Overview
Michel Lubrano is a Bayesian econometrician (GREQAM / Aix-Marseille School of Economics, CNRS) known for work on Bayesian inference in dynamic and nonlinear models, GARCH, cointegration, and income-distribution analysis.
Key Contributions / Features
- Bayesian GARCH via griddy-Gibbs (Bauwens-Lubrano 1998): showed how to do Bayesian inference on GARCH models with the griddy-Gibbs sampler, applied it to an asymmetric Student-t GARCH model and option pricing, and proved the improper-posterior result for a flat prior on the degrees of freedom. Econometrics Journal 1: C23–C46.
- Bayesian Inference in Dynamic Econometric Models (Bauwens–Lubrano–Richard 1999): a standard reference textbook (with Luc Bauwens and Jean-François Richard).
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