Mu igi, Michael; Ngui, Dianah; Ogada, Mau ice Juma
A icle
Impac o smallholde banana con ac a ming on a m
p oduc i i y and income in Kenya
Cogen Economics & Finance
P o ided in Coope a ion wi h:
Taylo & F ancis G oup
Sugges ed Ci a ion: Mu igi, Michael; Ngui, Dianah; Ogada, Mau ice Juma (2024) : Impac o
smallholde banana con ac a ming on a m p oduc i i y and income in Kenya, Cogen Economics
& Finance, ISSN 2332-2039, Taylo & F ancis, Abingdon, Vol. 12, Iss. 1, pp. 1-12,
h ps://doi.o g/10.1080/23322039.2024.2364353
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Impac o smallholde banana con ac a ming
on a m p oduc i i y and income in Kenya
Michael Mu igi, Dianah Ngui & Mau ice Juma Ogada
To ci e his a icle: Michael Mu igi, Dianah Ngui & Mau ice Juma Ogada (2024) Impac o
smallholde banana con ac a ming on a m p oduc i i y and income in Kenya, Cogen
Economics & Finance, 12:1, 2364353, DOI: 10.1080/23322039.2024.2364353
To link o his a icle: h ps://doi.o g/10.1080/23322039.2024.2364353
© 2024 The Au ho (s). Published by In o ma
UK Limi ed, ading as Taylo & F ancis
G oup
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DEVELOPMENT ECONOMICS | RESEARCH ARTICLE
Impac o smallholde banana con ac a ming on a m p oduc i i y
and income in Kenya
Michael Mu igi
a
, Dianah Ngui
b
and Mau ice Juma Ogada
c
a
School o Economics, Kenya a Uni e si y and Pa ne ship o Economic Policy (PEP), Nai obi, Kenya;
b
A ica Economic
Resea ch Conso ium (AERC), Nai obi, Kenya;
c
Tai a Ta e a Uni e si y, Nai obi, Kenya
ABSTRACT
Smallholde banana a me s in Kenya g apple wi h declining a m p oduc i i y and low ma -
ke p ices in a agmen ed, b oke -domina ed ma ke . To add ess hese challenges, he
Kenya Na ional Banana De elopmen S a egy ad oca es o he adop ion o con ac a m-
ing. This esea ch u ilizes Di e ence-in-Di e ences (DID) eg ession analysis o assess he
impac s o smallholde pa icipa ion in banana con ac a ming on a m p oduc i i y and
income. The empi ical esul s e eal posi i e impac s, emphasizing he po en ial o con ac
a ming o enhance p oduc i i y, inc ease incomes o smallholde a me s, and in igo a e
u al economies. These indings p o ide aluable insigh s in o he e icacy o con ac a m-
ing as a s a egy o add essing challenges in banana a ming. To maximize his po en ial,
he s udy ecommends policy in e en ions, including inc eased go e nmen suppo ,
imp o emen s in in as uc u e and ma ke accessibili y, ein o ced ins i u ional backing,
and he p omo ion o sus ainable p ac ices. These measu es aim o secu e endu ing bene-
i s o bo h a me s and ood ma ke ing i ms in Kenya.
IMPACT STATEMENT
This s udy examines he e ec i eness o con ac a ming in add essing he s uggles
o Kenyan smallholde banana a me s. The s udy inds ha pa icipa ing in con ac
a ming leads o inc eased a m p oduc i i y and income o hese a me s. These ind-
ings highligh he po en ial o con ac a ming o e i alize u al economies. To maxi-
mize hese bene i s, he esea ch ecommends policy changes, such as inc eased
go e nmen suppo and imp o ed in as uc u e, o c ea e a sus ainable and mu ually
bene icial sys em o bo h a me s and ood companies in Kenya.
