IDEAS home Printed from https://ideas.repec.org/a/eee/regeco/v42y2012i1p114-125.html
   My bibliography  Save this article

Measurement errors in a spatial context

Author

Listed:
  • Le Gallo, Julie
  • Fingleton, Bernard

Abstract

Measurement error in an independent variable is one reason why OLS estimates may not be consistent. However, as shown by Dagenais (1994), in some circumstances the OLS bias may be ameliorated somewhat given the presence of serially correlated disturbances, and OLS may prove superior to standard techniques used to correct for serial correlation. This paper considers the case of cross-sectional regression models with measurement errors in the explanatory variables and with spatial dependence. The study focuses on the evidence provided by an empirical illustration and Monte Carlo experiments examining measurement error impact in the presence of autoregressive error processes and autoregressive spatial lags.

Suggested Citation

  • Le Gallo, Julie & Fingleton, Bernard, 2012. "Measurement errors in a spatial context," Regional Science and Urban Economics, Elsevier, vol. 42(1-2), pages 114-125.
  • Handle: RePEc:eee:regeco:v:42:y:2012:i:1:p:114-125
    DOI: 10.1016/j.regsciurbeco.2011.08.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0166046211000986
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    2. Bernard Fingleton, 2003. "Increasing returns: evidence from local wage rates in Great Britain," Oxford Economic Papers, Oxford University Press, vol. 55(4), pages 716-739, October.
    3. Sandy Dall'erba & Julie Le Gallo, 2008. "Regional convergence and the impact of European structural funds over 1989-1999: A spatial econometric analysis," Papers in Regional Science, Wiley Blackwell, vol. 87(2), pages 219-244, June.
    4. Grether, D M & Maddala, G S, 1973. "Errors in Variables and Serially Correlated Disturbances in Distributed Lag Models," Econometrica, Econometric Society, vol. 41(2), pages 255-262, March.
    5. Luc Anselin & Nancy Lozano-Gracia, 2008. "Errors in variables and spatial effects in hedonic house price models of ambient air quality," Empirical Economics, Springer, vol. 34(1), pages 5-34, February.
    6. Stanislav Stakhovych & Tammo H.A. Bijmolt, 2009. "Specification of spatial models: A simulation study on weights matrices," Papers in Regional Science, Wiley Blackwell, vol. 88(2), pages 389-408, June.
    7. Baltagi, Badi H. & Liu, Long, 2009. "Spatial lag test with equal weights," Economics Letters, Elsevier, vol. 104(2), pages 81-82, August.
    8. Kelejian, Harry H. & Prucha, Ingmar R., 2007. "HAC estimation in a spatial framework," Journal of Econometrics, Elsevier, vol. 140(1), pages 131-154, September.
    9. Bernard Fingleton & Julie Le Gallo, 2008. "Estimating spatial models with endogenous variables, a spatial lag and spatially dependent disturbances: Finite sample properties," Papers in Regional Science, Wiley Blackwell, vol. 87(3), pages 319-339, August.
    10. N. Gregory Mankiw & David Romer & David N. Weil, 1992. "A Contribution to the Empirics of Economic Growth," The Quarterly Journal of Economics, Oxford University Press, vol. 107(2), pages 407-437.
    11. Lung-Fei Lee, 2004. "Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models," Econometrica, Econometric Society, vol. 72(6), pages 1899-1925, November.
    12. Dagenais, Marcel G., 1994. "Parameter estimation in regression models with errors in the variables and autocorrelated disturbances," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 145-163.
    13. Daniel Griffith & Jean Paelinck, 2007. "An equation by any other name is still the same: on spatial econometrics and spatial statistics," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 41(1), pages 209-227, March.
    14. J. Barkley Rosser, 2009. "Introduction," Chapters,in: Handbook of Research on Complexity, chapter 1 Edward Elgar Publishing.
    15. Peter Kennedy, 2003. "A Guide to Econometrics, 5th Edition," MIT Press Books, The MIT Press, edition 5, volume 1, number 026261183x.
    16. Jonathan R. W. Temple, 1998. "Robustness tests of the augmented Solow model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(4), pages 361-375.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Measurement error; Spatial autocorrelation; Instrumental variables; GMM; Monte-Carlo simulations;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

    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:eee:regeco:v:42:y:2012:i:1:p:114-125. 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: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/regec .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.