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.
The paper evaluates the input--output structure of Japan through the lens of a community-detection algorithm from network theory. Results suggest the existence of two input--output network structures: a stationary community and a transitional community. Also, industrial divergence and instability in community membership are not necessarily indicative of low productivity performance
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.
The formation of multiple clusters of convergence is a salient feature of inequality reduction in human development. In the long run, regional convergence is characterized by the transformation of a trimodal distribution into a left-skewed unimodal distribution.
An increasing tendency toward convergence that is driven by both slower forward mobility of the less developed regions and faster backward mobility of the more developed regions.
A clear pattern of regional divergence for the period 1988-2000. In contrast, the 2000-2014 period points to a much more complex pattern of di-convergence: the long-run equilibrium distribution is characterized by both a process of convergence arising from the top and a process of divergence near its bottom tail.
Cross-country productivity disparities rapidly increased in the 1980s, slowed down in the next decade, and stabilized in the mid-2000s. The upper tail the productivity distribution is more sensitive to improvements in human capital, while the lower tail is more sensitive to improvements in technology.
Differences in welfare-adjusted development are larger than those predicted by per-capita GDP. Differences in labor productivity account for most of the differences in both production and welfare-adjusted development. Inefficient production is the main factor holding down labor productivity.