Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper addresses the issue of convergence of per-capita GDP of the 20 Italian regions. The paper first focuses on the notion of σ-convergence and proposes a new hierarchical clustering algorithm, grouping regions according to the presence of a monotonically decreasing trend in entropy. Then alternative definitions of long-run convergence are given, based on the notion of cointegration and common trends and the evidence arising from application of stationarity tests to the time series of regional contrasts is examined. The conclusion is that both kind of convergence can be used to characterize the dynamics of regional per-capita GDP.