B0895
Title: A Bayesian change-point analysis of vector autoregressive processes
Authors: Stefano Peluso - Università degli Studi di Milano Bicocca (Italy) [presenting]
Siddhartha Chib - Washington University in Saint Louis (United States)
Antonietta Mira - University of Lugano (Switzerland)
Abstract: A Bayesian method is presented for conducting inference on the change points in VAR models. With a conjugate prior to the parameters of the VAR model, it is shown that, under regularity conditions, the posterior distribution of the change-point location concentrates on the true change-point as the sample size increases. The result is extended to a family of non-conjugate priors on the VAR parameters and the case of multiple change-points is discussed. The methodology is applied to macroeconomic and health problems.
