 dis...
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| Format: | Revue |
| Langue: | English |
| Publié: |
Washington, D.C. :
International Monetary Fund,
2003.
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| Collection: | IMF Working Papers; Working Paper ;
No. 2003/171 |
| Accès en ligne: | Full text available on IMF |
| Résumé: | 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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| Description: | <strong>Off-Campus Access:</strong> No User ID or Password Required <strong>On-Campus Access:</strong> No User ID or Password Required |
| Description matérielle: | 1 online resource (32 pages) |
| Format: | Mode of access: Internet |
| ISSN: | 1018-5941 |
| Accès: | Electronic access restricted to authorized BRAC University faculty, staff and students |