IDEAS home Printed from https://ideas.repec.org/p/man/sespap/2109.html
   My bibliography  Save this paper

Are Farmers "Efficient but Poor"? The Impact of Crop Choices on Agricultural Productivity and Poverty in Nigeria

Author

Listed:
  • Chisom Ubabukoh
  • Katsushi S. Imai

Abstract

This paper aims to test the "efficient-but-poor" hypothesis by estimating the determinants of smallholders' crop choices and whether their crop choices affect productivity and poverty using the national household panel data in Nigeria. As crop choices are endogenous in the sense that the farmers' crop choice is also influenced by resulting revenue from the crop, we carry out stochastic frontier analyses with the Greene (2010) correction for sample selection about farmers' crop choices and find that smallholders are generally efficient in their resource allocations. However, they are not necessarily rational in making their crop choices - defined in terms of the degree of crop's exportability or commercialization. This is because, even when some crops are found to be more productive than others, the "less productive" crop is often chosen for production. To figure out why, a treatment effects model is employed to estimate farmers' selection into the choice of a type of crop in the first stage and the impact of their choices on productivity and poverty outcomes in the second. The results show that farmers' access to free inputs, non-farm income and the use of seeds from the previous growing season are important determinants of crop choice. The choice of tuber and root crops is found to improve productivity and reduce poverty, while choosing highly commercialised crops reduces poverty but does not improve productivity.

Suggested Citation

  • Chisom Ubabukoh & Katsushi S. Imai, 2021. "Are Farmers "Efficient but Poor"? The Impact of Crop Choices on Agricultural Productivity and Poverty in Nigeria," Economics Discussion Paper Series 2109, Economics, The University of Manchester.
    • Handle: RePEc:man:sespap:2109
    as

