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Artificial Regressions

Author

Listed:
  • James G. MacKinnon

    (Queen's University)

  • Russell Davidson

    (McGill University)

Abstract

Associated with every popular nonlinear estimation method is at least one "artificial" linear regression. We define an artificial regression in terms of three conditions that it must satisfy. Then we show how artificial regressions can be useful for numerical optimization, testing hypotheses, and computing parameter estimates. Several existing artificial regressions are discussed and are shown to satisfy the defining conditions, and a new artificail regression for regression models with heteroskedasticity of unknown form is introduced.

Suggested Citation

  • James G. MacKinnon & Russell Davidson, 1999. "Artificial Regressions," Working Paper 978, Economics Department, Queen's University.
    • Handle: RePEc:qed:wpaper:978
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    File URL: https://www.econ.queensu.ca/sites/econ.queensu.ca/files/qed_wp_978.pdf
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    12. Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2006. "Joint LM test for homoskedasticity in a one-way error component model," Journal of Econometrics, Elsevier, vol. 134(2), pages 401-417, October.
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    19. Lamarche, Jean-Francois, 2003. "A robust bootstrap test under heteroskedasticity," Economics Letters, Elsevier, vol. 79(3), pages 353-359, June.
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    21. Patacchini, Eleonora, 2003. "On the estimation of covariance matrices using panel data artificial regressions," Discussion Paper Series In Economics And Econometrics 0303, Economics Division, School of Social Sciences, University of Southampton.
    22. Felicitas Nowak-Lehmann D. & Inmaculada Martínez- Zarzoso, 2003. "The interplay of export supply and the real exchange rate. Evidence for Mercosur exports to the EU," International Trade 0309020, University Library of Munich, Germany.
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    25. Tomaso Duso & Astrid Jung, 2007. "Market Conduct and Endogenous Lobbying: Evidence from the U.S. Mobile Telecommunications Industry," Journal of Industry, Competition and Trade, Springer, vol. 7(1), pages 9-29, March.

    More about this item

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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