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Fertilizer subsidies and the role of targeting in crowding out: evidence from Kenya

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  • David L. Mather

    (Michigan State University)

  • Thomas S. Jayne

    (Michigan State University)

Abstract

The impact of input subsidy programs depends on the extent to which they increase fertilizer use. We used panel data of smallholder farm households from Kenya to analyse the targeting criteria of two fertilizer subsidy programs in Kenya and how these targeting criteria affected farmers’ commercial demand for fertilizer and total fertilizer use. We found that every kilogram of subsidized fertilizer allocated to farmers reduced the quantity of commercial fertilizer purchased by 0.40 kg, a crowding-out effect that is double those found recently in Malawi and Zambia. The large magnitude of crowding out is driven by the fact that neither subsidy program focused on reaching households that had not previously been purchasing commercial fertilizer. There is little evidence that these programs systematically focused on relatively poor households either. The programs crowded out commercial fertilizer use most severely in medium/high potential zones (relative to low), and among households in the upper half of landholding/asset distributions (relative to the lower half). Different targeting criteria could substantially increase the contribution of these subsidy programs to total fertilizer use and hence to national food production and food security.

Suggested Citation

  • David L. Mather & Thomas S. Jayne, 2018. "Fertilizer subsidies and the role of targeting in crowding out: evidence from Kenya," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(2), pages 397-417, April.
  • Handle: RePEc:spr:ssefpa:v:10:y:2018:i:2:d:10.1007_s12571-018-0773-8
    DOI: 10.1007/s12571-018-0773-8
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    Cited by:

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    2. Pradyot Ranjan Jena & Hugo Groote & Bibhu Prasad Nayak & Annina Hittmeyer, 2021. "Evolution of Fertiliser Use and its Impact on Maize Productivity in Kenya: Evidence from Multiple Surveys," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(1), pages 95-111, February.
    3. Jongwoo Kim & Nicole M. Mason & David Mather & Felicia Wu, 2021. "The effects of the national agricultural input voucher scheme (NAIVS) on sustainable intensification of maize production in Tanzania," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(3), pages 857-877, September.
    4. Marcia F. Kwaramba & Srinivas Sridharan & Felix T. Mavondo, 2023. "Drivers and outcomes of smallholder market participation in Sub-Saharan Africa," Journal of the Academy of Marketing Science, Springer, vol. 51(5), pages 1165-1183, September.
    5. Chen, You-hua & Chen, Mei-xia & Mishra, Ashok K., 2020. "Subsidies under uncertainty: Modeling of input- and output-oriented policies," Economic Modelling, Elsevier, vol. 85(C), pages 39-56.
    6. Rutsaert, Pieter & Donovan, Jason & Kimenju, Simon, 2021. "Demand-side challenges to increase sales of new maize hybrids in Kenya," Technology in Society, Elsevier, vol. 66(C).

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