ARTICLE HISTORY
Recei ed 9 Feb ua y 2024
Re ised 22 Ap il 2024
Accep ed 29 May 2024
KEYWORDS
Banana; con ac ; impac ;
income; Kenya; p oduc i i y;
smallholde
REVIEWING EDITOR
Goodness Aye, Uni e si y o
Ag icul u e, Nige ia
SUBJECTS
Ru al De elopmen ;
De elopmen S udies;
Economics; Resea ch
Me hods in De elopmen
S udies; Sus ainable
De elopmen
In oduc ion
Ag icul u e se es as a c i ical d i e o economic de elopmen in Sub-Saha an A ica (SSA) coun ies, signi i-
can ly con ibu ing o employmen , li elihoods, and GDP. In Kenya, whe e ag icul u e di ec ly cons i u es
33% o he GDP wi h an addi ional 27% indi ec ly, he ho icul u al sec o s ands ou as a linchpin, con ibu-
ing subs an ially o o eign exchange ea nings, ood secu i y, and po e y alle ia ion (IFAD, 2019; Republic
o Kenya, 2019). Howe e , despi e i s g ow h, challenges such as high p oduc ion cos s, low a m p oduc i i y,
and inadequa e ma ke ing sys ems pose h ea s o he sus ainabili y o he ho icul u al sec o .
O pa icula impo ance wi hin Kenya’s ho icul u al domain is banana a ming, eme ging as he lead-
ing ho icul u al c op, comp ising 16 pe cen o he o al alue o ho icul u e and 33 pe cen o he
o al alue o ui s (AFA, 2021). Mos bananas a e cul i a ed on smallholde a ms, e lec ing a shi
owa ds his c op as a means o enhancing household ood secu i y and p o iding an al e na i e income
sou ce (Obaga & Mwau a, 2018). The signi icance o he banana c op is e iden in i s con inuous expan-
sion, wi h he p oduc ion a ea g owing om 113,660 ac es in 2008 o 179,040 ac es in 2020 (AFA, 2021).
CONTACT Michael Mu igi [email p o ec ed] School o Economics, Kenya a Uni e si y and Pa ne ship o Economic Policy (PEP),
Nai obi, Kenya
ß2024 The Au ho (s). Published by In o ma UK Limi ed, ading as Taylo & F ancis G oup
This is an Open Access a icle dis ibu ed unde he e ms o he C ea i e Commons A ibu ion License (h p://c ea i ecommons.o g/licenses/by/4.0/), which
pe mi s un es ic ed use, dis ibu ion, and ep oduc ion in any medium, p o ided he o iginal wo k is p ope ly ci ed. The e ms on which his a icle has been
published allow he pos ing o he Accep ed Manusc ip in a eposi o y by he au ho (s) o wi h hei consen .
COGENT ECONOMICS & FINANCE
2024, VOL. 12, NO. 1, 2364353
h ps://doi.o g/10.1080/23322039.2024.2364353
Unlike o he ho icul u al c ops, banana is p oduced yea - ound, wi h ising demand bo h domes ically
and in e na ionally due o changing consump ion habi s (Obaga & Mwau a, 2018).
Howe e , he success o he banana sec o aces challenges, including high p oduc ion cos s, low a m
p oduc i i y, and subop imal ma ke ing sys ems (IFAD, 2019). In esponse, a ious in e en ions, including
he p omo ion o con ac a ming, ha e been implemen ed by go e nmen al, non-go e nmen al, and p i-
a e sec o en i ies. Con ac a ming, in ol ing ag eemen s be ween buye s and a me s, is seen as a
s a egy o add ess p oduc ion and ma ke ing challenges. Majo co po a e en i ies such as S awi Foods
and F ui s Limi ed, Neo-Kenya, and Twiga Foods, along wi h go e nmen al and non-go e nmen al ini ia-
i es like he Smallholde Ho icul u e Empowe men P ojec (SHEP), Kenya Ag icul u al Value Chain
En e p ises (KAVES) p ojec , Na ional Ag icul u al and Ru al Inclusi e G ow h P ojec (NARIGP), and he
’Ini ia i e o Build a Compe i i e Banana Indus y in Kenya’P ojec , ha e ac i ely endo sed and ad anced
he cause o con ac a ming wi hin he banana sec o (AGRA, 2017; Bisma ck-Os en, 2021; Republic o
Kenya, 2020;USAID.,2018). Despi e hese e o s, banana p oduc ion pe uni a ea in Kenya has no ably
declined om abou 14,800 kilog ammes pe ac e in 2008 o 8,200 kilog ammes pe ac e in 2020, posing
a subs an ial sho all om he Na ional Banana De elopmen S a egy’s a ge ed 16,000 onnes pe ac e,
while income o smallholde banana a me s emains s agnan (AFA, 2021; Republic o Kenya, 2014).
