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Efficient Estimation and Identification of Simultaneous Equation Models with Covariance Restrictions

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  • J. Hausman
  • W. Newey
  • W. Taylor

Abstract

The authors consider estimation of simultaneous equations models with covariance restrictions. They consider FIML estimation and extend J. A. Hausman's instrumental variables interpretation of the FIML estim ator to the covariance restrictions case. A slight variation on the i nstrumental variables theme yields a simple, efficient alternative to FIML. The authors augment the original equation system by equations implied by the covariance restrictions, linearized around an initial consistent estimator, and perform three-stage least squares to obtain an asymptotically efficient estimator. They also present a simple me thod of obtaining an initial consistent estimator when the covariance restrictions are needed for identification. Finally, they consider i dentification from the standpoint of the moment restrictions implied by instrument-residual orthogonality and covariance restrictions. Copyright 1987 by The Econometric Society.
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Suggested Citation

  • J. Hausman & W. Newey & W. Taylor, 1983. "Efficient Estimation and Identification of Simultaneous Equation Models with Covariance Restrictions," Working papers 331, Massachusetts Institute of Technology (MIT), Department of Economics.
  • Handle: RePEc:mit:worpap:331
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    Cited by:

    1. Calzolari, Giorgio, 1992. "Stima delle equazioni simultanee non-lineari: una rassegna
      [Estimation of nonlinear simultaneous equations: a survey]
      ," MPRA Paper 24123, University Library of Munich, Germany, revised 1992.
    2. So Im, Kyung & Ahn, Seung C. & Schmidt, Peter & Wooldridge, Jeffrey M., 1999. "Efficient estimation of panel data models with strictly exogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 93(1), pages 177-201, November.
    3. Abou-Ali, Hala & Abdelfattah, Yasmine M., 2013. "Integrated paradigm for sustainable development: A panel data study," Economic Modelling, Elsevier, vol. 30(C), pages 334-342.
    4. Arnab Bhattacharjee & Sean Holly, 2013. "Understanding Interactions in Social Networks and Committees," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(1), pages 23-53, March.
    5. Panizza, Ugo & Presbitero, Andrea F., 2014. "Public debt and economic growth: Is there a causal effect?," Journal of Macroeconomics, Elsevier, vol. 41(C), pages 21-41.
    6. Jinyong Hahn & Jerry Hausman & Guido Kuersteiner, 2005. "Bias Corrected Instrumental Variables Estimation for Dynamic Panel Models with Fixed E¤ects," Boston University - Department of Economics - Working Papers Series WP2005-024, Boston University - Department of Economics.
    7. Hahn, Jinyong & Hausman, Jerry & Kuersteiner, Guido, 2007. "Long difference instrumental variables estimation for dynamic panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 574-617, October.
    8. Bhattacharjee, Arnab & Jensen-Butler, Chris, 2013. "Estimation of the spatial weights matrix under structural constraints," Regional Science and Urban Economics, Elsevier, vol. 43(4), pages 617-634.
    9. Hanan G. Jacoby & Ghazala Mansuri, 2010. "Watta Satta: Bride Exchange and Women's Welfare in Rural Pakistan," American Economic Review, American Economic Association, vol. 100(4), pages 1804-1825, September.
    10. Biørn, Erik, 2017. "Identification, Instruments, Omitted Variables, and Rudimentary Models: Fallacies in the ‘Experimental Approach’ to Econometrics," Memorandum 13/2017, Oslo University, Department of Economics.
    11. Calzolari, Giorgio & Sampoli, Letizia, 1989. "Instrumental variables interpretations of FIML and nonlinear FIML," MPRA Paper 29024, University Library of Munich, Germany.
    12. Prabuddha De & Yu (Jeffrey) Hu & Mohammad S. Rahman, 2010. "Technology Usage and Online Sales: An Empirical Study," Management Science, INFORMS, vol. 56(11), pages 1930-1945, November.
    13. Taghizadeh Hesary Farhad & Naoyuki Yoshino, 2013. "Empirical Analysis of Oil Price Determination Based on Market Quality Theory," Keio/Kyoto Joint Global COE Discussion Paper Series 2012-044, Keio/Kyoto Joint Global COE Program.
    14. Robert G. King & Mark W. Watson, 1997. "Testing long-run neutrality," Economic Quarterly, Federal Reserve Bank of Richmond, issue Sum, pages 69-101.
    15. Hartley, Peter R. & Whitt Jr, Joseph A., 2003. "Macroeconomic fluctuations: Demand or supply, permanent or temporary?," European Economic Review, Elsevier, vol. 47(1), pages 61-94, February.
    16. Hausman, Jerry A., 2003. "Triangular structural model specification and estimation with application to causality," Journal of Econometrics, Elsevier, vol. 112(1), pages 107-113, January.
    17. Krichene, Noureddine, 2002. "World crude oil and natural gas: a demand and supply model," Energy Economics, Elsevier, vol. 24(6), pages 557-576, November.
    18. Andrea Brischetto & Graham Voss, 1999. "A Structural Vector Autoregression Model of Monetary Policy in Australia," RBA Research Discussion Papers rdp1999-11, Reserve Bank of Australia.
    19. Steven Lehrer & Weili Ding, 2004. "Estimating Dynamic Treatment Effects from Project STAR," Econometric Society 2004 North American Summer Meetings 252, Econometric Society.

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