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Analyses of Household Specific Transaction Cost Factors in Livestock and Livestock Outputs Markets in Ethiopia Presented by Moti Jaleta, Berhanu Gebremedhin, Samson Jemaneh and Aklilu Bogale (ILRI-IPMS) for the 5th All Africa Conference on Animal Agriculture and the 18th Annual Meeting of the Ethiopian Society of Animal Production (ESAP), Addis Ababa, October 25-28, 2010
Outline  Background Objective Data and Methodology Results  Conclusions
Background Livestock contributes significantly to the Ethiopian economy: Livelihood for 60-70% of the population About 38% of the rural household income 15-18% of GDP 30-35% of agricultural GDP 14% of agricultural export Main source of draft power
Background (2) Huge and untapped livestock resource in the country (the first in Africa in its live animals population) Livestock population of Ethiopia (CSA, 2009):  49.3 million heads of cattle 26.9 million sheep 21.8 million goats  39.5 million poultry But, low off-take rate (Yacob, 2002; Negassa and Jabbar, 2008) Cattle … 7-8% Sheep and goats … 40.5% and 34%, respectively.
Background (3) Benefits from livestock are not attained to the maximum potential due to different factors: Underdeveloped livestock and livestock products markets. Higher transaction costs in these markets reduce or hinder smallholder participation (Staal et al 1997; Holloway, 2000; Makhura 2001; among others). The level of transaction costs that households face depend on product, market, and household characteristics.
Objective Analyze the household specific transaction cost factors in livestock and livestock products markets. Focus on transaction cost factors in: Small and large ruminants (live animals) markets Dairy products (fluid milk and butter) markets
Data  Using data from a household survey conducted during 2009 in 10 districts where IPMS project operates in Ethiopia. A total of 1192 sample households (more than 100 sample households per district). Sampling based on households’ participation in the IPMS project interventions, accounting for gender and wealth factors.
Data  Selling households’ evaluation of the specific transaction cost factors such as:   The extent of price information sellers (farmers) have compared to the different buyer types in the market. How contracts (written or verbal) are respected when dealing with different buyer types. Existence of hidden action like cheating on prices and measurement units by buyers. Average time spent in searching and waiting for potential buyers and in negotiating on prices.
Geographical locations of the 10 PLWs of the IPMS project
Methodology Analyses of descriptive statistics Ordered Probit models for household responses by rank/scale (poor/bad, medium/moderate, good)  Binary Probit analysis for questions with Yes/No response Ordinary Least Square regression analysis for continuous variables  (like the average time spent in searching, waiting, negotiating in markets).
Methodology (2) Each of these factors are analyzed per the potential buyer types available in the markets (consumers, traders, cooperatives, etc.) Analyses for those sample households: Producing and selling dairy products, and  Fattening and selling small and large ruminants.
Results
Use pattern of fluid milk and butter  ,[object Object],   milk is marketed. ,[object Object],   produced is consumed at home. ,[object Object],   processed at home.
Percentage of households selling fluid milk and butter
Buyer types of fluid milk and butter
Market places for selling fluid milk and butter
Market place for fattened animals ,[object Object],   engaged in small and large ruminants     fattening  business.   ,[object Object],   district markets.
Results Mean values of ranking on whether a seller is well informed about the price of outputs than a buyer.  Note:   Scale (1=Less informed, 2=Equally informed, 3=More informed)           * who sold dairy products (fluid milk and butter ) to the specific buyer types.
Results Mean values of ranking on how well contracts are respected when transacting  with the specific buyer type   Note: Scale (1=Low; 2=Medium;  3=High).
Results Mean values on whether sellers are cheated on prices when transacting  with the specific buyer type   Note: 1=Yes; 0=No
Results Mean values on whether sellers are cheated on measurement units when transacting with the specific buyer type   Note: 1=Yes; 0=No
Results Mean values of time spent in searching and waiting for the specific buyer type (in hours)
Results Mean values of time spent in negotiating on prices when transacting  with the specific buyer type  (in minutes).
Conclusions Fluid milk and/or butter selling households are better informed than buyers in prices when they are transacting with consumers (both farmer and non-farmer consumers).  Contracts are relatively respected when fluid milk and/or butter sellers are transacting with farmer-buyers/consumers and cooperatives.  Both in dairy products and fattened animals, longer searching and waiting time is spent when transacting with traders, but relatively shorter time when dealing with consumers and cooperatives.
Trying to explain the rankings of transaction cost factors made by selling households from the perspectives of sellers’ and buyers’ characteristics, nature of the products, and the nature of markets these actors are operating in.  Forward
Thank you!

