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Spatial issues on a hedonic estimation of rents in Brussels

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  • PHOLO BALA, Alain

    () (Department of Economics and Econometrics, University of Johannesburg, South Africa)

  • PEETERS, Dominique

    () (Université catholique de Louvain, CORE, Belgium)

  • THOMAS, Isabelle

    () (Université catholique de Louvain, CORE, Belgium)

Abstract

Using Belgian microdata, we assess the impact, on a hedonic regression, of the distortions arising from the choice of either a specific zoning system or the delineation of the study area. We also evaluate the biases that arise when spatial effects are not accounted for. Given that the dependent variable is interval-coded, controlling for spatial dependence in this context is challenging. We address this problem with two alternative strategies. Firstly, we use the Gibbs Sampling algorithm to estimate spatial econometric models which extends the interval regression model. A major drawback of this approach is that the implied estimation is proned to the endogeneity biases inherent to our hedonic regression model. To circumvent the endogeneity issues triggered by the first estimation strategy, we also use a two-stage estimation procedure with locational fixed effects. In all specifications, results are sensitive to the Modifiable Areal Unit Problem (MAUP) and to the choice of the delineation of the study area. Moreover, they confirm the existence of substantive spatial dependence. Conversely to the previous results with a negative elasticity for the percentage of the area covered by agriculture and a positive elasticity for the potential accessibility to jobs, the second approach implies opposite effects for those two variables. This indicates that dwellings close to agricultural areas and with a lower accessibility to the main employment centers are highly demanded and that endogeneity biases are not negligible.

Suggested Citation

  • PHOLO BALA, Alain & PEETERS, Dominique & THOMAS, Isabelle, 2013. "Spatial issues on a hedonic estimation of rents in Brussels," CORE Discussion Papers 2013036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Handle: RePEc:cor:louvco:2013036
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    References listed on IDEAS

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    Cited by:

    1. Carroll, James & Aravena, Claudia & Denny, Eleanor, 2016. "Low energy efficiency in rental properties: Asymmetric information or low willingness-to-pay?," Energy Policy, Elsevier, vol. 96(C), pages 617-629.
    2. Louis-Gaëtan Giraudet, 2018. "Energy efficiency as a credence good: A review of informational barriers to building energy savings," Policy Papers 2018.04, FAERE - French Association of Environmental and Resource Economists.
    3. Louis-Gaëtan Giraudet, 2018. "Energy efficiency as a credence good: A review of informational barriers to building energy savings," Working Papers 2018.07, FAERE - French Association of Environmental and Resource Economists.

    More about this item

    Keywords

    MAUP; interval regression; spatial dependence; spatial heterogeneity; Brussels;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

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