Renzhi, Nuobu; Bei ne, John
Wo king Pape
The nexus o pee - o-pee lending and mone a y policy
ansmission: E idence om he People's Republic o
China
ADB Economics Wo king Pape Se ies, No. 749
P o ided in Coope a ion wi h:
Asian De elopmen Bank (ADB), Manila
Sugges ed Ci a ion: Renzhi, Nuobu; Bei ne, John (2024) : The nexus o pee - o-pee lending and
mone a y policy ansmission: E idence om he People's Republic o China, ADB Economics
Wo king Pape Se ies, No. 749, Asian De elopmen Bank (ADB), Manila,
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WORKING PAPER SERIES
NO. 749
No embe 2024
The Nexus o Pee - o-Pee Lending and Mone a y Policy T ansmission
E idence om he People’s Republic o China
This pape examines how booms and bus s in pee - o-pee (P2P) lending in he People’s Republic o China
(PRC) a ec mone a y policy ansmission o in la ion and ou pu . Using s a e-dependen local p ojec ion
me hods, he esul s o he pape indica e a weake ansmission du ing boom phases. S ic e egula ion
on P2P lending since 2017 in he PRC and he subs an ial scaling back o P2P lending could posi i ely impac
he mone a y managemen o he economy.
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,
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loans, equi y in es men s, gua an ees, g an s, and echnical assis ance.
THE NEXUS OF PEER-TO-PEER
LENDING AND MONETARY
POLICY TRANSMISSION
EVIDENCE FROM THE PEOPLE’S REPUBLIC OF CHINA
Nuobu Renzhi and John Bei ne
ASIAN DEVELOPMENT BANK
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Nuobu Renzhi and John Bei ne
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The Nexus o Pee - o-Pee Lending and Mone a y Policy
T ansmission: E idence om he People’s Republic o China
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ABSTRACT
This pape empi ically in es iga es how he le el o pee - o-pee (P2P) lending a ec s
mone a y policy ansmission in he People’s Republic o China (PRC). Using s a e-
dependen local p ojec ion me hods, we ind ha he mac oeconomic e ec s o
unan icipa ed changes in mone a y policy a e dampened du ing he boom phase o he
P2P lending ma ke . The impulse esponses o indus ial p oduc ion and in la ion a e
signi ican ly nega i e in he non-boom s a e. In con as , he esponses o indus ial
p oduc ion and in la ion a e mu ed in he boom s a e. Se agains he con ex o s ic e
egula ion on P2P lending since 2017, ou esul s indica e ha he signi ican scaling back
o P2P lending ac i i y and i s g adual decline in he PRC could enhance he
e ec i eness o mone a y policy ansmission. Ou pape also sugges s ha u he wo k
is needed o s udy he in e ac ion be ween inancial inno a ion and mone a y policy.
Keywo ds: pee - o-pee lending, mone a y policy ansmission, in ech
JEL Codes: E44, E52, F33, F42
1. In oduc ion
The inancial sys em plays a cen al ole in ansmi ing mone a y policy o he eal
economy. In ecen yea s, he apid de elopmen in he inancial echnology (Fin ech)
indus y has g ea ly in luenced he inancial sys em. Taking ad an age o digi iza ion and
big da a echniques, Fin ech has played an impo an ole in making p og ess owa d
inancial inclusion and be e access o c edi o consume s, en ep eneu s, s a -ups,
and small and medium-sized en e p ises (SMEs) a a lowe cos (Philippon, 2016). On
he o he hand, he Fin ech indus y may ampli y he ecen end ha c edi in e media ion
is shi ing away om adi ional banks o nonbank inance, leading o a mo e di e se
inancial sys em (Be no h e al., 2017). In his sense, Fin ech may also b ing new isks o
he inancial sys em, which could pose challenges o cen al banks in achie ing hei
manda es.
Among Fin ech businesses, pee - o-pee (P2P) lending, allowing indi iduals and small
businesses o bo ow and lend on an online pla o m wi hou he p esence o adi ional
inancial ins i u ions, has been a leading al e na i e inance o ma . Bene i ing om being
a ma ke leade in digi al echnologies and a lax egula o y en i onmen , he P2P lending
indus y in he People’s Republic o China (PRC) expe ienced apid g ow h and se ed
as a dominan d i e o he global nonbank inance ma ke in ea lie yea s. The PRC’s
P2P lending indus y soa ed om a olume o CNY252 billion in 2014 o CNY2,804 billion
by 2017, peaking a a ound 30% as a sha e o o al new bank lending.