S udies ac oss a ious egions and c ops pain a mixed pic u e o con ac a ming’s impac on a m p oduc -
i i y and income. Igweosca (2014) highligh s signi ican ly highe cassa a a m p oduc i i y o con ac a me s
in Nige ia. Simila ly, in Tanzania, Mpe a e al. (2018) ound ha sun lowe a me s unde con ac s inc eased
land p oduc i i y by 20.8–25.1 kilog ams pe ac e, while Khan e al. (2019) e ealed signi ican ly highe p oduc -
i i y o po a o con ac a me s in Pakis an. Con e sely, Maganga-Nsimbila (2021)usinga ea men e ec s
model ound no signi ican impac o con ac a ming on smallholde co on a me s’p oduc i i y in Tanzania.
Mwambi e al. (2016) in Kenya epo ed no signi ican di e ence in incomes be ween con ac and non-con ac
a ocado a me s. In Nepal, Mish a e al. (2016) ound posi i e impac s o con ac High Yielding Va ie ies (HYV)
seed a ming on e enues and p o i s, while Olounlade e al. (2020) in Benin epo ed a signi ican ly nega i e
e ec o con ac ice a ming on income. These di e se indings unde sco e he need o conside con ex in
e alua ing he e ec i eness o con ac a ming s a egies o enhancing a m p oduc i i y and income.
This s udy adds o he exis ing li e a u e on con ac a ming, which has yielded inconclusi e indings
ega ding i s impac on a m p oduc i i y and income, wi h a ia ions obse ed ac oss c ops, ag icul u al
en e p ises, and egions (Wo ld Bank, 2017). Speci ically ocusing on smallholde banana a ming in
Kenya, a sec o o en o e looked in esea ch, his s udy employs he Di e ence-in-Di e ences (DID)
me hodology o analyse he impac o con ac a ming on a m p oduc i i y and income.
While p opensi y sco e ma ching is commonly used in he li e a u e o es ima e he impac o con ac
a ming on a m p oduc i i y o income, i elies hea ily on he condi ional independence assump ion and
only conside s obse ed (and obse able) cha ac e is ics, dis ega ding unobse able ac o s (F ed iksson &
Oli ei a, 2019). This limi a ion becomes pa icula ly challenging in he con ex o con ac a ming, whe e
a me s sel -selec based on ypically unobse ed ai s such as hei isk o ime p e e ences, pe cep ions, o
en ep eneu ial abili ies. S udies employing ma ching echniques o en do so wi h c oss-sec ional da a, which
poses u he limi a ions. Howe e , as no ed by F ed iksson and Oli ei a (2019), DID me hodology in eg a es
insigh s om bo h c oss-sec ional ea men -con ol compa isons and be o e-a e s udies, o e ing a mo e
obus es ima ion o causal e ec s. The e o e, i is deemed app op ia e o p o ide a comp ehensi e unde -
s anding o he a e age ea men e ec (ATE) wi hin he con ex o banana con ac a ming in Kenya.
The subsequen sec ions o he pape a e s uc u ed as ollows: ‘Ma e ials and me hods’sec ion delin-
ea es he me hodological app oach employed, ‘Empi ical esul s and discussion’sec ion p esen s and
discusses he esul s, and ‘Conclusion and policy implica ions’sec ion concludes he s udy while d awing
in e ences ega ding policy implica ions.
