IDEAS home Printed from https://ideas.repec.org/p/ags/aaea14/170646.html
   My bibliography  Save this paper

Climate Change and Crop Choice in Zambia: A Mathematical Programming Approach

Author

Listed:
  • Wineman, Ayala
  • Crawford, Eric W.

Abstract

While climate change is widely regarded as a threat to food security in southern Africa, few studies attempt to link the science of climate change impacts on agriculture with the specificities of smallholder livelihoods. In this paper, we build a series of linear programming (LP) farm-household models in Zambia in order to assess the impact of climate change on rural households and likely changes in land use and crop management. The LP models represent three household types (smallholders, emergent farmers, and female-headed households) in three agro-ecological zones with divergent cropping patterns and climate trends. Model parameters are drawn from several nationally representative rural household surveys, local meteorological records, and downscaled climate predictions of the Hadley (HadCM3) and CCSM models for the year 2050. The calorie-maximizing LP models are calibrated to best reflect baseline crop distributions at each site. Statistical analyses of crop yields over nine years reveal that crops in Zambia exhibit varying levels of sensitivity to climate shocks, and under climate change scenarios, the LP models indicate that farmers will shift their choices of technologies and crops. Among smallholder farms, calorie production from field crops changes by -13.56 to +5.13% under the Hadley predictions and -10.61 to +9.79% under the CCSM predictions. Although farm-households are expected to meet their consumption requirements even under climate change scenarios, the probability of falling below a minimum threshold of calorie production increases in two of our three study sites, and this is particularly true for smallholder farmers who face binding land constraints. Given the current choice set, autonomous on-farm adaptation generally will not be enough to offset the negative yield effects of climate change. Zambia therefore needs larger-scale institutional developments and agricultural research to provide farmers with additional adaptation options.

Suggested Citation

  • Wineman, Ayala & Crawford, Eric W., 2014. "Climate Change and Crop Choice in Zambia: A Mathematical Programming Approach," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170646, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea14:170646
    DOI: 10.22004/ag.econ.170646
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/170646/files/Wineman%20and%20Crawford%202014%20-%20Climate%20change%20and%20crop%20choice%20in%20Zambia.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.170646?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. B. Smit & I. Burton & R.J.T. Klein & R. Street, 1999. "The Science of Adaptation: A Framework for Assessment," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 4(3), pages 199-213, September.
    2. Hansen, James W. & Mishra, Ashok & Rao, K.P.C. & Indeje, Matayo & Ngugi, Robinson Kinuthia, 2009. "Potential value of GCM-based seasonal rainfall forecasts for maize management in semi-arid Kenya," Agricultural Systems, Elsevier, vol. 101(1-2), pages 80-90, June.
    3. Thornton, Philip K. & Jones, Peter G. & Alagarswamy, Gopal & Andresen, Jeff & Herrero, Mario, 2010. "Adapting to climate change: Agricultural system and household impacts in East Africa," Agricultural Systems, Elsevier, vol. 103(2), pages 73-82, February.
    4. Claudia Heidecke & Thomas Heckelei, 2010. "Impacts of changing water inflow distributions on irrigation and farm income along the Drâa River in Morocco," Agricultural Economics, International Association of Agricultural Economists, vol. 41(2), pages 135-149, March.
    5. Seo, S. Niggol & Mendelsohn, Robert, 2008. "An analysis of crop choice: Adapting to climate change in South American farms," Ecological Economics, Elsevier, vol. 67(1), pages 109-116, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Byman H. Hamududu & Hambulo Ngoma, 2020. "Impacts of climate change on water resources availability in Zambia: implications for irrigation development," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(4), pages 2817-2838, April.