This boom in he P2P lending ma ke u ned in o a conside able dec ease a he end
o 2017, when egula o s imposed a se o policy measu es on he sec o . While he
egula ion was implemen ed g adually, his was aimed a d ama ically educing isk
ac oss he PRC’s inancial sys em (Hsu e al., 2021). As no ed by Huang e al. (2021), a
2
u he s ic egula o y policy o he P2P lending ma ke , join ly announced by he
People’s Bank o China (PBoC) and he China Banking and Insu ance Regula o y
Commission a he end o 2017, aimed o egula e cash loans, p ohibi illegal inancing,
and abolish he p ac ice o using unds o s uden loans, in es men specula ion, and
down paymen s on eal es a e. Such es ic ions ha e a ec ed he P2P lending ma ke
signi ican ly. As egula o s epea edly seek o emedy P2P pla o ms h ough pla o m exi
and ans o ma ion, he numbe o no mal ope a ing pla o ms con inues o decline and
soon disappea s (Hsu e al., 2021). In 2019, P2P pla o ms we e con e ed in o small
loan c edi o s o comple ely shu down, essen ially elimina ing he P2P lending ma ke as
i once exis ed (Figu e 1).
Figu e 1: T ends in P2P Lending Ma ke Sha e in he People’s Republic o China
P2P = pee - o-pee .
No es: The igu e shows he dynamics o he a io o new P2P lending o o al new bank lending a
mon hly equencies. The sample pe iod is om he i s mon h (M1) o 2014 o M12 2019.
Sou ces: WDZJ and CEIC.
3
Howe e , P2P lending emains an ac i e indus y in he Uni ed S a es (US) and o he
de eloped economies. P2P lending has also been g owing in many de eloping
economies, including in Asia, no ably India, Indonesia, Malaysia, he Republic o Ko ea,
he Philippines, and Vie Nam (see Appendix Figu e). The indings in his pape a e
he e o e also ele an o o he economies wi h ac i e P2P lending ma ke s. This is
pa icula ly he case o economies whe e P2P lending and in ech indus y is likely o
con inue o g ow in he u u e. Th ough a sys ema ic in es iga ion o he impac o P2P
lending on he ansmission o mone a y policy in he PRC, he pape p o ides insigh s
on he implica ions o cen al banks.
Speci ically, we employ s a e-dependen local p ojec ions as in Jo dà (2005) and
Ramey and Zubai y (2018) o es ima e impulse esponses o key mac oeconomic
a iables o an unan icipa ed con ac iona y mone a y policy change in he PRC,
condi ioning on he boom and non-boom s a es o he P2P lending ma ke .
A key issue is o es ima e he PRC’s mone a y policy change se ies. To e lec he
coexis ence o quan i y and p ice a ge ing in he PRC’s mone a y policy, his pape
ollows he concep o “shadow policy a e” (Wu and Xia, 2016), using he mone a y supply
and eal sho - e m a e o cons uc he shadow policy a e (Xu and Jia, 2019). To
o e come mone a y policy endogenei y, we de i e a se ies o iden i ied shadow policy
changes, ollowing he app oach o Rome and Rome (2004). Using his app oach, we
o hogonalize shadow policy a e changes agains he cen al bank’s esponses o cu en ,
lagged, and o ecas able mac oeconomic condi ions by assuming a Taylo - ype ule o
ex ac he exogenous componen . The es ima ed esiduals he e o e can be ega ded as
exogenous mone a y policy changes and he basis o he impulse esponse unc ion
4
analysis. We es ima e he esponses o key mac oeconomic a iables o he es ima ed
unan icipa ed mone a y policy changes and ind ha indus ial p oduc ion and in la ion
decline, and he exchange a e inc eases s eadily a e a mone a y policy igh ening.
These ex book esul s sugges he alidi y o ou iden i ica ion.
