Using a novel dataset, we analysis the spatio-temporal dynamics of income per capita across 34 provinces and 514 districts in Indonesia over the 2010–2017 period.
This paper studies regional convergence and spatial dependence of homicides and personal injuries in Colombia. In particular, through the lens of both classical and distributional convergence frameworks, two spatial scales are contrasted: municipalities and states.
Results from the distributional convergence approach indicate the existence of two local convergence clusters within the overall and pure efficiency distributions.
The paper incorporates some recent developments from the unsupervised machine learning literature to re-evaluate the cross-country convergence hypothesis in a context beyond GDP. The application of a distribution-based clustering algorithm suggests the formation of three local convergence clubs.
While the LP framework shows relatively less mobility, two convergence clusters in the transition stage, and a bumpy distribution in the long run; the ACF framework shows relatively more backward mobility, a unique convergence cluster in the transition, and a highly symmetric distribution in the long run.