Adoption of farm mechanization for clean air: Evidence from farm trials in Pakistan

Mish a, Ashok K.; Haz ana, Jawe iah; Yamano, Takashi; Sa o, No iko; A i , Babu
Wasim
Wo king Pape
Adop ion o a m mechaniza ion o clean ai : E idence
om a m ials in Pakis an
ADB Economics Wo king Pape Se ies, No. 758
P o ided in Coope a ion wi h:
Asian De elopmen Bank (ADB), Manila
Sugges ed Ci a ion: Mish a, Ashok K.; Haz ana, Jawe iah; Yamano, Takashi; Sa o, No iko; A i , Babu
Wasim (2024) : Adop ion o a m mechaniza ion o clean ai : E idence om a m ials in Pakis an,
ADB Economics Wo king Pape Se ies, No. 758, Asian De elopmen Bank (ADB), Manila,
h ps://doi.o g/10.22617/WPS240587-2
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ADB ECONOMICS
WORKING PAPER SERIES
NO. 758
Decembe 2024
Adop ion o Fa m Mechaniza ion o Clean Ai
E idence om Fa m T ials in Pakis an
Many ice a me s bu n s ubble and s aw a e ha es , which wo sens ai pollu ion. This pape examines
he impac o aining o a me s in Punjab, Pakis an, on he adop ion o mechanized ice ha es e s
ha lea e sho ice s ubble, he eby educing he need o c op bu ning. The esul s show ha he aining
p og am inc eased a m pe o mance among ice a me s who adop ed he ice ha es e s, highligh ing
he need o adop ion o hese ha es e s o educe open ield bu ning and con ibu e o cleane ai .
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loans, equi y in es men s, gua an ees, g an s, and echnical assis ance.
ADOPTION OF
FARM MECHANIZATION
FOR CLEAN AIR
EVIDENCE FROM FARM TRIALS IN PAKISTAN
Ashok K. Mish a, Jawe iah Haz ana, Takashi Yamano, No iko Sa o, and Babu Wasim A i
ASIAN DEVELOPMENT BANK
The ADB Economics Wo king Pape Se ies
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ADB Economics Wo king Pape Se ies
Ashok K. Mish a, Jawe iah Haz ana,
Takashi Yamano, No iko Sa o,
and Babu Wasim A i
No. 758 | Decembe 2024
Ashok K. Mish a (ashok.k.mish [email protected])
is Kempe and E hel Ma ley Founda ion Chai and
Jawe iah Haz ana (jaw[email p o ec ed]om)
is a pos -doc o al ellow a A izona S a e Uni e si y.
Takashi Yamano ( [email protected] g) is a p incipal
economis a he Economic Resea ch and
De elopmen Impac Depa men ; No iko Sa o
(nsa [email protected] g) is a senio na u al esou ces specialis
o he Sec o s G oup; and Babu Wasim A i
(ba i .consul an @adb.o g) is a consul an a Pakis an
Residen Mission, Asian De elopmen Bank.
Adop ion o Fa m Mechaniza ion o Clean Ai :
E idence om Fa m T ials in Pakis an
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ABSTRACT
Many ice a me s bu n s ubble and s aw a e ha es , which wo sens ai pollu ion. This
pape examines he impac o aining on he adop ion o ad anced ice ha es ing
echnologies ha educe he need o c op bu ning. I uses da a om a clus e andomized
con olled ial in Pakis an. The esul s e eal ha he aining p og am imp o ed he a m
pe o mance o ice g owe s. The cos –bene i analysis shows ha a me s who ecei ed
he aining and used imp o ed mechanical ice ha es ing gene a ed highe p o i s, an
a e age gain o PRs19,784 pe ac e. The esul s highligh he po en ial o a ge ed
ex ension s a egies o accele a e he adop ion o p oduc i i y-enhancing and sus ainable
echnologies among smallholde a me s.
Keywo ds: ice a ming andomized con ol ial, di e ence-in-di e ence me hod,
e enues, ha es losses
JEL codes: C31, O33, Q12, Q16
______________________
The s udy was suppo ed by ADB TA 9940-REG Mains eaming Impac E alua ion,
Me hodologies, App oaches, and Capaci ies in Selec ed De eloping Membe Coun ies,
Subp ojec 1.
Co esponding au ho : Ashok K. Mish a (ashok.k.mish [email protected]).

1. In oduc ion
Inc easing ag icul u al p oduc i i y emains a key p io i y o policymake s and
de elopmen o ganiza ions in many de eloping and eme ging economies, whe e a
signi ican p opo ion o he popula ion li es in u al a eas and elies on ag icul u al
ac i i ies o hei li elihood (Gollin and Ud y 2021; Mca hu and Mcco d 2017). The
si ua ion is pa icula ly s a k in Sou h Asia, whe e app oxima ely 80% o he popula ion
li es in u al a eas. The ag icul u e sec o con ibu es a la ge sha e o he egion’s g oss
domes ic p oduc (55%), p o ides 45% o employmen oppo uni ies, and employs mo e
han wo- hi ds (65%) o he o al labo o ce (Wo ld Bank 2017). Inc easing p oduc i i y
could po en ially ini ia e a posi i e cycle o de elopmen , leading o imp o ed li elihoods,
inc eased ood secu i y, and equi able access o economic oppo uni ies.
Ag icul u al mechaniza ion is b oadly iewed as a c ucial way o inc ease
p oduc i i y, li elihood s a egy, yields, and income. Fo his eason, go e nmen s and
de elopmen pa ne s in many de eloping and eme ging economies alloca e subs an ial
esou ces o boos ag icul u al p oduc i i y. Fo ins ance, p og ams such as inpu
subsidies, machine y inancing schemes, ex ension se ices, and in as uc u e
de elopmen ha e been gea ed owa d imp o ing ag icul u al ou comes (Diao, Sil e , and
Takeshima 2016; Kienzle e al. 2013). Fu he mo e, mechaniza ion is an icipa ed o
ca alyze s uc u al ans o ma ion by di e ing labo om ag icul u e and in o mo e
p oduc i e non a m sec o s, ul ima ely con ibu ing o o e all economic g ow h (Gollin,
Pa en e, and Roge son 2002).
