Blay, James Ko i; Nayak, Aksha a; Abunyuwah, Isaac; Lokesha, Huchaiah; Paily,
G acy Chenno humalil
A icle
Asymme ic and h eshold p ice ansmission dynamics in
onion ma ke s in India
Cogen Economics & Finance
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G acy Chenno humalil (2024) : Asymme ic and h eshold p ice ansmission dynamics in onion
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Asymme ic and h eshold p ice ansmission
dynamics in onion ma ke s in India
James Kofi Blay, Aksha a Nayak, Isaac Abunyuwah, Huchaiah Lokesha &
G acy Chenno humalil Paily
To ci e his a icle: James Kofi Blay, Aksha a Nayak, Isaac Abunyuwah, Huchaiah Lokesha
& G acy Chenno humalil Paily (2024) Asymme ic and h eshold p ice ansmission
dynamics in onion ma ke s in India, Cogen Economics & Finance, 12:1, 2402557, DOI:
10.1080/23322039.2024.2402557
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GENERAL & APPLIED ECONOMICS | RESEARCH ARTICLE
Asymme ic and h eshold p ice ansmission dynamics in onion
ma ke s in India
James Ko i Blay
a,b
, Aksha a Nayak
c
, Isaac Abunyuwah
a
, Huchaiah Lokesha
b
and
G acy Chenno humalil Paily
d
a
Depa men o Ag icul u al Economics, Aken en Appiah-Menka Uni e si y o Skills T aining and En ep eneu ial
De elopmen (AAMUSTED), Mampong-Ashan i, Ghana;
b
Depa men o Ag icul u al Economics, UAS, GKVK, Bengalu u,
Ka na aka, India;
c
Ag icul u al De elopmen and Ru al T ans o ma ion Cen e, Ins i u e o Social and Economic Change
(ISEC), Bengalu u, Ka na aka, India;
d
Depa men o Ag icul u al Ma ke ing, Co-ope a ion and Ag ibusiness Managemen ,
UAS, GKVK, Bengalu u, Ka na aka, India
ABSTRACT
Func ional ag icul u al ma ke ing sys em is pu po ed o be he sil e bulle and
mul iplie o s imula ing p oduc ion and consump ion and, accele a ing he pace o
economic and u al en e p ise de elopmen . Thus, unde s anding e ec i eness o ag i-
cul u al p oduc s ma ke p ice ansmission dynamics in a unc ional ag icul u al ma -
ke ing sys em is use ul o all sec ions o socie ies conce ned wi h he ma ke ing o
ag icul u al p oduce. Thus, his s udy was conduc ed o assess he ma ke middlemen
esponse o onion p ice pe u ba ion. To s imula e policy e alua ion and in e en ion
in India onion ma ke s, se en majo s’onion ma ke s namely: Lasalgaon ( e e ence
ma ke ), Kanpu , Mumbai, Lucknow, Ko zhikode, Myso e, and Hyde abad we e exam-
ined using mon hly wholesale p ices om Janua y 2011 o Decembe 2018. Ma ke
middlemen esponse o p ice shocks was examined h ough he amewo k o
momen um h eshold au o eg essi e model and a egime-swi ch asymme ic h esh-
old ec o e o co ec ion model. The esul s o he es ima ion p ocedu e e ealed
ha he ma ke s we e cha ac e ized by h eshold co-in eg a ion and asymme ic
esponse adjus men pa h bo h in he sho and long un. The s udy esul s indica ed
ha wholesale s esponded as e o de ia ions ha end o inc ease hei p o i ma -
gin bu delayed in esponding o p ices changes ha end o bene i he p oduce s.
We ecommend s ingen measu es agains in ensi ica ion o exis ing egula ed
ma ke ing s uc u es ha seek o a ou middlemen a he expense o p oduce s and
consume s and, he conscious e o o imp o e ma ke in elligence s uc u e o
e icien conduc and pe o mance o onion ma ke s in India.
IMPACT STATEMENT
The esul s o he es ima ion p ocedu e e ealed ha he ma ke s we e cha ac e ized
by h eshold co-in eg a ion and asymme ic esponse adjus men pa h bo h in he
sho and long un. The s udy esul s indica ed ha wholesale s esponded as e o
de ia ions ha end o inc ease hei p o i ma gin bu delayed in esponding o p ice
changes ha end o bene i he p oduce s.
