紐約聯(lián)儲-貿(mào)易不確定性與美國銀行貸款（英）

Trade

Uncertainty

andU.S.

Bank

LendingNO.

1076NOVEMBER

2023Ricardo

Correa

|

Julian

di

Giovanni|

Linda

S.

Goldberg

|Camelia

MinoiuTradeUncertaintyandU.S.BankLendingRicardoCorrea,JuliandiGiovanni,LindaS.

Goldberg,andCameliaMinoiuFederalReserveBankofNewYorkStaffReports,no.

1076November2023/10.59576/sr.1076AbstractThispaperusesU.S.loan-levelcreditregisterdataand

the2018–2019TradeWar

totestfortheeffectsofinternationaltradeuncertaintyon

domesticcreditsupply.We

exploitcross-sectionalheterogeneityinbanks’ex-anteexposureto

tradeuncertaintyand

findthatan

increasein

tradeuncertaintyisassociatedwithacontraction

inbanklending

to

allfirmsirrespectiveof

theuncertaintythatthefirmsface.Thisbaselineresultholdsforlendingatthe

intensiveandextensivemargins.

Wedocumenttwochannelsunderlyingtheestimatedcreditsupplyeffect:await-and-seechannelbywhichexposedbanksassesstheirborrowersas

riskierandreducethematurity

oftheirloans,and

afinancialfrictionschannelbywhichexposedbanksfacingrelativelyhigherbalancesheetconstraintscontractlending

more.Thedeclineincreditsupplyhasrealeffects:firmsthatborrowfrommoreexposedbanksexperiencelowerdebtgrowthandinvestmentrates.Theseeffectsarestrongerforfirmsthataremorerelianton

bankfinance.JELclassification:F34,F42,G21Keywords:tradeuncertainty,bank

loans,tradefinance,globalvaluechains,tradewar_________________Giovanni,Goldberg:FederalReserveBankof

NewYork(emails:julian.digiovanni@,linda.goldberg@).Correa:BoardofGovernorsof

theFederalReserveSystem(email:ricardo.correa@).

Minoiu:FederalReserveBankofAtlanta

(email:camelia.minoiu@).TheauthorsthankMichelleAlexopoulos,ChrisBoehm,NickBloom,ValentinaBruno,StevenDavis,LorenzoGarlappi,KristineHankins,TarekHassan,DalidaKadyrzhanova,

MatteoIacovellio,AbelIglesias,SeungLee,RalfMeisenzahl(discussant),LubosPastor,

DianePierret(discussant),AndreaPolo(discussant),AndreaPresbitero,VeronicaRappoport(discussant),BradSetser(discussant),BoSun,EugeneTan,LenaTonzer(discussant),LilianaVarela(discussant),FrankWarnock,andparticipantsatIBRNworkshopsandmeetings,theGlobalRisk,Uncertainty,andVolatility(GRUV)workshopattheFederalReserveBoard,29thCEPREuropeanSummerSymposiuminInternationalMacroeconomics(ESSIM),IFABSannualconference,EuropeanFinanceAssociation(EFA)Annual

Meeting,FRBDallasConferenceonSupplyChainsin

aChangingGlobalLandscape,FRBNewYorkGlobalResearchForumonInternationalMacroeconomicsandFinance,5thEBRD-CEPRResearchSymposium,IMFConferenceonGeoeconomicFragmentation,Spring2023NBER

Conferenceon“InternationalFragmentation,SupplyChains,and

FinancialFrictions,”SwedishHouseofFinanceConferenceon

“TheEffectsofNewGeopoliticalRiskson

FinancialMarketsandFirms,”2023EuropeanEconomicAssociationAnnualMeeting,StanfordUniversity2023

SITEConference“TheMacroeconomicsofUncertaintyandVolatility,”andseminarsattheNorgesBank,BankofCanada,BankofEngland,

andBankof

Italyforusefulsuggestions.TheyalsothankStephanieSezen,DiegoSilva,andKelseyShipmanforresearchassistance.Thispaperpresentspreliminaryfindingsand

is

beingdistributedto

economistsand

otherinterestedreaders

solely

to

stimulatediscussionandelicitcomments.The

viewsexpressedinthispaperare

thoseoftheauthor(s)anddo

notnecessarilyreflectthe

positionoftheFederalReserveBankofNewYork,theFederalReserveBankofAtlanta,theBoardof

Governorsof

theFederalReserve,

ortheFederalReserveSystem.Anyerrorsoromissionsaretheresponsibilityoftheauthor(s).Toview

the

authors’disclosurestatements,

visit/research/staff_reports/sr1076.html.1

IntroductionThe

recent

era

of

trade

globalization

witnessed

?rms’

foreign

activities

proliferate

as

they

enterednew

markets

and

sourced

more

intermediate

inputs

from

abroad.