To in es iga e whe he he boom o P2P lending can ha e a mode a ing e ec on he
ansmission o mone a y policy, we use he a io o new P2P lending o o al new bank
lending as ou s a e a iable and es ima e impulse esponses o he boom and non-boom
s a es o he P2P lending ma ke . The es ima ion esul s indica e clea e idence o
he e ogeneous e ec s o unexpec ed con ac iona y changes in mone a y policy ac oss
he wo s a es. The impulse esponses o indus ial p oduc ion and in la ion a e
signi ican ly nega i e in he non-boom s a e. In con as , in he boom s a e o he P2P
lending ma ke , he esponses o indus ial p oduc ion and in la ion a e mu ed and no
signi ican ly di e en om ze o o mos ho izons. These esul s a e obus o a se o
sensi i i y checks ha include al e na i e mone a y policy measu es, al e na i e s a e
de ini ions, and conce ns abou addi ional ac o s ha may a ec esul s.
O e all, he es ima ed s a e-dependen e ec s o unan icipa ed con ac iona y
mone a y policy changes sugges ha he ongoing de elopmen o P2P inance is
nega i ely associa ed wi h he e ec i eness o mone a y policy ansmission. As P2P
lending unc ions as an al e na i e sou ce o ex e nal inancing, agen s a e less
cons ained by he ising cos o bank c edi s, dampening he o e all impac o
con ac iona y mone a y policy on he economy.
The pape con ibu es o a ious s ands o li e a u e. Fi s , ou pape complemen s he
ecen empi ical s udies ha examine he e ec i eness o mone a y policy ansmission
11
calcula e impulse esponses o exogenous mone a y policy changes. LPs ha e se e al
ad an ages o e he adi ional s uc u al ec o au o eg essi e (SVAR) app oach. Fi s ,
LPs a e easie o es ima e since hey simply equi e he es ima ion o a se ies o
eg essions o each ho izon and o each a iable o in e es . Second, LPs can easily
conduc he poin o join -wise in e ence. Thi d, using LPs o es ima e impulse esponses
is mo e obus when a VAR model is misspeci ied. Las , LPs can be easily ex ended o a
non-linea , s a e-dependen model by allowing he pa ame e s o change acco ding o he
s a e o he economy.5 Ou baseline linea model can be gi en as ollows:
𝑦𝑦 𝑡𝑡+ℎ =𝛼𝛼ℎ+ Φℎ(𝐿𝐿)𝑧𝑧𝑡𝑡−1 + 𝛽𝛽ℎ 𝑠𝑠ℎ𝑜𝑜𝑜𝑜𝑘𝑘𝑡𝑡+𝜀𝜀𝑡𝑡+ℎ ℎ= 0,1,2, ⋯,𝑛𝑛(3)
whe e 𝑦𝑦 is he a iable o in e es , Φℎ(𝐿𝐿) is a polynomial in he lag ope a o , 𝑠𝑠ℎ𝑜𝑜𝑜𝑜𝑘𝑘𝑡𝑡 is
he se ies o iden i ied unan icipa ed mone a y policy changes, and 𝑧𝑧 is a ec o o
con ol a iables including con empo aneous and lagged alues o 𝑦𝑦 and 𝑠𝑠ℎ𝑜𝑜𝑜𝑜𝑘𝑘𝑡𝑡 .
Speci ically, we le 𝑦𝑦 e e o each o ou selec ed P2P lending ma ke a iables (i.e., he
log o P2P lending olume, he P2P lending a e, he densi y o P2P bo owe s, and he
densi y o P2P lende s) and he indica o s o eal sec o including he log o indus ial
p oduc ion and in la ion. Ou speci ica ion includes 3 mon hs o lagged alues o he
mone a y policy change. The coe icien 𝛽𝛽ℎ gi es he esponse o 𝑦𝑦 a ime 𝑡𝑡+ℎ o he
change a ime 𝑡𝑡. Thus, one cons uc s he impulse esponses as a sequence o he 𝛽𝛽ℎ
es ima ed in a se ies o sepa a e eg essions o each ho izon ℎ.
5 Unlike egime-swi ching VARs, s a e-dependen LPs do no equi e one o ake a s and on he du a ion
o a gi en s a e o on he mechanism igge ing he ansi ion be ween egimes.
