Effects of Credit Constraints on Technical Efficiency of Dragon Farmers: Evidence from the District of Jhenaidah and Chuadanga

In e na ional Jou nal o Social Science and Human Resea ch
ISSN (p in ): 2644-0679, ISSN (online): 2644-0695
Volume 08 Issue 10 Oc obe 2025
DOI: 10.47191/ijssh / 8-i10-31, Impac ac o - 8.007
Page No: 7807-7816
IJSSHR, Volume 08 Issue 10 Oc obe 2025 www.ijssh .in Page 7807
E ec s o C edi Cons ain s on Technical E iciency o D agon Fa me s:
E idence om he Dis ic o Jhenaidah and Chuadanga
Md. Fi oz Hossain1, Mos . Shamima Nas in2*, Md. Humaun Kabi 3, Shahed Ahmed4
1Assis an P o esso , Depa men o De elopmen S udies, Islamic Uni e si y, Kush ia-7003, Bangladesh
2,3Assis an P o esso , Depa men o Economics, Islamic Uni e si y, Kush ia-7003, Bangladesh
4Associa e P o esso , Depa men o Economics, Islamic Uni e si y, Kush ia-7003, Bangladesh
ABSTRACT: This s udy examines he impac o c edi cons ain s on he echnical e iciency o d agon ui a me s in he
Jhenaidah and Chuadanga dis ic s o Bangladesh. The da a was ga he ed om 160 d agon a me s in he Jhenaidah and Chuadanga
dis ic s o Bangladesh using a simple me hod o andom sampling. P io o ca ying ou a ield su ey, a heo e ical model was
de eloped o dis inguish be ween d agon a me s who a e bound by c edi and hose who a e no cons ained. The acqui ed da a
was analyzed in wo s eps. Fi s ly, we examined he echnical e iciency o d agon a me s using he s ochas ic on ie model
(SFA). Secondly, we employed an ine iciency e ec model o e alua e he impac o c edi cons ain s on echnical e iciency. The
indings sugges c edi -cons ained d agon a me s (CCDF), a e 5.31% ewe echnical skills compa ed o c edi non-cons ained
d agon a me s (CNDF). The esul s also demons a e ha he educa ional le el o he household head, he numbe o amily
membe s, he usage o ce i ied seeds, he iming o sowing, access o ag icul u al ex ension se ices, income om non- a m
ac i i ies, and he amoun o sa ings in he household all ha e an impo an impac on he echnical e iciency o bo h ca ego ies o
d agon a me s. Mo eo e , he magni ude o he c edi has a signi ican ly posi i e e ec , whe eas he in e es a e applied o he
p incipal amoun has a signi ican ly ad e se e ec .
KEYWORDS: D agon Fa me s, C edi Cons ain s, Technical E iciency, Fa m Households, Bangladesh.
1. INTRODUCTION
Mos o he popula ion in Bangladesh esides in u al a eas, and hei p ima y sou ce o li elihood is ag icul u e and ela ed
ac i i ies. Acco ding o he es ima ion o (Bangladesh Economic Re iew (2023), he o e all con ibu ion o he b oad ag icul u e
sec o a he cons an p ice was 11.20 pe cen o GDP in he inancial yea 2022-23. Mo eo e , a ound 45.33% o he coun y's
o e all labou powe is in ag icul u e (Labo Fo ce Su ey, 2022).
D agon is he ecen ly in oduced supe ui in Bangladesh. I is a nou ishing and deligh ul exo ic ui g own in a id
egions wo ldwide, pa icula ly in Asian coun ies (A yal e al., 2020). I s beau i ul colou , delicious pulp wi h edible black seeds,
heal h bene i s, and s ong expo po en ial ha e made i ex emely popula among a me s and consume s. The lowe o he d agon
is so beau i ul ha i is called 'Queen o he Nigh ' (Gunasena e al., 2006 & Mo i e al., 2023). The cul i a ion o his ui is
conduc ed on a comme cial scale in se e al coun ies like Vie nam, Thailand, Malaysia, Taiwan, China, S i Lanka, Is ael, Aus alia,
Nica agua, and Cen al Ame ica (Resea ch & Ma ke s, 2020).
Access o c edi is a key ool o ag icul u al g ow h and u al de elopmen (Li e al. 2016; Lin e al. 2019; Amanullah e
al. 2020). On he one hand, he capi al equi emen s o ag icul u al communi ies ha e expe ienced a signi ican inc ease in ecen
yea s. Con e sely, o mal inancial ins i u ions a e wa y o alloca e unds o ag icul u e due o he inhe en unce ain ies in his
sec o (A shad e al. 2017a, b). Fa me s in de eloping coun ies ely ex ensi ely on bo h o mal and in o mal lending sec o s as a
esul o inadequa e sa ings. The heo y o p oduc ion and inancial s uc u e highligh s ha p o iding c edi op ions o inancially
cons ained a m households can lead o imp o ed o e all p oduc i i y pe o mance (Elahi e al. 2018).
I has been sugges ed in he exis ing li e a u e ( on C amon-Taubadel and Saldias 2014; Chandio e al. 2019; A ipoe e al.
