Accessibilty of bean seed delivery channels and farmers' willingness to participate in conventional...

ACCESSIBILITY OF BEAN SEED SOURCES AND FARMERS’ WILLINGNESS TO PARTICIPATE IN CONVENTIONAL AND

ALTERNATIVE IMPROVED BEAN SEED DELIVERY CHANNELS

Msc Thesis Research (MAAE)

Innocent Bikara

2012/HD/60U

Supervisors: Prof. Johnny Mugisha

Dr. Enid Katungi

INTRODUCTION• Quantity of various crops produced in SSA has generally been increasing over

the years

• Increase in production of many of these crops has mainly been a result of increased land allocation to the crops rather than from yield gain (Akibode, 2011; Breisinger et al., 2009; Gordon, 2000).

Crop

CountriesCongo Ghana Kenya Malawi Tanzania Uganda

Bananas 91

Beans 43 76 83 50Cassava 69

Coffee, green 90

Groundnuts 95 55 62 55

Maize 86 46 62 52

Millet 42 79 77

Pigeon peas 69

Rice, paddy 53 52 51

Sorghum 91 86

Table 1: Percent of 1961 to 2014 production increase as a result of area expansion

INTRODUCTION• With increasing population pressure, there is limited scope for further increase in

cultivated area (Breisinger et al., 2009).

• Agricultural intensification thru yield enhancing technologies, improved (bean)

seed, one of them.

• These technologies, such as improved (bean) seed, actually exist.

101 marketable bean varieties were released in seven countries East and Central Africa (Burundi, DRC,

Rwanda, Uganda, Ethiopia, Madagascar and Kenya) between 2009 and 2014 (Rubyogo et al., 2014).

• The majority of the already developed multi-trait varieties are yet to reach the

target recipients (Larochelle et al., 2013; Ogwal et al., 2012; Barnett et al., 2011).

• Results in perpetual yield gaps.

INTRODUCTION

Countries

Crop

Banana &

PlantainsCassava Groundnuts Maize Millet Rice Sorghum Beans

Congo 20 21 47 46 51

Ethiopia 40 35 35 27 29 36

Kenya 28 35 32 58 54 42 60

Malawi 34 16 52 60 60 52 62

Nigeria 45 15 21 45 25 30 41

Rwanda 36 35 30 46 42 8 37

Tanzania 44 35 32 45 55 37 42

Uganda 33 18 41 52 20 44 46 70

Zambia 61 34 46 49 52 54 60

Table 2: Percent Yield Gaps for Selected Crops in selected SSA Countries

Sources: You et al. (2014), Sebuwufu (2013)

STATEMENT OF THE PROBLEM

• Most of the farmers in SSA are smallholders

• Their seed demand is heterogeneous and yet the conventional seed

delivery model (seed co.s & a network of agro-input dealers)

concentrates mainly on a small range of crops that they find profitable

(AGRA, 2015; Romney, 2013)

• The use of improved seed of varieties of staple food crops, especially

those of OPVs and vegetatively propagated crops, has eluded many

farmers.


• Muthoni et al. (2007) reported that between 1996 and 2004

13%, Ethiopia

25%, Rwanda

22%, DRC

18%, Uganda

• PABRA, NBRPs and CIAT have been promoting the formation of integrated bean

seed systems (CIAT, 2013; Buruchara et al., 2011).

Multi-stakeholder, small seed pkts, seed credit, farmer groups to produce quality

declared seed

Bean varieties released, that were multiplied and delivered by the formal seed sectors


• These farmer groups (small commercial seed enterprises) are an alternative

means of delivering improved bean seed to marginal farmers

• Katungi et al. (2011) conducted a cost-benefit analysis for farmer-based seed

production of common bean in Kenya.

• Beyene (2010) and Yetagesu (2015) both examined the determinants of land

allocation to seed production in Ethiopia.

• No empirical comparative analysis of the conventional and alternative bean

seed delivery channels has been undertaken.


• Similarly, the effectiveness of the seed delivery channels

Accessibility by farmers

Farmers’ willingness to participate in the purchase and supply of improved been seed is

not well known.

• This makes it difficult for decision makers to understand the key success factors

for these bean seed delivery models and how best to target farmers.

OBJECTIVES

To assess the equity of existing bean seed sources and examine farmers’

willingness to participate as buyers and producers of improved bean seed.

Specific objectives:

i. To assess the reach of the bean sources across geographical space, gender

and wealth strata.

ii. To assess the factors that influence farmers’ willingness to participate in

seed production.

iii. To assess the factors that influence farmers’ decision to buy improved bean

seed from agro-input dealers and LSPs.