Ma e ials and me hods
Da a
The s udy u ilized seconda y da a sou ced om he ’Ini ia i e o Build a Compe i i e Banana Indus y in
Kenya’P ojec , which ecei ed unding om he Alliance o G een Re olu ion in A ica (AGRA) and he
2 M. MURIGI ET AL.
In e na ional Fund o Ag icul u al De elopmen (IFAD). The Uni e si y o Sydney and he Uni e si y o
Nai obi collabo a ed on he p ojec , acili a ed by he In e na ional Ini ia i e o Impac E alua ion (3ie).
Twiga Foods played a c ucial ole in engaging willing a me s in con ac a ming and deli e ing i al
ex ension se ices o imp o e ag icul u al p ac ices and p oduc i i y among smallholde s. The company
also acili a ed eliable and s eady ma ke access o smallholde banana a me s by ou lining p icing
mechanisms and paymen e ms wi hin he con ac . The con ac gua an eed he a me s an appealing
p ice, exceeding he local ma ke a e, wi h paymen made di ec ly a he a m ga e upon banana collec-
ion. Fu he mo e, he con ac manda ed ha Twiga Foods p o ide ex ension se ices o he a me s a
no addi ional expense. In e u n, he a me s we e obliged o ollow he p esc ibed guidelines o
banana cul i a ion and sell hei ha es exclusi ely o he con ac ing i m.
Da a collec ion ook place in Ki inyaga Coun y om 2,231 households du ing wo su ey ounds con-
duc ed be ween 2016 and 2020: he Baseline ound (Oc obe –Decembe 2016) and he Endline ound
(Oc obe 2019–Janua y 2020). This ex ensi e da ase co e s a wide ange o aspec s, including socioeco-
nomic de ails, land owne ship, banana p oduc ion p ac ices, decision-making in banana p oduc ion,
echnology adop ion, pa icipa ion in con ac a ming, household labou alloca ion, income and expend-
i u e, banana coope a i e in ol emen , aining, ime p e e ences, isk p e e ences, and social ne wo ks.
Theo e ical model
Random U ili y Theo y (RUT) p o ides a use ul amewo k o analysing he impac o con ac a ming
pa icipa ion on household u ili y by conside ing how i in luences a m p oduc i i y and income. Since
pa icipa ion in con ac a ming is a disc e e choice, RUT allows o compa ing a household’s expec ed
u ili y i hey engage in con ac a ming, such as banana a ming, wi h hei expec ed u ili y i hey do
no (Olounlade e al., 2020). Con ac a ming can in luence u ili y h ough i s e ec s on p oduc i i y
(e.g. access o be e inpu s, ex ension se ices) and income (e.g. gua an eed p ices, c edi o inpu s). I
households an icipa e g ea e u ili y om pa icipa ion due o hese po en ial imp o emen s in p oduc -
i i y and income, hey a e mo e inclined o pa icipa e in con ac a ming (Olounlade e al., 2020).
To es ima e he impac o banana con ac a ming pa icipa ion on a m p oduc i i y and income,
a DID design was p e e ed. DID designs compa e changes o e ime in ea men and con ol ou -
comes. Unde hese ci cums ances, he e o en exis plausible assump ions ha we can con ol o
ime-in a ian di e ences in he ea men and con ol/compa ison g oups and es ima e he causal
e ec s o he in e en ion (F ed iksson & Oli ei a, 2019;Winge al.,2018). The DID es ima e o
he impac o con ac a ming on he ou come a iables ( a m p oduc i i y and a m income) can be
w i en as ollows:
DID ¼ð
Ys¼T ea men ; ¼A e –
Ys¼T ea men ; ¼Be o eÞ–ð
Ys¼Con ol; ¼A e –
Ys¼Con ol; ¼Be o eÞ(1)
whe e Y is he ou come a iable ( a m p oduc i i y o a m income), he ba ep esen s he a e age
alue (a e aged o e indi iduals in he g oup), he g oup is indexed by sand is ime. Wi h be o e
and a e da a o he ea men and con ol g oups, he da a is hus di ided in o he ou g oups and
hedoubledi e ence–Equa ion (1) –is calcula ed. The equa ion, howe e , says no hing abou he
signi icance le el o he DID; he e o e, eg ession analysis, modelled using he ollowing equa ion, is
needed.