Howe e , inapp op ia e use o ag icul u al machine y can ha e unin ended
consequences. In Punjab, Pakis an, whea is he main s aple c op, and whea combine
ha es e s ha e been p omo ed in he pas . Because o hei ela i ely high a ailabili y,
2
a me s use whea combine ha es e s o ha es ice, e en hough whea ha es e s cu
he ice c op in he middle, lea ing sh edded ice s aws and high s ubbles in he ields.
Unable o emo e sh edded ice s aws and high s ubbles, a me s end o bu n hem.
The p ac ice o bu ning c op esidue has signi ican en i onmen al and heal h implica ions
(Kuma , Kuma , and Joshi 2015; Kaushal and P asha 2021) and con ibu es o ai
pollu ion and g eenhouse gas (GHG) emissions (Bha acha yya and Ba man 2018).1
P ope ice ha es e s, on he o he hand, can cu he ice plan s a he bo om, lea ing
only sho s ubble in he ields. In addi ion, long ice s aws, p ope ly cu a he bo om,
can be sold a a highe p ice han sh edded s aws. The use o p ope ice ha es e s,
he e o e, is expec ed o educe c op bu ning and help a me s inc ease hei pos ha es
income.
The objec i e o his s udy is o assess he impac o he ADB echnical assis ance
p og am Enhancing Technology-Based Ag icul u e and Ma ke ing (ETAM) in Ru al
Punjab on he a m pe o mance indica o s (ou come a iables) o ice a me s. The
ETAM p og am is a mul i ace ed in e en ion ha aims o p omo e imp o ed
mechaniza ion and enhance he li elihoods o smallholde s. The ETAM p og am includes
aining on ha es ing echnologies and imp o ed cul i a ion p ac ices, pos ha es
p ocessing me hods, ma ke linkages, and inc eased p o i abili y along he ice alue
chain. An impo an componen o he ETAM p og am is he p omo ion o a p ope ice
ha es e , which can cu he ice c ops a he lowes possible heigh .
1 In a mo e ecen s udy, Bha acha yya e al. (2021) es ima ed a ne gain (bo h economic and
en i onmen al) o $664 pe hec a e om he p oduc ion o bioe hanol om s aw, ollowed by he con e sion
o biocha ($183 pe hec a e) and conse a ion ag icul u e p ac ices wo h $131 pe hec a e.
3
To es ima e he ea men e ec s o he ETAM p og am on a m pe o mance
indica o s, we ha e conduc ed a s anda d di e ence-in-di e ences (D-I-D) analysis by
compa ing he change in a m pe o mance indica o s (ou come a iables) be ween he
ea ed and con ol samples be o e and a e he implemen a ion o he p og am. In
addi ion, we ha e used a iple di e ence (DDD) s a egy o examine he speci ic impac
o adop ing ice ha es e s in he ea ed g oup. The DDD analysis has compa ed he
change in a m pe o mance indica o s (ou come a iables) o he adop e s and non-
adop e s wi hin he ea ed illages ela i e o he change in a m pe o mance indica o s
p o i abili y o he con ol sample.
The s udy con ibu es o he li e a u e on ag icul u al mechaniza ion in se e al
ways. Fi s , by le e aging da a om a andomized con olled ial, we can es ima e he
causal impac s o an in e en ion p omo ing mechanized ice ha es ing and pos ha es
echnologies. In con as o many p e ious obse a ional s udies, ou expe imen al design
mi iga es conce ns abou sel -selec ion bias and endogenei y ha o en plague impac
e alua ions. Second, while mos exis ing s udies ha e p ima ily examined he e ec s o
mechaniza ion on p oduc i i y and/o p o i , we discuss se e al po en ial pa hways
h ough which mechaniza ion in luences a m pe o mance and p o i abili y. The
pa hways include changes in c op yields, pos ha es losses, ou pu p ices, and cos s.
Thi d, ou s udy con ibu es o he limi ed e idence on he impac o ag icul u al
mechaniza ion2 in he con ex o Pakis an. This s udy p o ides aluable insigh s in o he
2 Ag icul u al mechaniza ion has he po en ial o boos p oduc i i y and inc ease p o i abili y. The ex en o
he economic bene i s o en depends on con ex ual ac o s and he e ec i e implemen a ion o a ge ed
in e en ions.
4
po en ial impac s, challenges, and scalabili y o policy ini ia i es in a low-income
de eloping coun y se ing like Pakis an.
The emainde o he pape is o ganized as ollows. Sec ion 2 desc ibes he
backg ound, while sec ion 3 desc ibes he concep ual amewo k o he s udy. Sec ion 4
con ains he su ey and da a as well as desc ip i e s a is ics. Sec ion 5 ou lines he
empi ical amewo k. Sec ion 6 p esen s he esul s o he s udy. Sec ion 7 epo s on he
bene i -cos analysis. Finally, sec ion 8 p esen s a discussion and conclusions as well as
policy implica ions.
2. Backg ound
Pakis an is home o 8.2 million a m amilies (Pakis an Bu eau o S a is ics 2010) who a e
esponsible o mee ing he basic ood and nu i ion needs o an es ima ed popula ion o
212 million people. App oxima ely 65% o Pakis an’s o al popula ion li es in u al a eas
and is di ec ly o indi ec ly dependen on ag icul u e o hei li elihood. Ag icul u e is an
impo an sec o in Pakis an, employing o e 37% o he labo o ce and con ibu ing
nea ly 30% o g oss domes ic p oduc (GDP) (Go e nmen o Pakis an 2023). O e he
las ew decades, he con ibu ion o ag icul u e o GDP has declined in p opo ion o
changes in he composi ion o he sec o . Howe e , he ag icul u al indus y has a much
g ea e po en ial o con ibu e o Pakis an’s GDP i i adop s inno a i e and mode n
echnologies o eplace adi ional and ou da ed ag onomic and a ming echniques
(USAID 2018). Mechaniza ion o a ming in Pakis an is s ill in i s ea ly s ages, wi h limi ed
adop ion o mode n machine y and echnologies, especially among smallholde s
(Go e nmen o Pakis an 2023). The le el o a m mechaniza ion in Pakis an is es ima ed
11
d um. The ines e ec i ely pick up and anspo he paddy h ough he ha es e ’s
sys em.