HYPOTHESES

i. All existing bean seed sources are equitable with respect to geographical

space, gender and wealth strata.

ii. Farmer, farm, household and institutional factors do not affect farmers’

willingness to participate in seed production.

iii. Farmer, farm, household and institutional factors do not affect farmers’

decision to by seed from agro-input dealers and LSPs.

METHODOLOGY

METHODOLOGY

• 2 villages randomly selected from @s/c

• In @ village, a comprehensive list of households was obtained from a local leader.

• Systematic random sampling, with a random start, was employed in selecting 15

households from the list (270 hhs, 263 hhs)

• Non-bean growing hhs were replaced with the nearest neighbor (10 percent)

• Semi-structured questionnaire administered

• Hh survey complemented by FGDs with farmer groups growing bean seed &

interviews with agro-input dealers found selling improved bean seed

METHODOLOGY

• Objective 1:

ANOVA (F-test)

Z-test for equality of proportions

Spearman’s and Kendal’s rank correlation statistics

• Objective 2 & 3

• Econometric model

Dependent variable dichotomous

choice (Yes, No)

Probit Logit

Participation

Ordinary probit Ordered

probit

Bivariate probit

Natural ordering, e.g none, LSP, Agro, both

Joint probability

METHODOLOGY

ii XY

,0

,1

i

i

i TXif

TXifY

Probit model

METHODOLOGY

METHODOLOGY• Objective 2: Apriori expectations

Variable Name Type Description [Value] A priori

Signs

Household Characteristics

AGE Continuous Age of household head in completed years -

OFFARMINC Binary If household had other off-farm income [1=Yes, 0=No] +

RENT Binary If household rents land [1=Yes, 0=No] -

HHGENDER Binary If household head is female [1=Yes, 0=No] -

FAMLABOR Continuous Availability of family labor proxied by number of

household members between the age of 14& 65 years +

LABOROFAM Continuous Labor supplied off-farm. Generated as an interaction term

between OFFARMINC & FAMLABOR -

ASSET Continuous Value of household semi-durable assets (Ugsh ‘000,000) +

TLU Continuous Tropical livestock units in the household +

MARKPART Binary If household sold bean grain from previous season’s

harvest [1=Yes, 0=No] +

BREVENUE Continuous Income from the sale of beans from previous season’s

harvest (Ugsh, ‘000,000) +

Farmer Characteristics

EDUCFAMR Continuous Number of completed years of formal education +

GENDER Binary If plot owner/respondent is female [1=Yes, 0=No] -

OTHERVAR Binary If farmer prefers another variety [1=Yes, 0=No] +

TRAIN Binary If farmer has ever been trained or sensitized on issues

related to improved bean seed [1=Yes, 0=No] +

FAKESEED Binary If farmer has ever purchased substandard bean seed

[1=Yes, 0=No] +

METHODOLOGY• Objective 2: Apriori expectations (cont.)

Farm Characteristics

FARMSIZE Continuous Size of the farm (Acres)

Institutional Characteristics

GROUP Binary If member of household belongs to a farmer group [1=Yes,

0=No] +

EXTENSION Continuous Number of extension visits received by the farm household

in the previous cultivation season +

GRAINPRI Continuous Village level grain price (Ugsh, ‘1000) +

LOCATION Discrete Geographical location indicator. Used alternatively to

indicate district, sub-county, parish or village +/-

METHODOLOGY• Objective 3: Apriori expectations

Variable Name Type Description [Value] Apriori

Signs


FARMSIZE Continuous Size of cultivated land (acres) +/-

LANDBEAN Continuous Proportion of land allocated to bean growing +

NHI Continuous Natural hazard index +

FERTILIZER Binary If household used chemical fertilizer on the farm [1=Yes,

0=No]

+


LAND Continuous Size of land owned by the household (acres) +

MARITAL Binary If household head is married [1=Yes, 0=No] +

PURCH Binary If household used purchased agro-inputs [1=Yes, 0=No] +

BEANREV Continuous Revenue earned from the sale of beans from preceding

season’s harvest (Ugsh. ‘1000,000)

+

RENT Binary If household rented land [1=Yes, 0=No] -

HHGENDER Binary If household head is female [1=Yes, 0=No] +/-

MARKPART Continuous Proportion of bean grain harvest (from preceding season)

sold

+

FAMLABOR Continuous Family labor, proxied by number of household members

between the ages of 14 and 65 years

+

LABOROFAM Continuous Labor supplied off-farm. Generated as an interaction term

between OFFARMINC & FAMLABOR

-

ASSET Continuous Value of household semi-durable assets (Ugsh ‘000000) +

TLU Continuous Tropical livestock units in the household +


FAMAGE Continuous Age of farmer in completed years -

EDUCFAMR Continuous Number of completed years of formal education +

GENDER Binary If owner of respondent (bean farmer) is female [1=Yes,

0=No]

+/-

METHODOLOGY• Objective 3: Apriori expectations (cont..)