Yis ¼AsþB þbIs þeis (2)
whe e Asa e ea men /con ol g oup ixed e ec s; B a e he be o e/a e ixed e ec s; Is is an indica-
o a iable o ea men (¼1) o con ol (¼0) g oups; eis is he e o e m while he DID es ima e is
ob ained as he b-coe icien . To e i y ha he es ima e o bwill eco e he DID es ima e in (1), (2) is
used o ge :
EY
is js¼Con ol, ¼Be o eðÞ¼ACon ol þBBe o e (3)
EY
is js¼Con ol, ¼A e
ðÞ
¼ACon ol þBA e (4)
EY
is js¼T ea men , ¼Be o e
ðÞ
¼AT ea men þBBe o e (5)
COGENT ECONOMICS & FINANCE 3
EY
is js¼T ea men , ¼A e
ðÞ
¼AT ea men þBA e þb(6)
In he exp essions (3) o (6), E (Y
is
js) is he expec ed alue o Yis in popula ion subg oup (s, ), which
is es ima ed by he sample a e age Ys :Es ima ing (2) and plugging in he sample coun e pa o he
abo e exp essions in o (1), wi h he ha no a ion ep esen ing coe icien es ima es, gi es DID ¼^
b:
Indi idual-le el con ol a iables Xis can be added o make he eg ession mo e obus . Thus (2)
becomes:
Yis ¼AsþB þcXis þbIs þeis (7)
Empi ical model
Based on Equa ion (2), he DID eg ession model o be used in es ima ing he impac o pa icipa ing in
banana con ac a ming on banana a m p oduc i i y and income was de ined as:
Yis ¼AsþB þbIs þeis (8)
whe e Yis is he ou come a iable (banana a m p oduc i i y o income), Asa e ea men /con ol g oup
ixed e ec s, B
a e he be o e/a e ixed e ec s, Is is an indica o a iable o ea men (¼1) o con ol
(¼0) g oups, ?
is
is he e o e m while he DID es ima e is ob ained as he b-coe icien . To make he
model mo e obus , indi idual-le el con ol a iables Xis a e added (Vlachopoulou e al., 2013):
Yis ¼AsþB þcXis þbIs þeis
Empi ical esul s and discussion
The desc ip i e s a is ics we e as ollows:
As indica ed in Table 1, he s udy used a o al sample o 2,231 households engaged in banana a m-
ing. Among hese households, 35 pe cen pa icipa ed in banana con ac a ming, while he emaining
65 pe cen did no . Despi e ongoing e o s by go e nmen al and non-go e nmen al o ganiza ions o
p omo e con ac a ming as a iable s a egy o e i alizing he banana indus y and imp o ing a me
wel a e, he adop ion a e emains ela i ely low. This is p ima ily due o ac o s such as he limi ed
awa eness among smallholde a me s abou he exis ence and bene i s o con ac a ming schemes, as
well as he cons ained capaci y o ood-ma ke ing companies o en oll a me s in o such schemes
(Republic o Kenya, 2023).
The desc ip i e s a is ics also highligh ed ha he a e age size o a m households in he sample was
h ee membe s. This aligned a ou ably wi h he 2019 Kenya Popula ion and Housing Census, which
epo ed a na ional a e age household size o 3.9 membe s and Ki inyaga Coun y’s a e age o 3 mem-
be s (Kenya Na ional Bu eau o S a is ics, 2020). The a e age age o a a m household head a baseline
was 52 yea s, and he e was no signi ican di e ence in he a e age age be ween en olled/pa icipa ing
households and non-en olled/pa icipa ing households, as indica ed by he associa ed p obabili y o he
- alue (0.446). The o al ag icul u al land owned by a a m household a e aged 1.5 ac es, wi h land
unde banana cul i a ion a e aging 0.2 ac es. This unde sco es ha banana cul i a ion is p edominan ly
ca ied ou on smallholde a ms, ypically measu ing unde 5 ac es (Kenya Ag icul u al and Li es ock
Resea ch O ganiza ion (KALRO), 2019).