2020; Ekinci and Omay 2020; Long e al. 2020; Ka el e al. 2020) ha a me s' pe o mance is in luenced by en i onmen al ac o s
and c edi cons ain s in a a ie y o ways, which may esul in a dec ease in a m p oduc i i y. The inancial ma ke in de eloping
coun ies is cha ac e ized by agmen a ion. The ailu e o he sys em is due o he p esence o asymme ic in o ma ion, he impac
o in o mal lende s, s ic loan disbu semen e ms and condi ions, and con olled moni o ing among o he ac o s (Bha acha ya e
al., 2020). Despi e he e o s o inancial expe s in e na ionally o implemen sus ainable u al de elopmen p og ams h ough he
E ec s o C edi Cons ain s on Technical E iciency o D agon Fa me s: E idence om he Dis ic o Jhenaidah and
Chuadanga
IJSSHR, Volume 08 Issue 10 Oc obe 2025 www.ijssh .in Page 7808
p o ision o a ious inancial se ices a subsidized a es, a ming communi ies in many de eloping coun ies s ill lack su icien
access o o mal c edi (Dong e al. 2012; Li e al. 2018; Jin e al. 2019; Ma e al. 2019; Cao and Leung 2020; Oko uwa e al. 2020).
The cu en u al inancial ma ke in Bangladesh is cha ac e ized by signi ican impe ec ions, p ima ily due o a lack o
knowledge, complex in o ma ion, limi ed c edi a ailabili y, moni o ing challenges, high non-pe o ming po olio a ios (NPPs),
and he p e alence o p i a e money lende s. Fu he mo e, indi iduals seeking loans mus u nish a ious legal and suppo ing
documen s, which a y based on he loan amoun and he eques ed cash acili y (Ma e al. 2019). The p esence o hese obs acles
con ibu es o a demanding c edi en i onmen ha can lead o dec eased ag icul u al p oduc i i y (Bashi and Mehmood 2010;
Mehmood e al. 2018).
The a ming communi y in Bangladesh is con on ed wi h nume ous obs acles, such as a lack o mode n p oduc ion
echnology, wa e sca ci y, poo soil salini y, and insec and pes a acks, e en hough d agon cul i a ions make a subs an ial
con ibu ion o he coun y's GDP (Ahmed e al. 2021; Rana and Moni uzzaman 2021; Sa ka e al. 2021).
C edi cons ain s can ha e bo h di ec and indi ec e ec s. Di ec ly, hey can impac a me s' abili y o make pu chases.
Indi ec ly, hey can in luence a me s' isk a e sion, which limi s hei willingness o ake isks, such as in es ing in mode n
echnologies (Shew e al. 2019; Duong and Thanh 2019; Ca e e al. 2020; Ka el e al. 2020). Thus, a me s ha lack adequa e
cash o a e inancially es ic ed ha e been unable o a ain op imal le els o p oduc i i y. Simila o o he de eloping na ions,
a me s in Bangladesh ha e been caugh in an endless cycle o po e y and indeb edness. F om one pe spec i e, hey equi e
inancial assis ance in o de o acqui e essen ial ag icul u al inpu s (Bidisha e al. 2018; Long e al. 2020), a he same ime, inancial
ins i u ions a e unwilling o gi e hem loans because o he isks in he a m sec o (A shad e al. 2017b; Mehmood e al. 2017).
Typically, loan applica ions a e denied o app o ed o lowe amoun s by inancial ins i u ions. Financial ins i u ions in
u al Bangladesh ca e ully assess a ious ac o s when e alua ing a me s' eligibili y o loans, including hei ne wo h, yea s o
expe ience, p ope y o e ed as colla e al, and loan his o y. When a me s mee all hese equi emen s, banks will conside app o ing
loans a a ying in e es a es based on an equi y a io.
I appea s ha he e is a lack o esea ch on c edi cons ain s and he echnical e iciency o d agon a me s in Bangladesh.
Addi ionally, he exis ing s udies ha e ailed o conside impo an a iables in hei analysis. P e ious esea ch has examined
a ious issues and analysed he limi a ions on c edi om bo h he pe spec i e o bo owe s and lende s. By ca e ully examining
he gaps and aking in o accoun he c edi cons ain s on bo h he demand and supply sides, we we e able o assess he echnical
e iciency o he a m households. Using he same app oach as o he esea che s, we employed he s ochas ic on ie model (SFA)
and ine iciency e ec s model o examine he echnical e iciency o d agon a me s. Gi en he signi icance o echnical e iciency
and he inancial limi a ions aced by a me s, we ocused p ima ily on wo ques ions:
a) Do c edi cons ain s a ec he echnical e iciency o d agon ui s a me s?
b) Does access o c edi a ec he echnical e iciency o d agon ui s a me s?
2. THEORETICAL FRAMEWORK TO IDENTIFY CREDIT-CONSTRAINED HOUSEHOLDS
Be o e conduc ing he ield su ey, he au ho s de eloped a heo e ical amewo k and ca ego ized d agon a me s in o
hose wi h c edi cons ain s and hose c edi non cons ain s. Schola s ha e obse ed ha c edi cons ain s a ise om bo h he
supply and demand sides (Bouche e al. 2008; Diana e al. 2010; Chiu e al. 2014; Mehmood e al. 2017; Beyhaghi e al. 2020).
