Climate shocks, vulnerability, resilience and livelihoods in rural Zambia

References

• Ahmed, S. A., Diffenbaugh, N. S., & Hertel, T. W. (2009). Climate volatility deepens poverty vulnerability in developing countries. Environmental Research Letters, 4(3), Article 0034004. https://doi.org/10.1088/1748-9326/4/3/034004
   PubMed Web of Science ®Google Scholar
• Alem, Y., Eggert, H., & Ruhinduka, R. (2015). Improving welfare through climate-friendly agriculture: The case of the system of rice intensification. Environmental and Resource Economics, 62(2), 243–263. https://doi.org/10.1007/s10640-015-9962-5
   Web of Science ®Google Scholar
• Alfani, F., Arslan, A., McCarthy, N., Cavatassi, R., & Sitko, N. (2019). Climate-change vulnerability in rural Zambia: the impact of an El Niño-induced shock on income and productivity, available at http://www.fao.org/3/CA3255EN/ca3255en.pdf
   Google Scholar
• Al Mamun, A., Chapoto, A., Chisanga, B., D’Alessandro, S., Koo, J., Martin, W., & Samboko, P. (2018). Assessment of the Impacts of El Niño and Grain Trade Policy Responses in East and Southern Africa to the 2015–16 Event, available at http://www.ifpri.org/publication/assessment-el-ni%C3%B1o-impacts-and-grain-trade-policy-responses-east-and-southern-africa
   Google Scholar
• Angelsen, A., & Dokken, T. (2018). Climate exposure, vulnerability and environmental reliance: A cross-section analysis of structural and stochastic poverty. Environment and Development Economics, 23(3), 257–278. https://doi.org/10.1017/S1355770X18000013
   Web of Science ®Google Scholar
• Azzarri, C., & Signorelli, S. (2020). Climate and poverty in Africa south of the sahara. World Development, 125, Article 104691. doi:https://doi.org/10.1016/j.worlddev.2019.104691
   Web of Science ®Google Scholar
• Barrett, C. B., & Carter, M. R. (2013). The economics of poverty traps and persistent poverty: Empirical and policy implications. Journal of Development Studies, 49(7), 976–990. https://doi.org/10.1080/00220388.2013.785527
   Web of Science ®Google Scholar
• Barrett, C. B., & Constas, M. A. (2014). Toward a theory of resilience for international development applications. Proceedings of the National Academy of Sciences, 111(40), 14625–14630. https://doi.org/10.1073/pnas.1320880111
   PubMed Web of Science ®Google Scholar
• Bonilla-Findji, O., Ortega, A., Ouedraogo, M., Fall, M., Chabi, A., Andrieu, N., Eitzinger, A., Zougmoré, R., & Läderach, P. (2020). How are smallholder farmers coping with and adapting to climate-related shocks in Kaffrine Climate-Smart Village, Senegal? https://cgspace.cgiar.org/handle/10568/111561
   Google Scholar
• Braimoh, A., Mwanakasale, A., Chapoto, A., Rubaiza, R., Chisanga, B., Mubanga, N., Samboko, P., Giertz, A., & Obuya, G. (2018). Increasing agricultural resilience through better risk management in Zambia available at http://documents.worldbank.org/curated/en/330211524725320524/Increasing-agricultural-resilience-through-better-risk-management-in-Zambia
   Google Scholar
• Chapoto, A., Banda, D. J., Haggblade, S., & Hamukwala, P. (2011). Factors Affecting Poverty Dynamics in Rural Zambia, available https://ageconsearch.umn.edu/record/109888/
   Google Scholar
• Corbeels, M., Naudin, K., Whitbread, A. M., Kühne, R., & Letourmy, P. (2020). Limits of conservation agriculture to overcome low crop yields in sub-saharan Africa. Nature Food, 1(7), 447–454. https://doi.org/10.1038/s43016-020-0114-x
   Google Scholar
• CSO. (2015). Living conditions monitoring survey Key findings. Central Statistics Office.