This

exponential

expansion

ofinternational

trade

ended

after

the

Global

Financial

Crisis

(GFC),

with

events

such

as

Brexit,trade

wars,

and

the

COVID-19

pandemic

being

major

sources

of

increased

trade

uncertainty.

Thisuncertainty

may

also

impact

?nancial

intermediaries’

given

their

important

role

in

?nancing

globaltransactions.

In

particular,

an

increase

in

trade

uncertainty

can

a?ect

?rms’

creditworthiness

andbank

balance

sheets,

which

in

turn

can

induce

changes

in

banks’

lending

behavior

and

their

supplyof

credit.

Indeed,

according

to

a

Federal

Reserve

survey,

U.S.

banks

expected

to

take

a

range

ofactions

in

2019

to

mitigate

the

impact

of

international

trade

developments

on

their

balance

sheets,1including

tightening

lending

standards

and

hedging

credit

risks

through

derivatives.

Against

thisbackdrop,

we

ask

how

the

e?ects

of

international

trade

uncertainty

on

the

domestic

economy

maybe

propagated

and

ampli?ed

by

banks.This

paper

assesses

the

e?ects

of

trade

uncertainty

on

U.S.

banks’

credit

supply

by

exploitingthe

spike

in

trade

uncertainty

that

occurred

during

the

2018–2019

Trade

War.

A

priori,

it

istheoretically

ambiguous

how

uncertainty

associated

with

international

trade

developments

willa?ect

banks.

On

the

one

hand,

banks

could

serve

as

shock

dampeners

if

they

internalize

thedisruptions

in

their

borrowers’

activities

caused

by

trade

uncertainty.

On

the

other

hand,

banksmay

contract

lending

if

they

are

worried

about

the

prospect

of

balance

sheet

losses.

We

investigatethese

issues,

starting

with

the

construction

of

a

novel

measure

of

bank

exposure

to

trade

uncertaintyby

combining

?rm-level

information

on

trade

uncertainty

with

detailed

data

on

U.S.

banks’

loanexposures

to

domestic

borrowers.

We

exploit

the

cross-sectional

bank

heterogeneity

in

this

exposureto

test

for

the

credit

supply

e?ect

of

the

increase

in

uncertainty,

while

controlling

for

?rm-levelcredit

demand.

We

next

investigate

the

key

mechanisms

through

which

banks’

exposure

to

tradeuncertainty

a?ects

their

credit

supply.

Banks’

behavior

might

be

driven

by

a

wait-and-see

strategy,whereby

the

exposed

banks

are

more

prone

to

pull

back

from

risk-taking

and

to

shorten

loanmaturities.

Responses

might

also

be

driven

by

a

?nancial

frictions

channel

by

which

banks’

credit1Details

on

the

April

2019

Senior

Loan

O?cer

Opinion

Survey

conducted

by

the

Federal

Reserve

are

availablehere,

including

references

to

the

special

questions

investigating

C&I

lending

to

?rms

that

are

exposed

to

developmentsin

Asia

or

Europe.1supply

depends

on

balance

sheet

constraints.

Finally,

we

ask

whether

the

estimated

changes

incredit

supply

have

real

e?ects

on

?rms.Our

?rst

novel

?nding

is

that

an

increase

in

trade

uncertainty

is

associated

with

a

larger

creditcontraction

at

the

bank-?rm

level

for

more

exposed

banks,

that

is,

those

banks

with

a

larger

ex-anteshare

of

loans

to

?rms

in

sectors

facing

a

greater

increase

in

ex-post

trade

uncertainty.

This

resultholds

even

when

we

restrict

the

set

of

borrowers

to

?rms

that

are

relatively

less

exposed

to

anincrease

in

trade

uncertainty.

Second,

the

contraction

in

credit

supply

is

stronger

for

banks

thatface

larger

?nancial

frictions

and

is

also

consistent

with

exposed

banks

adopting

a

wait-and-seeattitude

on

lending

by

evaluating

all

borrowers—even

those

in

low-uncertainty

sectors—as

beingriskier.