Demand-side c edi cons ain s can a ise om a ious ac o s such as insu icien household income, p e ious c edi issues, lack o
colla e al o gua an ee, and mo e. On he o he hand, supply-side c edi cons ain s occu when lende s do no p o ide enough loans
o household a me s (Mehmood e al. 2017). When he loan p o ide de e mines ha he a me s a e unable o epay he p incipal
o in e es , he e is a signi ican likelihood ha he loan applica ion will be denied. These undamen al ac o s a e especially
impo an in si ua ions whe e inancial ma ke s a e impe ec o in e es a es a e excep ionally high (Jana 2015).
Acco ding o he heo e ical model, d agon a me s who ecei ed he ull amoun hey eques ed om inancial ins i u ions
we e classi ied as c edi non-cons ained d agon a me s (CNDF). On he o he hand, d agon a me s who ecei ed only a pa ial
amoun o had hei loan applica ions ejec ed by inancial ins i u ions we e classi ied as c edi -cons ained d agon a me s (CCDF).
Fu he mo e, i was pos ula ed ha i a me s we e g an ed he whole sough amoun by inancial ins i u ions, hey would be able
o ge ag icul u al supplies and in es in mode n echnologies, hence enhancing p oduc i i y. Con e sely, a me s who did no
ecei e su icien loans would ha e been unable o ob ain he op imal esou ces o p oduc ion, leading o educed e iciency.
Addi ionally, he ollowing igu e 1 illus a es he di ision among a me s who depend on c edi , wi h one g oup consis ing
o a me s who ha e no sough c edi , and he o he g oup consis ing o a me s who ha e applied o c edi . D agon ui a me s
who ha e applied o c edi a e ca ego ized in o h ee subg oups: The e a e h ee ca ego ies o a me s when i comes o c edi
applica ions. The i s g oup, known as CNDF, consis s o a me s who me all he equi emen s and we e g an ed he ull amoun
o c edi hey applied o . The second g oup includes a me s whose applica ions we e no accep ed o he ull amoun o c edi ,
and some we e e en ejec ed ou igh . Las ly, he e a e a me s who app oached p i a e lende s di ec ly o c edi , wi h mos o
hem success ully ob aining he loan, al hough a ew a me s ha e ye o ecei e i .
E ec s o C edi Cons ain s on Technical E iciency o D agon Fa me s: E idence om he Dis ic o Jhenaidah and
Chuadanga
IJSSHR, Volume 08 Issue 10 Oc obe 2025 www.ijssh .in Page 7809
Ul ima ely, he au ho s dis inguished h ee ca ego ies o a me s: (i) c edi -cons ained a me s; (ii) c edi -non-cons ained
a me s; and (iii) a me s who ha e e ained om applying o c edi due o a su icien amoun o unds. No ably, he inal ca ego y
was omi ed om he da ase .
Figu e 1: Theo e ical model o c edi cons ain s d agon a me s (CCDF) and c edi non-cons ain s d agon a me s
(CNDF)
The abo e igu e highligh s ha d agon a me s expe ience signi ican ba ie s in accessing o mal c edi , p ima ily due o issues
like lack o colla e al, gua an o s, and p ope documen a ion. Those who apply o c edi o en ace ejec ions, pa icula ly due o
high in e es a es, ea o losing p ope y, and insu icien ela ionships wi h inancial ins i u ions. Some a me s, awa e o hese
challenges, choose no o apply a all, ci ing easons such as high in e es a es and he ea o ejec ion. O he s u n o in o mal
lende s, bu hese lende s also p esen hei own se o challenges, including high-in e es a es and a lack o colla e al. Addi ionally,
many a me s ace exclusion due o insu icien in o ma ion abou a ailable inancial se ices, making i ha de o hem o access
ei he o mal o in o mal c edi . On he o he hand, some a me s who ha e su icien capi al o inpu p oduc ion a oid seeking
c edi en i ely. This indica es a deepe issue o inancial exclusion, whe e a me s s uggle due o ins i u ional ba ie s and pe sonal
ea s, leading o a eliance on in o mal and o en exploi a i e lending sys ems.
Apply o c edi
All he
necessa y
documen s
placed by
a me s ha ’s
why ecei ed
100% loan
G an ed c edi bu
less han 100% G an ed
c edi 100%
Inadequa e
amoun o c edi
sanc ion
D agon a me s
Ha e c edi
demand
Didn’ apply o c edi
Applica ion ejec ed by
inancial ins i u ion
Reasons:
1. Rejec ion
expec ed
2. High a e o
in e es
3. Fea o losing
p ope y
4. Documen a ion
p oblem
5. o he s
Rejec ed he a ms by
in o mal lende s
Loan sanc ioned by
in o mal lende s o d agon
a me s
CCDF
CNCDF
Reasons:
1.
Lack o gua an o s
2.
Lack o Secu i y
3.
High In e es a e
4.
Lack o ela ionship
5.
Fea o losing
p ope y
6.
No eady o sign
ag eemen
7.
O he s
Fa me s accessed o
in o ma ion lende s
o c edi
Fa ms ejec ed by
inancial
ins i u ions
Bo h g oup o d agon a me s
accessed o in o mal lende s o
c edi
Reasons:
1. Lack o
gua an o s
2. Lack o
ela ionship
3. Lack o
educa ion
4. Lack o
in o ma ion
5. Inadequa e o
colla e al
Ha en’ c edi demand
Reasons:
The capi al is
su icien enough
o inpu p oduc ion
ac o s.