12
We can u he adap he LP amewo k o es ima e a s a e-dependen model gi en as
ollows:
𝑦𝑦 𝑡𝑡+ℎ =𝐼𝐼𝑡𝑡−1�𝛼𝛼𝐴𝐴,ℎ+ Φ𝐴𝐴,ℎ(𝐿𝐿)𝑧𝑧𝑡𝑡−1 + 𝛽𝛽𝐴𝐴,ℎ 𝑠𝑠ℎ𝑜𝑜𝑜𝑜𝑘𝑘𝑡𝑡�
+(1 − 𝐼𝐼𝑡𝑡−1)�𝛼𝛼𝐵𝐵,ℎ+ Φ𝐵𝐵,ℎ(𝐿𝐿)𝑧𝑧𝑡𝑡−1 + 𝛽𝛽𝐵𝐵,ℎ 𝑠𝑠ℎ𝑜𝑜𝑜𝑜𝑘𝑘𝑡𝑡�+𝜀𝜀𝑡𝑡+ℎ
(4)
whe e 𝐼𝐼𝑡𝑡−1 ∈{0,1} is a dummy a iable ha indica es he s a e o he economy in e ms
o be o e he unan icipa ed change in mone a y policy hi s. In pa icula , 𝐼𝐼𝑡𝑡−1 akes a
alue o 1 in he boom s a e o he P2P lending ma ke and 0 o he wise. We discuss he
cons uc ion o his dummy a iable in mo e de ail in he nex subsec ion. We allow all o
he coe icien s o he model o a y acco ding o he s a e o he economy. One pa icula
complica ion associa ed wi h he LP me hod is he se ial co ela ion in he e o e ms
induced by he successi e leading o he dependen a iable. Thus, we use he Newey-
Wes co ec ion o ou s anda d e o s (Newey and Wes , 1987).
2.4 De ini ion o he P2P lending ma ke s a es
In o de o es whe he he ansmission o mone a y policy is a ec ed by he amoun o
P2P inance ac i i ies, we i s need o de ine which pe iods cons i u e he boom s a e o
he P2P lending ma ke . We use he a io o new P2P lending o o al new bank lending
as ou s a e a iable, since his no only e lec s he le el o P2P lending bu also accoun s
o he ela i e impo ance o P2P inance in he c edi ma ke . In o de o de ine he boom
and non-boom s a es o he P2P lending ma ke , ollowing Ramey and Zubai y (2018)
and Alpanda and Zubai y (2019), we build a gap measu e by aking he de ia ion o he
a io o new P2P lending o o al new bank lending om a smoo h end. We cons uc his
end by unning a Hod ick and P esco (HP) il e wi h a smoo hing pa ame e , 𝜆𝜆 =
13
14,400. We de ine boom s a es as pe iods in which he a io o new P2P lending o o al
new bank lending is abo e he ime- a ying end.6
3. Empi ical esul s
3.1 Mac oeconomic e ec s o unan icipa ed changes in mone a y policy
To eassu e he alidi y o ou iden i ica ion s a egy, we p esen he esponses o key
mac oeconomic a iables o he es ima ed exogenous mone a y policy changes. Figu e
3 shows he es ima ed impulse esponses based on he linea model o Eq. (3). The solid
line in each g aph ep esen s he es ima ed impulse esponses in pe cen age o e he
ollowing 10 mon hs o an unexpec ed con ac iona y mone a y policy change. We
no malized he scale o he mone a y policy change such ha i inc eases he shadow
policy a e by 100 basis poin s (bps). The do ed lines ep esen 90% con idence bands
based on obus s anda d e o s by Newey and Wes (1987).
Figu e 3: Impulse Responses o Mac oeconomic Va iables o an Unexpec ed
Con ac iona y Mone a y Policy Change
6 Fo ou sample pe iod, he boom phase co esponds o wo dis inc in e als: Sep embe 2015 o
Decembe 2015, and Feb ua y 2016 o June 2018. The non-boom phase spans he pe iods om Janua y
2014 o Augus 2015, Janua y 2016, and om July 2018 o Decembe 2019.