Rega ding banana a m p oduc i i y wi hin he s udy sample, he a e age was 2613 kilog ammes pe
ac e a baseline. Fo en olled a m households, p oduc i i y was sligh ly highe a 2633 kilog ams o
banana pe ac e compa ed o 2576 kilog ammes o non-en olled a m households. The di e ence
o app oxima ely 57, howe e , was s a is ically insigni ican , as e idenced by he associa ed p obabili y o
he - alue (0.660). A he endline, he a e age a m p oduc i i y o pa icipa ing a me s had inc eased o
3827 kilog ammes pe ac e compa ed o 2636 kilog ammes pe ac e o he non-pa icipa ing a me s,
a di e ence o 1,191, which was s a is ically signi ican a one pe cen le el.
The su eyed a m households ea ned an a e age amoun o Kenya shillings 12,406 om banana
a ming a baseline. The a e age amoun ea ned by he en olled a m households was 10,475, while he
a e age ea nings o he a m households no en olled was 15,649, hus a di e ence o abou 5,173,
4 M. MURIGI ET AL.
which was no s a is ically signi ican . A he endline, he a e age banana a m income o he pa icipa -
ing a me s had g own o 25,491 shillings compa ed o 16, 478 shillings o he non-pa icipa ing a m-
e s, a di e ence o 9,013 which was s a is ically signi ican a i e pe cen le el.
Following Nolan and Da Sil a San os (2019), s ochas ic dominance g aphs we e also used o compa e
banana a m p oduc i i y and income be ween pa icipan s and non-pa icipan s, a baseline.
Figu e 1 shows ha he dis ibu ion o banana a m p oduc i i y o he pa icipan s and non-pa icipan s
was nea ly simila o mos alues a baseline. This is because banana g owing condi ions be o e he oll-ou
o con ac a ming we e essen ially he same, and so we e he p oduc i i y le els. Also, he dis ibu ion o
banana income o he pa icipan s and non-pa icipan s was la gely simila , wi h nei he g oup domina ing
he o he a baseline. As all he banana a me s hen sold hei banana h ough he same ma ke ing chan-
nels, in open ma ke s, he a e age p ice o a kilo o bananas was oughly he same a Kenya shillings 19,
and so was hei income. No ably, he s udy sample was balanced a baseline in ela ion o he ou come
a iables o in e es : banana a m p oduc i i y and a m income.
Placebo es
Be o e pe o ming he ac ual eg ession analysis on he impac o con ac a ming on a m p oduc i i y
and income, a placebo es was conduc ed o con i m he c edibili y o he DID empi ical esea ch
Table 1. Desc ip i e s a is ics a baseline and end-line.