These a me s a e
excluded om ou
su ey
E ec s o C edi Cons ain s on Technical E iciency o D agon Fa me s: E idence om he Dis ic o Jhenaidah and
Chuadanga
IJSSHR, Volume 08 Issue 10 Oc obe 2025 www.ijssh .in Page 7810
3. METHODOLOGY OF THE STUDY
The me hodology sec ion o his esea ch elucida es he chosen esea ch design and app oach employed o examine he
e ec s o c edi cons ain s on he echnical e iciency o d agon ui a me s in he Jhenaidah and Chuadanga dis ic s o
Bangladesh. I p o ides a comp ehensi e amewo k o da a collec ion, analysis, and in e p e a ion.
3.1. S udy place and popula ion
The s udy a ea, Jhenaidah and Chuadanga, is an ag icul u e-p oducing egion si ua ed in he coun y's Sou h-Wes e n
po ion. Mos o he inhabi an s o hese dis ic s li e in u al a eas, and hey ha e been able o implemen ag icul u al mode niza ion
p ac ices. Apa om he usual ag icul u al p oduc s o Bangladesh, such as ice, whea , po a oes, ege ables, suga cane, ba le lea ,
len ils, ga lic, onion, ginge , and ui s like mango, banana, jack ui s, gua a, D agon, plum, e c. a e p oduced in he egion. Among
he ag icul u al p oduc s, ui s play a i al ole in enhancing he economic s a us o a m households. The opical ui D agon has
become a new and a ac i e ui o consume s and p oduce s.
Mo eo e , he selec ion o d agon ui cul i a ion was based on wo p ima y easons: i s ly, he opical ui D agon has
become a new and a ac i e ui o consume s and p oduce s; and secondly, D agon ui cul i a ion in Bangladesh can posi i ely
impac on he coun y's g ow h.
Figu e 2: S udy a ea in Jhenaidah and Chuadanga Dis ic , Bangladesh.
3.2. Su ey design and da a collec ion
P ima y da a we e collec ed h ough a household su ey using s uc u ed ques ionnai es. A mul i-s age andom sampling
was u ilized o selec he sample a m owne s o he su ey. In he i s s age, he s udy andomly selec ed he wo dis ic s, and he
nex , we andomly selec ed ou Upazilla om he wo dis ic s, Moshespu and Cou chadpu om Jhenaidh Dis ic and Jibonaga
and Damu huda om he Chuadanga dis ic . A e selec ing ou Upazilla om wo dis ic s, we pu posi ely selec ed eigh illages,
Gau ina hpu and Aloampu om Mohespu ; Fulho i and Somajkolla om Cou chadpu ; Kasipu and Khaye huda om
Jibonnaga ; and Pe k isnapu and Bas upu om Damu huda Upazila. In he p ocess o ou s udy, we collec ed da a om a o al o
160 indi iduals who we e engaged in D agon ui cul i a ion.
No ably, a m households who had nei he applied o a loan no aced c edi issues in bo h ca ego ies we e emo ed om
he da abase because hei loan demand om inancial ins i u ions was ze o. A lis o d agon a me s was ob ained om he
Ag icul u al Depa men o Bangladesh, and a o al o 160 we e in e iewed. Thus, he o al sample size is 160, including 56 CNDF
and 104 CCDF.
3.3. Econome ic es ima ion
3.3.1. Model Speci ica ion o Cobb Douglas P oduc ion Func ion:
The speci ica ion o he Cobb Douglas P oduc ion Func ion model is as ollows:
𝐘𝐢=𝛃𝟎 𝐗𝟏
𝛃𝟏 𝐗𝟐
𝛃𝟐 𝐗𝟑
𝛃𝟑 𝐗𝟒
𝛃𝟒 𝐗𝟓
𝛃𝟓 𝐗𝟔
𝛃𝟔 𝐗𝟕
𝛃𝟕𝐞𝐮𝐢
The log linea o m o he Cobb Douglas P oduc ion Func ion will be-
𝐥𝐧𝐘𝐢=𝛃𝟎+𝛃𝟏𝐥𝐧𝐗𝟏𝐢+𝛃𝟐𝐥𝐧𝐗𝟐𝐢+𝛃𝟑𝐥𝐧𝐗𝟑𝐢+𝛃𝟒𝐥𝐧𝐗𝟒𝐢+𝛃𝟓𝐥𝐧𝐗𝟓𝐢+𝛃𝟔𝐥𝐧𝐗𝟔𝐢+ 𝛃𝟕𝐥𝐧𝐗𝟕𝐢+𝐮𝐢
Whe e,
ln = Na u al loga i hm
Yi = G oss income o he i h a m (Tk/Bigha/Yea )
E ec s o C edi Cons ain s on Technical E iciency o D agon Fa me s: E idence om he Dis ic o Jhenaidah and
Chuadanga
IJSSHR, Volume 08 Issue 10 Oc obe 2025 www.ijssh .in Page 7811
X1i = Fa m land a ea
X2i = Labou cos o he i- h a m (Tk/Bigha/Yea )
X3i = Cos o seeding o he i- h a m (Tk/Bigha/Yea )
