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The exact distribution of exogenous variable coefficient estimators

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  • Phillips, P. C. B.

Abstract

This paper derives the exact probability density function of the instrumental variable (IV) estimator of the exogenous variable coefficient vector in a structural equation containing n+1 endogenous variables and N degrees of overidentification. A leading case of the general distribution that is more amenable to analysis and computation is also presented. Conventional classical assumptions or normally distributed errors and nonrandom exogenous variables are employed.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 26 (1984)
Issue (Month): 3 (December)
Pages: 387-398

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Handle: RePEc:eee:econom:v:26:y:1984:i:3:p:387-398

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Web page: http://www.elsevier.com/locate/jeconom

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Cited by:
  1. Peter C.B. Phillips, 1985. "The Distribution of FIML in the Leading Case," Cowles Foundation Discussion Papers 739, Cowles Foundation for Research in Economics, Yale University.
  2. Grant Hillier & Raymond Kan & Xiaolu Wang, 2008. "Computationally efficient recursions for top-order invariant polynomials with applications," CeMMAP working papers CWP07/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  3. Forchini, Giovanni, 2010. "The Asymptotic Distribution Of The Liml Estimator In A Partially Identified Structural Equation," Econometric Theory, Cambridge University Press, vol. 26(03), pages 917-930, June.
  4. Grant H. Hillier, 1987. "Joint Distribution Theory for Some Statistics Based on LIML and TSLS," Cowles Foundation Discussion Papers 840, Cowles Foundation for Research in Economics, Yale University.
  5. Cheung Ip, Wai & Phillips, Garry D. A., 1998. "The non-monotonicity of the bias and mean squared error of the two stage least squares estimators of exogenous variable coefficients," Economics Letters, Elsevier, vol. 60(3), pages 303-310, September.

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