Third,

?rm

characteristics

a?ect

how

banks

adjust

lending

in

the

face

of

changes

in

tradeuncertainty.

Notably,

banks

exposed

to

trade

uncertainty

contract

lending

more

to

?rms

that

areless

protected

by

trade

policy.

The

real

outcomes

for

?rms

are

worse

when

they

borrow

from

themore

exposed

banks,

with

this

result

stronger

for

those

?rms

that

are

more

reliant

on

bank

credit.Our

analysis

uses

a

comprehensive

loan-level

data

set

collected

through

the

Federal

Reserve(FR)

Y-14Q

form

(known

as

the

“U.S.

credit

register”).

The

data

are

comprised

of

quarterly

bank-?rm

loan

commitments

of

minimum

size

$1

million

extended

to

domestic

(public

and

private)

?rmsby

the

U.S.

banks

that

are

subject

to

annual

stress

tests

(those

banks

with

assets

above

$50

billion).We

use

this

data

set

to

examine

a

wide

range

of

outcomes

associated

with

the

intensive

and

extensivemargins

of

lending,

including

lending

volumes

and

spreads,

maturities,

and

the

probability

of

newloan

originations.

We

also

analyze

the

probabilities

of

default

assigned

by

banks

to

individualborrowers.

Furthermore,

we

use

these

data

to

construct

our

key

measure

of

bank

exposure

to

tradeuncertainty

by

combining

loan

exposures

with

?rm-level

measures

of

trade

uncertainty.

Firm-leveltrade

uncertainty

measures

are

sourced

from

Hassan

et

al.

(2019),

Hassan

et

al.

(2020a),

and

Hassanet

al.

(2020b)

and

are

based

on

textual

analysis

of

the

transcripts

of

listed

?rms’

quarterly

earningscalls.

Given

that

the

?rms

in

the

credit

register

and

the

uncertainty

data

do

not

overlap

perfectly,we

take

a

three-step

approach

in

constructing

the

bank

exposure

to

trade

uncertainty

variable.First,

we

aggregate

the

?rm-level

uncertainty

measures

to

the

sector-level.

Second,

we

assignthese

sector-level

uncertainty

measures

to

borrowers

in

the

credit

register

based

on

their

sectoralclassi?cation.

Finally,

we

aggregate

this

information

at

the

bank

level

by

taking

the

average

changein

uncertainty

between

2016–2017

and

2018–2019

across

sectors,

weighted

by

initial

loan

shares

in2a

given

sector.

The

loan

shares

are

taken

to

be

averages

over

2014–2015

so

they

are

lagged

relativeto

the

start

of

the

sample

and

hence

unlikely

a?ected

by

the

2018–2019

Trade

War.

This

approachmakes

the

bank

exposure

measure

more

likely

predetermined

with

respect

to

economic

conditionsduring

the

sample

period.We

use

a

di?erence-in-di?erences

estimation

framework.

Our

baseline

speci?cation

regresses

thegrowth

rate

in

outstanding

loans

at

the

bank-?rm

loan

level

on

the

measure

of

bank

exposure

totrade

uncertainty

interacted

with

a

P

ost

dummy

taking

the

value

of

one

for

the

years

of

heightenedtrade

uncertainty

in

2018

and

2019,

and

zero

for

the

years

2016

and

2017.

To

corroborate

that

theshifts

in

loan

quantities

are

consistent

with

a

shift

in

the

supply

of

credit,

we

estimate

complemen-tary

speci?cations

using

loan

spreads

as

the

dependent

variable.

We

make

sure

that

our

results

arenot

confounded

by

standard

determinants

of

banks’

lending

decisions

by

controlling

for

bank

size,capital,

core

deposits,

and

sectoral

specialization

(de?ned

as

in

Paravisini

et

al.,

2023)

in

levels

andinteracted

with

the

P

ost

dummy.

We

further

show

that

the

bank

exposure

measure

is

unrelated

tothese

control

variables

in

each

yearly

cross-section

of

banks

over

the

sample

period,

which

providesadditional

support

to

the

validity

of

the

assumption

that

the

bank

exposure

measure

is

unrelatedto

bank

attributes

that

might

also

a?ect

lending.A

key

empirical

challenge

in

isolating

the

e?ects

of

trade

uncertainty

on

credit

supply

is

the

factthat

credit

supply

by

banks

and

credit

demand

by

?rms

may

change

simultaneously

in

response

tochanges

in

the

trade

environment.