X4i = I iga ion cos o he i- h a m (Tk/Bigha/Yea )
X5i = Cos o pes icides o he i- h a m (Tk/Bigha/Yea )
X6i = Cos o e ilize o he i- h a m (Tk/Bigha/Yea )
X7i = Cos o he Pille , ope and wi e (Tk/Bigha/Yea )
βi = β0 o β6 a e unknown pa ame e s and
ui = he dis u bance e m
3.3.2. S ochas ic on ie analysis
The echnical e iciency o ice g owe s was assessed using he SFA, which was in oduced by Aigne e al. (1977). This
model has been ex ensi ely employed in p e ious esea ch (Tipi e al. 2009; Cab e a e al. (2010); He iqbaldi e al. (2015);
Bha acha yya and Mandal (2016); Hasnain e al. (2016). The undamen al equa ion is as ollows:
Yi= (Xi;β)exp( i−ui)……………….(1)
Whe e,
Yi = expec ed ou pu o i h d agon a me s
Xi = obse ed unc ion o inpu s o desc ip i e a iables
(Xi;β) = amewo k’s p oduc ion on ie
i = andom de ia ion o ou pu
ui = a se o non-nega i e andom a iables
Conside ing he dis ibu ion assump ion o a iance ( i) and (ui), we gene a ed an assessmen o (ui), om i s es ic i e p obabili y
by gene a ing he s anda d in eg al:
E(ui|εi)=ui∗+σi∗[φ(−ui
σi∗)
1−φ(−uiσi∗
⁄)]……………………. (2)
Whe e,
ui∗=(uσ
2+ϵiσu
2)/(σ
2+σu
2)
σ
∗2=σ
2σu
2/(σ
2+σu
2) and φ(.) deno es accumula i e dis ibu ion and likelihood densi y unc ions. The a iance
alue was de e mined by exchanging he alues o ( i) and (ui) in Eq. (1). he es ima ion o εiσi and l, which is associa ed wi h
ou pu - ela ed (TEi) o i h d agon cul i a o s. The ou pu le el is de ined as he a io o he pe cei ed ou pu o he highes possible
p oduc ion, ep esen ed by exp - i and exp essed as ollows:
TEiyi
(Xi;β)e( i)exp{−(uiIϵi)}
TIi=1−TEi………… (3)
The es ima ed TE o d agon cul i a o s was es ic ed o a ange o 0 o 1 by he dis ibu ion o (ui) om Eq. (3). Consequen ly, we
ob ained he e iciency sco e om a a ie y o d agon p oduce s in o de o conduc ou esea ch. Mo eo e , he SFA amewo k's
gene al s uc u e is desc ibed below in o de o e alua e he TE o d agon a me s:
lnYi=β0+∑βijlnXij+ i−ui
σ
K=i ………………. (4)
Whe e, Yi= The agg ega e ou pu o he d agon a me s
Xij= The selec ed inpu a iables explained as
X1= a mland a ea, X2= cos o seedling, X3= a m labo cos , X4= he cos o e ilize applica ion, X5= cos
o pes icides, X6= i iga ion cos and β0= coe icien s o desc ip i e a iables.
In he second phase o he comp ehensi e in es iga ion, he au ho s u ilized he ine iciency e ec s model o assess he echnical
e iciency o d agon a me s. Ba ese and Coelli (1995) de eloped by he esea ch conduc ed by Aigne e al. (1977) and es ablished
he ine iciency e ec s model using he s ochas ic on ie analysis (SFA). We employed he ine iciency e ec s model u ilizing he
maximum likelihood es ima ion me hod.
IEi=δZi+ui…………………. (5)
Whe e IEi= ine iciency sco es, Zi= ec o o designa ed a iables ha impac s ine iciency wi hin di e en classi ied g oups o
d agon a me s, and ui is a andom e o e m in he da abase se ,

E ec s o C edi Cons ain s on Technical E iciency o D agon Fa me s: E idence om he Dis ic o Jhenaidah and
Chuadanga
IJSSHR, Volume 08 Issue 10 Oc obe 2025 www.ijssh .in Page 7812
4. RESULTS AND DISCUSSION
4.1. Desc ip i e S a is ics
The da a se p esen ed p o ides a summa y o a ious cos componen s associa ed wi h a ming, speci ically measu ed pe
Bigha pe yea , along wi h he g oss income gene a ed by he a m. The da a includes he mean (a e age), s anda d de ia ion (S d.
De .), minimum (Min), maximum (Max), and he numbe o obse a ions (Obs) o each a iable. Le 's b eak down each
componen :
Table1: Summa y S a is ics
Va iable
Mean
S d. De .