   Google Scholar
• CSO/MAL/IAPRI. (2012). Rural agricultural livelihoods survey Lusaka.
   Google Scholar
• CSO/MAL/IAPRI. (2015). Rural Agricultural Livelihoods Survey, available at www.iapri.org.zm/surveys
   Google Scholar
• Diwakar, V., Subakanya, M., Lubungu, M., Chapoto, A., 2020. Rural poverty dynamics in Zambia: 2012-2019. Overseas development institute (ODI). London.
   Google Scholar
• FAO. (2011). Women in agriculture: Closing the gender gap for development, The State of Food and Agriculture 2010-11. Rome, Italy: Food and Agriculture Organization (FAO).
   Google Scholar
• Funk, C. C., Peterson, P. J., Landsfeld, M. F., Pedreros, D. H., Verdin, J. P., Rowland, J. D., Romero, B. E., Husak, G. J., Michaelsen, J. C., & Verdin, A. P. (2014). A quasi-global precipitation time series for drought monitoring: U.S. Geological Survey Data Series 832, 4p. https://pubs.usgs.gov/ds/832/
   Google Scholar
• Hamududu, B. H., & Ngoma, H. (2019). Impacts of climate change on water resources availability in Zambia: Implications for irrigation development, environment. Development and Sustainability, 1–22. https://doi.org/10.1007/s10668-019-00320-9.
   Web of Science ®Google Scholar
• Jain, S. (2007). An empirical economic assessment of impacts of climate change on agriculture in Zambia. World Bank Policy Research Working Paper.
   Google Scholar
• Karfakis, P., Lipper, L., & Smulders, M. (2012). The assessment of the socioeconomic impacts of climate change at household level and policy implications, building resilience for adaptation to climate change in the agriculture sector. Food and agriculture organization of the united nations (FAO).
   Google Scholar
• Matata, M. J., Ngigi, M. W., & Bett, H. K. (2023). Effects of cash transfers on household resilience to climate shocks in the arid and semi arid counties of northern Kenya. Development Studies Research, 10(1), https://doi.org/10.1080/21665095.2022.2164031
   Google Scholar
• Michler, J. D., Baylis, K., Arends-Kuenning, M., & Mazvimavi, K. (2019). Conservation agriculture and climate resilience. Journal of Environmental Economics and Management, 93, 148–169. doi:https://doi.org/10.1016/j.jeem.2018.11.008
   PubMed Web of Science ®Google Scholar
• Mulenga, B. P., Richardson, R. B., Tembo, G., & Mapemba, L. (2014). Rural household participation in markets for non-timber forest products in Zambia. Environment and Development Economics, 19(4), 487–504. https://doi.org/10.1017/S1355770X13000569
   Web of Science ®Google Scholar
• Mulenga, B. P., Wineman, A., & Sitko, N. J. (2017). Climate trends and farmers’ perceptions of climate change in Zambia. Environmental Management, 59(2), 291–306. https://doi.org/10.1007/s00267-016-0780-5
   PubMed Web of Science ®Google Scholar
• Mwongera, C., Shikuku, K. M., Twyman, J., Läderach, P., Ampaire, E., Van Asten, P., Twomlow, S., & Winowiecki, L. A. (2017). Climate smart agriculture rapid appraisal (CSA-RA): A tool for prioritizing context-specific climate smart agriculture technologies. Agricultural Systems, 151, 192–203. https://doi.org/10.1016/j.agsy.2016.05.009
   Web of Science ®Google Scholar
• Ngoma, H., Lupiya, P., Kabisa, M., & Hartley, F. (2021). Impacts of climate change on agriculture and household welfare in Zambia: An economy-wide analysis. Climatic Change, 167(3), 55. https://doi.org/10.1007/s10584-021-03168-z
   Web of Science ®Google Scholar
• Ngoma, H., Mason, M. N, Sitko, N. J. 2015. Does minimum tillage with planting basins or ripping raise maize yields? Meso-panel data evidence from Zambia. Agriculture, Ecosystems & Environment, 212: 21–29. https://doi.org/10.1016/j.agee.2015.06.021
   Web of Science ®Google Scholar
• Ngoma, H., Mulenga, B. P., & Jayne, T. S. (2016). Minimum tillage uptake and uptake intensity by smallholder farmers in Zambia. African Journal of Agricultural and Resource Economics, 11, 249–262.