ARTICLE HISTORY
Recei ed 13 No embe 2023
Re ised 2 July 2024
Accep ed 29 Augus 2024
KEYWORDS
P ices; asymme ic;
h eshold model;
ma ke dynamics
SUBJECTS
Economics; Economics and
De elopmen ; De elopmen
Policy
1. In oduc ion
The issues o b idging disc epancies and dispa i y gaps in income and li ing s anda ds among ag icul u al
commodi y p oduce s amids he mul i ace ed beha iou o ma ke middlemen in he compe i i e ma ke
economy in de eloping coun ies o enhance u al de elopmen ha e a ac ed conside able a en ion o e
he pas wo decades. Howe e , go e nmen e o s and in e en ions owa ds es uc u ing p oduce s’eco-
nomic s anda ds depend magnanimously on he complexi ies, conduc , s uc u e, and pe o mance o
CONTACT James Ko i Blay [email p o ec ed] Depa men o Ag icul u al Economics, Aken en Appiah-Menka Uni e si y o
Skills T aining and En ep eneu ial De elopmen (AAMUSTED), Mampong-Ashan i, Ghana
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, 2402557
h ps://doi.o g/10.1080/23322039.2024.2402557
ag icul u al ma ke s, as well as he in e linkages ha exis among p oduce s, wholesale s, e aile s, and o he
ma ke agen s in he economy. The dynamics o commodi ies p ices and e iciency o p e ailing ma ke ing
sys ems a e pi o al o economic de elopmen , and a e c ucial o po e y alle ia ion and sus ainable li eli-
hood policy s a egies in ag a ian economies (Panagio ou, 2021). The e has been a con inuing deba e con-
ce ning he impac and app op ia eness o go e nmen oles and in e en ional policies in he ma ke place
and he e ec o hese policies on p oduc ion and ma ke ing o ag icul u al commodi ies in enhancing li eli-
hoods. Howe e , go e nmen in e en ion in se ing p ice ceilings in a compe i i e ma ke economy emain
con o e sial. In quan i a i e de elopmen policy analysis, his may be jus i ied i he in e en ion does no
enhance p ice dis o ion and disequilib ium in o he exis ing ma ke s uc u e and pe o mance, o emedies
he exis ing ma ke impe ec ion. Howe e , he complexi ies in he in e linkages ha exis among in e me-
dia ies along he commodi y supply alue chains and he p o i -maximizing seeking beha iou o ma ke s
agen s o ade s (middlemen) in compe i i e ag icul u al ma ke s s uc u e o ce economic ac o s o adjus
hei p ices o new cos condi ions in a di e gen manne (F ey & Mane a, 2007;Kuma e al.,2022;La dic&
Mignon, 2008;San e amo,2015). Howe e , (Abdulai, 2002;Abunyuwah,2020) no ed ha he e ec i eness o
ag icul u al ma ke s in enhancing and s imula ing li elihoods o ag icul u al commodi y p oduce s wi hin he
amewo k o go e nmen in e en ion depend ex ensi ely on he magni ude and di ec ion o he p ice
di e gence beha iou ansmi ed among spa ially dis ibu ed ma ke s ac oss majo geog aphical bounda ies
o an economic space in a coun y.
Du ing he pas wo decades, esea che s ha e de eloped my iad app oaches o accessing pe o mance,
in eg a ion and p ice ansmission dynamics o ag icul u al ma ke s dis ibu ed ac oss economic space by
adop ing a ian o econome ic echniques and app oaches. These s a is ical ools and econome ic echni-
ques ha ha e been applied in p e ious li e a u e o iden i y ma ke in eg a ion and p ice ansmission
dynamics include he applica ion o o dina y Leas Squa es (OLS) and co ela ion analysis (Cudjoe e al.,
2008; Hossain & Ve beke, 2010), Ra allion dynamic model (Alde man, 1992), es s ha examines he s ochas-
ic dynamic p ocess among he spa ially sepa a ed ma ke s (linea E o Co ec ion Model (ECM) (Ba e & Li,
2002;Engle&Yoo,1987;Fackle &Goodwin,2001; Gole i e al., 1995; Mcnew & Fackle , 1997).
