On the specification of regression models with spatial dependence - an application of the accessibility concept
AbstractUsing 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
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Bibliographic InfoPaper provided by Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies in its series Working Paper Series in Economics and Institutions of Innovation with number 51.
Length: 28 pages
Date of creation: 28 Mar 2006
Date of revision:
Note: accessibility, spatial dependence, spatial econometrics, Monte Carlo Simulations, spatial spillovers
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Postal: CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology, SE-100 44 Stockholm, Sweden
Phone: +46 8 790 95 63
Web page: http://www.infra.kth.se/cesis/
More information through EDIRC
accessibility; spatial dependence; spatial econometrics; Monte Carlo Simulations; spatial spillovers;
Find related papers by 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-04-01 (All new papers)
- NEP-DCM-2006-04-01 (Discrete Choice Models)
- NEP-ECM-2006-04-01 (Econometrics)
- NEP-GEO-2006-04-01 (Economic Geography)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- J W Weibull, 1980. "On the numerical measurement of accessibility," Environment and Planning A, Pion Ltd, London, vol. 12(1), pages 53-67, January.
- Sara Johansson & Charlie Karlsson, 2007. "R&D accessibility and regional export diversity," The Annals of Regional Science, Springer, vol. 41(3), pages 501-523, September.
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