Raising the bar (16). Issue 4 (1st October 2020)

• Record Type: Journal Article
• Authors: Elhorst, Paul; Abreu, Maria; Amaral, Pedro; Bhattacharjee, Arnab; Chasco, Coro; Corrado, Luisa; Doran, Justin; Felsenstein, Daniel; Fuerst, Franz; Gallo, Julie Le; McCann, Philip; Monastiriotis, Vassilis; Quatraro, Francesco; Temursho, Umed; Yu, Jihai
• Is Part Of: Spatial economic analysis. Volume 15:Issue 4(2020)
• Page Start: 353
• Page End: 358
• Publication Date: 2020-10-01
• Subjects: Shrinkage -- spatial differences -- prices -- wage -- productivity -- clustering -- regionalization; C1 -- D5 -- J1 -- R1; 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: 10.1080/17421772.2020.1836818
• Languages: English
• ISSNs: 1742-1772

Abstract

ABSTRACT: This editorial summarises the papers published in issue 15.4 in order to raise the bar in applied spatial economic research and highlight new trends and knowledge. The first paper challenges the standard notion that more growth is better. The second paper challenges macroeconomic models by looking at them from a regional micro-grounded lens, where the effect of productivity shocks depends on the distribution of economic activity and the locations where shocks occur. The third paper investigates the wage-productivity nexus using the latest techniques on cross-sectional dependence. The fourth paper introduces a new method to determine regional price differentials. The fifth paper tests whether economic-theoretical insights obtained from urban economic models apply not only to cities in developed countries but also to those in developing countries. The sixth paper sets out an estimation method for a spatial random coefficients model for clusters of observations. The seventh paper proposes a new method for regionalizing national input–output tables. The final paper focuses on Big Data and its role in regional growth.