The h eshing d um, which is a ached o he ea o he machine, sepa a es he
g ains om he s aw h ough a high- eloci y h eshing and cleaning p ocess. The
h eshed g ains a e hen collec ed in an in eg a ed s o age ank wi h a capaci y o 0.8–
0.9 ons. Meanwhile, he in ac s aw is discha ged om he ha es e and laid back in
he ield in nea ows, making subsequen ield ope a ions easie . By demons a ing his
ad anced machine y, he p og am aimed o show smallholde a me s he e iciency,
p ecision, and labo -sa ing po en ial o mechanical ha es ing. The demons a ions
highligh ed he ha es e ’s abili y o minimize c op losses, imp o e he imeliness o
ope a ions, and educe he d udge y associa ed wi h adi ional manual ha es ing
me hods, ul ima ely con ibu ing o highe p oduc i i y and be e a m pe o mance o
adop e s.
4.2. Sample Selec ion
The su eys we e conduc ed in h ee dis inc phases in he ag icul u e sec o o u al
Punjab, co e ing he dis ic s o Sheikhupu a and Ha izabad. In he baseline su ey,
which was conduc ed in Sep embe –Oc obe 2020, 978 a me s we e in e iewed. The
same a me s we e in e iewed in he midline and endline su eys in Sep embe –
Decembe 2021 and 2023. The s udy used a clus e andomized con ol ial (CRCT)
design o p e en in o ma ion and se ices om spilling o e be ween a me s in he
ea men and con ol g oups, which is di icul o a oid when bo h g oups li e in he same
illage. To minimize such con amina ion, he s udy used he CRCT in which illages,

12
a he han indi idual a me s, we e andomly assigned o ea men and con ol g oups.
A h ee-s age p ocess was used o assign he illages.
In he i s s age, he ehsils we e selec ed. One ehsil was delibe a ely selec ed in
each a ge dis ic , conside ing c i e ia such as homogenei y in e ms o soil salini y,
dep h and quali y o g oundwa e , and he a ailabili y o se ice p o ide s, p ocesso s,
and expo e s. In he second s age, he qanungo halqas (QH) was selec ed. Each
selec ed ehsil consis s o ou o se en QHs. In each selec ed ehsil, wo QHs we e
selec ed based on he c i e ion o access o pa ed oads adequa e o he mo emen o
combine ha es e s o he illages and anspo a ion o p oduce o he loca ion o ade s,
p ocesso s, and expo e s. A e lis ing all smallholde a me s h ough comple e
enume a ion, one o he wo selec ed QHs om each ehsil was andomly assigned o he
ea men g oup. Finally, wi hin each selec ed QH, a ew illages in simila geog aphic
p oximi y we e chosen based on ha ing access o a sui able oad o anspo ing
machine y and p oduce. Villages ha we e e y la ge o had ex eme socioeconomic
di e si y, con lic s, o in luen ial people who could in luence p ojec implemen a ion we e
excluded.
A comp ehensi e enume a ion exe cise was ca ied ou in each illage o lis all
smallholde a me s p oducing he a ge c ops. Du ing he lis ing ac i i y, in o ma ion was
collec ed on household land owne ship unde a ious enancy con ac s, land size, c ops
g own in di e en seasons, sou ces o li elihood o landless households and hei
in ol emen in a m labo , and con ac de ails. In he illages wi hin he ea men QH, all
smallholde a me s we e in i ed o pa icipa e in he demons a ions and use he se ices
o he p o ide s. Table 1 shows he ehsils, he QHs selec ed om each ehsil, and he
13
numbe o illages om each QH. A o al o 41 illages we e selec ed om he ice-whea
c opping zones. Abou 978 smallholde a me s andomly selec ed om he QHs
pa icipa ed in each su ey. Table 2 p o ides in o ma ion on he pa icipan s om he
ea men and con ol QHs o he baseline su ey.
4.3. Da a Desc ip ion
Du ing he su eys, comp ehensi e da a we e collec ed in eigh hema ic blocks o
de elop a de ailed unde s anding o he esponden s’ ag icul u al p ac ices and
li elihoods. This mul i ace ed app oach was designed o p o ide a ho ough analysis o
he impac o he esea ch in e en ions and o cap u e di e en aspec s o he
esponden s’ ag icul u al ac i i ies and socioeconomic condi ions. The su ey collec ed
gene al in o ma ion abou he esponden s and key demog aphics such as gende , age,
ma i al s a us, educa ion le el, and a ming expe ience o he household head. In addi ion,
his sec ion asked abou households’ p ima y sou ces o li elihood, housing condi ions,
and land owne ship s a us, which p o ides in o ma ion on esponden s’ gene al li elihood
s a egies and s anda d o li ing. In o ma ion was also collec ed on land owne ship, an
impo an aspec o ag icul u al p oduc ion. Responden s p o ided de ailed in o ma ion
on he ype o land enu e a angemen s hey had en e ed in o, including owne ship,
en al, o o he con ac ual ag eemen s. Fu he mo e, he numbe o cul i a ed plo s, he
o al cul i able a ea, soil cha ac e is ics, and i iga ion sou ces we e eco ded, all o which
in luence ag icul u al p oduc i i y and a m decision-making.
A speci ic pa o he su ey ocused on c opped a eas o gain a comp ehensi e
unde s anding o esponden s’ c opping pa e ns. Responden s p o ided in o ma ion on
14
he speci ic c ops g own in di e en seasons and he a ea alloca ed o each c op. These
da a we e c ucial o analyzing c op choices, di e si ica ion s a egies, and he po en ial
impac on income and ood secu i y. The su ey also eques ed in o ma ion on
esponden s’ ag icul u al p ac ices, such as land p epa a ion me hods, use o inpu s (e.g.,
seeds, e ilize s, pes icides), and pos ha es handling echniques. This in o ma ion was
c ucial o iden i ying po en ial a eas o imp o emen , p omo ing sus ainable p ac ices,
and assessing he impac o in e en ions on ag icul u al p oduc i i y and esou ce
e iciency.
