Victor Afari Sefa, AVRDC "The Role of Traditional Vegetables on Household Economy and Nutritional Outcomes in Tanzania"

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The World Vegetable Center
vegetables + development
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Role of traditional vegetables on household economy and
nutritional outcomes in Tanzania
Victor Afari-Sefa (PhD)
Agricultural Economist & Global Theme Leader - Consumption
2013 Science Policy Forum, September 23-25, 2013, Bonn, Germany
Break-out Session 10: Economic Implications: Analysis of economic implications of shifting investments in
the primary production to better meet healthy dietary needs

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Structure of the Presentation
Part
1
• Background Statement
Part
II
• Research Questions & Objectives of the Study
Part
III
• Data Sources and Methods
Part
IV
• Results and Discussion
Part
V
• Conclusions & Policy Recommendations

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Background Statement
• Growing scourge of malnutrition due to unhealthy
and imbalanced diets has led to increased public
health concerns and advocacy for dietary
diversification into highly nutritious traditional
vegetables and fruits as essential complements to
staple-based diets for attainment of several MDGs.
• Production and marketing of traditional African
vegetables (TAVs) in Tanzania and other SSA
countries are facing critical bottlenecks.

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Research Questions & Objectives
Research Questions
• Does farmer’ increased awareness of nutritional
importance of TAVs enhance their decision to
diversify cultivation of major staples to TAVs?
• Do farmers gets better market access for TAVs
compared to major staple crops?
Objectives
1. Examine the effect of nutritional awareness of
farmers towards adoption of selected TAVs.
2. Measure determinants of TAV market participation
3. Suggest entry points for formulating policies to
improve smallholders’ market participation via
promotion of their nutritional awareness.

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Data Sources
Data Sources
Primary Survey
Vegetable
Growers Survey
Cropping Pattern,
Input-output usage
and marketing
issues
Nutritional
Awareness etc
Seed Growers
Survey
Traders Survey
Marketing System
Consumers
Survey
Nutritional
Awareness,
Willingness to Pay
etc
Secondary Survey
Population list, area,
production and number of
traders etc.

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Study Regions
Criteria 1: Large area under
TAV cultivation
Criteria 2: Market access
Dodoma
Dar Es Salaam

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Primary Survey Method, Selection of Study Area
and Criteria
Selection Criteria
i. Area under Cultivation & Production ii. Market Access
Multi-Stage Selection Procedure to select Study Region
Meeting with officials in horticulture department at respective study sites
Chasing of Lot Method (Acharya & Agarwal, 2011).
To trace out the value chain system

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Methodology - Econometric Model: Multiple Regression
Functions
• Y (Dependent variables)= Model 1; Share of TAVs in total area under cultivation
of all crops
• Model 2 = Share of sales value to total production value of TAVs
• Z (Independent variable)
• Z1 = Age (Age of household head for farm j).
• Z2 = Education (Household head’s years of schooling for farm j).
• Z4 = Extension contact (dummy)
• Z5 = Access to cash credit (dummy)
• Z6 = Net Operated Area per farm household j
• Z7 = Distance from farm to main road (km)
• Zi = bottleneck for seeds in terms of 1. timely availability, 2. price and 3. quality issues
(dummy)
• Z8 = Total input cost; includes seed, fertilizers, chemicals and labour cost
• Z9 = Nutritional Awareness on TAVs (scale 1=strongly disagree….5=Strongly agreed)
• Dd = Region dummies (D2 = Tanga (slope dummy); D1 = Arusha and D3 = Dar, D4 = Morogoro,
D4 = Dodoma region)

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Land Endowment and Farm Size Classification
Farm Size
Category
No. of
HH
%
Total Owned
Area (Ha)
Net
Operated
Area (NOA)
(Ha)
Net
operated
Irrigated
Area (Ha)
% of NOA*
(Weighted
by HH)
Marginal & Small
(0-2ha) 139
77
0.7 (0.6) 0.8 (0.5) 0.4 43.9
Medium (2-4ha) 32
18
2.8 (1.1) 2.7 (0.5) 0.5 34.1
Large (>4ha) 10
5
6.0 (2.2) 6.9 (3.4) 0.5 27.2
Overall 181
100
1.4 (1.6) 1.4 (1.8) 0.5 100
NOA: Net operated area
In Brackets – SD; * indicates that weighted average ; (# of HHs*NOA)/(Total # of HH*NOA)

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Distribution of HHs by Crops (%)
0
100
200
300
400
500
600
Fruits Vegetable Cereals Pules Roots Oilseed Others
Dodoma
Morogoro
Dar
Tanga
Arusha