Howe e , con empo a y ma ke in eg a ion and p ice ansmission dynamics analyses mos ly ocused
on dynamic models ha ha e he po en ial o cap u e he complex beha iou o economic agen s o e
ime (K is ou ek & Lunacko a, 2015). In he con ex o analysing he dynamic esponse beha iou o ag i-
cul u al ma ke economic agen s, esea che s ha e ocused on aspec s conce ned wi h he applica ion o
h eshold ec o e o co ec io model, h eshold asymme ic e o -co ec ion model (Abdulai, 2002;
Abunyuwah, 2020; Blake & Fomby, 1997; Ende s & Siklos, 2001; Von-C amon & Meye , 2004, Elalaoui
e al., 2018)asi ’s c i ical o unde s and he mul i ace ed beha iou o ma ke in e media ies and, also
p o ides he impulse o access he impac o policy in e en ion ha conce ns he di ec ion o wel a e
ans e as well as he sha e o p oduce s’p ices paid by consume s along he supply and alue chain,
and he conduc o he ma ke , and he applica ion o Ma ko -swi ching ECM (Holmes & O e o, 2023;
Rezi is & Tsionas, 2018; Su bak i e al., 2022). Mo eo e , he magni ude and elas ici y o ma ke in eg a-
ion and asymme y p o ide an indica ion on he compe i i eness and specializa ion o he ma ke s
acco ding o compa a i e ad an age (Ahmed & Singla, 2017; McLa en, 2015) and e icien u iliza ion o
p oduc ion esou ces (Abunyuwah, 2020; Blay e al., 2015).
In India, he con inuous go e nmen in e en ion in ag icul u al ma ke ing sys ems o imp o e ma ke
e iciency, and li elihood o p oduce s calls o c i ical e alua ion and deepe insigh s in o he p ice o -
ma ion dynamics and le els o ag icul u al ma ke in e connec edness and pe o mance. In India, onion
is ega ded as an essen ial c op o comme cial p oduc ion and a majo cons i uen o he c opping
in ensi y and di e si ica ion p og amme o po e y alle ia ion as indi iduals’abili y o pu chase o no
able o a o d is how po e y is unde s ood by a sec ion o he socie y ac oss he coun y. As a esul ,
onions ma ke s ha e become one o he mos poli ically sensi i e commodi ies ma ke s, and p ice hikes
plays signi ican ole in in de e mining poli ical o unes and measu e o good go e nance.
Consequen ly, onion ma ke s conduc has ecei ed mos o he popula a en ion because o go e n-
men in e en ional ole in con olling p ice o ma ion.
Despi e he signi icance o he onion ma ke conduc in policy in e en ion o mula ion in India, as sig-
ni ican numbe o s udies on spa ial p ice ansmission dynamics a e modelled wi hou conside ing he
asymme ic beha iou o majo economic ac o s (Ahmed & Singla, 2017;Reddye al.,2012; Sendhil e al.,
2 J. K. BLAY ET AL.
2014; Ujjwal e al., 2017;Von-C amon,1998) by adop ing models ha assume symme ic adjus men owa ds
long- un equilib ium due o p ice changes. Thus, esul s om such s udies may yield misleading es ima es
ha may be ei he unde es ima ion o o e es ima ion o dynamic p ocesses wi h ega ds o he beha iou
o ma ke agen s. In his ega d, an a emp has been made o apply a no el non-linea h eshold asymme -
ic adjus men model ha inco po a es asymme ic and symme ic dis ibu ed lag e ec o examine p ice
dynamics in majo onion ma ke s in India. Thus, we con ibu e o p e ious s udies ha emphasize on p ice
ansmission dynamics in he Indian onion ma ke s o p o ide in-dep h insigh in o he beha iou o ma ke
agen s along he onion ma ke ing chain due o he signi ican o he ma ke o go e nmen in policy o mu-
la ion. The emaining sec ions o his pape a e o ganized as ollows. Sec ion 2 p o ides a b ie desc ip ion
o he da a and econome ic modeling app oach adop ed, and Sec ion 3 desc ibes he empi ical analysis
and esul s. Sec ion 4 con ains concluding ema ks.