GRAINPRI Continuous Price received for bean grain, village, parish, sub-county

and district averages progressively used for those who did

not sale

-

AWARENESS Binary If farmer is aware of seed distribution channel [1=Yes,

0=No]

+

GROUP Binary If a household member belongs to a farmer group [1=Yes,

0=No]

+

EXTENSION Continuous Number of extension visits received by the farm household

in the previous cultivation season

+

CREDIT Binary If farmer was a recipient of credit/loan in preceding one

year [1=Yes, 0=No]

+

TRAIN Binary If farmer has ever been trained or sensitized on issues

related to improved bean seed [1=Yes, 0=No]

DISTRICT Discrete District where farm household is located [1=Busia, 2=Lira

3=Rakai]

+/-

Seed related Characteristics

FAKESEED Binary If farmer has ever purchased fake or sub-standard seed

[1=Yes, 0=No]

+

OTHERVAR Binary If farmer prefers a variety different from the one(s) found

in the [1=Yes, 0=No]

+

MEANS Binary If farmer purchased bean seed [1=Yes, 0=No] +

OWNSEED Binary If farmer used own saved seed [1=Yes, 0=No] -

IISI Continuous Importance of improved seed index +

METHODOLOGY• Objective 3: Apriori expectations (cont..)

LABEL Discrete Importance of labeling seed [1=Not important 2=Slightly

important

3=Somewhat important 4=Moderately important

5=Extremely important]

+

PACKAGING Discrete Importance of packaging seed [1=Not important

2=Slightly important



+

PRICE Discrete Importance of seed price in decision to purchase [1=Not

important 2=Slightly important



-

SEI Continuous Seed experience index -

OSEI Continuous Seed experience index for own saved seed -

RESULTS

Source of Bean Seed

Mean Distance (km)

Pooled Busia Lira Rakai P-value

Agro-dealer 11.5 12.0 17.0 10.3 0.918

Government/NGOs 8.0 8.0 8.0 __ 1.000

Local shop 5.8 5.3 7.7 4.1 0.008

Neighbor or Friend 0.9 1.0 0.9 0.9 0.996

P-value 0.000 0.307 0.105 0.012

• Objective 1:

Geographical distance

The market-based conventional channel of improved bean seed (agro-input dealers) is located within

the locale of bean growing households, alternatives such as local grain/seed shops are located closer

RESULTS• Objective 1:

Gender equity (not equality)

PooledDistrict

Busia Lira Rakai

Gender

indicator

Farmer 0.414 0.402 0.352 0.488

Household head 0.190 0.184 0.114 0.272

Proportion of female farmers and female-headed household in the study areas



Gender of the farmer

Source Pooled Busia Lira Rakai

Mean P-val. Mean P-val. Mean P-val. Mean P-val.

Agro-input dealer 0.142 0.145 na na na na 0.200 0.197

Government 0.750 0.173 1.000 0.034 0.000 na na naLocal shops 0.403 0.806 0.333 0.330 0.395 0.554 0.535 0.618

Neighbor/friend 0.429 0.915 1.000 0.223 0.000 0.202 0.500 0.943

Own stock 0.429 0.756 0.441 0.644 0.350 0.976 0.488 0.997

0.402



Gender of the household head

Source Pooled Busia Lira Rakai

Mean P-val. Mean P-val. Mean P-val. Mean P-val.

Agro-input dealer 0.000 0.200 0.000 0.635 0.000 0.720 0.000 0.171

Government 0.250 0.760 0.333 0.504 0.000 0.720 na na

Local shops 0.134 0.122 0.083 0.072 0.116 0.957 0.250 0.787

Neighbor/friend 0.214 0.818 1.000 0.035 0.000 0.535 0.200 0.606

Own stock 0.252 0.085 0.294 0.097 0.125 0.821 0.333 0.361

0.1840.190


Gender equity

The results different depending on the choice of the gender indicator.

