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Market participation, on-farm crop diversity and household welfare: micro-evidence from Kenya

Published online by Cambridge University Press:  11 July 2012

Solomon Asfaw ,
Leslie Lipper ,
Timothy J. Dalton  and
Patrick Audi
Solomon Asfaw
Affiliation:
FAO of the United Nations, Agricultural Development Economics Division (ESA), Viale delle Terme di Caracalla – 00153 Rome, Italy. Tel: +39 06 570 55504. Fax: +39 06 570 55522. Email: [email protected]
Leslie Lipper
Affiliation:
FAO of the United Nations, Agricultural Development Economics Division (ESA), Italy. Email: [email protected]
Timothy J. Dalton
Affiliation:
Department of Agricultural Economics, Kansas State University, USA. Email: [email protected]
Patrick Audi
Affiliation:
International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Kenya. Email: [email protected]
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Abstract

This paper examines determinants of output and input market participation. It employs propensity score matching techniques to evaluate the impact of market participation on pigeonpea diversity and household welfare, using cross-sectional data of 333 households from Kenya. Results show that input and output market participation decisions are quite distinct. Output market participation is influenced by household demographics, farm size and radio ownership, while input market participation is determined by farm size, bicycle ownership and access to a salaried income. The findings reveal a positive and significant impact of output market participation on pigeonpea diversity, while input market participation had a negative and significant impact on diversity. The results indicate that output market participants have significantly higher food security status than non-participants, in line with the general findings of the literature. However, no significant impact is found between indicators of household welfare and input market participation.

Type
Research Article
Information
Environment and Development Economics , Volume 17 , Issue 5: Seed supply in local markets: supporting sustainable use of crop genetic resources , October 2012 , pp. 579 - 601
Copyright
Copyright © Cambridge University Press 2012

