IDEAS home Printed from https://ideas.repec.org/p/qed/wpaper/390.html
   My bibliography  Save this paper

Model Specification Tests Based on Artificial Linear Regressions

Author

Listed:
  • Russell Davidson
  • James G. MacKinnon

Abstract

This paper develops a general procedure for performing a wide variety of model specification tests by running artificial linear regressions and then using conventional significance tests. In particular, this procedure allows us to develop non-nested hypothesis tests for any set of models which attempt to explain the same dependent variable(s), even when the error specifications of the models differ. For example, it is straightforward to test linear regression models against loglinear ones. These procedures are illustrated with an application to estimate competing models of personal savings in Canada.

Suggested Citation

  • Russell Davidson & James G. MacKinnon, 1980. "Model Specification Tests Based on Artificial Linear Regressions," Working Papers 390, Queen's University, Department of Economics.
  • Handle: RePEc:qed:wpaper:390
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bettin, Giulia & Lucchetti, Riccardo & Zazzaro, Alberto, 2012. "Endogeneity and sample selection in a model for remittances," Journal of Development Economics, Elsevier, vol. 99(2), pages 370-384.
    2. MacKinnon, J G, 1989. "Heteroskedasticity-Robust Tests for Structural Change," Empirical Economics, Springer, vol. 14(2), pages 77-92.
    3. Y. K. Tse & Z. L. Yang, 2004. "Tests of Functional Form and Heteroscedasticity," Econometric Society 2004 Far Eastern Meetings 424, Econometric Society.
    4. Li Dong & Le Canh, 2010. "Nonlinearity and Spatial Lag Dependence: Tests Based on Double-Length Regressions," Journal of Time Series Econometrics, De Gruyter, vol. 2(1), pages 1-18, June.
    5. Benjamin Born & Jörg Breitung, 2011. "Simple regression‐based tests for spatial dependence," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 330-342, July.
    6. Murphy, Anthony, 1996. "Simple LM tests of mis-specification for ordered logit models," Economics Letters, Elsevier, vol. 52(2), pages 137-141, August.
    7. Davidson, R. & MacKinnon & J.G., 1999. "Artificial Regressions," G.R.E.Q.A.M. 99a04, Universite Aix-Marseille III.
    8. Badi Baltagi & Long Liu, 2014. "Testing for spatial lag and spatial error dependence using double length artificial regressions," Statistical Papers, Springer, vol. 55(2), pages 477-486, May.
    9. Davidson, Russell & MacKinnon, James G, 1988. "Double Length Artificial Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 50(2), pages 203-217, May.
    10. Davidson, Russell & MacKinnon, James G., 1989. "Testing for Consistency using Artificial Regressions," Econometric Theory, Cambridge University Press, vol. 5(03), pages 363-384, December.
    11. McAleer, Michael, 1994. " Sherlock Holmes and the Search for Truth: A Diagnostic Tale," Journal of Economic Surveys, Wiley Blackwell, vol. 8(4), pages 317-370, December.
    12. Godwin Nwaobi, 2002. "A vector error correction and nonnested modeling of money demand function in Nigeria," Economics Bulletin, AccessEcon, vol. 3(4), pages 1-8.
    13. Marie-Estelle Binet & Fabrizio Carlevaro & Michel Paul, 2014. "Estimation of Residential Water Demand with Imperfect Price Perception," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 59(4), pages 561-581, December.
    14. Baltagi, Badi H., 1997. "Testing linear and loglinear error components regressions against Box-Cox alternatives," Statistics & Probability Letters, Elsevier, vol. 33(1), pages 63-68, April.
    15. Dowrick, Steve & Dunlop, Yvonne & Quiggin, John, 2003. "Social indicators and comparisons of living standards," Journal of Development Economics, Elsevier, vol. 70(2), pages 501-529, April.
    16. Bontemps, Christian & Meddahi, Nour, 2005. "Testing normality: a GMM approach," Journal of Econometrics, Elsevier, vol. 124(1), pages 149-186, January.
    17. William H. Greene & David A. Hensher, 2008. "Modeling Ordered Choices: A Primer and Recent Developments," Working Papers 08-26, New York University, Leonard N. Stern School of Business, Department of Economics.
    18. Davidson, Russell & MacKinnon, James G, 1998. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," The Manchester School of Economic & Social Studies, University of Manchester, vol. 66(1), pages 1-26, January.
    19. Robin Pope, 2009. "Risk starvation contributes to dementias and depressions: Whiffs of danger are the antidote," Bonn Econ Discussion Papers bgse28_2009, University of Bonn, Germany.
    20. West, Kenneth D & McCracken, Michael W, 1998. "Regression-Based Tests of Predictive Ability," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 817-840, November.
    21. Russell Davidson & James G. MacKinnon, 1988. "Specification Tests Based on Artificial Regressions," Working Papers 707, Queen's University, Department of Economics.
    22. W. Yang, 1999. "The Demand for and Supply of Shares. An Empirical Study of the Limit Order Book on the ASX," Economics Discussion / Working Papers 99-03, The University of Western Australia, Department of Economics.
    23. Le, Canh Quang & Li, Dong, 2008. "Double-Length Regression tests for testing functional forms and spatial error dependence," Economics Letters, Elsevier, vol. 101(3), pages 253-257, December.
    24. Hosoya, Yuzo & Terasaka, Takahiro, 2009. "Inference on transformed stationary time series," Journal of Econometrics, Elsevier, vol. 151(2), pages 129-139, August.

    More about this item

    JEL classification:

    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L22 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Organization and Market Structure
    • L68 - Industrial Organization - - Industry Studies: Manufacturing - - - Appliances; Furniture; Other Consumer Durables

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:qed:wpaper:390. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mark Babcock). General contact details of provider: http://edirc.repec.org/data/qedquca.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.