    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. Wang, Teng & Yi, Fujin & Liu, Huilin & Wu, Ximing & Zhong, Funing, 2021. "Can Agricultural Mechanization Have a Mitigation Effect on China's Yield Variability?," 2021 Conference, August 17-31, 2021, Virtual 315098, International Association of Agricultural Economists.
    2. Heleene Tambet & Yaniv Stopnitzky, 2021. "Climate Adaptation and Conservation Agriculture among Peruvian Farmers," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 900-922, May.
    3. Claudia Schwirplies & Andreas Ziegler, 2017. "Adaptation of future travel habits to climate change," Tourism Economics, , vol. 23(6), pages 1275-1295, September.
    4. Abdoul G. Sam & Babatunde O. Abidoye & Sihle Mashaba, 2021. "Climate change and household welfare in sub-Saharan Africa: empirical evidence from Swaziland," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(2), pages 439-455, April.
    5. Giuseppe Maggio & Marina Mastrorillo & Nicholas J. Sitko, 2022. "Adapting to High Temperatures: Effect of Farm Practices and Their Adoption Duration on Total Value of Crop Production in Uganda," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(1), pages 385-403, January.
    6. Tesfaye, Wondimagegn & Tirivayi, Nyasha, 2020. "Crop diversity, household welfare and consumption smoothing under risk: Evidence from rural Uganda," World Development, Elsevier, vol. 125(C).
    7. Maeda, Eduardo Eiji & Clark, Barnaby J.F. & Pellikka, Petri & Siljander, Mika, 2010. "Modelling agricultural expansion in Kenya's Eastern Arc Mountains biodiversity hotspot," Agricultural Systems, Elsevier, vol. 103(9), pages 609-620, November.
    8. Ji, Xinde & Cobourn, Kelly M. & Weng, Weizhe, 2018. "The Effect of Climate Change on Irrigated Agriculture: Water-Temperature Interactions and Adaptation in the Western U.S," 2018 Annual Meeting, August 5-7, Washington, D.C. 274306, Agricultural and Applied Economics Association.
    9. Yonas Alem & Mintewab Bezabih & Menale Kassie & Precious Zikhali, 2010. "Does fertilizer use respond to rainfall variability? Panel data evidence from Ethiopia," Agricultural Economics, International Association of Agricultural Economists, vol. 41(2), pages 165-175, March.
    10. Seo, Niggol & Mendelsohn, Robert & Dinar, Ariel & Kurukulasuriya, Pradeep & Hassan, Rashid, 2008. "Long-term adaptation : selecting farm types across agro-ecological zones in Africa," Policy Research Working Paper Series 4602, The World Bank.
    11. Azam Lashkari & Amin Alizadeh & Ehsan Rezaei & Mohammad Bannayan, 2012. "Mitigation of climate change impacts on maize productivity in northeast of Iran: a simulation study," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 17(1), pages 1-16, January.
    12. Singh, Amarendra Pratap & Narayanan, Krishnan, 2016. "How can weather affect crop area diversity? Panel data evidence from Andhra Pradesh, a rice growing state of India," Studies in Agricultural Economics, Research Institute for Agricultural Economics, vol. 118(2), pages 1-10, August.
    13. Pires, Marcel Viana & Cunha, Dênis Antônio da, 2014. "Climate Change and Adaptive Strategies in Brazil: the economic effects of genetic breeding," Revista de Economia e Sociologia Rural (RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 52(4), January.
    14. Shimpei Iwasaki & Bam Razafindrabe & Rajib Shaw, 2009. "Fishery livelihoods and adaptation to climate change: a case study of Chilika lagoon, India," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 14(4), pages 339-355, April.
    15. Iqbal, Md. Hafiz & Aziz, Ahsan, 2022. "Crop selection as climate change adaptation: A study on Koyra Upazila of Bangladesh," Ecological Economics, Elsevier, vol. 199(C).
    16. Catarina Roseta‐Palma & Yiğit Sağlam, 2019. "Downside risk in reservoir management," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(2), pages 328-353, April.
    17. Phemelo Tamasiga & Helen Onyeaka & Adenike Akinsemolu & Malebogo Bakwena, 2023. "The Inter-Relationship between Climate Change, Inequality, Poverty and Food Security in Africa: A Bibliometric Review and Content Analysis Approach," Sustainability, MDPI, vol. 15(7), pages 1-35, March.
    18. Lovo, Stefania & Veronesi, Marcella, 2019. "Crop Diversification and Child Health: Empirical Evidence From Tanzania," Ecological Economics, Elsevier, vol. 158(C), pages 168-179.
    19. Coronese, Matteo & Occelli, Martina & Lamperti, Francesco & Roventini, Andrea, 2023. "AgriLOVE: Agriculture, land-use and technical change in an evolutionary, agent-based model," Ecological Economics, Elsevier, vol. 208(C).
    20. Severen, Christopher & Costello, Christopher & Deschênes, Olivier, 2018. "A Forward-Looking Ricardian Approach: Do land markets capitalize climate change forecasts?," Journal of Environmental Economics and Management, Elsevier, vol. 89(C), pages 235-254.

    More about this item

    Keywords

    Consumer/Household Economics; Food Security and Poverty; International Development;
    All these keywords.

    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:ags:aaea14:170646. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.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.