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Measurement errors in a spatial context

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  • 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
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    Cited by:

    1. Geniaux, Ghislain & Martinetti, Davide, 2018. "A new method for dealing simultaneously with spatial autocorrelation and spatial heterogeneity in regression models," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 74-85.
    2. Xu Ning & Francis K. C. Hui & Alan H. Welsh, 2023. "A double fixed rank kriging approach to spatial regression models with covariate measurement error," Environmetrics, John Wiley & Sons, Ltd., vol. 34(1), February.

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    More about this item

    Keywords

    Measurement error; Spatial autocorrelation; Instrumental variables; GMM; Monte-Carlo simulations;
    All these keywords.

    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

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