Modified Two Stage Least Squares Estimators for the Estimation of a Structural Vector Autoregressive Integrated Process
AbstractWe 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.
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Bibliographic InfoPaper provided by Institute of Economic Policy Research (IEPR) in its series IEPR Working Papers with number 05.23.
Length: 36 pages
Date of creation: May 2005
Date of revision:
Structural vector autoregression; Unit root; Cointegration; Asymptotic properties; Hypothesis testing;
Other versions of this item:
- Hsiao, Cheng & Wang, Siyan, 2006. "Modified two-stage least-squares estimators for the estimation of a structural vector autoregressive integrated process," Journal of Econometrics, Elsevier, Elsevier, vol. 135(1-2), pages 427-463.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-06-14 (All new papers)
- NEP-ECM-2005-06-14 (Econometrics)
- NEP-ETS-2005-06-14 (Econometric Time Series)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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