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Lag-augmented two- and three-stage least squares estimators for integrated structural dynamic models

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  • Cheng Hsiao
  • Siyan Wang

Abstract

We consider a lag-augmented two- or three-stage least-squares estimator for a structural dynamic model of non-stationary and possibly cointegrated variables without the prior knowledge of unit roots or rank of cointegration. We show that the conventional two-and three-stage least-squares estimators are consistent but contain non-standard distributions without the strict exogeneity assumption; hence the conventional Wald type test statistics may not be chi-square distributed. We propose a lag order augmented two- or three-stage least-squares estimator that is consistent and asymptotically normally distributed. Limited Monte Carlo studies are conducted to shed light on the finite sample properties of various estimators. Copyright Royal Economic Society 2007

Suggested Citation

  • Cheng Hsiao & Siyan Wang, 2007. "Lag-augmented two- and three-stage least squares estimators for integrated structural dynamic models," Econometrics Journal, Royal Economic Society, vol. 10(1), pages 49-81, March.
  • Handle: RePEc:ect:emjrnl:v:10:y:2007:i:1:p:49-81
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    Cited by:

    1. repec:nbp:nbpbik:v:47:y:2016:i:6:p:435-462 is not listed on IDEAS
    2. Krzysztof Bartosik & Jerzy Mycielski, 2017. "The output employment elasticity and the increased use of temporary contracts: evidence from Poland," Working Papers 2017-23, Faculty of Economic Sciences, University of Warsaw.
    3. Matthew Oliver & Charles Mason & David Finnoff, 2014. "Pipeline congestion and basis differentials," Journal of Regulatory Economics, Springer, vol. 46(3), pages 261-291, December.

    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables

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