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Structural Vector Autoregressions with Markov Switching

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Listed author(s):
  • Markku Lanne
  • Helmut Luetkepohl
  • Katarzyna Maciejowska

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.

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Paper provided by European University Institute in its series Economics Working Papers with number ECO2009/06.

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Date of creation: 2009
Handle: RePEc:eui:euiwps:eco2009/06
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Keywords: Cointegration; Markov regime switching model; vector error correction model; structural vector autoregression; mixed normal distribution;

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Find related papers by JEL classification:
  • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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