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

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The World Vegetable Centervegetables + 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

PartIII

• 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 unhealthyand imbalanced diets has led to increased publichealth concerns and advocacy for dietarydiversification into highly nutritious traditionalvegetables and fruits as essential complements tostaple-based diets for attainment of several MDGs.

• Production and marketing of traditional Africanvegetables (TAVs) in Tanzania and other SSAcountries are facing critical bottlenecks.

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Research Questions & ObjectivesResearch Questions

• Does farmer’ increased awareness of nutritionalimportance of TAVs enhance their decision todiversify cultivation of major staples to TAVs?

• Do farmers gets better market access for TAVscompared to major staple crops?

Objectives

1. Examine the effect of nutritional awareness offarmers towards adoption of selected TAVs.

2. Measure determinants of TAV market participation

3. Suggest entry points for formulating policies toimprove smallholders’ market participation viapromotion 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 Areaand 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) 3218

2.8 (1.1) 2.7 (0.5) 0.5 34.1

Large (>4ha) 105

6.0 (2.2) 6.9 (3.4) 0.5 27.2

Overall 181100

1.4 (1.6) 1.4 (1.8) 0.5 100

NOA: Net operated areaIn 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

129

20

58

0

27

02

22

1215

55

32

12

20

0

10

20

30

40

50

60

70

80

ArushaTangaDarMorogoroDodomaOverallAmaranth 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_effectAwareness 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 145R-squared 0.624 0.624Number of Region 5t-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 145R-squared 0.442t-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

Technology

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