Desc ip i e s a is ics a baseline
Va iable
To al sample Pa icipan s Non-pa icipan s
Di e ence p alue
Mean
(S.D)
Mean
(S.D)
Mean
(S.D)
Household head age (yea s) 51.690
(14.537)
51.5
(14.46)
52.02
(14.69)
−0.52 0.446
Household size 3.000
(1.363)
3
(1)
3
(1)
0.00 0.640
To al land size (ac e) 1.47
(1.266)
1.49
(1.35)
1.45
(1.09)
0.04 0.161
Land unde banana (ac e) 0.223
(0.202)
0.23
(0.21)
0.21
(0.18)
0.02 0.280
Banana a m income 12406.410
(78651.702)
10475.19
(20138.02)
15647.87
(130387.26)
−5172.68 0.667
Banana a m-ga e p ice 19.750
(5.668)
19.69
(5.59)
19.87
(5.82)
−0.18 0.695
O - a m income 144104.700
(307328.093)
138919.1
(319209.14)
154065.82
(283238.71)
−15146.72 0.311
Banana a m p oduc i i y 2612.950
(3805.451)
2632.72
(3735.95)
2576.17
(3933.64)
56.55 0.660
Desc ip i e s a is ics a end-line
To al sample Pa icipan s Non-pa icipan s
Va iable
Mean
(S.D)
Mean
(S.D)
Mean
(S.D) Di e ence p alue
Household head age (yea s) 54.83
(14.49)
54.61
(14.45)
55.24
(14.56)
−0.63 0.385
Household size 3.00
(1.36)
3
(1)
3
(1)
0.00 0.640
To al land size (ac e) 1.46
(1.09)
1.46
(1.14)
1.46
(0.99)
0.00 0.111
Land unde banana (ac e) 0.23
(0.18)
0.24
(0.18)
0.21
(0.18)
0.03 0.279
Banana a m income 18576.35
(19311.83)
25490.85
(26598.77)
16477.6
(17104.51)
9013.25 0.001
Banana a m-ga e p ice 23.11
(3.98)
25.92
(3.42)
21.6
(3.40)
4.32 0.000
O - a m income 101933.69
(107373.63)
107041.84
(106748.47)
99761.09
(108040.77)
7280.75 0.431
Banana a m p oduc i i y 3052.27
(2418.35)
3826.9 (2843.38) 2635.86
(2038.31)
1191.04 0.000
n 2231 780 1451
n¼Numbe o obse a ions, as e isks and deno e le els o s a is ical signi icance a 1% and 5%, espec i ely and P. alue is p obabil-
i y alue associa ed wi h di e ences in p opo ions be ween he en olled/pa icipan s and non-en olled/non-pa icipan s.
Sou ce: Uni e si y o Sydney (2023). An impac assessmen o EAMDA’s banana ini ia i e o inc ease echnology adop ion by smallholde a me s
in Kenya. AEA RCT egis y.
COGENT ECONOMICS & FINANCE 5
design and especially o he ‘Pa allel ends’assump ion (Cunningham, 2021). Acco ding o Wo ld Bank
(2020), o a placebo es , you pe o m an addi ional DID es ima ion using a ake ou come –an ou come
known no o be a ec ed by he in e en ion. Two ake ou comes we e iden i ied o his es : o - a m
income and o he ag icul u al income. The wo hypo heses conside ed o he es :
Null Hypo hesis (H0): The e is no s a is ically signi ican impac o con ac a ming on he ake ou -
comes (o - a m income and o he ag icul u al income).
Al e na i e Hypo hesis (H1): The e is a s a is ically signi ican impac o con ac a ming on he ake
ou comes (o - a m income and o he ag icul u al income).
I he DID es ima ion e eals a signi ican impac on o – a m income and o he ag icul u al income,
leading o he ejec ion o he null hypo hesis, his would indica e po en ial sho comings in he s udy’s
design (Wo ld Bank, 2020).
As shown in Table 2, he simple linea DID eg ession did no yield any signi ican impac o con ac
a ming on o - a m income and o he ag icul u al income. Following Vlachopoulou e al. (2013), inco -
po a ing some con ol a iables iden i ied h ough s epwise eg ession (access o hi ed labou , use o is-
sue-cul u e banana plan le s, access o c edi , access o i iga ion acili ies, access o aining, household
Figu e 1. S ochas ic dominance g aphs on banana a m p oduc i i y and income a baseline.
Sou ce: Uni e si y o Sydney (2023).
Table 2. Placebo es using o - a m income and o he ag icul u al income.
Simple linea eg ession Mul i a ia e linea eg ession
Es ima ed impac on o - a m income −0.032
(0.075)
−0.006
(0.019)
Es ima ed impac on o he ag icul u al income 0.201
(0.082)
0.160
(0.022)
S anda d e o s a e in pa en heses; As e isks ,,deno e le els o s a is ical signi icance a 1%, 5% and 10%, espec i ely.
Sou ce: Uni e si y o Sydney (2023).
