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Is Regional Integration Beneficial for Agricultural Productivity in Sub-Saharan Africa? The Case of CEMAC and WAEMU

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Part of the Advances in African Economic, Social and Political Development book series (AAESPD)

Abstract

This paper examines the effects of regional euro-currency integration on agricultural productivity in Sub-Saharan Africa. We utilize a propensity score matching estimator to estimate the treatment effect of Sub-Saharan African countries joining regional euro-currency integration on agricultural value-added. Our parameter estimates reveal that regional euro-currency integration membership has positive effects on agricultural value-added. This suggests that as an institutional arrangement, regional currency union membership can improve agricultural productivity in Sub-Saharan Africa, which is an important component of achieving economic growth that is effective in reducing poverty.

JEL Classification

F15 L25 H32 O55 

Keywords

Currency integration Sub-Saharan Africa Agriculture value-added 

References

  1. Abadie A, Drukker D, Herr JL, Imbens GW (2001) Implementing matching estimators for average treatment effects in Stata. Stata J 1:1–18Google Scholar
  2. African Development Report (2014) Excecutive summary on “Regional integration and inclusive growth”. pp 1–6Google Scholar
  3. Alston JM, Pardey PG (2014) Agriculture in the global economy. J Econ Perspect 28:121–146CrossRefGoogle Scholar
  4. Augurzky B, Kluve J (2007) Assessing the performance of matching estimates when selection into treatment is strong. J Appl Econ 22:533–557CrossRefGoogle Scholar
  5. Christiaensen L, Demery L, Kuhl J (2011) The (evolving) role of agriculture in poverty reduction—an empirical perspective. J Dev Econ 96:239–254CrossRefGoogle Scholar
  6. Collier P, Dercon S (2014) African agriculture in 50 years: smallholders in a rapidly changing world? World Dev 63:92–101CrossRefGoogle Scholar
  7. Dethier J-J, Effenberger A (2012) Agriculture and development: a brief review of the literature. Econ Syst 36:175–205CrossRefGoogle Scholar
  8. Diao X, Hazell P, Thurlow J (2010) The role of agriculture in African development. World Dev 38:1375–1383CrossRefGoogle Scholar
  9. Djurfeldt AA (2013) African re-agrarianization? accumulation or pro-poor agricultural growth? World Dev 41:217–231CrossRefGoogle Scholar
  10. Dorward A, Kydd J, Morrison J, Urey I (2004) A policy agenda for pro-poor agricultural growth. World Dev 32:73–89CrossRefGoogle Scholar
  11. Elu JU, Price GN (2008) The impact of the Euro-CFA Franc zone on economic growth in Sub-Saharan Africa. In: Globalisation, institutions, and African economic development: Proceedings of the African Economic Conference 2008. Economica Publishers, Paris, pp 255–272Google Scholar
  12. Elu JU, Price GN (2014) Terrorism and regional integration in Sub-Saharan Africa: the case of the CFA Franc zone. In: Seck D (ed) Regional economic integration in West Africa. Springer, Cham, pp 253–267CrossRefGoogle Scholar
  13. Holland PW (1986) Statistics and causal inference. J Am Stat Assoc 81:945–970CrossRefGoogle Scholar
  14. Imbens G (2004) Nonparametric estimation of average treatment effects under exogeneity: a review. Rev Econ Stat 86:4–29CrossRefGoogle Scholar
  15. Imbens GW, Rubin DB (2010) Rubin causal model. In: Durlaur SN, Blume LE (eds) Microeconometrics. Macmillan, London, UK, pp 229–241CrossRefGoogle Scholar
  16. Kydd J, Dorward A, Morrison J, Cadisch G (2004) Agricultural development and pro-poor economic growth in Sub-Saharan Africa: potential and policy. Oxf Dev Stud 32:37–57CrossRefGoogle Scholar
  17. Markus B (2012) Economic growth, size of the agricultural sector, and urbanization in Africa. J Urban Econ 71:26–36CrossRefGoogle Scholar
  18. Millard-Ball A (2012) Do city climate plans reduce emissions? J Urban Econ 71:289–311CrossRefGoogle Scholar
  19. Nielsen R, Sheffield J (2009) Matching with time-series cross-sectional data. In: Paper Presented at the 26th Annual Meeting of the Society for Political Methodology, July 23–25, Yale University, New Haven, CTGoogle Scholar
  20. Price GN, Spriggs W, Swinton O (2011) The relative returns to graduating from a historically Black College/University: propensity score matching estimates from the national survey of black Americans. Rev Black Polit Econ 38:103–130CrossRefGoogle Scholar
  21. Rajaonarison HM (2014) Food and human security in Sub-Saharan Africa. Proc Environ Sci 20:377–385CrossRefGoogle Scholar
  22. Rosenbaum PR, Rubin DB (1983) The central role of the propensity score in observational studies for causal effects. Biometrika 70:41–55CrossRefGoogle Scholar
  23. Todd PE (2010) Matching estimators. In: Durlauf S, Blume L (eds) Microeconometric. Palgrave Macmillan, Basingstoke, pp 101–121Google Scholar
  24. World Development Indicators (2013) The international bank for reconstruction and development. WDI, Washington, DCGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Department of EconomicsMorehouse CollegeAtlantaUSA

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