Min
Max
Obs
G oss income o he a m
(Tk/Bigha/Yea )
611868.8
81414.39
400000
785000
160
Labou cos o he a m
(Tk/Bigha/Yea )
113815.6
5788.902
101000
125000
160
Land P epa a ion cos o he
a m (Tk/Bigha/Yea )
6480.313
369.1354
5400
7200
160
Cos o seed o he a m
(Tk/Bigha/Yea )
53035.94
2514.168
44000
58000
160
I iga ion cos o he a m
(Tk/Bigha/Yea )
12438.13
885.9399
10000
14200
160
Cos o pes icides o he a m
(Tk/Bigha/Yea )
44168.75
1915.123
40000
48000
160
Cos o e ilize o he a m
(Tk/Bigha/Yea )
93188.75
6894.816
75000
112000
160
Cos o he Pille , ope and
wi e (Tk/Bigha/Yea )
11444.69
885.4093
10000
13500
160
Sou ce: Au ho ’s Es ima ion
This indica es ha , on a e age, he a m gene a es an income o 611868.8 Tk pe Bigha pe yea , wi h a a iabili y (s anda d
de ia ion) o 81414.39 Tk. The income anges om a minimum o 400000 Tk o a maximum o 785000 Tk ac oss 160 obse a ions.
On a e age, he labou cos pe Bigha pe yea is 113815.6 Tk, wi h a s anda d de ia ion o 5788.902 Tk, indica ing some a ia ion
a ound his mean. The labou cos anges om 101000 Tk o 125000 Tk.
The a e age cos o land p epa a ion is 6480.313 Tk pe Bigha pe yea , wi h a ela i ely low s anda d de ia ion o
369.1354 Tk, sugges ing consis en cos s ac oss obse a ions. The ange is om 5400 Tk o 7200 Tk.The a e age seed cos is
53035.94 Tk pe Bigha pe yea , wi h a s anda d de ia ion o 2514.168 Tk. The cos s ange om 44000 Tk o 58000 Tk. The a e age
i iga ion cos is 12438.13 Tk pe Bigha pe yea , wi h a s anda d de ia ion o 885.9399 Tk. The i iga ion cos s ange om 10000
Tk o 14200 Tk.
The a e age e ilize cos is 93188.75 Tk pe Bigha pe yea , wi h a s anda d de ia ion o 6894.816 Tk. The cos s ange
om 75000 Tk o 112000 Tk. The a e age cos o pilla s, ope, and wi e is 11444.69 Tk pe Bigha pe yea , wi h a s anda d
de ia ion o 885.4093 Tk. The cos s ange om 10000 Tk o 13500 Tk.
4.2. Es ima ion o Cobb-Douglas P oduc ion Func ion
The ollowing able 1 ep esen s he g oss ou come o he Cobb-Douglas p oduc ion unc ion o wo dis ic s oge he .
Table 2: Es ima ion o Cobb-Douglas P oduc ion Func ion Jhenaidah and Chuadanga Dis ic
Jhenaidah and Chuadanga Dis ic
Me hod: O dina y Leas Squa es
Dependen a iable: To al Re enue/Ou pu (lnY)
Numbe o Obse a ion: 160 ( a m owne s)
Explana o y Va iables
Coe icien s
S d. E .
-S a is ic
P obabili y
C
-13.46987
1.322343
-10.18637
0.0000
Fa m land a ea (lnX1)
0.028141
0.093947
4.891917
0.0000
Fa m Labo Cos (lnX2)
0.671705
0.119479
5.621970
0.0000
Seedling Cos (lnX3)
0.225424
0.118644
1.899999
0.0593
I iga ion Cos (lnX4)
-0.190789
0.084336
-2.262258
0.0251
Pes icide Cos (lnX5)
-0.044715
0.187518
-0.238456
0.8118
Fe ilize Cos (lnX6)
0.165047
0.084155
1.961234
0.0417
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Cos o he pilla - ope-wi e (lnX7)
-0.214071
0.070444
-3.038875
0.0028
R-squa ed
0.825248
Adjus ed R-squa ed
0.817200
F-S a is ic
102.5433
P ob (F-S a is ic)
0.000000
Sou ce: Es ima ed by EViews 10 using su ey da a
The es ima ed esul s indica e ha labo , land p epa a ion, i iga ion, and e ilize cos s exhibi s a is ically signi ican posi i e
impac s. In con as , he cos o he pilla ope wi e has a s a is ically signi ican nega i e impac on a me s' income. Among hese
ac o s, labou eme ges as he mos in luen ial, wi h a 1% inc ease in labou cos co ela ing o a signi ican 178.91% ise in a me s'
income. Following closely, land p epa a ion s ands ou as he second mos c ucial ac o o d agon ui cul i a ion, whe e a 1%
inc ease in land cos , wi h o he ac o s held cons an , leads o a subs an ial 67% inc ease in a me s' income. The coe icien o R-
squa e 0.825248 ep esen s ha he explana o y a iables can explain 83% o he a ia ion in he a me 's income om d agon ui
cul i a ion. The F-s a is ic alue is posi i e (102.5433), and i s espec i e p obabili y alue is less han 5%, indica ing ha all he
ac o s ha e a combined posi i e impac on he income/ou pu o D agon ui cul i a ion.