6 M. MURIGI ET AL.
size, and age o he household head) in he mul i a ia e eg ession also yielded a non-signi ican impac
on o - a m income and o he ag icul u al income. The absence o a signi ican e ec on he ake ou -
comes indica ed ha he e was no basis o ejec he null hypo hesis. This len c edence o he sui abil-
i y o he DID me hodology o de e mine he impac o con ac a ming on banana a m p oduc i i y
and income (Wo ld Bank, 2020).
DID eg ession esul s
The esul s o he DID eg ession on he impac o con ac a ming on banana a m p oduc i i y and
income a e p esen ed.
Table 3 shows ha , o he impac o con ac a ming on banana a m p oduc i i y, simple linea
eg ession yielded a posi i e coe icien o 0.198 which was s a is ically signi ican a one pe cen le el
implying ha on a e age banana a me s ha pa icipa ed in con ac a ming p oduced 19.8 pe cen
mo e pe ac e han hei non-pa icipa ing coun e pa s. Following Vlachopoulou e al. (2013), s epwise
eg ession was used o iden i y he ollowing indi idual con ol a iables o inco po a ion in he mul i-
a ia e linea eg ession o accoun o po en ial con ounde s and p o ide a mo e nuanced analysis o
he ea men e ec : Banana coope a i e membe ship, access o c edi , access o hi ed labou , access o
banana aining, access o ma ke in o ma ion, and o al land size. The mul i a ia e linea eg ession
yielded a posi i e coe icien o 0.261, also s a is ically signi ican a one pe cen le el, implying ha he
a e age inc ease in banana a m p oduc i i y due o pa icipa ion in con ac a ming was 26.1 pe cen .
These indings mi o hose o Mpe a e al. (2018), who ound ha he impac o con ac a ming pa -
icipa ion by sun lowe a me s in Tanzania on land p oduc i i y a e aged 24 pe cen . Fo he s udy
based in India, Mish a e al. (2018) also ound a posi i e impac o con ac a ming on land p oduc i i y
in baby co n p oduc ion. While hey ound a posi i e and signi ican impac o con ac a ming on
po a o p oduc i i y in Pakis an, Khan e al. (2019) ound no signi ican impac on p oduc i i y in maize
a ming. Maganga-Nsimbila (2021) ound ha he impac o con ac a ming on p oduc i i y in small-
holde co on a ming in Tanzania was insigni ican .
These indings suppo he iew ha pa icipa ion in con ac a ming inc eases a m p oduc i i y in
small-holde banana a ming. Con ac a ming b idges he in o ma ion asymme y p e alen in small-
holde ag icul u e as con ac o s p o ide help ul in o ma ion and aining o a me s o p oduce o hei
equi ed quan i y and quali y (Mugwagwa e al., 2020; Wo ld Bank, 2017). In he s udy case, banana a m-
e s pa icipa ing in he Twiga Foods’con ac scheme ecei ed egula aining on banana o cha d
Table 3. Impac o con ac a ming on a m p oduc i i y and income: DID eg ession analysis.
Impac on a m p oduc i i y
Simple linea eg ession Mul i a ia e linea eg ession
Es ima ed impac on a m p oduc i i y 0.198
(0.025)
0.261
(0.030)
Banana a m size Pe cen age o he sample Es ima ed impac on a m p oduc i i y Di e ence
0–0.2 ac es 43.5% 0.222
(0.034)
0.024
(0.047)
Abo e 0.2 ac es 56.5% 0.246
(0.028)
Impac on a m income
Simple linea eg ession Mul i a ia e linea eg ession
Es ima ed impac on a m income 0.030
(0.030)
0.109
(0.037)
Banana a m size Pe cen age o he sample Es ima ed impac on a m income Di e ence
0–0.2 ac es 43.5% 0.076
(0.049)
0.077
(0.057)
Abo e 0.2 ac es 56.5% 0.153
(0.088)
S anda d e o s a e in pa en heses; As e isks ,,deno e le els o s a is ical signi icance a 1%, 5% and 10%, espec i ely.
Sou ce: Uni e si y o Sydney (2023).
COGENT ECONOMICS & FINANCE 7
