Raising the bar (9). Issue 4 (2nd October 2018)

• Record Type: Journal Article
• Authors: Elhorst, Paul; Abreu, Maria; Amaral, Pedro; Bhattacharjee, Arnab; Corrado, Luisa; Doran, Justin; Fingleton, Bernard; Fuerst, Franz; Igliori, Danilo; Gallo, Julie Le; McCann, Philip; Monastiriotis, Vassilis; Quatraro, Francesco; Yu, Jihai
• Is Part Of: Spatial economic analysis. Volume 13:Issue 4(2018)
• Page Start: 379
• Page End: 382
• Publication Date: 2018-10-02
• Subjects: agglomeration -- congestion -- spillovers -- productivity -- model bias; C12 -- C23 -- G01 -- L81 -- R12; Space in economics -- Periodicals; Economic geography -- Periodicals; Space in economics -- Econometric models -- Periodicals; Urbanization -- Periodicals; Espace (Économie politique) -- Périodiques; Économétrie -- Périodiques; Géographie économique -- Périodiques; Économie industrielle -- Périodiques; Économie du travail -- Périodiques; Économie urbaine -- Périodiques; Politique économique -- Périodiques; Relations économiques internationales -- Périodiques; 330.9
• DOI: 10.1080/17421772.2018.1529012
• Languages: English
• ISSNs: 1742-1772

Abstract

ABSTRACT: This editorial summarizes the papers published in issue 13(4) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper develops an economic geography model with trade costs in all sectors and different shares of unskilled labour in all locations. The second paper translates an economic geography model into a dynamic spatial econometric model and then estimates the unknown parameters to test for congestion spillover effects among Chinese cities. The following paper also investigates spillover effects, but of sovereign and banking risks across countries. The fourth paper empirically examines if a higher market potential results in higher average productivity and lower productivity dispersion of Italian retailers. The fifth paper demonstrates that modelling more than one spatial lag in the independent variables, using different specifications of the spatial weight matrix, can be used as a tool to correct for an omitted variable bias. The final paper develops a test for the existence of non-parametric non-linearities in a linear spatial econometric model.