Finally, a sepa a e sec ion looked a ag icul u al p oduc ion and asked abou he
ice a ie ies g own, i iga ion me hods used, seed quan i ies u ilized, seed p ocu emen
sou ces, p oduc ion le els, plan ing echniques, ag onomic p ac ices used, and
ha es ing me hods. The su ey collec ed i al in o ma ion om a me s on he
ma ke able su plus and ma ke ing channels o he ice p oduced. This sec ion also
included in o ma ion on o al p oduc ion disagg ega ed by a ie y, quan i ies ese ed o
household consump ion, quan i ies s o ed o u u e sale, and he a ious means a me s
use o acili a e he sale o hei ice p oduce. Fu he mo e, he su ey included a sec ion
on access o ag icul u al ex ension se ices, sou ces o ma ke in o ma ion, c edi
p o ide s, asse owne ship, and po e y le els.
4.3.1. Ou come a iables
We use mul iple ou come a iables o igo ously e alua e he impac o he ETAM
p og am on he a m pe o mance o ice-p oducing households in Punjab p o ince. The
selec ion o pe o mance indica o s ac oss he en i e p oduc ion cycle, om ha es o
15
pos ha es p ocesses, p o ides a comp ehensi e pic u e. Ou i s ou come is yield
(maunds [Md] pe ac e),5 which is a di ec measu e o p oduc i i y. By making ha es ing
ope a ions mo e e icien and educing c op losses wi h manual me hods, he use o ice
ha es e s can inc ease ice yield on cul i a ed plo s. Second, we also quan i y he losses
and damage o he ice c op du ing ha es . No e ha such measu emen s p o ide di ec
e idence o whe he he echnologies imp o e he e iciency o he ha es ing p ocess.
C op loss and damage a es du ing ha es cap u e he e iciency o he p ocess i sel .
Manual ha es ing o en esul s in spillage, b oken g ains, and loss o ou pu . Mechanized
ha es ing wi h specialized ice ha es e s can minimize such losses, which bene i s
a me s. Thi d, we check i he e is a p ice p emium o incen i e o paddy ha es ed
mechanically. This measu e sheds ligh on he po en ial e enue bene i s o a me s
esul ing om he adop ion o mechanical ice ha es e s. A p ice p emium o
mechanically ha es ed paddy e lec s he ma ke demand o highe quali y g ain wi h
less impu i ies (such as b oken ice and ice husk). This p emium ep esen s a po en ial
e enue bene i o a me s om adop ion.
Fou h, we also assess he alue o ex a s aw by-p oduc s ha a e made
a ailable as odde h ough mechanical ha es ing. The by-p oduc s, such as baled ice
s aw, p o ide addi ional ancilla y bene i s, o example, li es ock eed, animal bedding
and uel— ice palle s.6 The amoun o s aw by-p oduc s a ailable o use as odde o
uel also has mone a y alue. Du ing mechanical ha es ing, he pieces o s aw a e no
damaged o sho ened, which inc eases he usable s aw ou pu and hus o e s an
5 1 maund = 37.32 kilog ams.
6 Palle iza ion o ice s aw is a o m o mass and ene gy densi ica ion (Ishii and Fu uichi 2014). The pelle s
a e easy o handle, anspo , s o e, and u ilize because o he inc ease in bulk densi y.
16
addi ional bene i . Finally, we es ima e he cos sa ings om he adop ion o he
mechanical ice ha es e in p epa ing he land o he nex c op cycle. This indica o
demons a es a longe - e m impac on ime and budge managemen . Timely and e icien
ha es ing can acili a e he imely plan ing o he nex c op and sa e land p epa a ion
cos s. Indeed, such longe - e m cos sa ings om he use o mechanical ice ha es e s
u he con ibu e o a m p o i abili y. In sum, he selec ed indica o s include me ics ha
a e di ec ly linked o p oduc i i y and p o i abili y h oughou he p oduc ion cycle—
quan i ying ha es ing e iciency, cos sa ings, e enue gains, and ancilla y bene i s. The
comp ehensi e co e age hus p o ides app op ia e e idence o assessing he impac o
he ansi ion om adi ional ice ha es ing me hods o mechanical ice ha es ing
echnologies a he a m le el.
4.4. Desc ip i e S a is ics
Table 3 p esen s he desc ip i e s a is ics o he pooled sample, he ea ed and he
con ol g oups. O no e is he i s panel o Table 3, whe e he ice yield o all sampled
a me s in he su ey egion was abou 36 Md pe ac e. Howe e , he yield o he ea ed
g oup o a me s (37 Md pe ac e) is highe han ha o he con ol g oup o a me s (35
Md pe ac e). The s aw p ice ecei ed by a me s in he egion also a ied be ween he
ea men and con ol g oups. The p ice o s aw o all sampled a me s in he su ey
egion was abou PRs7,589 pe ac e. Howe e , he p ice o s aw ecei ed is highe o
he ea ed g oup o a me s (abou PRs7,696 pe ac e) han o he con ol g oup o
a me s (PRs7,384 pe ac e). The las ow o he op panel in Table 3 shows he cos
sa ings in p epa ing he land o he nex sowing by using he mechanical ice ha es e .
In ac , hese cos sa ings a e much highe o he ea ed g oup o a me s, whose

17
a e age sa ings a e PRs3,421 pe ac e compa ed o he con ol g oup o a me s
(PRs2,855 pe ac e) and he a me s o he en i e sample (PRs3,251 pe ac e). The
second panel o he able shows he socioeconomic cha ac e is ics o he households in
he sample. Fa me s in he ea ed g oup a e sligh ly younge (44 yea s old), ha e less
a ming expe ience (22 yea s), and de i e a lowe p opo ion o hei income om a ming
(47%) han a me s in he con ol g oup.
Figu e 1 p esen s he ke nel densi ies o he ou come a iables o he con ol and
ea men g oups. The igu e e eals ha he dis ibu ion o ice yields o he ea men
g oup is sligh ly shi ed o he igh compa ed o he con ol g oup, indica ing highe
a e age yields o he ea ed a me s. The dis ibu ion o ha es losses o he ea men
g oup is skewed owa d lowe alues compa ed o he con ol g oup. The pa e n implies
ha he ETAM p og am was e ec i e in educing ha es losses o he ea ed a me s,
possibly h ough imp o ed ha es ing echniques and echnologies. Simila ly, he
dis ibu ions o he p ice o paddy and he addi ional p ice o s aw a e shi ed o he igh
in he ea men g oup compa ed o he con ol g oup. The esul sugges s ha he ea ed
a me s we e able o e ch highe p ices o hei paddy and ea n addi ional income om
s aw sales. This is likely due o imp o ed quali y, be e ma ke linkages, o g ea e
ba gaining powe p omo ed by he ETAM p og am.
