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Generalized Two-Step Maximum Likelihood Estimation of Structural Vector Autoregressive Models partially identified with Short-Run Restrictions

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Author Info
Kyungho Jang
Abstract

This paper presents a generalized two-step maximum likelihood estimation method for partially identified vector autoregressive models. We suggest a likelihood ratio test for over-identification in a sub-system and derive the asymptotics for impulse responses and forecast-error variance decomposition for partially identified models. As an application, we consider an open economy model to investigate the effects of monetary policy on exchange rates and term structures. We find that exchange rates tend to overshoot and term structures have hump-shaped responses to monetary policy shocks

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Publisher Info
Paper provided by Econometric Society in its series Econometric Society 2004 Far Eastern Meetings with number 569.

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Date of creation: 11 Aug 2004
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Handle: RePEc:ecm:feam04:569

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Related research
Keywords: ML estimation; VAR model; Identification; Likelihood ratio test; Asymptotic distribution; Impulse response; Forecast-error variance decomposition; Monetary policy; Exchange rate;

Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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