International

trade

is

important

for

the

banking

sector

as

changesin

?rms’

foreign

activities

often

shift

their

credit

demand

(Amiti

and

Weinstein,

2011).

To

addressthis

issue,

we

exploit

the

granular

nature

of

our

data,

at

the

bank-?rm

loan-level,

with

controls

for?rm×quarter

?xed

e?ects

to

absorb

time-varying

credit

demand

shifts

for

a

given

?rm

(Khwaja

andMian,

2008;

Jim′enez

et

al.,

2020).

We

also

control

for

?rm×bank

?xed

e?ects

to

account

for

time-invariant

bank-speci?c

loan

demand

for

individual

?rms

and

for

potential

endogenous

matchingbetween

banks

and

?rms

(Chodorow-Reich,

2014;

Farinha

et

al.,

2022;

Paravisini

et

al.,

2023).Placebo

tests

indicate

that

banks

with

di?erent

levels

of

exposure

to

trade

uncertainty

have

similarlending

patterns

before

the

sample

period,

suggesting

that

unobservable

bank

characteristics

donot

explain

our

results.

Throughout

the

analyses,

we

reinforce

the

importance

of

controlling

forcredit

demand

by

presenting

results

on

bank

lending

for

two

borrower

samples:

(i)

all

?rms,

and(ii)

?rms

that

are

in

low-uncertainty

sectors

and

less

likely

to

have

strong

endogenous

shifts

in3credit

demand.2We

have

three

sets

of

main

results.

Our

?rst

result

is

that

an

increase

in

trade

uncertainty

isassociated

with

a

larger

credit

contraction

for

more

exposed

banks

vis-a`-vis

all

borrowers,

includingthose

that

are

less

exposed

to

an

increase

in

trade

uncertainty.

This

spillover

e?ect

through

banksis

evident

on

both

the

intensive

and

extensive

margins

of

lending:

more

exposed

banks

reduceloan

growth,

charge

higher

spreads,

and

are

less

likely

to

grant

new

loans

than

other

banks.

Thecredit

supply

contraction

is

economically

meaningful.

The

point

estimates

from

regressions

for

thefull

sample

imply

that

a

one

standard

deviation

increase

in

bank

exposure

to

trade

uncertainty

isassociated

with

a

2.6

percentage

point

(ppt)

decline

in

loan

growth

(compared

to

0%

median

loangrowth

for

the

sample)

and

an

increase

in

loan

spreads

by

6.5

basis

points

(bps)

(compared

to

185bps

median

loan

spread

for

the

sample).

Numbers

are

similar

when

restricting

the

regression

sampleto

low-uncertainty

?rms:

a

2.8

ppt

contraction

in

loan

growth

and

a

7.1

bps

rise

in

loan

spreads.

Aone

standard

deviation

increase

in

bank

exposure

to

trade

uncertainty

cuts

the

probability

of

newloan

origination

by

0.5%.The

second

set

of

results

addresses

the

mechanisms

through

which

trade

uncertainty

can

a?ectbanks’

credit

supply.

Consistent

with

real-options

theory

and

adopting

a

wait-and-see

attitude(Dixit

and

Pindyck,

1994),

more

exposed

banks

reduce

the

maturity

of

loans

and

shift

toward

typesof

loans

that

can

be

called

in

early

by

banks

(so-called

demandable

loans).

Moreover,

given

thatexposed

banks

anticipate

a

wider

dispersion

in

loan

returns

and

may

have

di?culties

forecastingrevenues

and

capital

needs,

they

downgrade

the

perceived

creditworthiness

of

?rms,

as

re?ected

in3higher

assessed

probabilities

of

default.

Exposed

banks

also

contract

their

lending

more

stronglyto

?rms

that

are

perceived

as

likely

to

be

adversely

a?ected

by

the

Trade

War

and

hence

riskier

exante,

which

we

measure

in

two

ways:

those

?rms

in

manufacturing

sectors

that

receive

low

importprotection

and

those

?rms

in

sectors

with

high

import

dependence.

The

?nancial

constraintschannel

is

supported

as

well,

as

exposed

banks

with

lower

levels

of

current

and

stressed

capitallevels

contract

their

lending

by

more

than

other

banks.