Agricultural production simultaneously carried out on many plots controlled

by different members of the household

Household head may not necessarily be the decision-maker as regards cropping

and input choices (Smale & Mason, 2012; Peterman et al., 2010; Udry et al.,

1995)

The findings at the farmer level are thus of more empirical importance

Bean seed sources were equitable with respect to gender


Wealth strata

Sources PooledDistricts

Busia Lira Rakai P-valueMean TLUAgro-input dealer 2.449 9.280 5.300 0.512 0.000

Government 1.35 1.267 1.600 __ 0.8328

Local shops 0.893 0.701 0.969 1.103 0.3196

Neighbor/friend 0.616 0.300 1.420 0.406 0.2330

Own stock 1.297 1.237 1.695 0.988 0.1503

P-value 0.025 0.000 0.049 0.4453

Mean semi-durable asset value (‘000000 UGX)Agro-input dealer 0.542 0.178 0.215 0.680 0.786

Government 0.174 0.153 0.235 __ 0.073

Local shops 0.270 0.307 0.231 0.266 0.790

Neighbor/friend 0.161 0.000 0.302 0.135 0.123

Own stock 0.269 0.145 0.267 0.361 0.206

P-value 0.6142 0.667 0.9962 0.361


Wealth strata

Spearman’s and Kendal’s rank correlation statistics: TLU rank ≠ semi-durable assets

rank

Semi-durable asset weights subjective valuations by respondents

TLU weights standard values

Livestock endowment was highest among households that obtained bean seed from

agro-input dealers (however, n=7), caution

Government/NGO (2), own stock (3) and local shops (4), neighbors/friends (5/least)

Inconclusive, but alternatives, such as shops could reach less endowed farmers

RESULTS• Objective 2: Willingness to participate in bean seed productionVariable

Model A Model B Model C

Coeff. Marginal

Effect

Coeff.

Marginal

Effect

Coeff.

Marginal

Effect


AGE -0.048* -0.007 -0.048* -0.007 -0.051* -0.008

OFFARMINC -0.677 -0.677 -0.735

RENT 0.145 0.113 0.146

HHGENDER 0.620^ 0.093 0.565 0.580

FAMLABOR -0.078 -0.074 -0.085

LABOROFAM 0.325 0.325 0.351^ 0.052

ASSET 1.550^ 0.233 1.380^ 0.206 1.450 0.046

TLU 0.308* 0.046 0.290** 0.043 0.313* 0.214

MARKPART 1.094* 0.165 1.048** 0.156 1.129* 0.166

BREVENUE -2.320 -2.390 -1.87


EDUCFAMR -0.052 -0.058 -0.060

GENDER -0.912* -0.137 -0.913* -0.136 -0.939* -0.138

OTHERVAR 0.412 0.401 0.382

TRAIN 0.479 0.532 0.540

FAKESEED 1.152* 0.173 1.123* 0.168 1.155* 0.170


FARMSIZE -0.042 -0.042 -0.059


GRAINPRI -0.399 0.417 -0.782** -0.115

GROUP 0.836** 0.126 0.838** 0.125 0.788** 0.116

EXTENSION -0.233 -0.263 -0.227

LOCATION -0.002 0.028 0.051^ 0.008

Constant 3.249* 3.098* 3.561*

Goodness-of-fit

Number of

observations

263 263 263

LR chi2 (df=20) 95.06 96.18 98.01

Prob > chi2 0.0000 0.0000 0.0000

Log likelihood -71.24 -70.67 -69.76

McFadden’s R2 0.4002 0.4049 0.4126

Mean VIF 1.61 1.60 1.63

Count R2

(Correctly

classified)

87.45 88.21 89.35

Hosmer-

Lemeshow

chi2(8), 10

groups

5.46 3.62 13.08

Prob > chi2 0.7071 0.8896 0.1093

*, ** & ^ denotes statistical significance at 1%, 5%, & 10% levels respectively.

RESULTSObjective 3: Willingness to buy improved bean seed

Measure of goodness-of-fit Agro-input Dealer LSP

Reduced Model Unreduced Model Reduced Model Unreduced Model

Number of observations 250 250 257 257

LR chi2 (df=32, 33, 28, 29) 90.03 92.70 69.38 69.38

Prob > chi2 0.0000 0.0000 0.0000 0.0000

Log likelihood -44.705 -43.371 -49.514 -49.512

Number of iterations 6 6 6 6

McFadden’s R2 0.5017 0.5166 0.4120 0.4120

Mean VIF 2.71 5.40 2.64 5.54

Count R2 (Correctly classified) 92.40 92.00 91.83 91.83

Hosmer-Lemeshow chi2(8), 10

groups

3.16 4.51 21.02 21.48

Prob > chi2 0.9241 0.8088 0.0071 0.0060

Likelihood-ratio test for nested models: Reduced models found to be true

Agro-input dealer: p-value=0.1023

LSP: p-value=0.9524

RESULTS

Agro-input Dealer LSP

Variable Coeff. Marg. Coeff. Marg.