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References

Alene, D.A., Manyong, V.M., Omanya, G., Mignouna, H.D., Bokanga, M., and Odhiambo, G.D. (2008), ‘Smallholder marketed surplus and input use under transactions costs: maize supply and fertilizer demand in Kenya’, Food Policy 32: 318–328.Google Scholar
Ali, A. and Abdulai, A. (2010), ‘The adoption of genetically modified cotton and poverty reduction in Pakistan’, Journal of Agricultural Economics 61(1): 175–192.Google Scholar
Asfaw, S., Amare, M., Lipper, L., and Davis, B. (2011), ‘Welfare effects of market participation under transaction costs: evidence from Tanzania’, Working Paper, Agricultural Development Economics Division, FAO.Google Scholar
Asfaw, S., Kassie, M., Simtowe, F., and Lipper, L. (2012a), ‘Poverty reduction effects of agricultural technology adoption: a micro-evidence from rural Tanzania’, Journal of Development Studies, forthcoming.Google Scholar
Asfaw, S., Shiferaw, B., Simtowe, F., and Lipper, L. (2012b), ‘Impact of modern agricultural technologies on smallholder welfare: evidence from Tanzania and Ethiopia’, Food Policy 37(3): 283–295.CrossRefGoogle Scholar
Audi, P.O., Nagarajan, L., and Jones, R. (2008), ‘Seed interventions and cultivar diversity in pigeonpea: a farmer based assessment in Eastern Kenya’, Journal of New Seeds 9(2): 111–127.Google Scholar
Audi, P.O., Jones, R., and Nagarajan, L. (2010), ‘Pigeonpea seed supply and diversity: a case study of local seed markets in Makueni District, eastern Kenya’, in Lipper, L., Leigh, A. and Dalton, T.J. (eds), Seed Trade in Rural Markets: Implications for Crop Diversity and Agricultural Development, Chapter 6, London: Earthscan.Google Scholar
Badstue, L.B., Bellon, M.R., Berthaud, J., Juárez, X., Rosas, I.M., Solano, A., and Ramírez, A. (2006), ‘Examining the role of collective action in an informal seed system: a case study from the central valleys of Oaxaca, Mexico’, Human Ecology 34(2): 249–273.Google Scholar
Barrett, C.B. (2008), ‘Smallholder market participation: concepts and evidence from Eastern and Southern Africa’, Food Policy 33: 299–317.Google Scholar
Benfica, R. (2006), ‘Interlinked transactions in cash cropping economies: the determinants of farmer participation and performance in the Zambezi river valley of Mozambique’, Ph.D. dissertation, Department of Agricultural Economics, Michigan State University, Michigan.Google Scholar
Brush, S., Taylor, J.E., and Bellon, M.R. (1992), ‘Technological adoption and biological diversity in Andean potato agriculture’, Journal of Development Economics 39(2): 365–388.Google Scholar
Caliendo, M. and Kopeinig, S. (2008), ‘Some practical guidance for the implementation of propensity score matching’, Journal of Economic Surveys 22(1): 31–72.Google Scholar
Cavatassi, R., Lipper, L., and Narloch, U. (2010), ‘Modern variety adoption and risk management in drought prone areas: insights from the sorghum farmers of eastern Ethiopia’, Agricultural Economics 42(3): 279–292.CrossRefGoogle Scholar
Dehejia, H.R. and Wahba, S. (2002), ‘Propensity score matching methods for non-experimental causal studies’, Review of Economics and Statistics 84(1):151–161.Google Scholar
de Janvry, A., Dustan, A., and Sadoulet, E. (2010), ‘Recent advances in impact analysis methods for ex-post impact assessments of agricultural technology: options for the CGIAR’, Paper prepared for the workshop organized by the CGIAR Standing Panel on Impact Assessment, SPIA, October 2, Berkeley.Google Scholar
Dercon, S. and Krishnan, P. (1998), ‘Changes in poverty in rural Ethiopia 1989–1995: measurement, robustness tests and decomposition’, Working Paper No. 98-7, Centre for the Study of African Economies, University of Oxford, Oxford.Google Scholar
FAO (2011), ‘Guidelines for measuring dietary diversity’, Rome, Italy, [Available at] http://www.fao.org/docrep/014/i1983e/i1983e00.pdf.Google Scholar
Foster, A.D. and Rosenzweig, M.R. (2010), ‘Microeconomics of technology adoption’, Annual Review of Economics 2: 395–424.CrossRefGoogle ScholarPubMed
Heckman, J., Ichimura, H., Smith, J., and Todd, P. (1998), ‘Characterizing selection bias using experimental data’, Econometrica 66(5): 1017–1098.Google Scholar
Heckman, J. and Navarro-Lozano, S. (2004), ‘Using matching, instrumental variables and control functions to estimate economic choice models’, Review of Economics and Statistics 86(1): 30–57.Google Scholar
Hellin, J. and Higman, S. (2005), ‘Crop diversity and livelihood security in the Andes’, Development in Practice 15(2): 165–174.Google Scholar
Isakson, S.R. (2007), ‘Peasant farmers’ market engagements and the on-farm conservation of crop genetic resources in the Guatemalan highlands’, Working Paper Series 122, University of Massachusetts, Amherst.Google Scholar
Key, N., Sadoulet, E., and de Janvry, A. (2000), ‘Transactions costs and agricultural household supply response’, American Journal of Agricultural Economics 82(2): 245–259.CrossRefGoogle Scholar
Leuven, E. and Sianesi, S.B. (2003), ‘PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing’, Statistical Software Components series, No. S432001, Department of Economics, Boston College, MA.Google Scholar
Lipper, L., Cavatassi, R., and Winters, P. (2006), ‘Seed supply and the on-farm demand for diversity: a case study from Eastern Ethiopia’, in Smale, M. (ed.), Valuing Crop Biodiversity: On Farm Genetic Resources and Economic Change, Wallingford: CABI Publishing, pp. 223–250.Google Scholar
Lipper, L., Anderson, C.L., and Dalton, T.J. (eds) (2010), Seed Trade in Rural Markets: Implications for Crop Diversity and Agricultural Development, Rome: FAO and London: Earthscan.Google Scholar
Morris, M.L., Rusike, J., and Smale, M. (1998), ‘Maize seed industries: a conceptual framework’, in Morris, M.L. (ed.), Maize Seed Industries in Developing Countries, London: Lynne Rienner.CrossRefGoogle Scholar
Rosenbaum, P.R. (2002), Observational Studies, New York: Springer.Google Scholar
Rosenbaum, P.R. and Rubin, D.B. (1983), ‘The central role of the propensity score in observational studies for causal effects’, Biometrika 70(1): 41–55.Google Scholar
Rosenbaum, P.R. and Rubin, D.B. (1985), ‘Constructing a control group using multivariate matched sampling methods that incorporate the propensity score’, American Statistician 39(1): 33–38.Google Scholar
Sianesi, B. (2004), ‘An evaluation of the Swedish system of active labour market programmes in the 1990s’, Review of Economics and Statistics 86(1): 133–155.Google Scholar
Smale, M. (ed.) (2006), Valuing Crop Biodiversity: On Farm Genetic Resources and Economic Change, Wallingford: CABI Publishing.Google Scholar
Smith, J.A and Todd, P.E. (2005), ‘Does matching overcome LaLonde's critique of nonexperimental estimators?’, Journal of Econometrics 125: 305–353.Google Scholar
Sperling, L. and Maguire, S. (2010), ‘Understanding and strengthening informal seed markets’, Experimental Agriculture 49: 119–136.Google Scholar
Vadez, V., Reyes-García, V., Godoy, R.A., Apaza, V.L., Byron, E., Huanca, T., Leonard, W.R., Perez, E., and Wilkie, D. (2004), ‘Does integration to the market threaten agricultural diversity? Panel and cross-sectional data from a horticultural-foraging society in the Bolivian Amazon’, Human Ecology 32: 635–646.CrossRefGoogle Scholar
Van Dusen, M.E. (2000), ‘In-situ conservation of crop genetic resources in the Mexican Milpa System’, Ph.D. dissertation, University of California, Berkley.Google Scholar
World Bank (2008), World Development Report 2008: Agriculture for Development, World Bank, Washington, DC.Google Scholar