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XTSUR: Stata module to estimate seemingly unrelated regression model on unbalanced panel data

Author

Listed:
  • Minh Cong Nguyen

    (American University)

Programming Language

Stata

Abstract

xtsur fits a many-equation seemingly-unrelated regression (SUR) model of the y1 variable on the x1 variables and the y2 variable on the x1 or x2 variables and etc..., using random effect estimators in the context of unbalanced panel data. The approach for this command is based on constructing a stepwise algorithm using Generalized Least Squares (GLS) and the Maximum Likelihood (ML) procedures. The method is originally developed by Erik Biorn (Journal of Econometrics, 2004).

Suggested Citation

  • Minh Cong Nguyen, 2008. "XTSUR: Stata module to estimate seemingly unrelated regression model on unbalanced panel data," Statistical Software Components S456953, Boston College Department of Economics, revised 01 Oct 2010.
    • Handle: RePEc:boc:bocode:s456953
    Note: This module should be installed from within Stata by typing "ssc install xtsur". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/bocode/x/xtsur.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/x/xtsur.sthlp
    File Function: help file
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/x/xtsur_example.dta
    File Function: sample data file
    Download Restriction: no
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    Citations

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    Cited by:

    1. Bayona, Anna & Brandts, Jordi & Vives, Xavier, 2020. "Information frictions and market power: A laboratory study," Games and Economic Behavior, Elsevier, vol. 122(C), pages 354-369.
    2. Mitze, Timo & Stephan, Andreas, 2013. "Simultaneous-equations Analysis in Regional Science and Economic Geography," Working Paper Series in Economics and Institutions of Innovation 309, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    3. Vives, Xavier & Bayona, Anna & Brandts, Jordi, 2016. "Supply Function Competition, Private Information, and Market Power: A Laboratory Study," IESE Research Papers D/1146, IESE Business School.

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