The study analyzes factors determining the market position of smallholder farmers in Ethiopia's Feed the Future zones, highlighting the low uptake of improved farm inputs and weak market links. Utilizing a multinomial probit model on a survey of 7,011 households, it identifies characteristics influencing whether farmers are net sellers, buyers, or in autarky, finding that higher production levels and better access to resources enhance market participation. The findings indicate that net seller households are more likely to adopt agricultural technologies and benefit from improved road quality and productive assets.

1. ETHIOPIAN DEVELOPMENT
RESEARCH INSTITUTE
Determinants of Smallholder Market Participation: Evidence from
Feed the Future(FtF) zones of Ethiopia
Bethelhem Koru and Alemayehu Seyoum Taffesse
IFPRI ESSP
Ethiopian Economics Association
13th International Conference on the Ethiopian Economy
July 23-25, 2015
Addis Ababa
1

2. 2
Introduction
• Markets are important in the livelihood strategy of most rural households
• The government policy on agricultural development has recently started to emphasize the
transformation of subsistence agriculture into market orientation
• Agriculture sector in Ethiopia → low uptake of improved farm inputs, week links to markets,
high transport costs, and lack of information on markets and prices
• Little literature exists on why farmers find themselves as either net sellers, autarkic or net
buyers
• The primary objectives of the paper is thus to analyze those factors that determine the
market position of small holder farmers in Ethiopia , with a particular focus on food crops

3. Definition of Commercialization
• The concept and level of agricultural commercialization has been defined differently across
studies
• In most literature, a farm household is assumed to be commercialized if it is producing a
significant amount of cash commodities
• Gabremadhin et al. (2007) level of household commercialization is measured as the
percentage of agricultural output sold to total agricultural production
• Pender and Alemu (2007) → the ratio of the value of crop sales in households over the total
value of crop production
• For this study we define market position based on the level of annual surplus production less
of annual consumption available for marketing

4. Cont’d
Annual Production - Annual Consumption
Net seller → if HH sells more than 50 kg of a crop
Net buyer → if HH buys more than 50 kg of a crop
Autarky → if HH sells/buys less than 50 kg of a crop

5. Data
• Our empirical finding is based on Feed the future (FtF) baseline survey collected by
International Food Policy Research Institute along with Central Statistical Agency (CSA) in the
year 2013
• One of the key FtF learning agenda question is to support and facilitate market (Promoting
access to market with lower risks and lower entry barriers)
• The study covers 84 woredas from five Regional States of Oromiya, Amhara, Tigray, SNNPR
and Somali in Ethiopia. A total of 7011 household were collected
• A community (or Kebele)-level survey that brings a wealth of information on infrastructures,
access to markets was also administered to complement household-level data

6. Methods
-The estimation was based on multinomial Probit (MNP) model which enable us to treat the
three category of market position
𝑃 𝑌 = 𝑗/𝑋 =
exp(𝑋𝛽𝑗)
[1 + Σ exp(𝑋𝛽 𝑘 ]
, 𝑗 = 1,2, … . 𝐽
Y = Measure of commercial categories of farmers (Net seller, Net buyer, Autarky)
X = denote a set of explanatory variables:
-Household and household head characteristics,
-Access to markets and transport infrastructure
-Access to institutional service (extension, credit)
-Access and ownership of farm equipment
This method can be used to analyze the impact of various explanatory variables on the
probability of being in one or another category (outcome).

7. Descriptive results
22.66
14.98
16.84
34.16
11.36
Proportion of HH Producing Crop (%)
Teff Barley Wheat Maize Sorghum

8. Descriptive results
0
5
10
15
20
25
30
35
Teff Barly Wheat Maize Sorghum
% HH Participating in Crop Sale

9. Descriptives
Net market position of the household
Market position Teff Maize
Autarky 8 7
Net seller 45 50
Net buyer 48 43

10. Descriptives (cont’d)
Crop Classification Net seller Net buyer Autarky
Cereal 61.2 57.4 63.0
Pulses 13.4 14.2 13.7
Oil seeds 3.6 3.1 3.5
Vegetables 1.5 2.2 1.8
Root crops 3.6 4.6 4.5
Fruits 1.0 1.4 0.5
Chat 1.2 1.6 1.1
Coffee 3.2 3.5 2.8
Enset 4.8 5.8 3.8
Others 6.6 6.3 5.4
Total 100 100 100

11. Descriptive statistics by net market position of Teff and Maize producers
Teff Maize
Variables Net Seller Net Buyer Sig. Net Seller Net Buyer Sig.
Proportion of primary occupation
Crop production 32 31 39 27 ***
Livestock production 0.9 1 1 1
Non-farm activities 26 24 25 24
Male head of household
(1=Male)
78 72 *** 76 72 ***
Age of household head 43 42 * 42 41 **
Proportion of working age HH
members
56 55 55 53 ***
HH education (1=can write and
read)
39 40 39 37 *

12. Conti….
Teff Maize
Variables Net Seller Net Buyer Sig. Net Seller Net Buyer Sig.
Output (kg) 431 96 *** 885 128 ***
Farm equipment(Birr) 724 629 ** 741 507 ***
Member of a cooperative (%) 16 13 ** 18 15 ***
Area of land operated (ha) 1.88 1.53 *** 1.8 1.3 ***
HH has at least one irrigated
plot (%)
1.9 1 * 4 1 ***
Use fertilizer (%) 67 49 *** 55 36 ***
Use improved seed variety (%) 25 18 *** 36 13 ***
Extension visit (%) 32 26 *** 36 28 ***

13. Econometric Result: Multinominal probit (MNP) model: TEFF
Marginal Effects of the Multinomial Probit Model on Market Position
Autarky Net seller
Proportion of children -0.11** 0.44***
proportion of working age HH members -0.08 0.48***
Age 0.002 0.003***
HH Sex (1= Male) -0.002 0.04*
Dummy improved seed(1=yes) 0.02 0.029
Dummy fertilizer use (1=yes) 0.011 0.126***
HH membership in cooperative(1=yes) -0.03* 0.07
Log prod. Asset 0.005 0.02***
Land size(ha) 0.002 0.015***
HH have phone (1=yes) -0.005 -0.04*

14. Econometric Result: Multinomial probit (MNP) model: Maize
Marginal Effects of the Multinomial Probit Model on Market Position
Autarky Net seller
Road quality rank -0.008*** 0.01*
Extension visit(1=yes) -0.007 0.046**
Irrigation use at least in one plot (1=yes) -0.002 0.195***
Dummy improved seed(1=yes) -0.001 0.193***
Dummy fertilizer use (1=yes) 0.01 0.05*
Credit(1=yes) -0.005 0.007
HH membership in mahiber(1=yes) -0.02* 0.04*
Log prod. Asset -0.01** 0.03***
Land size(ha) 0.001 0.021

15. Conclusion
 In general, we found statistical evidence suggesting that the higher the level of
production, the higher will be the probability of farmers being engaged in
commercialization;
 Results from both descriptive and econometric analysis suggest that net sellers
households are more likely to adopt agricultural technologies;
 The prevalence of lower market transaction costs (higher quality of road) also
improves household involvement in food market;
 Productive assets that increase potential production of Teff and maize such as land,
ownership of farm equipment owned by the households have positively associated
with being net seller;