Weather extremes and household welfare in rural Kenya
- 411 Downloads
Households in rural Kenya are sensitive to weather shocks through their reliance on rain-fed agriculture and livestock. Yet the extent of vulnerability is poorly understood, particularly in reference to extreme weather. This paper uses temporally and spatially disaggregated weather data and three waves of household panel survey data to understand the impact of weather extremes –including periods of high and low rainfall, heat, and wind– on household welfare. Particular attention is paid to heterogeneous effects across agro-ecological regions. We find that all types of extreme weather affect household well-being, although effects sometimes differ for income and calorie estimates. Periods of drought are the most consistently negative weather shock across various regions. An examination of the channels through which weather affects welfare reveals that drought conditions reduce income from both on- and off-farm sources, though households compensate for diminished on-farm production with food purchases. The paper further explores the household and community characteristics that mitigate the adverse effects of drought. In particular, access to credit and a more diverse income base seem to render a household more resilient.
KeywordsFood security Household welfare Kenya Resilience Weather shocks
The authors gratefully acknowledge financial support from USAID/Kenya for funding this study through the Tegemeo Agricultural Policy Research and Analysis (TAPRA) Project. They also wish to thank Jordan Chamberlin and Jenni Gronseth for their assistance. The views expressed in this study are those of the authors only.
Compliance with ethical standards
Conflicts of interest
The authors certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.
- Argwings-Kodhek, G., Jayne, T. S., Nyambane, G., Awuor, T., & Yamano, T. (1998). How can micro-level household information make a difference for agricultural policy making? Selected examples from the KAMPAP survey of smallholder agriculture and non-farm activities for selected districts in Kenya. Nairobi: Tegemeo Institute of Agricultural Policy and Development. Available at http://tegemeo.org/images/downloads/publications/technical_reports/TR26.pdf. Cited 12 April 2016.
- Baez, J., de la Fuente, A., & Santos, I. (2010). Do natural disasters affect human capital? An assessment based on existing empirical evidence. Discussion paper no. 5164. Bonn: Institute for the Study of Labor (IZA).Google Scholar
- Béné, C., Wood, R. G., Newsham, A., & Davies, M. (2012). Resilience: new utopia or new tyranny? Reflection about the potentials and limits of the concept of resilience in relation to vulnerability reduction programmes. Working paper no. 405. Brighton: Institute for Development Studies.Google Scholar
- Burgess, R., Deschenes, O., Donaldson, D., & Greenstone, M. (2011). Weather and death in India. Cambridge: Massachusetts Institute of Technology, Department of Economics. Mimeo.Google Scholar
- Cissé, J. D., & Barrett, C. B. (2016). Estimating development resilience: A conditional moments-based approach. Paper presented at the Centre for the Study of African Economies conference, 20–22 March, Oxford.Google Scholar
- Constas, M., Frankenberger, T., & Hoddinott, J. (2014). Resilience measurement principles. Food security information network technical series 1. Rome: Food and Agricultural Organization and World Food Programme.Google Scholar
- Cooper, P., Dimes, J., Rao, K., Shapiro, B., Shiferaw, B., & Twomlow, S. (2008). Coping better with current climatic variability in the rain-fed farming systems of sub-Saharan Africa: an essential first step in adapting to future climate change? Agriculture, Ecosystems, and Environment, 126(1–2), 24–35.CrossRefGoogle Scholar
- Dell, M., Jones, B. F., & Olken, B. A. (2012). Temperature shocks and economic growth: evidence from the last half century. American Economic Journal: Macroeconomics, 4(3), 66–95.Google Scholar
- Famine Early Warning Network (FEWSNET) (2011). Livelihoods zoning “plus” activity in Kenya. Available at http://www.fews.net/sites/default/files/documents/reports/KE_livelihood_profiles.pdf. Cited 12 April 2016.
- Food and Agricultural Organization of the United Nations (FAO) (2015). Crop calendar. Available at http://www.fao.org/agriculture/seed/cropcalendar. Cited 12 April 2016.
- 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, doi: 10.3133/ds832.
- Guerrero Compeán, R. (2013). Weather and welfare: health and agricultural impacts of climate extremes, evidence from Mexico. Working paper no. 391. Washington, D. C: Inter-American Development Bank.Google Scholar
- HarvestChoice (2015). Tropical Livestock Units. Available at http://harvestchoice.org/maps/total-livestock-population-tlu-2005. Cited 12 April 2016.
- Herrero, M., Ringler, C., van de Steeg, J., Thornton, P., Zuo, T., Bryan, E., Omolo, A., Koo, J., & Notenbaert, A. (2010). Climate variability and climate change and their impacts on Kenya’s agricultural sector. Nairobi: International Livestock Research Institute.Google Scholar
- Hirvonen, K. (2016). Temperature shocks, household consumption and internal migration: evidence from rural Tanzania. American Journal of Agricultural Economics, 98(4), 1230–1249.Google Scholar
- Hoddinott, J. (2014). Understanding resilience for food and nutrition security. 2020 resilience conference paper no. 8. Building resilience for food and nutrition security. Washington, D. C: International Food Policy Research Institute.Google Scholar
- Intergovernmental Panel on Climate Change (IPCC). (2014). Climate change 2014: impacts, adaptation, and vulnerability. Part a: global and sectoral aspects. Contribution of working group II to the fifth assessment report of the intergovernmental panel on climate. Cambridge: Cambridge University Press.Google Scholar
- Lukmanji, Z., Hertzmark, E., Mlingi, N., Assey, V., Ndossi, G., & Fawzi, W. (2008). Tanzania food composition tables. Dar es Salaam: Muhimbili University of Health and Allied Sciences, Tanzania Food and Nutrition Centre, and Harvard School of Public Health.Google Scholar
- National Oceanic and Atmospheric Administration (NOAA) (2015). National Weather Service Glossary. Available at http://w1.weather.gov/glossary/. Cited 12 April 2016.
- Republic of Kenya. (2007). Basic report on well-being in Kenya. Nairobi: Kenya National Bureau of Statistics.Google Scholar
- United States Department of Agriculture (USDA) (2011). National Nutrient Database for Standard Reference. Available at http://ndb.nal.usda.gov/. Cited 10 August 2015.
- Wooldridge, J. M. (2010). Econometric analysis of cross section and panel data (2nd ed.). Cambridge: MIT Press.Google Scholar