Detecting Convergence Clubs

Fuat C. Beylunioglu (), Thanasis Stengos and Ege Yazgan ()
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Fuat C. Beylunioglu: Istanbul Bilgi University

No 1604, Working Papers from University of Guelph, Department of Economics and Finance

Abstract: The convergence hypothesis, which is developed in the context of growth economics, asserts that the income differences across countries are transitory, and developing countries will eventually attain the level of income of developed ones. On the other hand convergence clubs hypothesis claim that the convergence can only be realized across groups of countries that share some common characteristics. In this study, we propose a new method to find convergence clubs that combine pairwise method of testing convergence with maximal clique algorithm. Unlike many of those already developed in the literature, this new method aims to find convergence clubs endogenously without depending on priori classifications. In a Monte Carlo simulation study, the success of the method in finding convergence clubs, is compared with a similar algorithm. Simulation results indicated that the proposed method perform better than the compared algorithm in most cases. In addition to the Monte Carlo, a new empirical evidence on the existence of convergence clubs is presented in the context of real data applications

Keywords: Growth Economics; Convergence Hypothesis; Convergence Clubs; Maximal Clique Algorithm. (search for similar items in EconPapers)
JEL-codes: C32 O47 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2016
New Economics Papers: this item is included in nep-cmp
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Citations: View citations in EconPapers (7)

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Related works:
Journal Article: DETECTING CONVERGENCE CLUBS (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:gue:guelph:2016-04

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