4.3. Maximum likelihood es ima es o he p oduc ion on ie
Table 3: Maximum likelihood es ima es o p oduc ion on ie
Va iables
CNDF No. (56)
CCDF No. (104)
Full sample No. (160)
In e cep
0.577 (0.070) ***
0.731 (0.094) ***
0.785 (0.063) ***
Ln a m land a ea
0.032 (0.009) **
0.088 (0.011) **
0.082 (0.008) ***
Ln cos o seedling
0.560 (0.050) ***
0.489 (0.064) ***
0.491 (0.044) **
Ln a m labo cos
0.010 (0.008)
0.045 (0.011) **
0.039 (0.010)
Ln cos o e ilize
0.129 (0.029) ***
0.151 (0.040)
0.066 (0.008) *
Ln cos o pes icides
0.095 (0.015) **
0.048 (0.017) **
0.058 (0.010) ***
Ln i iga ion cos
0.064 (0.023) **
0.064 (0.035)
0.021 (0.013)
Ln σ2
−10.828(0.184) ***
−8.358 (0.112) ***
−7.969 (0.095) ***
No es: The alues in pa en hesis speci y s anda d e o s. Signi ican le el a ***p=1%; **p=5%, and *p=10%
The able 3 displays he da a indica ing ha he coe icien s o he a mland a ea a iables a e 0.032 and 0.088 o CNDF
and CCDF, espec i ely. The coe icien alue indica es ha a 1% inc ease in he uni o a med a ea leads o an es ima ed inc ease
in d agon yield by 0.03% o he CNDF and 0.08% o CCDF. When conside ing he cos o seedlings, we obse e he g ea es
impac on d agon p oduc ion. The p edic ed elas ici ies o CNDF and CCDF a e 0.56 and 0.489, espec i ely. A key con ibu o is
ha he majo i y o a me s in he s udy a ea u ilized highe -g ade seeds o d agon p oduc ion, esul ing in a subs an ial and posi i e
inc ease in d agon yield.
The coe icien alue o ag icul u al labou cos in he CCDF model is 0.045, and i is s a is ically signi ican a a 5% le el
o p obabili y. The coe icien alues o he cos o e ilize in CNDF and CCDF a e 0.129 and 0.151, espec i ely. The coe icien s
o he cos o pes icides alues a e 0.095 o CNDF and 0.048 o CCDF, espec i ely. The coe icien alue o he i iga ion cos
o CNDF is 0.064 and s a is ically signi ican a he 5% le el o p obabili y. Howe e , o CCDF, he same coe icien alue is no
s a is ically signi ican .
4.4. Range o echnical e iciency
The ollowing able shows he esul s o he mean echnical e iciency o CNDF and CCDF.
Table 4: E iciency es ima es o c edi cons ained, c edi non-cons ained, and ull sample size
E iciency
ange
CNDF (N=56)
CCDF (N=104)
Full sample (N=160)
Numbe s
Pe cen age
Numbe s
Pe cen age
Numbe s
Pe cen age
<80%
14
25.50
56
53.51
66
41.22
81–85%
9
14.00
20
19.45
30
18.94
86–90%
10
17.50
8
7.56
15
9.29
91–95%
13
23.50
11
11.08
28
17.19
>95%
10
19.50
9
8.37
21
13.33
To al
56
100
104
100
160
100
Mean
0.9167
91.67%
0.8636
86.36%
Sou ce: au ho ’s es ima ion
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Acco ding o he indings, he a e age echnical e iciency o CNDF is 91.67% and 86.36% o CCDF (Table 4). The di e ence in
he a e age echnical e iciency is 5.31%, sugges ing ha he e a e gaps in echnical e iciency be ween CNDF and CCDF. Thus,
in bo h si ua ions, he ice cul i a o s may enhance he e iciency le el by 8.33% o CNDF and 13.64% o CCDF, u ilizing he
exis ing quan i y o esou ces. In Sou h Asia, he ange o echnological e iciency anged be ween 0.82% and 0.97% (Bibi e al.,
2020).
4.5. Technical ine iciency e ec s es ima e
The echnical ine iciency o d agon cul i a o s is in luenced by he ac o s lis ed in Table 5. The au ho s illus a ed he
esul s o he ine iciency e ec s model wi h espec o echnical e iciency, abiding o he me hodologies o Cab e a e al. (2010)
and Mehmood e al. (2017). This sugges s ha echnical e iciency is posi i ely in luenced by a nega i e impac on echnical
ine iciency. The pa ame e s ha we e calcula ed indica e ha he chie age o he household (which is ega ded as ag icul u al
a ming expe ience) has a subs an ial bu de imen al impac on CNDF. The nega i e sign indica es ha he p oduc i i y o olde
a me s in he su eyed loca ion is lowe han ha o hei younge coun e pa s. The educa ion le el coe icien s in bo h ca ego ies
o g owe s a e posi i e and signi ican ; howe e , he e ec appea s o be mo e p onounced on CNDF. The coe icien o household
size is bo h posi i e and signi ican o bo h ca ego ies o a me s. This sugges s ha he echnical e iciency o p oduce s inc eases
as he size o hei households inc eases. This may be a ibu able o he ac ha a g ea e numbe o amily membe s a e in ol ed
in ag icul u al p ac ices and assis a me s in he managemen o a m ac i i ies. The coe icien s o ce i ied seed o bo h CNDF
and CCDF a e bo h posi i e and s a is ically signi ican .