Consistent

with

both

mechanisms,

we?nd

that

exposed

banks

rotate

their

balance

sheets

away

from

loans

and

into

safer

assets,

notably2In

addition,

we

show

that

credit

demand,

as

re?ected

in

credit

line

utilization

rates,

actually

goes

up

during

theTrade

War

for

?rms

in

high-uncertainty

sectors.3In

fact,

a

Federal

Reserve

survey

revealed

in

April

2019

that

U.S.

banks

with

sizable

loan

commitments

to

?rmsexposed

to

international

trade

developments

expected

the

outlook

for

loan

losses

to

deteriorate

over

the

course

of

theyear

(as

discussed

further

in

Section

4.3).4securities.The

third

set

of

results

focuses

on

the

consequences

of

exposed

banks’

credit

contraction

forthe

real

sector.

Our

analysis

of

real

e?ects

uses

a

loan-weighted

average

of

each

?rm’s

exposure

totheir

banks’

exposure

to

trade

uncertainty.

We

test

whether

?rms

that

are

more

exposed

to

tradeuncertainty

through

their

banks

are

a?ected

in

terms

of

their

investment

and

total

debt

growth.We

?nd

that

the

more

exposed

?rms

are

unable

to

substitute

for

reduced

bank

lending

throughalternative

sources

of

?nance

and

these

?rms

exhibit

lower

total

debt

growth

and

investment

rates.A

one

standard

deviation

increase

in

?rms’

exposure

to

trade

uncertainty

via

their

relationshipwith

exposed

banks

is

associated

with

an

economically

meaningful

decrease

of

the

growth

rate

ofthe

?rms’

total

debt

and

of

their

investment

ratio

in

2018–2019

by

2.4

and

2.7

ppts,

respectively.These

results

are

consistent

with

a

credit

supply

contraction

having

a

material

adverse

e?ect

onexposed

?rms’

real

outcomes.

We

also

?nd

that

private

?rms—more

likely

to

depend

on

bank?nancing—

and

?rms

with

a

higher

share

of

bank

debt

experience

relatively

worse

real

outcomes,which

con?rms

banks

as

a

conduit

for

amplifying

the

e?ects

of

trade

uncertainty.We

conduct

additional

tests

to

increase

con?dence

in

the

interpretation

of

our

results.

First,we

present

evidence

to

allay

the

potential

concern

that

our

results

are

driven

by

the

e?ects

ofthe

Trade

War

on

realized

and

expected

returns

on

loans

(a

?rst-moment

e?ect)

instead

of

theuncertainty

regarding

loan

returns

(a

second-moment

e?ect).

Speci?cally,

we

show

that

the

resultsare

invariant

to

controlling

for

two

measures

of

returns

on

loans—bank

exposure

to

changes

inactual

trade

policy

(that

is,

the

loan

share

to

tari?s-hit

sectors)

and

bank

exposure

to

changes

inoverall

sentiment

(constructed

in

the

same

way

as

the

baseline

exposure

measure).

Results

do

notchange

when

we

additionally

control

for

bank

exposure

to

changes

in

non-trade

uncertainty

(thatis,

political

uncertainty

in

sectors

other

than

trade).

Second,

we

show

that

our

results

are

robustto

other

potential

explanations

for

our

baseline

?ndings,

including

the

possibility

that

changes

inmacroeconomic

conditions—such

as

?uctuations

in

the

value

of

the

U.S.

dollar

and

in

commodityprices—may

correlate

with

the

trade

environment

and

a?ect

banks’

lending

decisions

during

thesample

period.

Our

main

results

hold

up

when

controlling

for

bank

cyclicality,

for

bank

exposuresto

tradable-goods

producing

sectors

and

to

?rms

integrated

in

global

value

chains

(arguably

moreexposed

to

exchange

rate

?uctuations),

or

when

dropping

oil

companies

from

the

sample

(as

theoil

sector

experienced

a

protracted

credit

contraction

starting

in

2015).5Additional

results

and

alternative

methodological

choices

further

support

our

baseline

?ndings.We

show

our

results

are

not

limited

to

the

standard

terms

of

loan

contracts—volumes,

spreads,and

maturities—but

also

extend

to

other

margins,

with

more

exposed

banks

consistently

tighteningcollateral

requirements

on

loans

to

all

borrowers

compared

to

other

banks.

