Determinants of Households’ Market Participation around Community Milk Cooling Plants, Western Kenya


  •  Justus I. Emukule    
  •  Mary J. Kipsat    
  •  Caroline C. Wambui    

Abstract

Market participation in sub-Saharan Africa has been assessed mainly based on already producing households by looking at whether they sold or not, and if they sold, what quantities. The objective of this study was to determine the socio economic factors that influenced households’ decisions on market participation in terms of dairy cow ownership and quantity of milk sold while taking into consideration the non-producers using Heckman two stage model. The model allowed for not only determination of the effects of household characteristics on volume of milk surplus sold by already producing households but also drew inferences on the effect of household characteristics on probabilities of dairy cow ownership whileadding new information to literature by generating the truncation effect. A multistage sampling technique was used to select 544 producer and non-producer households and primary data collected using a semi structured interview schedule through personal interviews. From the results, probit marginal effects for dairy cow ownership were associated positively and statistically significant with household size, the level of education and land size owned by the households. The Heckman selection estimates revealed that increased number of dairy cows per household positively influenced the volumes of milk sold, while household size influenced negatively the quantity of milk sold. In conclusion, milk sales conditional on dairy cow ownership suffered from negative selectivity bias whereby a household with sample average characteristics who selected into dairy cow ownership secured 40% lower quantity of milk sold than would a household drawn at random.



This work is licensed under a Creative Commons Attribution 4.0 License.
  • Issn(Print): 1916-9752
  • Issn(Onlne): 1916-9760
  • Started: 2009
  • Frequency: monthly

Journal Metrics

(The data was calculated based on Google Scholar Citations)

  • Google-based Impact Factor (2016): 2.28
  • h-index (December 2017): 31
  • i10-index (December 2017): 304
  • h5-index (December 2017): 22
  • h5-median (December 2017): 27

Contact