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

Author

Listed:
  • Cheng Hsiao
  • Siyan Wang

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.

Suggested Citation

  • Cheng Hsiao & Siyan Wang, 2005. "Modified Two Stage Least Squares Estimators for the Estimation of a Structural Vector Autoregressive Integrated Process," IEPR Working Papers 05.23, Institute of Economic Policy Research (IEPR).
    • Handle: RePEc:scp:wpaper:05-23
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    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
    • 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

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