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3 - Anti-growth syndromes in Africa: a synthesis of the case studies

Published online by Cambridge University Press:  09 January 2010

Benno J. Ndulu
Affiliation:
The World Bank
Stephen A. O'Connell
Affiliation:
Swarthmore College, Pennsylvania
Robert H. Bates
Affiliation:
Harvard University, Massachusetts
Paul Collier
Affiliation:
University of Oxford
Chukwuma C. Soludo
Affiliation:
Central Bank of Nigeria
Augustin Kwasi Fosu
Affiliation:
Deputy Director of the World Institute for Development Economics Research (WIDER) United Nations University in Helsinki
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Summary

Introduction: the anti-growth syndromes

As part of the Collaborative Research project conducted by the African Economic Research Consortium (AERC) on “Explaining African Economic Growth Performance” (the “Growth Project”), a number of anti-growth syndromes were identified by the project's editorial committee based on previously commissioned project case studies and other evidence. These classifications for practically all of SSA, involving forty-six countries, as well as for the sample of twenty-six country cases, over the period between country official independence from colonial rule and the year 2000, are presented in table 3.1. These are: State controls (SC), Adverse redistribution (AR), Intertemporally unsustainable spending (IUS), and State breakdown (SB); also presented is the complementary Syndrome-free (SF) category.

As the non-weighted row of table 3.1 indicates, the classification with the largest relative frequency is SC (34 percent), followed by SF (25 percent), then AR (22 percent), SB (10 percent), and IUS (9 percent). Considering the population-weighted frequencies (table 3.1), however, the ranking changes somewhat. The AR category is now first (32 percent), followed closely by SC (26 percent), then by SF (19 percent), IUS (13 percent), and SB (10 percent). Thus, larger countries tend to be relatively skewed toward AR and IUS, while SF is less prevalent in larger states and SB is invariant to country size.

The estimates for the twenty-six case countries, also reported in table 3.1, somewhat over-estimate the incidence of SC and IUS, and slightly under-estimate that of AR and SB, relative to the forty-six-country (non-weighted) sample.

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Publisher: Cambridge University Press
Print publication year: 2007

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