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

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

53%

25%

21%

1%

Fluid milk

Processed Consumed Sold Given out Consumed Sold Given out0

10

20

30

40

50

60

57.1

39.7

3.2

Butter

• Relatively small proportion of fluid milk is marketed.

• More than half of fluid milk produced is processed at home.

• Relatively larger proportion of butter

produced is consumed at home.

Percentage of households selling fluid milk and butter

83%

17%

Non-sellers Sellers

Sellers =136Non-sellers = 679Producers =815

Percentage of HHs selling fluid milk

39.4%

60.6%

Non-sellers Sellers

Sellers =466Non-sellers = 303Producers =769

Percentage of HHs selling butter

Butter

ProducersNon-

producers Total Sellers Non-sellers

Fluid milk

Sellers 88 26 22 136

Non-sellers 378 277 24 679

Total 466 303 46 815

Buyer types of fluid milk and butter

Consumer68%

Trader33%

Proportion of butter buyers (in percentage)

44%

34%

22%

Proportion of fluid milk buyers (in percentage)

Consumers Traders Cooperatives

Market places for selling fluid milk and butter

Market place for fattened animals

Ox Bull Cow Sheep Goat0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

22.0

4.3

60.0

13.4 10.9

45.7

56.5

40.0

19.637.0

32.0

26.165.5

52.2

0.313.0

1.5 0.0

Proportion of fattened animals sold at each market type

Regional Market District MarketLocal MarketFarm-gate

• 204 of the 1192 sample households are

engaged in small and large ruminants fattening business.

• Most fattened animals are sold at local and

district markets.

Type of animals fattened

No. of householdsengaged in fattening

Average animal

fattened per household

Total animals fattened

Ox 129 2.5 306Bull 13 1.8 23Cow 4 1.3 5Sheep 64 5.3 336Goat 17 2.8 46

Results

Market outlet(Buyer type)

Milk and milk products(Milk and/or butter

sellers) (N=514)

Fattened animals(HHs engaged in fattening)

(N=204)

Obs* Mean Std. Dev

Obs Mean Std. Dev

Farmer-consumer 149 2.19 0.46 97 2.12 0.53Assembler 94 1.69 0.72 108 1.45 0.65Retailer 109 1.85 0.58 53 1.87 0.62Processor 43 1.58 0.70Non-farmer consumer 371 2.19 0.60 111 2.10 0.63Cooperative 14 1.71 0.61Note: Scale (1=Less informed, 2=Equally informed, 3=More informed) * who sold dairy products (fluid milk and butter ) to the specific buyer types.

Mean values of ranking on whether a seller is well informed about the price of outputs than a buyer.

Results


Milk and milk products

(Milk and/or butter sellers) (N=514)

Fattened animals(for those who were engaged in fattening

(N=204)Obs Mean Std. Dev Obs Mean Std. Dev

Farmer-buyer 51 2.39 0.64 69 2.38 0.67Assembler 37 1.95 0.58 67 1.82 0.63Retailer 61 1.97 0.52 28 1.54 0.51Processor 27 1.81 0.68Non-farmer consumer

176 2.13 0.6854 1.94 0.66

Cooperative 13 2.38 0.77

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







371 0.11 0.31110 0.17 0.40


Mean values on whether sellers are cheated on prices when transacting with the specific buyer type

Note: 1=Yes; 0=No

Results




Obs Mean Std. Dev

Farmer-buyer 148 0.01 0.12Assembler 94 0.15 0.36Retailer 107 0.34 0.47Non-farmer consumer

367 0.12 0.33


Mean values on whether sellers are cheated on measurement units when transacting with the specific buyer type

Note: 1=Yes; 0=No

Results







355 1.45 1.1047 2.60 1.85


Mean values of time spent in searching and waiting for the specific buyer type (in hours)

Results







355 14.35 16.82107 30.48 21.05


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!

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

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