2. Da a and econome ics model
To assess p ice ansmission dynamics and ma ke e iciency in onion ma ke s, se en majo Indian onion
ma ke s, namely Lasalgaon, Kanpu , Mumbai, Lucknow, Ko zhikode, Myso e, and Hyde abad, we e con-
side ed. These ma ke s se e as he la ges ma ke s in he majo onion p oducing s a es in India wi h
Lasalgaon being he highly concen a ed onion ma ke as he e e ence ma ke . The da a se used o
he analysis was mon hly wholesale p ices om Janua y 2011 o Decembe 2018 ob ained om
Agma kne . The ime span up o 2018 was chosen o delinea e he e ec o he co id-19 pe iod as a
esul o signi ican a i icial upsu ge in commodi y p ice du ing he pe iod so as o p o ide a p ope
unde s anding o p ice dynamics and beha iou o middlemen in he conduc o he onion ma ke in
India. The uni a ia e da a gene a ing p ocess (DGP) o he p ice se ies was e alua ed h ough he ame-
wo k o he augmen ed Dickey- Fulle (ADF) es . The es ima ions o he subsequen econome ic mod-
els we e based on he loga i hm ans o ma ion o he da ase .
2.1. Th eshold co-in eg a ion
To cap u e he dynamic beha iou o ma ke agen s, which has he po en ial o non-linea i ies and
asymme ies in he p ice adjus men p ocess, he applica ion o h eshold co-in eg a ion models in ma -
ke in eg a ion (MI) analysis has gained much momen um in ecen esea ch s udies as he adi ional
models assume linea i y and symme ic adjus men owa ds equilib ium (Abdulai, 2002; Abunyuwah,
2020; Blake & Fomby, 1997; Ende s & Siklos, 2001). Following his no a ion, he h eshold au o eg essi e
model (TAR) and momen um au o eg essi e model (M-TAR) co-in eg a ion app oaches as p oposed by
Ende s and Siklos (2001) we e employed. The h eshold au o eg essi e model can be exp essed as:
Dl ¼I q1l þ1−I
ðÞ
q2l −1þXp
i¼1cDl −1þx (1)
Whe e I is he Hea iside indica o unc ion such ha
I ¼1i l s
0i l <s
(2)
whe e sis he alue o he h eshold and x is a sequence o ze o-mean, cons an a iance independen
iden ically dis ibu ed andom a iables, such ha x is is independen o l :Howe e , when he
Hea iside indica o depends on he change in l −1,
I ¼1i l −1s
0i l −1<s
(3)
whe e l se ies exhibi s ‘momen um’in one di ec ion. The s alue is usually se o ze o in mos eco-
nomic applica ions such ha he co-in eg a ing ec o coincides wi h he a ac o . Howe e , in an eco-
nomic sense, he e is no jus i iable eason o expec he h eshold o coincide wi h he a ac o ; hus, i
is necessa y o es ima e he h eshold alue ðsÞ:Thus, Chan’s(1993) me hodology which yield a supe -
consis en es ima e o he h eshold by minimizing he sum squa ed o e o s was adop ed.
COGENT ECONOMICS & FINANCE 3
2.2. T ansmission dynamics o p ice linkages
Asymme ic e ec s may appea in se ies ha a e economically in e connec ed. In o de o de e mine
whe he ma ke playe s eac di e en ly o posi i e and nega i e shocks owa ds long- un equilib ium,
he Hansen and Seo (2002) (HS) es was conduc ed o examine he p esence o a signi ican h eshold
co-in eg a ion e ec . Following he HS
1
es o he h eshold e ec , i he null hypo hesis o he symme -
ic e ec is ejec ed, he h eshold e o co ec ion model (TVECM) is adop ed. Thus, he h eshold ec o
e o co ec ion model can be exp essed as
DP ¼
q1c0P −1þh1þX
M
m¼1
~1䉭P −mþe ,c0P −1WRegime1
ðÞ
q2c0P −1þh2þX
M
m¼1
~2m䉭P −mþe ,W<c0P −1Regime2
ðÞ
8
>
>
>
>
<
>
>
>
>
:
(4)
The TVECM model explains p ice changes due o p ice shocks in bo h he sho and long e ms bu
depends on he magni ude o he de ia ion om he long- e m equilib ium. I he e is asymme ic pa h
o adjus men whe e c0P −1W<c0P −1 hen we inco po a e asymme ies by assuming ha (x) has a
di e en impac on (y) as
DPy ¼X
h
;hPy −hþX
s
i¼0
aþPþ
x −iþX
q
j¼0
a−P−
x −jþe (5)
whe e P
y
