Abstract: This paper explores the implications that spatial effects can hold for the application of measures of sigma-convergence. The bias of a common indicator of convergence is examined for a family of spatial process models including: [a] spatial lag, [b] spatial error, and [c] spatial moving average. We show that the measure of sigma-convergence is sensitive to a number of distinct influences including global dispersion, spatial dependence and a variety of forms of spatial heterogeneity. We suggest a decomposition of the convergence indicator into two components: one reflecting global dispersion and one reflecting the influence of spatial effects. We then illustrate this approach with a case study of the U.S. states over the 1929-2000 period.
HouSI: A heuristic for the delimitation of housing submarkets and price homogeneous areas
Python library with spatially constrained clustering algorithms
Interactive tool for visualizing the interindustry dynamics in Colombian economy.
The Center for Urban and Environmental Studies, Urbam, is a new RiSE's partner. Interesting projects are coming!
Doctor Xinyue Ye, a RiSE’s academic affiliate, was awarded the Regional Development and Planning (RDPSG) Emerging Scholar by the Association of American Geographers (AAG).
The VI World Conference of the Spatial Econometrics Association (SEA) Conference in Latin America