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% of HHs who Grow TAVs
14
35
68
16
70
41
16
55
0
32
42
29
23
50
23
12
9
20
58
0
27
0
2
22
12
15
55
32
12
20
0
10
20
30
40
50
60
70
80
ArushaTangaDarMorogoroDodomaOverall
Amaranth African Eggplant Night Shade E-Mustard Sweet Potato

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Market Access Indicators
Market Access Indicators % HH
Difficulty in Selling Produce? 55
Access to Public Extension Services? 57
Access to Credit in last season for Agricultural Activities? 8
Access to Good Roads? 95
Seed Purchase in last season? 72
Fertilizer Purchase in last season? 55

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Awareness on Nutritional Importance of TAVs
Farm Size
Score (Liked
Scale
(1=Strongly
disagree
5=Strongly
agree)
Marginal & Small Farms 3.9
Medium Farms 4.1
Large Farms 4.2
Overall 4.0

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Determinants of Crop Diversification towards TAVs
(1) (2)
VARIABLES without regional_effect with regional_effect
Female -0.00163 -0.00446
(-0.0414) (-0.114)
Level of Education (Years) -0.0118** -0.0111**
(-2.509) (-2.367)
Age (Years) 0.000280 0.0357
(0.149) (1.490)
Square of Age -0.448
(-1.483)
Family Size 0.0162* 0.0174**
(1.862) (2.001)
Log of NOA -0.215*** -0.215***

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Determinants of Crop Diversification towards TAVs.
(1) (2)
VARIABLES without regional_effect with regional_effect
Awareness on nutrition value of TAVs (scale) 0.0427 0.0437*
(1.634) (1.677)
Extension Services (Dummy) -0.0410 -0.0397
(-0.955) (-0.928)
Credit Access (Dummy) 0.205*** 0.193***
(2.931) (2.747)
Log of Total Input Cost (excl. family labour) 0.0547*** 0.0558***
(3.275) (3.354)
Time_seed (Dummy) -0.0368 -0.0407
(-0.624) (-0.692)
Price_seed (Dummy) -0.0460 -0.0380
(-0.797) (-0.659)
Quality_seed (Dummy) 0.0368 0.0420
(0.647) (0.740)
Log of family labour cost 0.0947*** 0.0979***
(3.631) (3.758)
Constant -1.191*** 0.145
(-4.097) (0.153)
Observations 145 145
R-squared 0.624 0.624
Number of Region 5
t-statistics in parentheses
*** p<0.01, ** p<0.05, * p<0.1

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Market Access
(1)
VARIABLES with regional_effect
Female -0.0151
(-0.0966)
Level of Education (years) 0.0367**
(1.982)
Age (Years) 0.00169
(0.228)
Family Size 0.0245
(0.711)
Log of NOA 0.242***
(3.282)
Awareness about Nutrition from Veg (Scale) -0.0345
(-0.340)
Access to Extension Service (dummy) 0.322*
(1.906)
Access to Credit Service (dummy) -0.219
(-0.776)

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Market Access…. (1)
VARIABLES with regional_effect
Log of Total Input cost 0.127*
(1.876)
Time_seed (dummy) -0.0765
(-0.332)
Price_seed (dummy) 0.174
(0.767)
Quality_seed (dummy) -0.0257
(-0.117)
Access to Motor Road 1.010***
(2.729)
Home to Sales Location (KM) -0.00825**
(-2.004)
Transaction Time at Sales Location (Hrs) -0.0154
(-0.530)
Production of TAVs (Kg) 0.000389***
(5.657)
Constant 8.850***
(9.642)
Observations 145
R-squared 0.442
t-statistics in parentheses
*** p<0.01, ** p<0.05, * p<0.1

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African eggplant is now a popular cash crop in Tanzania
Farmers get on the average
$1,200/ha/season

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Line DB3
Linking farmers to High value markets
Linkage to high
value markets

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Conclusions and Policy Recommendations
• Target intervention programs towards smallholders and
home gardeners since the former (44%) contributes the
highest volume of TAVs for both market and home
consumption.
• In addition to higher farm gate values of TAVs per unit
area, HHs seem to be much aware of the their nutritional
importance ; a main driver of their production &
consumption decisions. Need to measure dietary diversity.
• There are marked regional differences in TAV preferences
that need to be noted in targeting future interventions.
• Need for farmers to target high value added niche markets
for enhanced income and economic empowerment of women.

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AmaranthEthiopian mustard
Jute mallow
Affrican eggplant
Okra
Thank You
Bitter leafRoselle
Moringa

Victor Afari Sefa, AVRDC "The Role of Traditional Vegetables on Household Economy and Nutritional Outcomes in Tanzania"

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