   Google Scholar
• Ngoma, H., Mulenga, P. M., Snyder, J., Banda, A., & Chapoto, A. (2019). Poverty and weather shocks: a panel data analysis of structural and stochastic poverty in Zambia available at http://www.iapri.org.zm/images/WorkingPapers/wp150_for_pdf_poverty_final.pdf
   Google Scholar
• Patel, N., Chopra, P., & Dadhwal, V. (2007). Analyzing spatial patterns of meteorological drought using standardized precipitation index. Meteorological Applications, 14, 329–336.
   Web of Science ®Google Scholar
• Petrie, M. D., Peters, D. P., Yao, J., Blair, J. M., Burruss, N. D., Collins, S. L., Derner, J. D., Gherardi, L. A., Hendrickson, J. R., Sala, O. E., & Starks, P. J. (2018). Regional grassland productivity responses to precipitation during multiyear above- and below-average rainfall periods. Global Change Biology, 24(5), 1935–1951. https://doi.org/10.1111/gcb.14024
   PubMed Web of Science ®Google Scholar
• Rahut, D. B., Aryal, J. P., & Marenya, P. (2021). Understanding climate-risk coping strategies among farm households: Evidence from five countries in eastern and Southern Africa. Science of the Total Environment, 769. https://doi.org/10.1016/j.scitotenv.2021.145236
   PubMed Web of Science ®Google Scholar
• Sesmero, J., Ricker-Gilbert, J., & Cook, A. (2018). How Do African farm households respond to changes in current and past weather patterns? A structural panel data analysis from Malawi. American Journal of Agricultural Economics, 100(1), 115–144. https://doi.org/10.1093/ajae/aax068
   Web of Science ®Google Scholar
• Skoufias, E., & Vinha, K. (2012). Climate variability and child height in rural Mexico. Economics & Human Biology, 10(1), 54–73. https://doi.org/10.1016/j.ehb.2011.06.001
   PubMed Web of Science ®Google Scholar
• Thierfelder, C., Chivenge, P., Mupangwa, W., Rosenstock, T. S., Lamanna, C., & Eyre, J. X. (2017). How climate-smart is conservation agriculture (CA)? – its potential to deliver on adaptation, mitigation and productivity on smallholder farms in Southern Africa. Food Security, 9(3), 537–560. https://doi.org/10.1007/s12571-017-0665-3
   Web of Science ®Google Scholar
• Thurlow, J., Zhu, T., & Diao, X. (2012). Current climate variability and future climate change: Estimated growth and poverty impacts for Zambia. Review of Development Economics, 16(3), 394–411. https://doi.org/10.1111/j.1467-9361.2012.00670.x
   Web of Science ®Google Scholar
• Umar, B. B. (2021). Adapting to climate change through conservation agriculture: A gendered analysis of eastern Zambia. Frontiers in Sustainable Food Systems, 5. https://doi.org/10.3389/fsufs.2021.748300
   Google Scholar
• Wineman, A., & Crawford, E. W. (2017). Climate change and crop choice in Zambia: A mathematical programming approach. NJAS: Wageningen Journal of Life Sciences, 81(1), 19–31. https://doi.org/10.1016/j.njas.2017.02.002
   Web of Science ®Google Scholar
• Wooldridge, J. M. (2010). Econometric analysis of cross section and panel data (2nd ed.). MIT Press.
   Google Scholar
• World Bank. (2018). Zambia climate-smart agriculture investment plan. Analyses to Support the Climate-Smart Development of Zambia’s Agriculture Sector. © World Bank, Washington, DC. http://hdl.handle.net/10986/31383 License: CC BY 3.0 IGO.” URI http://hdl.handle.net/10986/31383.
   Google Scholar