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Investigating the Role of Poultry in Livelihoods and the Impact of HPAI on Livelihoods Outcomes in Africa: Evidence from Ethiopia, Ghana, Kenya and Nigeria

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  • Birol, Ekin
  • Asare-Marfo, Dorene
  • Ayele, Gezahegn
  • Mensah-Bonsu, Akwasi
  • Ndirangu, Lydia K.
  • Okpukpara, Benjamin
  • Roy, Devesh
  • Yakhshilikov, Yorbol

Abstract

In this paper we investigate the role of poultry in the livelihoods portfolios of households and the impact of supply and demand shocks that may be caused by Highly Pathogenic Avian Influenza (HPAI) on various livelihoods outcomes of households in four Sub-Saharan African (SSA) countries. The study countries include Ethiopia and Kenya in East Africa and Ghana and Nigeria in West Africa. These countries represent a spectrum of SSA countries in terms of disease status, role of poultry sector and means of disease spread. By using nationally representative household level secondary data and discrete choice methods (probit model and zero inflated negative binomial model) we profile the household, farm and regional characteristics of those households who are most likely to keep poultry, and those who are most likely to be engaged in intensive poultry production, i.e., keep larger household flocks. We estimate the impact of the disease outbreaks and scares/threats on livelihood outcomes by using matching methods (i.e., propensity score matching). The results of this study generate valuable information regarding the role of poultry in the livelihoods of small-scale poultry producing households and the livelihood impacts of HPAI induced demand and supply shocks. Such information is critical for the design of targeted and hence efficient and effective HPAI control and mitigation policies.

Suggested Citation

  • Birol, Ekin & Asare-Marfo, Dorene & Ayele, Gezahegn & Mensah-Bonsu, Akwasi & Ndirangu, Lydia K. & Okpukpara, Benjamin & Roy, Devesh & Yakhshilikov, Yorbol, 2010. "Investigating the Role of Poultry in Livelihoods and the Impact of HPAI on Livelihoods Outcomes in Africa: Evidence from Ethiopia, Ghana, Kenya and Nigeria," 2010 AAAE Third Conference/AEASA 48th Conference, September 19-23, 2010, Cape Town, South Africa 97084, African Association of Agricultural Economists (AAAE).
  • Handle: RePEc:ags:aaae10:97084
    DOI: 10.22004/ag.econ.97084
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    References listed on IDEAS

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    1. William H. Greene, 1997. "FIML Estimation of Sample Selection Models for Count Data," Working Papers 97-02, New York University, Leonard N. Stern School of Business, Department of Economics.
    2. Diao, Xinshen, 2009. "Economywide impact of avian flu in Ghana: A dynamic CGE model analysis," IFPRI discussion papers 866, International Food Policy Research Institute (IFPRI).
    3. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," Review of Economic Studies, Oxford University Press, vol. 65(2), pages 261-294.
    4. Grogger, J T & Carson, Richard T, 1991. "Models for Truncated Counts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(3), pages 225-238, July-Sept.
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    1. repec:zib:zjhcdc:v:1:y:2021:i:3:p:41-46 is not listed on IDEAS
    2. Oparinde, Adewale & Hodge, Ian, 2011. "Building livelihood resilience: a case study of factors affecting farm households’ adoption of coping and adaptive strategies in rural Nigeria," MPRA Paper 39162, University Library of Munich, Germany.
    3. Oparinde, Adewale & Birol, Ekin, 2011. "Farm households' preference for cash-based compensation versus livelihood-enhancing programs: A choice experiment to inform avian flu compensation policy in Nigeria," IFPRI discussion papers 1072, International Food Policy Research Institute (IFPRI).

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    Livestock Production/Industries;

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