Sample Size Requirements for Estimation in SUR Models

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Sample Size Requirements for Estimation in SUR Models

Author Info

Chotikapanich, D.
Griffiths, W.E.
Skeels, C.L.

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Abstract

This paper explores sample size requirements for the estimation of SUR models by (two-stage) feasible generalized least squares, maximum likelihood and Bayesian methods. It is found that the sample size requirements presented in standard treatments of SUR models are incomplete and potentially misleading. It is also demonstrated that likelihood-based methods potentially require larger sample sizes than does the two-stage estimator considered in this paper.

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Paper provided by The University of Melbourne in its series Department of Economics - Working Papers Series with number 794.

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Length: 18 pages
Date of creation: 2001
Date of revision:
Handle: RePEc:mlb:wpaper:794

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Find related papers by JEL classification:
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

References listed on IDEAS
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Phillips, Peter C B, 1985. "The Exact Distribution of the SUR Estimator," Econometrica, Econometric Society, vol. 53(4), pages 745-56, July. [Downloadable!] (restricted)
Chib, Siddhartha & Greenberg, Edward, 1996. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometric Theory, Cambridge University Press, vol. 12(03), pages 409-431, August. [Downloadable!]
John Freebairn & Bill Griffiths, 2006. "Introduction," The Economic Record, The Economic Society of Australia, vol. 82(s1), pages S1-S1, 09. [Downloadable!] (restricted)
Denzil Fiebig & Jae Kim, 2000. "Estimation and inference in sur models when the number of equations is large," Econometric Reviews, Taylor and Francis Journals, vol. 19(1), pages 105-130. [Downloadable!] (restricted)
repec:cup:etheor:v:12:y:1996:i:3:p:409-31 is not listed on IDEAS

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Cited by:
(explanations, 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.)

W.E. Griffiths & Ma. Rebecca Valenzuela, 2004. "Gibbs Samplers for a Set of Seemingly Unrelated Regressions," Department of Economics - Working Papers Series 912, The University of Melbourne. [Downloadable!]
Griffiths, W.E., 2001. "Bayesian Inference in the Seemingly Unrelated Regressions Models," Department of Economics - Working Papers Series 793, The University of Melbourne. [Downloadable!]
Wolff, Hendrik & Heckelei, Thomas & Mittelhammer, Ron C., 2004. "Imposing Monotonicity And Curvature On Flexible Functional Forms," 2004 Annual meeting, August 1-4, Denver, CO 20256, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association). [Downloadable!]

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This page was last updated on 2009-11-23.

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