is he p ice le el o he e e ence ma ke and P
x
is he p ice le el o he o he ma ke s unde
s udy in ela ion o he e e ence ma ke . F om Equa ion (5), he es o he null hypo hesis aþ¼a−
p o ides in o ma ion abou he impac o Pxþand Px−on Py, which speci ies asymme ic o symme ic
pa hs owa ds long- un. The dis ibu ed lag e ec due o he impac o Pxþand Px−a any lag was
examined by es ing he null aþ
i¼a−
j,i¼1...s,j¼1...q, which, i ejec ed (no ejec ed), deno es an
asymme ic o symme ic dis ibu ed lag e ec . The cumula i e symme ic and asymme ic e ec s o
Pxþand Px−a lag −kwe e also examined by es ing o Ps
i¼kaþ
i¼Pq
j¼ka−
jwi h K 2½0, min s,q
ðÞ
(Kang e al., 2018)
In summa y, he analy ical amewo k adop ed in his s udy ollows he ollowing es ima ion p ocess:
he da a-gene a ing p ocess o he se ies was analyzed using uni oo es s and he Johansen co-
in eg a ion es o es ima e he co-in eg a ing eg ession. The lagged es ima ed esiduals om he
co-in eg a ing eg ession we e hen employed o speci y he e o -co ec ion e ms used in he speci ica-
ion o bo h he TAR and M-TAR models. Finally, he h eshold e o co ec ion models we e es ima ed,
and he co esponding hypo hesis es s we e conduc ed. The s udy adop ed he Box-Ljung es as indi-
ca ed as (LB) o es au oco ela ions o he esiduals and i ness o he ime se ies model.
3. Resul s and discussion
3.1. Desc ip i e analysis o p ice da a
P ice end analysis helps o p edic he esponds o ma ke in e media ies o u u e mo emen o a
p ice changes. Figu e 1 showed he isual plo o he mon hly wholesale p ices o onion om Janua y
2011–Decembe 2018 ac oss all egional ma ke s conside ed. The p ices we e cha ac e ized by luc ua-
ions wi h a ise in p ice o onion which begun a ound 2013 which was as a esul o onion supply c isis
due o la e monsoon ains accompanied by he poo pe o mance o he Indian upees leading o high
in la ion a e du ing he season.
The desc ip i e s a is ics o he seasonally unadjus ed nominal p ices o onions ac oss he majo ma ke s
unde conside a ion a e p esen ed in Table 1. The esul s indica ed ha , ac oss he spa ially sepa a ed ma -
ke , he highes nominal wholesale p ice was obse ed in he Kozhikode ma ke wi h a maximum alue o `
7200/100 kg whe eas he minimum p ice o `211 was eco ded in Lasalgaon ma ke .
F om he esul s, he highes a e age wholesale p ice o `1512.5 was obse ed in Lucknow ma ke
wi h he lowes a e age wholesale p ice o `1260 obse ed in Myso e ma ke . The minimum p ice in
Lasalgaon was expec ed as he ma ke ecei es he highes olume o onion a i al in he a ea as
4 J. K. BLAY ET AL.
li e a u e poin s ou ha Maha ash a is he leading p oduce o onions in India wi h Lasalgaon as he
majo p oducing ma ke unlike Mumbai, which is conside ed a consump ion cen e (Ujjwal e al., 2017).
Thus, u he analysis was conduc ed wi h Lasalgaon in Maha ash a as he e e ence ma ke .
3.2. Uni a ia e analysis: uni oo es
P ices o ag icul u al p oduc s luc ua e and ollow dis inc seasonal ends ha e lec he a ied ma ke ing
s a egies used by a me s and ma ke in e media ies as well as he p oduc ion’sinhe en biologicallag
p ocesses. The e o e, he p ice se ies was decomposed and seasonally adjus ed be o e u he analyses
we e conduc ed. Table 2 p esen s he esul s on he e alua ion o he uni a ia e da a gene a ing p ocess
(DGP) o he seasonally adjus ed p ices h ough he amewo k o he augmen ed Dickey- Fulle (ADF) es .
The esul s o he es s a is ic ailed o ejec he null hypo hesis o a uni oo a le el o all he
ma ke s unde s udy. Howe e , he null hypo hesis was ejec ed a 1pe cen signi icance le el a e he
i s di e en ial implying ha he ma ke s we e in eg a ed o he same o de and hus, sha e common
long- un dynamic s ochas ic dynamic p ocesses.