Farm characteristics

FARMSIZE -0.039 -0.159

LANDBEAN -0.654 -0.245

NHI 0.271 -0.104

FERTILIZER -0.479

Household characteristics

LAND -0.062

MARITAL -1.148 -0.786

PURCH -0.042 -0.327

BEANREV 8.750

RENT -0.200

HHGENDER -0.005 0.254

MARKPART -0.407 0.737

FAMLABOR -0.093 -0.063

LABOROFAM -0.135 -0.213** -0.023

ASSET 1.080 1.350

TLU 0.578** 0.058 0.191

Farmer characteristics

FAMAGE 0.005 -0.023^ -0.002

EDUCFAMR -0.030

GENDER 0.368 -0.302

Institutional characteristics

GRAINPRI -0.213 -0.513

AWARENESS 1.248* 0.125

GROUP 0.917** 0.092 0.362

EXTENSION -0.117 -0.165

CREDIT -1.225** -0.123 1.140

TRAIN -0.892^ -0.089

DISTRICT -0.747** -0.075 -0.128

Seed related characteristics

FAKESEED 0.017 0.723^ 0.079

OTHERVAR 2.007* 0.201 1.432* 0.156

MEANS 1.172 1.046

OWNSEED 0.546 0.593

IISI 1.179* 0.118 0.419

LABEL 0.181 0.460^ 0.050

PACKAGING -0.158 -0.289

PRICE -0.158

SEI -0.119 0.063

OSEI

Constant -3.227 1.083

*, ** & ^ denotes statistical significance at 1%, 5%, & 10% levels respectively.

Objective 3: Willingness to buy improved bean seed

RESULTSObjective 3 (Additional)

Pooled Busia Lira Rakai P-value

PricesAgro-input dealer 4,023 4,500 4,538 4,006

LSP 1,664 1,459 1,682 1,701

WTPAa

Agro-input dealer2,295b

(1,050)

2,353b

(887)

2,332b

(1,096)

2,203b

(1,160)0.6362

LSP1,824c

(825)

1,756c

(549)

1775

(751)

1,936c

(1,075)0.3241

a-Figure in brackets are standard deviationsb-significantly lower than selling prices at one percent levelc-significantly higher than the selling price at five percent level.

CONCLUSIONS & RECOMMENDATIONS• Conventional market-based sources of improved bean seed (agro-input

dealers) were found to be the most distant from bean growing households

Alternative sources of improved bean seed established closer to bean growing

households may enhance access

• The bean seed sources were found to be equitable in terms of gender (farmer)

• The access to bean seed sources was significantly varied by wealth strata.

Indication that agro-input dealers are a primary source of bean seed for households with

high livestock endowment, tho sample limitations necessitate caution..

Channeling improved bean seed thru agro-input dealers may not benefit marginal farmers

CONCLUSIONS & RECOMMENDATIONS• Willingness to participate in bean seed production

Incentives for bean seed production E.g price guarantees and/or a coupon system,

supported by the public sector.

• Willingness to buy improved bean seed production from agro-input dealers

Demand ↑sed by ↑sed awareness of the availability and importance of using improved

seed, especially among farmer groups.

Subsidized to make it affordable to less endowed farmers.

CONCLUSIONS & RECOMMENDATIONS• Willingness to buy improved bean seed production from LSPs

Targeting existing farmer groups, households with relatively young heads, and farmers

who participate in the bean output market will most likely enhance the success of bean

seed production.

Labelling bean seed produced by LSPs could improve their acceptance.

• Monitoring (or stepping up) the quality of bean seed provided by both agro-

input dealers and LSPs to curb opportunism, would maintain the trust in these

channels and enhance demand.

CONCLUSIONS & RECOMMENDATIONS• Overall, a multi-pronged approach will most likely deliver improved bean seed

to a larger scope of farmers, at affordable prices, within their locale, leading to

more socially efficient outcomes (Pareto optimality)

Accessibilty of bean seed delivery channels and farmers' willingness to participate in conventional...

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