Con inued on he nex page
14
No es: The igu e plo s he impulse esponses o indus ial p oduc ion, in la ion, and eal e ec i e
exchange a e o a 100-bps unexpec ed con ac iona y mone a y policy change. 90% con idence bands in
dashed lines a e epo ed. The inc ease in he exchange a e e e s o an app ecia ion o CNY. The
ho izon al axis ep esen s mon hs.
Sou ce: Au ho s’ calcula ions.
The impulse esponses o mac oeconomic a iables a e consis en wi h he p edic ion
o s anda d mac oeconomic heo y, indica ing he soundness o ou mone a y policy
se ies. Following an unexpec ed con ac iona y mone a y policy change, indus ial
p oduc ion dec eases pe sis en ly wi h a maximum impac o a ound 1.8 bps. The in la ion
a e also shows a dampening and s a is ically signi ican e ec a e he unan icipa ed
igh ening. A 100-bps hike is associa ed wi h a 0.56% decline in in la ion a e 10 mon hs.
The eal e ec i e exchange a e yields simila esponses: a mone a y policy igh ening
leads o a pe sis en inc ease in he exchange a e (i.e. an app ecia ion o CNY). Ou
esul s a e consis en wi h he indings o o he empi ical s udies dealing speci ically wi h
mone a y policy ansmission in he PRC (Chen e al., 2017; Kambe and Mohan y, 2018).
3.2 Responses o P2P lending ma ke s o unan icipa ed mone a y policy changes
Tu ning o P2P lending ma ke a iables, he impulse esponses shown in Figu e 4 a e
s ongly in line wi h he ela ed li e a u e, pa icula ly, he heo e ical amewo k o Wong
and Eng (2020). Wi h an unexpec ed mone a y policy igh ening ha empo a ily
inc eases he policy a e by 100 bps, agen s’ access o adi ional bank inance is
cons ained, incen i izing agen s o seek inancing owa d P2P lending ma ke s (Hsu e
al., 2021). As mo e agen s low in o P2P lending ma ke s, he bo owe s’ densi y
inc eases pe sis en ly, wi h a maximum o a ound 0.2%. Mo eo e , wi h a dense pool o
bo owe s in he P2P lending ma ke , implying he e a e mo e in es men op ions, he
densi y o P2P lende s inc eases s eadily wi h a peak e ec o 0.17%. Gi en he
15
p ocessing ee (Hsu e al., 2021), P2P lende s a e willing o accep a lowe lending a e
as long as he pool o bo owe s is dense . We can obse e ha he e is a sho - e m d op
in he P2P lending a e igh a e he unan icipa ed igh ening in mone a y policy, peaking
a –0.3%. In addi ion, he P2P lending olume ises s eadily and signi ican ly wi h a peak
e ec o a ound 0.15%.
While i may be expec ed ha P2P lending a es should ise ollowing a igh ening in
mone a y policy, gi en he ise in demand o P2P lending, a lowe ing in P2P a es can
also occu o se e al easons. Fo example, sea ching o yield by in es o s in a highe
in e es a e en i onmen could lead o po olio ealloca ion owa ds ixed income
in es men , he eby lowe ing he supply o unds a ailable o P2P lending and po en ially
leading o lowe P2P lending a es. In addi ion, in a highe in e es a e en i onmen whe e
he isk o de aul is highe , P2P lende s may lowe a es o a ac high-quali y bo owe s.
This can also help o lowe he isk exposu e o he P2P lende s’ po olio. I can also be
he case ha a igh ening in mone a y policy igge s a con ac ion in economic ac i i y
and o e all lending, such ha P2P lende s may o e lowe a es o incen i ize bo owing
(e.g. Wong and Eng, 2020).
16
Figu e 4: Impulse Responses o P2P Lending Ma ke Va iables o an Unexpec ed
Con ac iona y Mone a y Policy Change
P2P = pee - o-pee .
No es: The igu e plo s he impulse esponses o P2P lending ma ke a iables o a 100-bps unexpec ed
con ac iona y mone a y policy change. 90% con idence bands in dashed lines a e epo ed. The
ho izon al axis ep esen s mon hs.
Sou ce: Au ho s’ calcula ions.
