Measuring Contagion with a Bayesian, Time-Varying Coefficient Model
By Matteo Ciccarelli, Alessandro Rebucci. Social Science Research Network, 2003
96 citations recorded by the source corpus.
We propose to use a time-varying coefficient model to measure contagion. The proposed measure works in the joint presence of heteroskedasticity and omitted variables. It requires knowledge of the source of the crisis but not its timing. The estimation procedure is Bayesian and is based on Markov Chain Monte Carlo methods. We asses the performance of the proposed measure both with simulated and actual data.
Subfields: Finance, Global and Planetary Change, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/69293859fb4dd4171c3992d8bee70e8a7f4bd0ff
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In Finance
In Global and Planetary Change
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Citations in the corpus
- Implications of oil prices shocks for the major emerging economies: A comparative analysis of BRICS (2018, background): “Later, Ciccarelli and Rebucci (2003) extend the framework of Boivin (2001) allowing for t-distributed errors, which account for non-persistent changes in the scale of the variances over time.”