2017
DOI: 10.1080/17421772.2017.1286373
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A two-step approach to account for unobserved spatial heterogeneity

Abstract: Empirical analysis in economics often faces the difficulty that the data is correlated and heterogeneous in some unknown form. Spatial parametric approaches have been widely used to account for dependence structures, but the problem of directly deal with spatially varying parameters has been largely unexplored. The problem can be serious in all those cases in which we have no prior information justified by the economic theory. In this paper we propose an algorithm-based procedure which is able to endogenously … Show more

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Cited by 34 publications
(23 citation statements)
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“…Overall our results validate the concerns of Longley and Tobón (); Billé et al (, ) and Bourdin () that there can be sizable differences in coefficient estimates across different spatial regimes. Note that, our findings also validate the early concerns of Doğruel and Doğruel () that examine the west‐east duality with the help of sample split and traditional convergence models.…”
Section: Resultssupporting
confidence: 90%
See 1 more Smart Citation
“…Overall our results validate the concerns of Longley and Tobón (); Billé et al (, ) and Bourdin () that there can be sizable differences in coefficient estimates across different spatial regimes. Note that, our findings also validate the early concerns of Doğruel and Doğruel () that examine the west‐east duality with the help of sample split and traditional convergence models.…”
Section: Resultssupporting
confidence: 90%
“…GWR is a powerful tool to analyse the extent of spatial heterogeneity (Bivand, ). Recent advances in spatial analyses underline the possibility of controlling for spatial dependence in GWR type of models (Billé, Benedetti, & Postiglione, ). Detection of different spatial regimes and control of spatial spillovers within each regime is a good exercise to understand spatial mechanisms.…”
Section: Resultsmentioning
confidence: 99%
“…The pioneering non-parametric technique introduced by Reference [44] will be our method of choice. Spatial autocorrelation is often generated by spatial heterogeneity issues [45]. We choose the Phillips-Sul approach outlined in Reference [44] because, in the presence of such heterogeneity, standard cointegration and unit root testing are no longer sufficient for testing for convergence [44,46].…”
Section: Club Convergencementioning
confidence: 99%
“…In addition, the journal receives many submissions making the point that GWR outperforms the ordinary least squares (OLS) approach in that it provides a better model fit, especially in hedonic housing price studies. The fifth paper in this issue, by Billé, Benedetti, and Postiglione (2017), stands out in that it is trying to make a major methodological step forward. It proposes a two-step procedure to identify endogenously spatial regimes in the first step and then to account for spatial dependence in the second step.…”
Section: )mentioning
confidence: 99%