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On the specification of regression models with spatial dependence - an application of the accessibility concept

Author

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  • Andersson, Martin

    (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology)

  • Gråsjö, Urban

    (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology)

Abstract

Using the taxonomy by Anselin (2003), this paper investigates how the inclusion of spatially discounted variables on the ‘right-hand-side’ (RHS) in empirical spatial models affects the extent of spatial autocorrelation. The basic proposition is that the inclusion of inputs external to the spatial observation in question as a separate variable reveals spatial dependence via the parameter estimate. One of the advantages of this method is that it allows for a direct interpretation. The paper also tests to what extent significance of the estimated parameters of the spatially discounted explanatory variables can be interpreted as evidence of spatial dependence. Additionally, the paper advocates the use of the accessibility concept for spatial weights. Accessibility is related to spatial interaction theory and can be motivated theoretically by adhering to the preference structure in random choice theory. Monte Carlo Simulations show that the coefficient estimates of the accessibility variables are significantly different from zero in the case of modelled effects. The rejection frequency of the three typical tests (Moran’s I, LM-lag and LM-err) is significantly reduced when these additional variables are included in the model. When the coefficient estimates of the accessibility variables are statistically significant, it suggests that problems of spatial autocorrelation are significantly reduced. Significance of the accessibility variables can be interpreted as spatial dependence

Suggested Citation

  • Andersson, Martin & Gråsjö, Urban, 2006. "On the specification of regression models with spatial dependence - an application of the accessibility concept," Working Paper Series in Economics and Institutions of Innovation 51, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    • Handle: RePEc:hhs:cesisp:0051
    Note: accessibility, spatial dependence, spatial econometrics, Monte Carlo Simulations, spatial spillovers
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    References listed on IDEAS

    as
    1. J W Weibull, 1980. "On the Numerical Measurement of Accessibility," Environment and Planning A, , vol. 12(1), pages 53-67, January.
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    Cited by:

    1. Andersson, Åke E. & Andersson, David Emanuel & Daghbashyan, Zara & Hårsman, Björn, 2014. "Location and spatial clustering of artists," Regional Science and Urban Economics, Elsevier, vol. 47(C), pages 128-137.
    2. Urban Gråsjö, 2012. "Imports, R&D and Local Patent Production," Chapters, in: Charlie Karlsson & Börje Johansson & Roger R. Stough (ed.), The Regional Economics of Knowledge and Talent, chapter 14, Edward Elgar Publishing.
    3. Sara Johansson & Charlie Karlsson, 2007. "R&D accessibility and regional export diversity," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 41(3), pages 501-523, September.
    4. Andersson , Åke E. & Andersson , David E. & Daghbashyan, Zara & Hårsman, Björn, 2013. "Spatial Clustering Of Artists," INDEK Working Paper Series 2013/2, Royal Institute of Technology, Department of Industrial Economics and Management.
    5. Charlie Karlsson & Börje Johansson & Roger R. Stough (ed.), 2012. "The Regional Economics of Knowledge and Talent," Books, Edward Elgar Publishing, number 13425.

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    More about this item

    Keywords

    accessibility; spatial dependence; spatial econometrics; Monte Carlo Simulations; spatial spillovers;
    All these keywords.

    JEL classification:

    • 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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