Real Convergence in the WAEMU Area: A Bayesian Analysis

Chapter
Part of the Insight and Innovation in International Development book series (IIID, volume 4)

Abstract

The objective of this study is to understand the process of development of Union countries by analysing real convergence. To reach this goal, it analyses absolute and conditional convergence on one hand and sigma convergence on the other. The data used comes from several sources: the World Bank, Penn World Tables, the ADB and the BCEAO.

In analyzing absolute and conditional convergence, the study uses the Bayesian estimation method to determine the speed of (absolute and conditional) convergence for each country. This study chose not to use the stacked method because it does not enable one to obtain the speed of convergence for each country. This latter method determines a single speed for all the countries. Analysis of sigma convergence is done using a graph. The idea is to represent and analyse the per capita GDP variance ratio. This ratio is the relation between per capita GDP variance at year t and at year 1994. The year 1994 was chosen because it is the year the Union was founded. The results of the study show that there is weak absolute convergence within the Union and that the educational policies, just as the openness policies, could accelerate growth and convergence in these countries.

The study also notes the presence of sigma convergence for the periods 1980–1994 and 2000–2008. Note that the first period is a “before-integration” period and the second an “after-integration” period. For the latter, one can say that the countries are in the process of economic integration. The absence of sigma convergence during the 1994–2000 period does not in any way bring into question the positive impact of integration on sigma convergence. In effect, it is possible that a policy does not produce immediate effects. Generally, there is a time-lag between when a policy is put into place and when the effects of the policy can be felt. That could be the case in this study. Countries often take time to adapt to the new rules and measures, and as a result, the date the treaty comes into effect does not coincide with the practical application of its measures.

The heterogeneity of data sources is a limitation of this study. In addition, there was no data for Guinea-Bissau for the entire study period and was therefore excluded from the analysis of absolute and conditional convergence. Other equally important variables were not integrated into the analysis. These are variables that measure the quality of institutions such as democracy, good governance, property rights protection, etc. Future research could take these aspects into account.

Keywords

Migration Europe Income Shrinkage Coherence 

References

  1. Anna, Tikhonenko (2003), Une étude de convergence appliquée au panel des pays de l’UE et des pays de l’Europe de l’Est candidats à l’adhésion. Université de Nice Sophia-Antipolis ATER CEMAFIGoogle Scholar
  2. Barnier, Michel (2001), Deuxième rapport sur la cohésion économique et sociale.Google Scholar
  3. Barro, R. J. (1991),‘Economic growth in a cross-section of countries’, Quarterly Journal of Economics, vol. 106, 2: 407–443. CrossRefGoogle Scholar
  4. Barro, R.J. and X. Sala-I-Martin (1990), ‘Economic Growth and convergence across the United States’, Working Papers, no. 3419, National Bureau of Economic Research, may Google Scholar
  5. Barro, R.J. and X. Sala-I-Martin (1991), ‘Convergence across states and regions’ Brooking Papers on Economic Activity no. 1:107–182 Google Scholar
  6. Bensidoun, Isabelle and Laurence Boone (1998) L’économie mondiale. P. 94–103. Edition La Découverte, collection Repère, Paris.Google Scholar
  7. Coulombe, Serge (1997), ‘Les disparités régionales au Canada: diagnostics, tendances et leçons pour la politique économique’, Document de travail no. 18, Université d’Ottawa. Google Scholar
  8. Ekomie, Jean Jacques (1999), ‘La Convergence des économies d’Afrique Centrale’, Revue d’Economie LEA Volume 1 Numéro 2. Google Scholar
  9. Gaulier, G. and Frédéric Carluer (2001), ‘Productivité des régions françaises pour moyenne période : Une convergence de façade’, Revue économique. Volume 52, Numéro 1 janvier 2001:147–166. Google Scholar
  10. Li H., G.S. Maddala and R.P. Trost (1996), ‘Estimation des élasticités de court et de long termes de la demande d’électricité sur données de panel à partir d’estimateurs à rétrécissement’, Economie et Prévision, no. 126(5) :127–137. CrossRefGoogle Scholar
  11. Mosse, Philippe (2000), ‘Les théories de la convergence appliquées à l’analyse économique des réformes des systèmes hospitaliers’, Communication présentée au Congrès 2000 de l’Association française de Science Economique.Google Scholar
  12. Ouedraogo, Tambila (1999), ‘La convergence des politiques macroéconomiques au sein de la zone UEMOA’. Mémoire, UFR/SEG, Université de OuagadougouGoogle Scholar
  13. Rodriguez, Francisco, and Dani Rodrik (1999), Trade Policy and Economic Growth: A Skeptic’s Guide to cross-National Literature,’ NBER Working Paper 7081Google Scholar
  14. Simoes, Marta Cristina (2000), La convergence réelle Selon la Théorie de la Convergence : Quelles explications pour l’Union Européenne ? Estudo Do Gemf (2) : 1–38Google Scholar
  15. UNPD (2002), Rapport mondial sur le développement humain 2002. Paris, De Boeck et LarcierGoogle Scholar
  16. WAEMU (2003), Document-cadre d’orientations générales de la politique d’aménagement du territoire.Google Scholar
  17. Willoughby, Christopher (2003), Infrastructure and Pro-Poor Growth: Implications of Recent Research, United Kingdom Department for International Development.Google Scholar
  18. Yerbanga, Antoine (2004), ‘La convergence réelle des économies de l’UEMOA’, Mémoire de DEA/PTCI. Université de Ouagadougou.Google Scholar

Copyright information

© International Development Research Centre 2012

Authors and Affiliations

  1. 1.UFR/SEG (Research and Training Centre in Economics and Management) at the University of Ouagadougou IIOuagadougouBurkina Faso

Personalised recommendations