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Does heterogeneity in goals and preferences affect efficiency? A case study of farm households in northern Nigeria

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  • Ezra D. Berkhout
  • Robert A. Schipper
  • Arie Kuyvenhoven
  • Ousmane Coulibaly

Abstract

Household characteristics are commonly used to explain variation in smallholder efficiency levels. The underlying assumption is that differences in intended behavior are well described by such variables, while there is no a priori reason that this is the case. Moreover, heterogeneity in farmer goals and preferences, in relation to the role of the farm enterprise, are not well documented in developing countries. This article makes a contribution to fill this gap, by empirically determining heterogeneity in farmer goals and attitudes in Nigeria through a pair‐wise ranking, supplemented with Likert scales. Factor analysis is used to reduce these data into behavioral factors. We estimate technical and allocative efficiency levels and analyze how these are related to farm characteristics and the identified behavioral factors. The models in which both intended behavior and farmer characteristics are included give a significantly better fit over models in which only household characteristics are included. These regression results suggest that the socioeconomic environment affects efficiency levels both directly and indirectly, through changes in goals and attitudes.

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  • Ezra D. Berkhout & Robert A. Schipper & Arie Kuyvenhoven & Ousmane Coulibaly, 2010. "Does heterogeneity in goals and preferences affect efficiency? A case study of farm households in northern Nigeria," Agricultural Economics, International Association of Agricultural Economists, vol. 41(3‐4), pages 265-273, May.
    • Handle: RePEc:bla:agecon:v:41:y:2010:i:3-4:p:265-273
    DOI: 10.1111/j.1574-0862.2010.00449.x
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    4. Pérez-Blanco, C. D & Standardi, G., 2019. "Farm waters run deep: a coupled positive multi-attribute utility programming and computable general equilibrium model to assess the economy-wide impacts of water buyback," Agricultural Water Management, Elsevier, vol. 213(C), pages 336-351.
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    7. Arora, Poonam & Bert, Federico & Podesta, Guillermo & Krantz, David H., 2015. "Ownership effect in the wild: Influence of land ownership on agribusiness goals and decisions in the Argentine Pampas," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 58(C), pages 162-170.
    8. Agnes Gold & Stefan Gold, 2019. "Drivers of Farm Efficiency and Their Potential for Development in a Changing Agricultural Setting in Kerala, India," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 31(4), pages 855-880, September.
    9. Robertson R.B. Khataza & Atakelty Hailu & Graeme J. Doole & Marit E. Kragt & Arega D. Alene, 2019. "Examining the relationship between farm size and productive efficiency: a Bayesian directional distance function approach," Agricultural Economics, International Association of Agricultural Economists, vol. 50(2), pages 237-246, March.
    10. Chiara Calabrese1 & Stefan Mann1 & Michel Dumondel, 2012. "Patterns of occupational choice in the Swiss alpine labor market," Journal of Socio-Economics in Agriculture (Until 2015: Yearbook of Socioeconomics in Agriculture), Swiss Society for Agricultural Economics and Rural Sociology, vol. 5(1), pages 31-54.
    11. Maria Marino & Benedetto Rocchi & Simone Severini, 2021. "Conditional Income Disparity between Farm and Non‐farm Households in the European Union: A Longitudinal Analysis," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(2), pages 589-606, June.
    12. Juan Wu & Wenjing Yu & Xiaobing Liu & Yali Wen, 2022. "Analysis of Influencing Factors and Income Effect of Heterogeneous Agricultural Households’ Forestland Transfer," Land, MDPI, vol. 11(9), pages 1-17, September.

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