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Modified Two Stage Least Squares Estimators for the Estimation of a Structural Vector Autoregressive Integrated Process

Cheng Hsiao and Siyan Wang ()

No 05.23, IEPR Working Papers from Institute of Economic Policy Research (IEPR)

Abstract: We consider the estimation of a structural vector autoregressive model of nonstationary and possibly cointegrated variables without the prior knowledge of unit roots or rank of cointegration. We propose two modified two stage least squares estimators that are consistent and have limiting distributions that are either normal or mixed normal. Limited Monte Carlo studies are also conducted to evaluate their finite sample properties.

Keywords: Structural vector autoregression; Unit root; Cointegration; Asymptotic properties; Hypothesis testing (search for similar items in EconPapers)
JEL-codes: C32 C12 C13 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2005-05
New Economics Papers: this item is included in nep-ecm and nep-ets
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Journal Article: Modified two-stage least-squares estimators for the estimation of a structural vector autoregressive integrated process (2006) Downloads
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