Figu e 1. Plo o mon hly p ices o majo onion ma ke s in India.
Table 1. Desc ip i e s a is ics o p ices o majo onion ma ke s in Rupees (`).
Lasalgaon (`) Kanpu (`) Kozhikode (`) Lucknow (`) Mumbai (`) Myso e (`) Hyde abad (`)
Minimum 211.0 500.0 900 600 480.0 400 400
1
s
Qua 637.5 900 1300 897.0 750 800 800
Median 1000.5 1150 2100 1300 1050 1000 1164
Mean 1399.5 1420 2535 1512.5 1441 1260 1410
3
d
Qua 2137.5 1562 3225 1650 1625 1540 1700
Maximum 4600.0 5200 7200 5200 5500 4750 5400
Table 2. Resul s uni oo es .
Ma ke s De e minis ic e m Lags
Tes alue C i ical alue
Le el Di e ence 1% 5%
Lasalgaon T end 2 −3.20 −7.00 −4.04 −3.45
Kanpu T end 3 −3.04 −6.32 −4.04 −3.45
Kozhikode T end 1 −3.73 −9.67 −4.04 −3.45
Lucknow T end 1 −3.89 −6.41 −4.04 −3.45
Mumbai T end 1 −3.72 −6.31 −4.04 −3.45
Myso e T end 2 −3.45 −7.86 −4.04 −3.45
Hyde abad T end 2 −3.52 −7.81 −4.04 −3.45
COGENT ECONOMICS & FINANCE 5
3.3. Co-in eg a ion analysis
The app oach o es ing he in eg a ion o spa ially sepa a ed ma ke s is based on he ac ha de ia-
ions om he equilib ium condi ions o he wo o mo e non-s a iona y a iables should be s a iona y.
This implies ha while p ice se ies may wande ex ensi ely, pai s should no di e ge om one ano he
in he long un (Abdulai, 2002). Thus, he mul i a ia e co-in eg a ion ank be ween he spa ial ma ke s
was es ima ed using Johansen’s me hodology. The esul o he Johansen co-in eg a ion es is p e-
sen ed in Table 3.
The esul s e ealed ha all he ma ke s unde s udy sha e a common long- un dynamic p ocess as
he ank o no co-in eg a ion ( ¼0) was ejec ed. This p o ides he exis ence and e idence o a com-
mon domes ic and e icien onion ma ke in India whe e in e -ma ke p ices adjus o achie e long- un
ma ke equilib ium. This esul con i ms a s udy conduc ed by Ahmed and Singla (2017) who epo ed
an in eg a ed o majo onion ma ke s in India. Howe e , Johansen’s adi ional co-in eg a ion app oach
implici ly assumes a symme ic adjus men mechanism, which may no be ealis ic owing o echno-
logical p og ess, changes in people’s p e e ences, economic c ises, policy o egime al e a ion, and ins i-
u ional de elopmen , and hus, has low powe in he p esence o asymme ic adjus men (A il e al.,
2014; Bo ens ein e al., 1997). Howe e , u he analysis ha inco po a es asymme ic and non-linea s o-
chas ic e ec s was s udied in he nex sec ion.
3.3.1. Th eshold and asymme ic co-in eg a ion modelling
In his sec ion, we es o possibili ies o asymme ic adjus men s and h eshold co-in eg a ion (non-
linea i y), o he han assuming symme ic and linea ela ions, as in he case o adi ional econome ic
app oach o ma ke in eg a ion and p ice dynamics. In his ega d, he h eshold au o eg essi e (TAR)
and momen um h eshold au o eg essi e (M-TAR) models and hei ex ensions wi h asymme ic adjus -
men , as p oposed by Ende s and Siklos (2001) as speci ied in Equa ions 1–3we e es ima ed o examine
whe he he p ices o he ma ke s unde s udy exhibi h eshold co-in eg a ion and asymme ic adjus -
men . The esul s o he TAR and M-TAR models and hei ex ended models a e p esen ed in Tables 4A
and 4B, espec i ely.
