This paper uses the Market Information and Food Insecurity Response Analysis Framework to analyze data on food market intermediation and on consumer behavior and preferences in order to clarify whether market-based cash and voucher programs are likely to prove effective for addressing food insecurity in rural and urban study sites in Kenya. The findings carry important implications for food security interventions by government and operational agencies. We confirm that context matters when undertaking a response analysis. While we find that cash and/or vouchers are appropriate in both urban and rural locations, markets in surveyed urban settlements can respond better to a large injection of cash or vouchers than can surveyed rural areas. Moreover, household vulnerabilities are associated with household preferences in different ways across the two sites. In rural areas, female headed households and households reporting a physical limit to market access were among the groups that strongly preferred food aid to cash or vouchers while households with these characteristics in urban areas preferred the flexibility of cash or vouchers to food.
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2009 Population and Housing Census, Kenya National Bureau of Statistics (2010a)
Further details about the design and implementation of the CRS voucher programs are available upon request from the authors.
The FAO’s State of Food Insecurity in the World (2009) defines food security as when “all people, at all times, have physical, social and economic access to sufficient, safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life” (p. 8).
2009 Population and Housing Census, Kenya
All households reporting that they did not use credit in the past two weeks for food indicated that credit would be extremely difficult to get. It is not necessarily the case therefore, that households not using credit in the sample are better off financially.
Staple crops included in the survey were maize, millet, sorghum, beans, and pulses (cowpeas, pigeon peas, dolichos, and green grams).
In contrast to Mathare, the marginal propensity to consume a cash transfer as food in Makueni may exhibit seasonal variation. A household’s staple harvest meets their staple consumption needs for between three and five months (CRS-CU survey), and a household’s propensity to use a transfer for food purchases may differ during the lean season, when they have no stored staples. We do not present findings on average share of income spent on food for Makueni because income is highly seasonal and recall was deemed too time consuming and susceptible to error, especially given MIFIRA’s focus on parsimonious data collection.
The induced food demand of 160 households receiving a restricted food voucher worth KSh 1,500 would be KSh 240,000 and would exceed both the lower and upper bounds of excess capacity in the Kitise sub-location. In this case, the maximum number of recipients is calculated to be 120 households (a demand increase of KSh 180,000 for food-restricted vouchers) so as not to exceed the lower bound excess capacity of traders in the sub-location.
An important next step before program implementation is to aggregate estimated excess supply capacity within a marketshed and compare the total estimate with the estimated excess capacity of the common source market. For example, if Mithumba and Mavindini wholesalers share a common set of dedicated wholesalers, one would verify that the shared dedicated wholesalers could also meet the estimated demand increase without increasing costs.
We do not estimate an interaction term for gender of household head and gender of respondent for the Makueni sample because when only eleven female household head respondents are further subdivided by prior experience with forms of aid, the multinominal results are highly unstable.
Albu, M. (2010). The emergency market mapping and analysis toolkit. Rugby: Practial Action Publishing Ltd.
Barrett, C. B. (2002). Food security and food assistance programs. In B. L. Gardner & G. C. Rausser (Eds.), Handbook of agricultural economics. Amsterdam: Elsevier Science.
Barrett, C. B., Bell, R., Lentz, E. C., & Maxwell, D. G. (2009). Market information and food insecurity response analysis. Food Security, 1, 151–168.
Central Bureau of Statistics, World Bank, SIDA, and SID (2005). Geographic dimensions of well-being in Kenya: Who and where are the poor? A constituency level profile, vol. II. Accessed on July 26, 2010. http://www.scribd.com/doc/2224390/geographic-Dimensions-of-WellBeing-in-Kenya.
Famine Early Warning Systems Network. (2011). Special brief: Market functioning in Southern Somalia. July 28.
FAO. (2009). The State of food insecurity in the world: Economic crisis—Impacts and lessons learned. Rome, Italy.
Harvey, P. (2007). Cash-based responses in emergencies. Overseas Development Institute Humanitarian Policy Group Report No. 24. January.
Harvey, P., Proudlock, K., Clay, E., Riley, B. & Jaspars, S. (2010). Food Aid and Food Assistance in Emergency and Transitional Contexts: A Review of Current Thinking. Report for the Government of Germany, Federal Ministry for Economic Cooperation and Development (BMZ). London, ODI.
Kenya National Bureau of Statistics. (2010a). Population and housing census of 2009.
Kenya National Bureau of Statistics. (2010b). Consumer price index. Accessed on July 26, 2010. http://www.knbs.or.ke/.
KFSSG. (2007). Food security district profile: Makueni district, Eastern Province. Accessed on July 26, 2010. http://www.kenyafoodsecurity.org/images/stories/files/dps/eastern/makueni.pdf.
KFSSG. (2008). The impact of rising food prices on disparate livelihoods groups in Kenya. Accessed on July 26, 2010. http://documents.wfp.org/stellent/groups/public/documents/ena/wfp182903.pdf.
KFSSG. (2010). The 2009–2010 short-rains season assessment report. Accessed on July 26, 2010. http://www.kenyafoodsecurity.org/images/stories/files/sra2010/SRA_2010.pdf.
Ouma, R., Mude R., Lentz E. (2010). Responding to food Insecurity: A case for cash in rural Northern Kenya. Working Paper.
Ruel, M. T., Garrett, J. L., Hawkes, C., Cohen, M. J. (2010). The food, fuel, and financial crises affect the urban and rural poor disproportionately: a review of the evidence. The Journal of Nutrition, 140, 170–176.
UN-HABITAT. (2006). Nairobi: Urban sector profile. Nairobi, Kenya.
Upton, J. Lentz E. (2012). Chapter 5: Expanding the food assistance toolbox. In C. Barrett, A. Binder, J. Steets (Eds.), Uniting on food assistance: The case for translantic cooperation. New York: Routledge.
World Food Programme. (2007). Malawi assessment of appropriateness and feasibility of cash based response options. Special Initiative for Cash and Voucher Programming. June.
We are grateful to Japheth Muli and Martin Waweru at Catholic Relief Services in Nairobi and our enumerator teams from the Diocese of Machakos and the Archdiocese of Nairobi. Aschelew Tesfaye of the World Food Program, and Justus Liku of CARE provided valuable guidance throughout. The research was funded through a United States Agency for International Development BASIS Assets and Market Access Collaborative Research Support Program grant No. EDH-A-00-06-00003-00. The views expressed are solely the authors’ and do not represent any official agency. Any remaining errors are ours alone.
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Michelson, H., Lentz, E.C., Mulwa, R. et al. Cash, food, or vouchers? An application of the Market Information and Food Insecurity Response Analysis Framework in urban and rural Kenya. Food Sec. 4, 455–469 (2012). https://doi.org/10.1007/s12571-012-0177-0
- Food insecurity
- Response analysis
- Urban food insecurity