An impo an componen o he ETAM p og am is he p omo ion and use o he
Kubo a ice ha es e , a mechanized ha es ing echnology designed o add ess he
labo -in ensi e and ime-sensi i e na u e o ice ha es ing ope a ions. Figu e 2 illus a es
he p opo ion o a me s who used ice ha es e s in bo h he con ol and ea men
g oups o e he h ee wa es o he su ey. A no able upwa d end in adop ion can be
18
obse ed in bo h g oups, wi h a pa icula ly p onounced inc ease in he ea men g oup.
In he baseline wa e o he su ey be o e he implemen a ion o he ETAM p og am, he
adop ion a es o ice ha es e s we e ela i ely low a 7.95% in he con ol g oup and
19.11% in he ea men g oup. In he cou se o he subsequen su ey wa es, he
p opo ion o a me s using ice ha es e s inc eased in bo h g oups. Howe e , he
di e ence in adop ion a es be ween he con ol and ea men g oups widened o e ime,
om 11.16 pe cen age poin s (19.11–7.95) a he baseline su ey o 18.25 (34.62–16.37)
a he midline, and 22.65 pe cen age poin s (44.03–21.65) a he endline su ey. The
esul s indica e ha he widening gap in he adop ion o he ice ha es ing machine y
sugges s ha he ETAM p og am, wi h i s a ge ed aining and demons a ions, played a
signi ican ole in accele a ing he adop ion o ice ha es e s by ea ed a me s
compa ed o he con ol g oup.
5. Empi ical F amewo k
We begin by es ima ing a di e ence-in-di e ences (D-I-D) speci ica ion o he model. The
D-I-D echnique compa es he ou comes in he ea ed and con ol g oups be o e and
a e he echnical assis ance demons a ions. This allows us o measu e he a e age
e ec o he demons a ions on ou comes. Fo mally, we es ima e equa ion:
FPi =α+βTP(T ea edi ∗Pos )+βXXi +δi+εi (1)
whe e FPi ep esen s he ou come a iable o a m pe o mance (yields, ha es losses,
addi ional p ice o paddy, p ice o s aw sa ed, and cos sa ings in land p epa a ion7 o
he nex sowing) o household h and pe iod . T ea edi is a bina y a iable ha akes he
7 All con inuous a iables in he eg ession a e in loga i hmic o m.
19
alue o 1 i a household is in he ea men g oup, 0 o he wise. Pos is a bina y a iable
ha akes he alue o 0 i he yea is be o e he ETAM p og am and he alue o 1 a e
he implemen a ion o he p og am. Xi is a ec o o household cha ac e is ics, δi is he
panel ixed e ec s, and 𝜀𝜀𝑖𝑖𝑖𝑖 is he e o e m. No e ha he s anda d e o s a e clus e ed
a he illage le el, which is consis en wi h he le el o ea men assignmen (Be and,
Du lo, and Mullaina han 2004; Abadie e al. 2017).
The coe icien o in e es is βTP, which measu es he D-I-D es ima e o he a e age
e ec o ETAM on he ou come a iables o a m pe o mance; in o he wo ds, he change
in ou comes be ween households ha ecei ed he ETAM p og am in e en ion (i.e.,
ea ed) and hose ha did no (i.e., con ol) compa ed o he pe iod be o e he
in e en ion. Howe e , he analysis assumes ha wi hou he ea men , bo h he ea ed
g oup and he con ol g oup would ha e ollowed he same pa h wi h espec o hei a m
pe o mance indica o s (ou come a iables). A posi i e coe icien 𝛽𝛽𝑇𝑇𝑇𝑇 indica es ha he
a m pe o mance indica o s o he a m households ecei ing ea men imp o ed a e
he in e en ion compa ed o hose no ecei ing he ea men . Al hough he D-I-D model
is in o ma i e in ob aining he a e age ea men e ec s o he ETAM demons a ions, i
does no allow us o measu e he di e en ial o addi ional impac o he Kubo a ice
ha es e —an impo an componen o he ETAM p og am. The e o e, o es ima e he
e ec o he Kubo a ice ha es e on a m pe o mance indica o s, we modi ied ou main
speci ica ion and speci ied a iple di e ence design (DDD). The DDD app oach allows
us o compa e he impac o he ETAM p og am on he ea ed g oup, which was
di e en ia ed by he adop ion o he Kubo a ice ha es e (KRH) ela i e o he con ol
g oup.
20
FPi =α+βTPK(T ea edi ∗Pos ∗KRH )+βTP(T ea edi ∗Pos )+βXXi +δi+εi (2)
whe e KRH is a dummy a iable ha indica es he adop ion o he Kubo a ice ha es e
in he pos ea men pe iod; KRH akes he alue o 1 i he household adop ed he Kubo a
ice ha es e in he pos ea men pe iod; 0 o he wise. The emaining a iables in
equa ion (2) a e de ined as in he D-I-D model p esen ed in equa ion 2. In he DDD
speci ica ion, βTPK measu es he e ec o he ETAM p og am on he a m pe o mance
indica o s (ou come a iables) o households ha adop ed he Kubo a ice ha es e .
The coe icien cap u es he a ia ion in ou comes speci ic o adop e households in he
ea ed g oup ( ela i e o he con ol g oup) be o e and a e he p og am ollou . In
con as , βTP measu es he o e all e ec o he ETAM in e en ion on a m pe o mance
indica o s (ou come a iables) o households ha we e exposed o he ea men .
Pa allel ends assump ion
The D-I-D me hodology elies on he assump ion o “pa allel ends,” acco ding o which,
wi hou ea men , he ea ed g oup and he con ol g oup would ha e ollowed he same
end in he ou comes s udied. This assump ion is c ucial because i helps o ensu e ha
he obse ed e ec s a e ea men a e due o he ea men i sel and no o p eexis ing
ends. We es his pa allel end assump ion by p o iding some sugges i e e idence.
