Are poorer countries catching up to richer ones? Using international income data, we test whether poorer countries grow faster and whether income gaps across the world are shrinking, and we see how the answer changed after 2000. This Stata tutorial comes with an interactive app that runs in your web browser.
Why have poor countries grown faster than rich ones since around 2000, after decades of falling behind? We reproduce a 2021 study by Kremer, Willis and You showing that the policies, institutions and schooling that predict growth have themselves become more alike across countries. This Stata tutorial comes with an interactive app that runs in your web browser.
The book provides a succinct review of the recent club convergence literature, a comparative view of developed and developing countries, and a tutorial on how to implement the club convergence framework in Stata and R.
This paper studies the evolution of economic and social disparities across subnational regions in South America using simple spatial convergence models.
Examine why countries follow different productivity paths and whether groups converge toward common outcomes. This book compares developed and developing economies through labor productivity, capital accumulation, and aggregate efficiency using a framework that identifies convergence clubs. A focused literature review, comparative evidence, and a Stata implementation tutorial help graduate students and researchers apply the approach to their own work.
Across ASEAN regions, almost 60 percent of the differences in GDP per capita can be predicted by a luminosity-based measure of GDP. Based on this measure, regional inequality within most countries has not significantly decreased, spatial dependence is increasing, and spatial clusters (hotspots and coldspots) cross multiple national boundaries.