    Download full text from publisher

    File URL: http://hummedia.manchester.ac.uk/schools/soss/economics/discussionpapers/EDP-2109.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Edward Martey & Alexander N. Wiredu & Prince M. Etwire & John K.M. Kuwornu, 2019. "The impact of credit on the technical efficiency of maize-producing households in Northern Ghana," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 79(3), pages 304-322, May.
    2. Coelli, Tim J. & Battese, George E., 1996. "Identification Of Factors Which Influence The Technical Inefficiency Of Indian Farmers," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 40(2), pages 1-26, August.
    3. Rahman, Sanzidur, 2011. "Resource use efficiency under self-selectivity: the case of Bangladeshi rice producers," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 55(2), pages 1-18.
    4. Maertens, Miet & Swinnen, Johan F.M., 2009. "Trade, Standards, and Poverty: Evidence from Senegal," World Development, Elsevier, vol. 37(1), pages 161-178, January.
    5. Boris Bravo-Ureta & Daniel Solís & Víctor Moreira López & José Maripani & Abdourahmane Thiam & Teodoro Rivas, 2007. "Technical efficiency in farming: a meta-regression analysis," Journal of Productivity Analysis, Springer, vol. 27(1), pages 57-72, February.
    6. Murekezi, Abdoul Karim & Loveridge, Scott, 2009. "Have coffee reforms and coffee supply chains affected farmers' income? The case of coffee growers in Rwanda," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49597, Agricultural and Applied Economics Association.
    7. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    8. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    9. William Greene, 2010. "A stochastic frontier model with correction for sample selection," Journal of Productivity Analysis, Springer, vol. 34(1), pages 15-24, August.
    10. Loveridge, Scott & Nyarwaya, Jean Baptiste & Shingiro, Emmanuel, 2003. "Decaffeinated? Situation, Trends, and Prospects for Smallholder Coffee Production in Rwanda," Food Security Collaborative Policy Briefs 55354, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    11. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    12. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    13. Nan Jiang & Basil Sharp, 2015. "Technical efficiency and technological gap of New Zealand dairy farms: a stochastic meta-frontier model," Journal of Productivity Analysis, Springer, vol. 44(1), pages 39-49, August.
    14. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    15. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chisom Lotanna Ubabukoh & Katsushi S. Imai, 2023. "Are farmers ‘efficient but poor’? The impact of crop choices on technical efficiency and poverty in Nigeria," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(1), pages 191-213, February.
    2. Bravo-Ureta, Boris E. & Higgins, Daniel & Arslan, Aslihan, 2020. "Irrigation infrastructure and farm productivity in the Philippines: A stochastic Meta-Frontier analysis," World Development, Elsevier, vol. 135(C).
    3. Akamin, Ajapnwa & Bidogeza, Jean-Claude & Minkoua N, Jules René & Afari-Sefa, Victor, 2017. "Efficiency and productivity analysis of vegetable farming within root and tuber-based systems in the humid tropics of Cameroon," MPRA Paper 85329, University Library of Munich, Germany.
    4. Per J. Agrell & Mehdi Farsi & Massimo Filippini & Martin Koller, 2013. "Unobserved heterogeneous effects in the cost efficiency analysis of electricity distribution systems," Working Papers 0038, Swiss Economics.
    5. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    6. Quang Nguyen & Sean Pascoe & Louisa Coglan & Son Nghiem, 2021. "The sensitivity of efficiency scores to input and other choices in stochastic frontier analysis: an empirical investigation," Journal of Productivity Analysis, Springer, vol. 55(1), pages 31-40, February.
    7. Bravo-Ureta, Boris E. & Jara-Rojas, Roberto & Lachaud, Michee A. & Moreira L., Victor H. & Scheierling, Susanne M., 2015. "Water and Farm Efficiency: Insights from the Frontier Literature," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 206076, Agricultural and Applied Economics Association.
    8. Madau, Fabio A., 2012. "Technical and scale efficiency in the Italian Citrus Farming: A comparison between Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis(DEA) Models," MPRA Paper 41403, University Library of Munich, Germany.
    9. Alexander Bilson Darku & Stavroula Malla & Kien C. Tran, 2016. "Sources and Measurement of Agricultural Productivity and Efficiency in Canadian Provinces: Crops and Livestock," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(1), pages 49-70, March.
    10. Mehdi Farsi & Aurelio Fetz & Massimo Filippini, 2007. "Benchmarking and Regulation in the Electricity Distribution Sector," CEPE Working paper series 07-54, CEPE Center for Energy Policy and Economics, ETH Zurich.
    11. Moritz Flubacher & George Sheldon & Adrian Müller, 2015. "Comparison of the Economic Performance between Organic and Conventional Dairy Farms in the Swiss Mountain Region Using Matching and Stochastic Frontier Analysis," Journal of Socio-Economics in Agriculture (Until 2015: Yearbook of Socioeconomics in Agriculture), Swiss Society for Agricultural Economics and Rural Sociology, vol. 7(1), pages 76-84.
    12. I. Fraser & W. Horrace, 2003. "Technical Efficiency of Australian Wool Production: Point and Confidence Interval Estimates," Journal of Productivity Analysis, Springer, vol. 20(2), pages 169-190, September.
    13. Magambo, Isaiah & Dikgang, Johane & Gelo, Dambala & Tregenna, Fiona, 2021. "Environmental and Technical Efficiency in Large Gold Mines in Developing Countries," MPRA Paper 108068, University Library of Munich, Germany.
    14. Martin, Sheila Ann, 1992. "The effectiveness of state technology incentives: evidence from the machine tool industry," ISU General Staff Papers 1992010108000011381, Iowa State University, Department of Economics.
    15. Ali D. Cagdas & Scott R. Jeffrey & Elwin G. Smith & Peter C. Boxall, 2016. "Environmental Stewardship and Technical Efficiency in Canadian Prairie Canola Production," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(3), pages 455-477, September.
    16. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
    17. Sickles, Robin C. & Song, Wonho & Zelenyuk, Valentin, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," Working Papers 18-008, Rice University, Department of Economics.
    18. Radha R. Ashrit, 2023. "Estimation of technical efficiency of Indian farms for major crops during 2013–2014 and 2017–2018: a stochastic Frontier production approach," SN Business & Economics, Springer, vol. 3(2), pages 1-32, February.
    19. Massimo Del Gatto & Adriana Di Liberto & Carmelo Petraglia, 2011. "Measuring Productivity," Journal of Economic Surveys, Wiley Blackwell, vol. 25(5), pages 952-1008, December.
    20. Nelson Mango & Clifton Makate & Benjamin Hanyani-Mlambo & Shephard Siziba & Mark Lundy & Caroline Elliott, 2015. "A stochastic frontier analysis of technical efficiency in smallholder maize production in Zimbabwe: The post-fast-track land reform outlook," Cogent Economics & Finance, Taylor & Francis Journals, vol. 3(1), pages 1117189-111, December.

    More about this item

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • N57 - Economic History - - Agriculture, Natural Resources, Environment and Extractive Industries - - - Africa; Oceania
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:man:sespap:2109. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Marianne Sensier (email available below). General contact details of provider: https://edirc.repec.org/data/semanuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.