Finally,

the

baseline?ndings

are

invariant

to

speci?cation

changes

such

as

(a)

including

no

?xed

e?ects;

(b)

includ-ing

loan-type×quarter

and

?rm×loan-type×quarter

?xed

e?ects

for

trade

?nance

and

other

loans;(c)

using

a

weighted-least-squares

estimation

that

accounts

for

variations

in

the

precision

of

sec-toral

estimates

of

trade

uncertainty;

and

(d)

varying

the

period

of

analysis

to

allow

for

potentialanticipation

e?ects

of

the

Trade

War.Related

literature

Our

paper

contributes

to

several

strands

of

literature.

Prior

studies

provideevidence

that

banks

facilitating

international

trade

amplify

the

e?ects

of

trade

shocks

on

?rms

andhouseholds

(Amiti

and

Weinstein,

2011;

Niepmann

and

Schmidt-Eisenlohr,

2017a,b;

Niepmann,2015;

Michalski

and

Ors,

2012;

Paravisini

et

al.,

2023).

Our

focus

is

instead

on

the

direction

oflinkage

from

trade

to

banks,

which

has

received

little

attention.

Federico

et

al.

(2020)

documentthat

policy

actions

associated

with

China’s

accession

to

the

World

Trade

Organization

in

2001

hadsizeable

e?ects

on

bank

loan

supply

to

Italian

?rms.

The

authors

?nd

that

endogenous

?nancialfrictions

arise

as

a

result

of

the

trade

shock’s

negative

e?ects

on

bank

loan

portfolios.

Hankins

etal.

(2022)

examine

the

e?ects

of

metal

and

steel

tari?s

enacted

in

2018

on

the

supply

of

auto

loansby

U.S.

?nance

companies

and

document

negative

spillover

e?ects

of

these

policies

on

consumercredit.

Our

contribution

emphasizes

the

e?ects

of

trade

uncertainty

on

bank

commercial

lending,and

establishes

a

rich

set

of

mechanisms

underlying

the

real

consequences

of

the

credit

supplyresponse.Our

work

also

relates

to

the

literature

on

the

real

and

?nancial

e?ects

of

uncertainty

(Kaviani

etal.,

2020;

Berger

et

al.,

2020;

Husted

et

al.,

2020;

Baker

et

al.,

2016;

Bloom,

2014;

Buch

et

al.,

2015).Global

banks

play

an

important

role

in

the

international

transmission

of

?nancial

stresses

throughlending

and

liquidity

?ows

(Amiti

and

Weinstein,

2018;

De

Haas

and

Van

Horen,

2013;

Cetorelli

andGoldberg,

2012;

Schnabl,

2012;

Peek

and

Rosengren,

2000).

Some

papers

document

consequencesof

uncertainty

for

bank

lending

(Crozet

et

al.,

2022;

Jasova

et

al.,

2021;

Wu

and

Suardi,

2021;Soto,

2021;

Alessandri

and

Bottero,

2020;

Bordo

et

al.,

2016;

Valencia,

2017),

while

others

relate6¨uncertainty

to

global

liquidity

or

capital

?ows

(Rey,

2015;

Avdjiev

et

al.,

2020;

Kalemli-Ozcan

andKwak,

2020).

The

latter

literature

emphasizes

di?erent

reasons

why

aggregate

risk

conditions

maya?ect

bank

credit,

including

through

banks’

value-at-risk

constraints

and

leverage

(Bruno

and

Shin,2015).

Relative

to

this

strand

of

literature,

we

focus

on

a

speci?c

type

of

uncertainty—around

thetrade

environment—with

potentially

crucial

implications

for

the

global

activities

of

banks

and

theintegration

of

trade

and

?nance.

Trade

uncertainty

di?ers

from

aggregate

uncertainty

because

ofits

sectoral

and

geographic

speci?city,

which

allows

us

to

delve

deeper

into

the

mechanisms

at

work.Beyond

international

trade

and

uncertainty,

our

paper

also

speaks

to

the

literature

on

bank-intermediated

spillovers

of

sectoral

shocks

to

broader

groups

of

borrowers

(see

Gilje

et

al.,

2016;Cort′es

and

Strahan,

2017;

Huber,

2018;

Dell’Ariccia

et

al.,

2021;

Mayordomo

an