Fi s , we ely on baseline da a collec ed in 2020 be o e he implemen a ion o he ETAM
p og am o show ha household a m pe o mance indica o s (o ou come a iables used
in his s udy) ollowed simila ends in he ea ed and con ol g oups. Howe e , he
p esen s udy has da a limi a ions ha p e en he es ablishmen o pa allel p e ea men
ends. In pa icula , households we e obse ed only once be o e ea men .
27
o paddy, income om s aw sales, highe yields, and cos sa ings in land p epa a ion.
In his sec ion, we p esen a comp ehensi e bene i –cos analysis o he ETAM p og am
using a e age alues om he su ey da a. Table 8 shows he bene i –cos analysis o
he ETAM p og am ac oss he h ee su ey ounds o he ea men g oup ha also
adop ed he mechanized ice ha es e (KRH). While he ini ial cos o adop ing a KRH is
highe han ha o a adi ional combined ha es e , his addi ional in es men is o se by
he nume ous bene i s de i ed om adop ing he KRH and implemen ing he ETAM
p og am’s aining and p ac ices. One o he signi ican ad an ages o he ETAM p og am
is he educ ion o ha es losses. Ha es losses a e a majo sou ce o ine iciency in
adi ional ice a ming, as a conside able po ion o he c op is los du ing ha es ing and
pos ha es handling. The ETAM p og am helped a me s minimize hese losses by
aining hem in p ope ha es ing echniques and p omo ing he KRH echnology. In all
su ey ounds, he educ ion in ha es losses due o he adop ion o KRH anged om
3.5 o 3.8 Md pe ac e. This ansla es in o addi ional e enue a ibu ed o he educ ion
in ha es losses, which anges om PRs6,243 o PRs14,062 pe ac e and con ibu es
di ec ly o a m income. In addi ion, he ETAM p og am enabled a me s o e ch a highe
p ice o hei paddy by imp o ing he quali y o he ice and acili a ing be e ma ke
linkages. Fa me s who pa icipa ed in he ETAM p og am wi h he KRH can ea n
addi ional e enue due o a highe p ice p emium anging om PRs75 o PRs138 pe
ac e, depending on he su ey ound.
Complemen ing he ad an ages men ioned abo e, pa icipa ion in he ETAM
p og am and he adop ion o KRH gene a ed addi ional income o a me s h ough he
sale o s aw. T adi ionally, a signi ican amoun o s aw is los o was ed du ing

28
ha es ing and pos ha es ope a ions. Howe e , by adop ing he KRH and implemen ing
he ETAM p og am’s p ac ices, a me s we e able o e icien ly bundle he s aw using he
KRH and sell a la ge po ion o he s aw. In his way, a ming amilies we e able o ea n
an addi ional income anging om PRs5,273 o PRs11,441 pe ac e du ing he su ey
ounds. This addi ional income om s aw sales can be an impo an sou ce o e enue,
especially in a eas whe e s aw is in high demand. Mo eo e , he adop ion o ad anced
echnologies and mechaniza ion h ough he ETAM p og am has educed he cos o land
p epa a ion o he nex sowing cycle. By implemen ing e icien land p epa a ion
echniques, imp o ed a m machine y, and be e esou ce managemen p ac ices
p omo ed by he ETAM p og am and he adop ion o KRH, a me s sa ed cos s anging
om PRs2,196 o PRs5,690 pe ac e du ing he su ey ounds. This cos -sa ing aspec
u he con ibu es o he o e all economic iabili y o he ETAM p og am and he adop ion
o he KRH. The las ow o Table 8 indica es ha he ne bene i pe ac e om
pa icipa ion in ETAM p og am p ac ices and KRH adop ion anges om PRs10,584 in
he baseline su ey o PRs25,079 in he endline su ey. The signi ican ne bene i s
highligh he economic iabili y and po en ial o scaling up ETAM in e en ions o imp o e
a m pe o mance, educe pos ha es losses, and p omo e sus ainable ag icul u al
de elopmen in he egion.
8. Conclusion and Implica ions
Pakis an’s ag icul u e sec o aces nume ous challenges, such as low p oduc i i y,
pos ha es losses, and limi ed mechaniza ion, especially among smallholde a me s.
Despi e he po en ial o ag icul u al mechaniza ion o boos p oduc i i y, he adop ion o
29
ha es ing echnologies among smallholde a me s in de eloping coun ies emains low.
The Go e nmen o Pakis an and na ional esea ch agencies ha e been wo king wi h he
Asian De elopmen Bank o educa e and p o ide ex ension se ices and new
echnologies o inc ease ice p oduc i i y and a m pe o mance in he ice alue chain.
This s udy examined he impac o he ETAM p og am on he a m pe o mance o ice
a me s in he u al Punjab p o ince o Pakis an. The esul s e ealed ha he ETAM
p og am had a posi i e impac on a a ie y o a m pe o mance ou comes, including
highe ice yields, educed ha es losses, addi ional income om he sale o paddy and
s aw, and cos sa ings in land p epa a ion. The inc eased adop ion o a p ope ice
ha es e is expec ed o educe c op bu ning in open ields. The posi i e impac o he
ETAM p og am aligns wi h he go e nmen ’s e o s o inc ease ag icul u al p oduc i i y,
achie e ood sel -su iciency, and educe ai pollu ion.
In addi ion, he educ ion in ha es losses obse ed in his s udy is pa icula ly
no ewo hy, as pos ha es losses a e one o he main causes o ine iciency in Pakis an’s
ag icul u e sec o . The ETAM p og am ocused on p omo ing imp o ed ha es ing
echniques and mechanized echnologies such as he Kubo a ice ha es e . In addi ion
o yield gains and educed ha es losses, he ETAM p og am also enabled highe p ices
o paddy and addi ional income om he sale o s aw. The long ice s aws le by he
Kubo a ha es e a e mo e aluable han sh edded ice s aws le by whea combined
ha es e s. The e o e, he indings o his s udy highligh he ole o he ETAM p og am in
imp o ing ma ke linkages, ba gaining powe , mechaniza ion, and he o e all alue chain
o ice cul i a ion in Pakis an.