F om he esul s o M-TAR and i s ex ension consis en M-TAR, he null hypo hesis o no co-in eg a-
ion (q1¼q2¼0) was ejec ed a he 5 pe cen signi icance le el o all ma ke pai s, indica ing non-lin-
ea dynamic p ocess. A e con i ming he co-in eg a ion be ween he ma ke pai s unde conside a ion,
he null hypo hesis o no asymme y (q1¼q2) was also examined. Focusing on he Consis en M-TAR
(Tables 4A and 4B), all he ma ke pai s exhibi ed asymme ic adjus men in he long un as compa ed
o ea lie s udies on onion ma ke s in India (Ahmed & Singla, 2017; Gummagolma h & Rajalaxmi, 2019)
who epo ed co-in eg a ion bu could no accoun o whe he he adjus men s a e asymme ic by sim-
ply assuming symme y in he modelling app oach. Mo eo e , he poin es ima es o he Lasalgaon –
Kanpu ma ke ela ionship we e ound o be q1¼−0.072 and q2¼−0.368 sugges ing con e gence a
app oxima ely 7 pe cen o he posi i e de ia ion and 36.8 pe cen o he nega i e de ia ion om he
equilib ium we e elimina ed wi hin one mon h. Howe e , since jq1j<jq2j, implies ha he ma ke s
exhibi li le adjus men o a posi i e pe u ba ion as compa ed o subs an ial decay o a nega i e
shock signi ying highe speed o adjus men owa ds long- un equilib ium akes place when he p ice
sp ead di e ges below he equilib ium. This esul suppo s a s udy conduc ed by Ka hick e al. (2022)
Table 3. Johansen es o coin eg a ion.
Hypo heses Tes s a is ics ( ace s a is ics)
C i ical alues
1% 5%
<¼6 7.40 16.26 12.25
<¼5 16.85 30.54 25.32
<¼4 39.15 48.45 42.44
<¼3 69.20 70.05 62.99
<¼2 102.72 96.58 87.31
<¼1 154.51 124.75 114.90
¼0 226.46 158.49 146.76
,, indica e 10%, 5% and 1% le el o signi icance espec i ely.
6 J. K. BLAY ET AL.
ha epo ed long- un s ochas ic dynamic p ocess among majo onion ma ke s in India bu a a e y
slow pace o adjus men owa ds long un equilib ium le el. In o he wo ds, p ice inc eases a e pe sis -
en and end o e e back o he a ac o less apidly, bu dec eases end o e e quickly owa ds
he long- un equilib ium. This implies ha 93 pe cen and 63.2 pe cen o posi i e and nega i e de ia-
ions om he equilib ium would pe sis in he ma ke o he ollowing mon hs, espec i ely. This
adjus men p ocess signi ies ha wholesale s espond much mo e quickly o shocks ha squeeze p o i
ma gins han o hose ha s e ch hem. The asymme ic adjus men in he ma ke can be a ibu ed o
he ac ha he de e mina ion o p ice is hea ily in luenced by he ade ’s associa ions a he han he
ue auc ion o demand and supply e ec s no mally associa ed wi h ee ade as Lasalgaon se es as
he p oduce ma ke whe e majo i y o p oduc ion akes place. The wholesale s o m aci ca el unde
he in luence o associa ion leade s, which gi es hem much ma ke powe o egula e he p ice and ol-
ume o sales in a speci ic pe iod. This phenomenon in he ma ke sugges s ha inc ease in wholesale
p ices in he e e ence ma ke is ansmi ed mo e apidly o o he egional ma ke s han p ice educ-
ions. When a h eshold co-in eg a ion model is es ima ed, i is c ucial o examine whe he he nonlinea
model ( h eshold e ec ) is signi ican . In iew o his conside a ion, Hansen and Seo (2002) es was
employed o asce ain he p esence o signi ican h eshold dynamic adjus men s. The g id sea ch o
he h eshold alue (k) was conduc ed o e 60 g id poin s wi h he ixed eg esso boo s ap expe i-
men s used o calcula e he p- alues o he SupLM es . The esul s a e p esen ed in Table 5.
Table 4A. Th eshold and asymme ic co-in eg a ion in onion ma ke .