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Analyses of household specific transaction cost factors in livestock and livestock outputs markets in Ethiopia

  • 1. Analyses of Household Specific Transaction Cost Factors in Livestock and Livestock Outputs Markets in Ethiopia Presented by Moti Jaleta, Berhanu Gebremedhin, Samson Jemaneh and Aklilu Bogale (ILRI-IPMS) for the 5th All Africa Conference on Animal Agriculture and the 18th Annual Meeting of the Ethiopian Society of Animal Production (ESAP), Addis Ababa, October 25-28, 2010
  • 2. Outline Background Objective Data and Methodology Results Conclusions
  • 3. Background Livestock contributes significantly to the Ethiopian economy: Livelihood for 60-70% of the population About 38% of the rural household income 15-18% of GDP 30-35% of agricultural GDP 14% of agricultural export Main source of draft power
  • 4. Background (2) Huge and untapped livestock resource in the country (the first in Africa in its live animals population) Livestock population of Ethiopia (CSA, 2009): 49.3 million heads of cattle 26.9 million sheep 21.8 million goats 39.5 million poultry But, low off-take rate (Yacob, 2002; Negassa and Jabbar, 2008) Cattle … 7-8% Sheep and goats … 40.5% and 34%, respectively.
  • 5. Background (3) Benefits from livestock are not attained to the maximum potential due to different factors: Underdeveloped livestock and livestock products markets. Higher transaction costs in these markets reduce or hinder smallholder participation (Staal et al 1997; Holloway, 2000; Makhura 2001; among others). The level of transaction costs that households face depend on product, market, and household characteristics.
  • 6. Objective Analyze the household specific transaction cost factors in livestock and livestock products markets. Focus on transaction cost factors in: Small and large ruminants (live animals) markets Dairy products (fluid milk and butter) markets
  • 7. Data Using data from a household survey conducted during 2009 in 10 districts where IPMS project operates in Ethiopia. A total of 1192 sample households (more than 100 sample households per district). Sampling based on households’ participation in the IPMS project interventions, accounting for gender and wealth factors.
  • 8. Data Selling households’ evaluation of the specific transaction cost factors such as: The extent of price information sellers (farmers) have compared to the different buyer types in the market. How contracts (written or verbal) are respected when dealing with different buyer types. Existence of hidden action like cheating on prices and measurement units by buyers. Average time spent in searching and waiting for potential buyers and in negotiating on prices.
  • 9. Geographical locations of the 10 PLWs of the IPMS project
  • 10. Methodology Analyses of descriptive statistics Ordered Probit models for household responses by rank/scale (poor/bad, medium/moderate, good) Binary Probit analysis for questions with Yes/No response Ordinary Least Square regression analysis for continuous variables (like the average time spent in searching, waiting, negotiating in markets).
  • 11. Methodology (2) Each of these factors are analyzed per the potential buyer types available in the markets (consumers, traders, cooperatives, etc.) Analyses for those sample households: Producing and selling dairy products, and Fattening and selling small and large ruminants.
  • 13.
  • 14. Percentage of households selling fluid milk and butter
  • 15. Buyer types of fluid milk and butter
  • 16. Market places for selling fluid milk and butter
  • 17.
  • 18. Results Mean values of ranking on whether a seller is well informed about the price of outputs than a buyer. Note: Scale (1=Less informed, 2=Equally informed, 3=More informed) * who sold dairy products (fluid milk and butter ) to the specific buyer types.
  • 19. Results Mean values of ranking on how well contracts are respected when transacting with the specific buyer type Note: Scale (1=Low; 2=Medium; 3=High).
  • 20. Results Mean values on whether sellers are cheated on prices when transacting with the specific buyer type Note: 1=Yes; 0=No
  • 21. Results Mean values on whether sellers are cheated on measurement units when transacting with the specific buyer type Note: 1=Yes; 0=No
  • 22. Results Mean values of time spent in searching and waiting for the specific buyer type (in hours)
  • 23. Results Mean values of time spent in negotiating on prices when transacting with the specific buyer type (in minutes).
  • 24. Conclusions Fluid milk and/or butter selling households are better informed than buyers in prices when they are transacting with consumers (both farmer and non-farmer consumers). Contracts are relatively respected when fluid milk and/or butter sellers are transacting with farmer-buyers/consumers and cooperatives. Both in dairy products and fattened animals, longer searching and waiting time is spent when transacting with traders, but relatively shorter time when dealing with consumers and cooperatives.
  • 25. Trying to explain the rankings of transaction cost factors made by selling households from the perspectives of sellers’ and buyers’ characteristics, nature of the products, and the nature of markets these actors are operating in. Forward