Table 5: Pa ame e es ima es o ine iciency e ec s model
Va iables
CNRG No. (56)
CCRG No. (104)
Full sample No. (160)
Cons an
−6.571 (0.868) ***
−3.882 (0.570) ***
−4.597 (0.441) ***
Household head age(yea s)
0.025 (0.022) **
0.007 (0.008)
0.014 (0.007)
Household head educa ion (yea s)
−0.103 (0.036) ***
−0.078 (0.037) **
−0.086 (0.029) **
Household amily size (numbe s)
−0.066 (0.017) **
−0.060 (0.029) **
−0.064 (0.023) **
Ce i ied seed (yes=1; o he wise=0)
−0.751 (0.595) **
−0.690 (0.345)
−0.683 (0.280) **
Sowing ime (yes=1; o he wise=0)
−0.968 (0.276) ***
−0.748 (0.376) *
−0.453 (0.275) **
Owned ube-well (yes=1; o he wise=0)
0.523 (0.336)
−0.682 (0.396)
−0.075 (0.314)
Ex ension se ices (yes=1; o he wise=0)
−0.887 (0.285) **
−0.709 (0.354) **
−0.748 (0.215) **
Li es ock holding (yes=1; o he wise=0)
−1.422 (0.425) **
−0.512 (0.338) *
−0.909 (0.260) **
O - a m income (yes=1; o he wise=0)
−0.790 (0.495) **
−1.074 (0.472) **
−0.876 (0.343) *
Household sa ings (1000 BDT)
−0.002 (0.026) **
−0.002 (0.001) **
−0.002 (0.001) **
C edi size
−0.0002 (0.0002) **
−0.0003 (0.0001) **
−0.003 (0.0001) *
In e es a es (pe cen age)
0.017 (0.014) **
0.030 (0.011) **
0.026 (0.009) *
C edi a ailabili y (yes=1)
--
--
−0.456 −0.273**
No es: The alues in pa en hesis speci y s anda d e o s Signi ican deg ee a ***p< 1%; **p< 5%, and *p< 10%
Bo h he CNDF and CCDF g oups a e a ec ed by he c edi size indica o in signi ican ways o he be e . The e a e wo
clea ways o see how he amoun o c edi a ec s hings. A i s , aising he amoun o c edi would encou age a m households o
use new echnologies and help hem dis ibu e hei esou ces in a sma way.
Basically, he comp ehensi e assessmen o he sample pa ame e s is simila o ha o CNDF and CCDF o some ex en .
The p ima y objec i e is o e alua e how c edi cons ain s impac he echnical e iciency o a me s. A e ca e ully analyzing
mul iple s udies, we e alua ed c edi a ailabili y as a bina y a iable. Technical e iciency is in luenced by he a ailabili y o c edi ,
which was e alua ed using he di ec elici a ion me hod. Based on he analysis, i is e iden ha he p esence o c edi has a
signi ican and posi i e e ec on he echnical e iciency o d agon ui a me s.
5. CONCLUSIONS AND POLICY IMPLICATIONS
An in es iga ion was conduc ed o examine he impac o c edi cons ain s on he echnical e iciency o d agon a me s.
The s udy u ilized c oss-sec ional da a ob ained om he Jhenaidah and Chuadanga dis ic s in Bangladesh. The au ho s employed
he me hod o di ec elici a ion o ca ego ise d agon a me s in o wo dis inc g oups: CCDF and CNDF. A simple andom selec ion
me hod was u ilized o selec a o al o 160 a m households in o de o ga he he equi ed in o ma ion. The SFA was employed o
assess he echnical e iciency o d agon a me s. The a e age echnical e iciency o CNDF is 91.67% and CCDF is 86.36%. The
indings sugges ha he CNDF and CCDF migh po en ially imp o e hei echnical e iciency by 8.33% and 13.64%, espec i ely,
based on he su ey conduc ed in he a ea. The dispa i y in echnical e iciency sco es be ween CNDF and CCDF is 5.31%.
E ec s o C edi Cons ain s on Technical E iciency o D agon Fa me s: E idence om he Dis ic o Jhenaidah and
Chuadanga
IJSSHR, Volume 08 Issue 10 Oc obe 2025 www.ijssh .in Page 7815
Fu he mo e, he esul s o he ine iciency e ec s model indica e ha he echnical e iciency o bo h g oups o d agon
a me s is in luenced by ac o s such as he le el o educa ion, he size o he household, he iming o sowing, he a ailabili y o
ex ension se ices, ea nings om non- a ming ac i i ies, and he sa ings o he household head. The c edi size a iable has a
posi i e impac , bu he in e es a es on he p incipal amoun ha e a signi ican ly nega i e impac on he echnical e iciency o
d agon cul i a ion.
Ou esea ch indica es ha ha ing access o o mal c edi assis ance can alle ia e inancial cons ain s o households,
enabling hem o a o d necessa y a m inpu s. Thus, i is impe a i e o he go e nmen and p i a e inancial o ganiza ions o
simpli y he loan p ocess and lowe he in e es a e o ag icul u al businesses. In addi ion, i is c ucial o he go e nmen o aise
he c edi limi pe ac e, aking in o accoun he inancial needs and inpu expenses. I would be help ul o inancial ins i u ions o
conside opening b anches in emo e a eas o Jhenaidah and Chuadanga Dis ic . This would help a me s access he se ices hey
need and po en ially con ibu e o an inc ease in he ins i u ions' loan po olio.
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