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: C12 C13 C32 (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
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Journal Article: Modified two-stage least-squares estimators for the estimation of a structural vector autoregressive integrated process (2006)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:scp:wpaper:05-23

Access Statistics for this paper

More papers in IEPR Working Papers from Institute of Economic Policy Research (IEPR) Contact information at EDIRC.
Bibliographic data for series maintained by ().