Hence, we ind ha con ac iona y exogenous mone a y policy changes may igge an
inc ease in P2P inance ac i i ies, which could po en ially become a sou ce o inancial
dis ess and ha e implica ions o mone a y policy ansmission.
17
3.3 S a e-dependen e ec s o unan icipa ed mone a y policy changes
In his pa o he analysis, we allow he esponses o indus ial p oduc ion and in la ion
o unan icipa ed mone a y policy changes o a y ac oss s a es o he P2P lending ma ke .
Figu e 5 shows he impulse esponses o a con ac iona y mone a y policy change o
he wo s a es o he P2P lending ma ke , namely he non-boom (le panel) and he boom
( igh panel). A compa ison o hese wo panels e eals he impac o P2P inance on
mone a y policy ansmission. No e ha he esponses o indus ial p oduc ion and
in la ion a e signi ican ly nega i e in he non-boom s a e. They a e also shaped simila ly
o he baseline linea case and a e ypically o a la ge magni ude ela i e o he baseline
linea model. In pa icula , he in la ion a e esponse peaks a 0.75% in esponse o an
unan icipa ed 100 bps mone a y policy igh ening in he non-boom s a e, ela i e o 0.56%
in he baseline model. Indus ial p oduc ion also signi ican ly declines in he non-boom
s a e ela i e o he baseline case, especially o he ini ial pe iods. In con as , in he
boom o he P2P lending ma ke , we ind ha he nega i e esponse o in la ion becomes
s a is ically signi ican only a e 10 mon hs, while he esponses o indus ial p oduc ion
a e also mu ed and a e no signi ican ly di e en om ze o o mos ho izons.
18
Figu e 5: S a e-Dependen Impulse Responses o an Unexpec ed Con ac iona y
Mone a y Policy Change
(a) Indus ial P oduc ion
(b) In la ion Ra e
No es: The igu e plo s he impulse esponses o indus ial p oduc ion and in la ion o an unexpec ed 100-
bps con ac iona y mone a y policy change o he boom and non-boom s a es o he P2P lending ma ke .
We de ine boom s a es as pe iods in which he a io o new P2P lending o o al new bank lending is abo e
he ime- a ying end cons uc ed by unning a HP il e wi h a smoo hing pa ame e , λ= 14,400. 90%
con idence bands in dashed lines a e epo ed. The ho izon al axis ep esen s mon hs.
Sou ce: Au ho s’ calcula ions.
The es ima ed s a e-dependen e ec s o exogenous mone a y policy igh ening
sugges ha he ongoing de elopmen o P2P inance is nega i ely associa ed wi h he
e ec i eness o mone a y policy ansmission. As P2P lending unc ions as an al e na i e
19
sou ce o ex e nal inancing, agen s a e less cons ained by he ising cos o bank c edi s,
dampening he o e all impac o con ac iona y mone a y policy on he economy.
3.4 Robus ness
3.4.1 Al e na i e measu e o unan icipa ed mone a y policy changes
Thus a , we ha e ollowed he s anda d app oach by assuming a Taylo - ype ule o
ex ac he exogenous componen s o policy a e a ia ions as a measu e o unexpec ed
mone a y policy changes. Nex , we conduc he same analysis as in he p e ious
subsec ion bu use a na a i e se ies as an al e na i e measu e o cap u e he PBoC’s
policy s ance. In his pape , we ely on he app oach by Sun (2018), using a na a i e
mone a y policy s ance index o measu e he PBoC’s policy s ance based on he
in o ma ion om he PBoC’s policy announcemen s.7 We con e he se ies o mone a y
policy s ance om a mee ing equency in o a mon hly ime se ies by assigning indexes
o he mon h in which i occu ed. I he e a e mul iple mee ings wi hin a pe iod, hen we
agg ega e he associa ed index by summing up indexes wi hin ha ime pe iod. I he e
a e no policy mee ings, he co esponding index is se o ze o.
Figu e 6 epo s s a e-dependen impulse esponses based on he mone a y policy
s ance index. We also no malized he scale o he mone a y policy s ance unan icipa ed
change such ha i inc eases he shadow policy a e by 100 bps. The esul s a e e y
simila when using al e na i e measu emen s o unexpec ed changes in mone a y policy.