30
O e all, he he e ogenei y analyses unde sco e he impo ance o conside ing
a m size and access o in o ma ion when designing and implemen ing ag icul u al
de elopmen p og ams. Tailo ed s a egies, suppo mechanisms, and complemen a y
policies may be equi ed o add ess he a ying cons ain s and needs o di e en
subg oups and ensu e equi able and inclusi e bene i s om such ini ia i es. I is
no ewo hy ha he ETAM p og am had a posi i e and signi ican impac on a m
pe o mance indica o s in he small and la ge holding a m ca ego ies, highligh ing he
po en ial o inclusi e bene i s om he in e en ions. None heless, he esul s unde sco e
he need o ailo ed suppo mechanisms and complemen a y policies o add ess he
speci ic cons ain s and challenges aced by smallholde a me s in adop ing and
maximizing he bene i s o mechanized echnologies. Simila ly, ou indings highligh he
c i ical ole o access o in o ma ion and ex ension se ices in acili a ing he e ec i e
adop ion and u iliza ion o new echnologies and p ac ices. Households wi h be e access
o in o ma ion a e mo e likely o be awa e o he po en ial bene i s, op imal iming, p ope
implemen a ion me hods, and a m pe o mance. The inding unde sco es he need o
s eng hen ag icul u al ex ension se ices and imp o e in o ma ion dissemina ion
mechanisms in Pakis an, especially o ma ginalized and esou ce-cons ained a ming
communi ies.
The indings o his s udy ha e se e al policy implica ions o p omo ing
sus ainable ag icul u al de elopmen and imp o ing a m pe o mance in Pakis an. Fi s ,
policies such as he ETAM p og am, which p omo es mechaniza ion, imp o ed cul i a ion
p ac ices, and ma ke linkages, need o be scaled up and inco po a ed in he mains eam.
These measu es con ibu e signi ican ly o achie e he coun y’s ag icul u al de elopmen
31
goals by boos ing p oduc i i y, educing pos ha es losses, and inc easing a me s’
incomes. Second, a ge ed suppo mechanisms such as subsidies, c edi acili ies, and
capaci y-building p og ams could be designed o add ess he speci ic cons ain s and
needs o smallholde a me s. The he e ogenei y analysis e ealed ha while he ETAM
p og am had a posi i e impac on all a m sizes, he bene i s we e mo e p onounced o
la ge a ms. The esul s o his s udy unde sco e he impo ance o ensu ing ha
mechaniza ion ini ia i es bene i all by p o iding ailo ed suppo o smallholde a me s
who o en ace limi a ions in accessing c edi , ex ension se ices, and economies o
scale.
Thi d, s eng hening ag icul u al ex ension se ices and imp o ing in o ma ion
dissemina ion mechanisms a e c ucial o acili a e he e ec i e adop ion and u iliza ion o
new echnologies and p ac ices. Ta ge ed e o s o imp o e he each and quali y o
ex ension se ices, coupled wi h e ec i e communica ion s a egies, can empowe
a ming communi ies, pa icula ly in esou ce-cons ained a eas, o maximize he
po en ial bene i s o such ini ia i es. Finally, complemen a y policies and in es men s in
in as uc u e, such as u al oads and s o age acili ies, a e essen ial o suppo he
adop ion and scalabili y o mechanized echnologies. Imp o ed in as uc u e can educe
pos ha es losses, enhance ma ke access o a me s, and acili a e he e icien
anspo a ion and handling o ag icul u al p oduce, hus con ibu ing o he o e all
economic iabili y and sus ainabili y o mechaniza ion ini ia i es.
32
Figu e 1: Ke nel Densi y Es ima es o Ou comes by T ea men G oups o Sampled
Households, Pakis an
Md = maund. 1 maund = 37.32 kilog am.
Sou ce: Au ho s’ calcula ion.

33
Figu e 2: Pe cen age o Fa me s Adop ing he Kubo a Rice-Ha es e Be o e and A e
he Technical Assis ance Demons a ions
Sou ce: ADB. Pakis an: Enhancing Technology-Based Ag icul u e and Ma ke ing in Ru al Punjab.
h ps://www.adb.o g/p ojec s/52232-001/main.
34
Figu e 3: Diagnos ics o Pa allel T ends
Sou ce: Au ho s’ calcula ions.
35
Table 1: Zone, Selec ed Tehsil, Selec ed Qanungo Halqas, and Numbe o Selec ed
Villages o he Su eys
Tehsil
Qanungo Halqa
No. o Selec ed Villages
Mu idke
Ahdian
8
Mu idke
11
Ha izabad
Chak Cha ha
9
Ha izabad
13
Sou ce: ADB. Pakis an: Enhancing Technology-Based Ag icul u e and Ma ke ing in Ru al Punjab.
h ps://www.adb.o g/p ojec s/52232-001/main.
Table 2: Con ol and T ea men Samples in he Baseline, Midline, and Endline Su eys
in Ru al Punjab, Pakis an
G oup
Qanungo
Halqa
Numbe o Pa icipan s
Pe cen age o Pa icipan s
Baseline
Midline
Endline
Baseline
Midline
Endline
Con ol
Ahdian
169
151
137
90.01
95.45
90.31
Chak Cha ha
176
165
153
91.01
96.85
91.64
Sub o al
345
316
290
90.49
96.12
90.95
T ea men
Ha izabad
317
293
250
88.07
96.75
87.28
Mu idke
316
308
273
90.05
98.54
90.67
Sub o al
633
601
523
89.13
97.70
89.08
To al
978
917
813
89.60
97.15
89.74
Sou ce: ADB. Pakis an: Enhancing Technology-Based Ag icul u e and Ma ke ing in Ru al Punjab.
h ps://www.adb.o g/p ojec s/52232-001/main.