Lasalgaon –Kanpu Lasalgaon –Kozhikode Lasalgaon –Lucknow
Pa ame e s TAR MTAR CTAR CMTAR TAR MTAR CTAR CMTAR TAR MTAR CTAR CMTAR
s00−0.355 −0.130 0 0 0.715 −0.302 0 0 −0.216 0.074
q1 0.064
[0.464]
−0.063
[0.545]
−0.072
[0.371]
−0.038
[0.672]
−0.047
[0.490]
−0.066
[0.358]
−0.027
[0.711]
0.055
[0.328]
−0.040
[0.641]
0.002
[0.985]
−0.013
[0.874]
0.032
[0.772]
q2−0.363
[0.002]
−0.258
[0.008]
−0.460
[0.000]
−0.368
[0.001]
−0.186
[0.012]
−0.159
[0.028]
−0.180
[0.008]
−0.332
[0.002]
−0.352
[0.004]
−0.257
[0.008]
−0.454
[0.000]
−0.245
[0.008]
q1¼q2¼0 5.334
[0.006]
3.765
[0.027]
6.693
[0.002]
5.958
[0.004]
3.436
[0.037]
2.791
[0.067]
3.652
[0.030]
5.573
[0.005]
4.459
[0.014]
3.717
[0.028]
7.334
[0.001]
3.951
[0.028]
q1¼q2 5.195
[0.025]
2.225
[0.139]
7.760
[0.007]
6.371
[0.013]
2.154
[0.146]
0.928
[0.338]
2.566
[0.113]
6.218
[0.014]
5.400
[0.022]
3.968
[0.049]
10.942
[0.001]
4.421
[0.038]
LB(4) 0.443 0.428 0.464 0.480 0.753 0.772 0.870 0.644 0.612 0.595 0.793 0.623
LB(8) 0.399 0.275 0.407 0.423 0.824 0.795 0.906 0.792 0.577 0.539 0.699 0.477
, indica e 10% and 5% le el o signi icance. Values in b acke s a e he p obabili y le els o he es ima es.
Table 4B. Th eshold and asymme ic co-in eg a ion in onion ma ke .
Lasalgaon –Mumbai Lasalgaon –Myso e Lasalgaon –Hyde abad
Pa ame e s TAR MTAR CTAR CMTAR TAR MTAR CTAR CMTAR TAR MTAR CTAR CMTAR
s0 0 0.175 0.255 0 0 0.325 0.221 0 0 0.213 0.019
q1 0.003
[0.976]
−0.080
[0.415]
0.009
[0.916]
0.161
[0.309]
−0.098
[0.346]
−0.275
[0.035]
−0.099
[0.319]
−0.265
[0.056]
−0.051
[0.535]
−0.110
[0.239]
−0.033
[0.680]
−0.079
[0.348]
q2−0.349
[0.005]
−0.125
[0.239]
−0.36
[0.006]
−0.153
[0.058]
−0.291
[0.031]
−0.096
[0.371]
−0.340
[0.021]
−0.116
[0.265]
−0.225
[0.035]
−0.120
[0.199]
−0.282
[0.011]
−0.173
[0.100]
q1¼q2¼0 4.146
[0.019]
0.930
[0.398]
4.015
[0.021]
2.700
[0.073]
2.580
[0.081]
2.460
[0.091]
2.943
[0.058]
3.143
[0.048]
2.362
[0.100]
1.391
[0.254]
3.353
[0.039]
2.654
[0.076]
q1¼q2 6.416
[0.013]
0.108
[0.398]
6.159
[0.015]
3.581
[0.062]
1.560
[0.215]
1.329
[0.252]
2.258
[0.136]
0.882
[0.350]
1.891
[0.173]
0.008
[0.930]
3.814
[0.054]
0.609
[0.437]
LB(4) 0.780 0.744 0.760 0.829 0.938 0.569 0.950 0.884 0.988 0.975 0.983 0.879
LB(8) 0.644 0.543 0.638 0.544 0.175 0.258 0.209 0.101 0.863 0.785 0.881 0.732
,, indica e 10%, 5% and 1% le el o signi icance espec i ely. Values in b acke s a e he p obabili y le els o he es ima es.
Table 5. Hansen-Seo es o h eshold coin eg a ion.
Ma ke Pai s Sup-LM s a C i ical alues
Lasalgaon-Kanpu 38.7536.78
Lasalgaon-Kozhikodde 14.9813.90
Lasalgaon-Lucknow 23.5823.24
Lasagaon-Mumbai 22.8919.68
Lasalgaon-Myso e 21.0418.76
Lasalgaon-Hyde abad 14.98 12.41
, indica e 10% and 5% le el o signi icance.
COGENT ECONOMICS & FINANCE 7
