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The Mundlak Approach in the Spatial Durbin Panel Data Model

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  • Nicolas Debarsy

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - ULCO - Université du Littoral Côte d'Opale - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper extends the Mundlak approach to the spatial Durbin panel data model (SDM) to help the applied researcher to determine the adequacy of the random effects specification in this setup. We propose a likelihood ratio (LR) test that assesses the significance of the correlation between regressors and individual effects. By contrast to the Hausman test, the Mundlak approach identifies (to some extend) the regressors correlated with individual effects. The second advantage is that once the correlation with individual effects has been modeled through an auxiliary regression, the random effects specification provides consistent estimators and the effect of time-constant variables can be estimated. Some Monte Carlo simulations study the properties of this proposed LR test in small samples and show that in some cases, it has a better behavior than the Hausman test. We finally illustrate the usefulness of the extended Mundlak approach by estimating a house price model where some of the price determinants are timeconstant. We show that ignoring the endogeneity of regressors with respect to individual effects leads to unreliable estimated parameters while results obtained using the Mundlak approach and the fixed effects specification are similar (concerning time-varying variables), implying that correlation between regressors and individual effects is well captured.

Suggested Citation

  • Nicolas Debarsy, 2012. "The Mundlak Approach in the Spatial Durbin Panel Data Model," Post-Print hal-04989094, HAL.
    • Handle: RePEc:hal:journl:hal-04989094
    DOI: 10.1080/17421772.2011.647059
    Note: View the original document on HAL open archive server: https://hal.science/hal-04989094v1
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    References listed on IDEAS

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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