36
Table 3: Summa y S a is ics o Fa m, Household, and Plo A ibu es o Sampled
Households in Punjab, Pakis an
To al Sample
T ea ed
Con ol
Mean
SD
Mean
SD
Mean
SD
Yields (Md/ac e)a
36.62
13.04
37.25
13.13
35.49
12.79
Ha es losses (Md/Ac e)
3.55
1.29
3.539
1.25
3.58
1.41
Paddy p ice (PRs/Md)
97.88
76.59
97.363
78.50
99.05
72.18
P ice o s aw (PRs/ac e)
7,589.04
4,150.24
7,695.85
4,264.06
7,384.00
3,916.36
Cos sa ings in land
p epa a ion o nex season
(PRs/ac e)
3,251.31
2,202.74
3,421.02
2,253.99
2,855.08
2,025.62
Household Con ols
Household size (numbe )
8.361
4.26
8.44
4.26
8.32
4.26
Income om c ops (%)
58.22
325.57
78.13
548.65
47.49
22.70
Fa ming expe ience (yea s)
22.44
13.29
23.34
13.31
21.953
13.26
Li e acy o household head (%)
75.64
42.93
77.06
42.05
73.00
44.41
Age o household head (yea s)
44.74
14.56
45.18
14.33
44.51
14.68
Ma i al s a us (%)
88.06
32.43
89.20
31.05
87.44
33.14
Plo Con ols
Soil ype (%)
Clay loam
35.10
47.73
34.37
47.51
35.49
47.85
Clay
11.19
31.53
8.44
27.81
12.68
33.28
Loam
22.66
41.86
24.26
42.88
21.79
41.29
O he s
0.35
5.88
0.15
3.89
0.45
6.70
Sandy
0.27
5.16
0.23
4.77
0.29
5.35
Sandy loam
5.52
22.83
4.94
21.69
5.83
23.43
Sil y loam
24.92
43.26
27.60
44.72
23.47
42.39
I iga ion sou ce (%)
Canal
24.92
43.26
27.61
44.72
23.47
42.39
Tubewell
52.98
49.92
70.95
45.42
43.29
49.56
Canal + Tubewell
1.57
12.44
0.99
9.89
1.89
13.61
Obse a ions
3,233
2,083
1,150
Md = maund, PRs = Pakis an upees, SD = s anda d de ia ion.
a1 maund = 37.32 kilog ams.
Sou ce: ADB. Pakis an: Enhancing Technology-Based Ag icul u e and Ma ke ing in Ru al Punjab.
h ps://www.adb.o g/p ojec s/52232-001/main.
43
Box: Rice Ha es e Type by Sampled Households, Pakis an
The Kubo a ice ha es e used by Cen e o Ag icul u e and Biosciences In e na ional
(CABI) as pa o he echnical assis ance was esponsi e o all ield condi ions whe e
he c op a ma u i y is ei he e ec o lodged. The ER-112 was he la es model o
paddy-speci ic hal - eed ha es e in Punjab ha ing six s aw walke s wi h a cu e wid h
o 7 ee and 112-HP common ail engine. I essen ially consis s o ou majo pa s: he
heade , he con eying chains, he h eshing d um, and he g ain s o age ank. I cu s he
paddy a he lowes possible heigh and he chains a e ins alled on he heade assembly
wi h he ines moun ed on he chains. The ines a e used o g ab he paddy and a e
guided h ough chains o he h eshing d um. The g ains a e h eshed and cleaned
using high- eloci y blowe s and an in eg a ed h eshing d um moun ed on he ea side
o he machine. The h eshed g ains a e s o ed in a s o age ank wi h a capaci y o 0.8–
0.9 ons. The in ac /whole s aw is mo ed ou o he ha es e and h own back on o he
ield in ows.
The Thinke XG750S is a ull- eed paddy-speci ic ha es e ha pe o ms h ee
sepa a e ope a ions: eaping, h eshing, and winnowing ins ead o sepa a e machines.
The wide heade (7 ee ) a he on o he ha es e ga he s he c op in o he machine.
The eel pushes he c op owa d he cu e blade, which cu s he c op. The g ains a e
hen anspo ed o he h eshing d um ia a con eye bel . The e, he g ains a e
sepa a ed om he s alks and collec ed in a sepa a e d um wi h a s o age capaci y o
0.3–0.4 ons, which is discha ged h ough he machine’s side pipe auge . The ha es e
is capable o ha es ing bo h s anding and lodged c ops. Howe e , a me s only
in e es ed in ha es ing he lodged c op wi h his ha es e .
Sou ce: ADB. Pakis an: Enhancing Technology-Based Ag icul u e and Ma ke ing in
Ru al Punjab. h ps://www.adb.o g/p ojec s/52232-001/main.

44
Figu e A1: His og am o Fa m Size and Sampled Households, Pakis an
Sou ce: ADB. Pakis an: Enhancing Technology-Based Ag icul u e and Ma ke ing in Ru al Punjab.
h ps://www.adb.o g/p ojec s/52232-001/main.
45
Figu e A2: Pe cen age o Sampled Households Accessing In o ma ion, Pakis an
Sou ce: Sou ce: Au ho s’ calcula ion.
46
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ASIAN DEVELOPMENT BANK
ASIAN DEVELOPMENT BANK
6 ADB A enue, Mandaluyong Ci y
1550 Me o Manila, Philippines
www.adb.o g
ADB ECONOMICS
WORKING PAPER SERIES
NO. 758
Decembe 2024
Adop ion o Fa m Mechaniza ion o Clean Ai
E idence om Fa m T ials in Pakis an
Many ice a me s bu n s ubble and s aw a e ha es , which wo sens ai pollu ion. This pape examines
he impac o aining o a me s in Punjab, Pakis an, on he adop ion o mechanized ice ha es e s
ha lea e sho ice s ubble, he eby educing he need o c op bu ning. The esul s show ha he aining
p og am inc eased a m pe o mance among ice a me s who adop ed he ice ha es e s, highligh ing
he need o adop ion o hese ha es e s o educe open ield bu ning and con ibu e o cleane ai .
Abou he Asian De elopmen Bank
ADB is commi ed o achie ing a p ospe ous, inclusi e, esilien , and sus ainable Asia and he Paci ic,
while sus aining i s e o s o e adica e ex eme po e y. Es ablished in 1966, i is owned by 69 membe s
—49 om he egion. I s main ins umen s o helping i s de eloping membe coun ies a e policy dialogue,
loans, equi y in es men s, gua an ees, g an s, and echnical assis ance.
ADOPTION OF
FARM MECHANIZATION
FOR CLEAN AIR
EVIDENCE FROM FARM TRIALS IN PAKISTAN
Ashok K. Mish a, Jawe iah Haz ana, Takashi Yamano, No iko Sa o, and Babu Wasim A i