Structural Vector Autoregressions with Markov Switching
Title: Structural Vector Autoregressions with Markov Switching
Publisher: European University Institute
Series/Report no.: EUI ECO; 2009/06
Abstract. It is argued that in structural vector autoregressive (SVAR) analysis a Markov regime switching (MS) property can be exploited to identify shocks if the reduced form error covariance matrix varies across regimes. The model setup is formulated and discussed and it is shown how it can be used to test restrictions which are just-identifying in a standard structural vector autoregressive analysis. The approach is illustrated by two SVAR examples which have been reported in the literature and which have features which can be accommodated by the MS structure.
Subject: Cointegration; Markov regime switching model; vector error; structural vector autoregression; mixed normal distribution; C32
Type of Access: openAccess