7 Howe e , using policy announcemen s as he policy ins umen may also call in o ques ion. When he
cen al bank makes announcemen s, i does no only p esen pu e mone a y policy news, bu also p i a e
in o ma ion on he economy, causing he p i a e sec o o swi ch i s ou look on mac oeconomic
de elopmen s (Bu e al., 2021). Thus, mone a y policy news may s ill e lec changes in economic
undamen als no ela ed o mone a y policy. Fo hese conce ns, we only use na a i e mone a y policy
index as a obus ness check.
20
Ou key indings emain obus as esponses o bo h indus ial p oduc ion and in la ion in
he non-boom s a e o he P2P lending ma ke end o be s onge han he esponses in
he boom s a e.
Figu e 6: S a e-Dependen Impulse Responses o an Unexpec ed Con ac iona y
Mone a y Policy Change: Na a i e-Based Mone a y Policy Indexes
(a) Indus ial P oduc ion
(b) In la ion Ra e
No es: The igu e plo s he impulse esponses o indus ial p oduc ion and in la ion o an unexpec ed 100-
bps con ac iona y mone a y policy change o he boom and non-boom s a es o he P2P lending ma ke ,
using he mone a y policy s ance index. 90% con idence bands in dashed lines a e epo ed. The ho izon al
axis ep esen s mon hs.
Sou ce: Au ho s’ calcula ions.
27
APPENDIX
A.1 Da a de ini ions and sou ces
Indus ial P oduc ion: Mon hly indus ial p oduc ion index wi h seasonally-adjus ed, IMF
S a is ics. Va ia ion om he in la ion changes is adjus ed.
In la ion Ra e: Mon hly consume p ice index in he o m o yea -on-yea change,
Na ional Bu eau o S a is ics o he People’s Republic o China.
P2P Lending Volume: Mon hly P2P lending ansac ion olume, Wang Dai Zhi Jia.
P2P Lending Ra e: Mon hly in eg a ed a e o P2P lending, Wang Dai Zhi Jia.
Densi y o P2P Bo owe s: Sha e o he numbe o bo owe s o he numbe o pla o ms
in a mon hly equency, Wang Dai Zhi Jia.
Densi y o P2P Lende s: Sha e o he numbe o lende s o he numbe o pla o ms in
a mon hly equency, Wang Dai Zhi Jia.
Shadow policy a e: Mon hly shadow sho a e se ies cons uc ed by using mone a y
supply and eal sho - e m in e es a e, Xu and Jia (2019).
Economic policy unce ain y: Mon hly PRC economic policy unce ain y index se ies
cons uc ed by Huang and Luk (2020).
28
A.2 P2P lending in selec ed Asian economies
Appendix Figu e: De elopmen o P2P Lending Ma ke in Eme ging Asia, 2013-2020
IND = India, INO = Indonesia, KOR = Republic o Ko ea, MAL = Malaysia, P2P = pee - o-pee ,
PAK = Pakis an, PHI = Philippines, SIN = Singapo e, VIE = Vie Nam.
No es: The igu e shows he dynamics o P2P lending olumes (in loga i hm) in eme ging Asian economies.
The sample pe iod is om 2013 o 2020. The da a come om he Camb idge Cen e o Al e na i e Finance.
Sou ce: Au ho s’ calcula ions.
29
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The Nexus o Pee - o-Pee Lending and Mone a y Policy T ansmission
E idence om he People’s Republic o China
This pape examines how booms and bus s in pee - o-pee (P2P) lending in he People’s Republic o China
(PRC) a ec mone a y policy ansmission o in la ion and ou pu . Using s a e-dependen local p ojec ion
me hods, he esul s o he pape indica e a weake ansmission du ing boom phases. S ic e egula ion
on P2P lending since 2017 in he PRC and he subs an ial scaling back o P2P lending could posi i ely impac
he mone a y managemen o he economy.
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,
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loans, equi y in es men s, gua an ees, g an s, and echnical assis ance.
THE NEXUS OF PEER-TO-PEER
LENDING AND MONETARY
POLICY TRANSMISSION
EVIDENCE FROM THE PEOPLE’S REPUBLIC OF CHINA
Nuobu Renzhi and John Bei ne
