A Triple-Hurdle Model of Production and Market Participation in Kenya's Dairy Market

Existing analyses of market participation are based on a "double-hurdle" modeling approach. Such models are appropriate only when all members of the population of interest actually produce the good. In some contexts, however (e.g., smallholder farmers), many members of the population do no...

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Veröffentlicht in:American journal of agricultural economics 2015-07, Vol.97 (4), p.1227-1246
Hauptverfasser: Burke, William J., Myers, Robert J., Jayne, Thomas S.
Format: Artikel
Sprache:eng
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Zusammenfassung:Existing analyses of market participation are based on a "double-hurdle" modeling approach. Such models are appropriate only when all members of the population of interest actually produce the good. In some contexts, however (e.g., smallholder farmers), many members of the population do not produce particular goods that they could produce and that their neighbors do produce. Policies influencing market participation among producers may thus also induce additional farmers to become producers. Previous double-hurdle approaches do not allow explicitly for this possibility. To address these limitations, this article presents a "triple-hurdle" approach with an initial stage that includes nonproducers. The model is used to identify the factors associated with Kenyan smallholder farmers choosing to participate in dairy production, and the role that these producers choose to play (or not) in the marketplace. In the midst of debates underway over the privatization of the parastatal Kenya Creameries Company, new knowledge about smallholder participation in dairy could be an important contribution. Results suggest the importance of rural electrification, training, and improved grazing practices. We find that expected net sales are significantly higher when farmers have access to informal private markets. We also describe a version of the ordered tobit model that includes nonproducers and is nested in our triple-hurdle model. A likelihood ratio test shows the latter to be a significantly better fit to our data. We discuss how insights gained from this study differ from the insights that would come from a double-hurdle ordered tobit that also includes nonproducers.
ISSN:0002-9092
1467-8276
DOI:10.1093/ajae/aav009