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Simple tests for endogeneity of spatial weights matrices

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  • Bera, Anil K.
  • Doğan, Osman
  • Taşpınar, Süleyman

Abstract

In this study, we propose a Rao's score (RS) statistic (Lagrange multiplier (LM) statistic) to test for endogeneity of the spatial weights matrix in a spatial autoregressive model. To achieve this, we start with a spatial autoregressive model with an acceptable form for the generating process for the elements of the endogenous spatial weights matrix as in Qu and Lee (2015). Our test statistic is simple to calculate because it requires computationally simple estimations. By construction, the test statistic is robust in the sense that its asymptotic null distribution is a centered chi-square distribution regardless of the (local) presence of a spatial autoregressive parameter in the alternative model. We summarize the asymptotic properties of our test statistic under the null and the alternative hypotheses. To investigate its finite sample size and power properties, we conduct a Monte Carlo study. The results are in line with our theoretical findings and indicate that the robust test has good size and power properties.

Suggested Citation

  • Bera, Anil K. & Doğan, Osman & Taşpınar, Süleyman, 2018. "Simple tests for endogeneity of spatial weights matrices," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 130-142.
  • Handle: RePEc:eee:regeco:v:69:y:2018:i:c:p:130-142
    DOI: 10.1016/j.regsciurbeco.2018.01.007
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    Cited by:

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    5. Jieun Lee, 2022. "Evidence and Strategy on Economic Distance in Spatially Augmented Solow-Swan Growth Model," Papers 2209.05562, arXiv.org.

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    More about this item

    Keywords

    Endogenous spatial weights matrix; SAR model; Rao's score test; LM test; Robust LM test; Inference; Specification testing; Parametric misspecification;
    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
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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