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Power Properties of the Sargan Test in the Presence of Measurement Errors in Dynamic Panels


  • Dahlberg, Matz

    () (Department of Economics)

  • Johansson, Eva

    () (Department of Economics)

  • Tovmo, Per

    (Norwegian University of Science and Technology)


This paper investigates the power properties of the Sargan test in the presence of measurement errors in dynamic panel data models. The general conclusion from the Monte Carlo simulations is that the Sargan test, in many cases, leads the econometrician to accept misspecified models with sometimes severely biased parameter estimates as a result. This is especially true when the number of cross-sectional units is small and when there are measurement errors in the dependent variable. To investigate if the simulation results have any bearing in real applications, we used the data in Arellano and Bond (1991) and re-estimated their employment equations with the difference that we deliberately imposed additive and multiplicative measurement errors in the employment and wage variables. It turned out that the Sargan test always accepted the misspecified models while we at the same time ended up with biased parameter estimates. The conclusion from this paper is that in the very likely case of measurement errors in either the dependent or any of the independent variables, we will, if we rely on the Sargan test, quite likely accept a misspecified model and end up with biased results.

Suggested Citation

  • Dahlberg, Matz & Johansson, Eva & Tovmo, Per, 2002. "Power Properties of the Sargan Test in the Presence of Measurement Errors in Dynamic Panels," Working Paper Series 2002:13, Uppsala University, Department of Economics.
  • Handle: RePEc:hhs:uunewp:2002_013

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    References listed on IDEAS

    1. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1989. "The Revenues-Expenditures Nexus: Evidence from Local Government Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(2), pages 415-429, May.
    2. Hall, Peter & Horowitz, Joel L, 1996. "Bootstrap Critical Values for Tests Based on Generalized-Method-of-Moments Estimators," Econometrica, Econometric Society, vol. 64(4), pages 891-916, July.
    3. Bowsher, Clive G., 2002. "On testing overidentifying restrictions in dynamic panel data models," Economics Letters, Elsevier, vol. 77(2), pages 211-220, October.
    4. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
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    Cited by:

    1. Ali-Yrkkö, Jyrki, 2004. "Impact of Public R&D Financing on Private R&D - Does Financial Constraint Matter?," Discussion Papers 943, The Research Institute of the Finnish Economy.
    2. Joeri Smits & Jeffrey S. Racine, 2013. "Testing Exclusion Restrictions in Nonseparable Triangular Models," Department of Economics Working Papers 2013-02, McMaster University.
    3. Auld, M. Christopher, 2011. "Effect of large-scale social interactions on body weight," Journal of Health Economics, Elsevier, vol. 30(2), pages 303-316, March.
    4. Takuya Hasebe, 2012. "The tests for the level moment conditions: GMM estimation in a linear dynamic panel data model," Economics Bulletin, AccessEcon, vol. 32(1), pages 412-420.
    5. Angelica Gonzalez, 2007. "Angelica Gonzalez," ESE Discussion Papers 168, Edinburgh School of Economics, University of Edinburgh.

    More about this item


    Sargan test; Measurement errors; Dynamic panels;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models


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