Is there an international β-convergence? A meta-regression analysis
Bahiani, Antoine
Promotor(s) : Walheer, Barnabé
Date of defense : 7-Sep-2020/11-Sep-2020 • Permalink : http://hdl.handle.net/2268.2/10560
Details
Title : | Is there an international β-convergence? A meta-regression analysis |
Translated title : | [fr] Y a-t-il une β-convergence international? Un analyse par méta-régression. |
Author : | Bahiani, Antoine |
Date of defense : | 7-Sep-2020/11-Sep-2020 |
Advisor(s) : | Walheer, Barnabé |
Committee's member(s) : | Tharakan, Joseph
Prettner, Klaus |
Language : | English |
Number of pages : | 56 |
Keywords : | [en] beta [en] convergence [en] growth [en] conditional [en] meta-regression [en] GDP per capita |
Discipline(s) : | Business & economic sciences > International economics |
Institution(s) : | Université de Liège, Liège, Belgique |
Degree: | Master en sciences économiques, orientation générale, à finalité spécialisée en macroeconomics and finance |
Faculty: | Master thesis of the HEC-Ecole de gestion de l'Université de Liège |
Abstract
[fr] Do poor countries grow faster than rich countries? In other words, does the gap of GDP per capita among countries decrease over time?
The purpose of this study is 1) to describe the empirical tools available to investigate the international convergence of product per capita, 2) to expose by a literature review the different findings on the subject, 3) to assess the pros and cons of the different empirical methods, 4) to investigate, by a meta-regression, the reasons of the multiple different findings in term of β-convergence, 5) to estimate the ‘true’ β-convergence speed.
Beta, sigma, gamma, total factor productivity, unit root, Markov chains, non-parametric analysis among others, these are possible methods to investigate the concept of international convergence of GDP per capita. The literature review shows that these different methods lead to different findings. Moreover, a single method applied by different authors can result in different findings. In front of this multitude of results, we are going to focus on the β-convergence.
Within the framework of a meta-regression realized with 116 different estimations of speed of β-convergence from 14 different authors, we found what was the cause of the differences in the findings. The statistical estimator used shows a great influence on the result: the use of an OLS estimator results in very small speed of convergence compared to a fixed-effect or a GMM estimator. The source of the data and the homogeneity of the countries included in each study also have a relevant impact on the result. In terms of conditional convergence, the choice of the conditioning variables is crucial since each of them influences differently the results. The time period under study has obviously an impact on the resulting speed of convergence.
The empirical results show that from an international point of view, there has been a conditional β-convergence of GDP per capita during the period 1960-2016. On the other-hand, the results do not provide any evidence for international absolute convergence. Therefore, the gap of GDP per capita between poor and rich countries is not vanishing.
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