International Banking and Cross-Border Effects of …International Banking and Cross-Border Effects...
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International Banking and Cross-Border Effectsof Regulation: Lessons from the United States∗
Jose M. Berrospide,a Ricardo Correa,a Linda S. Goldberg,b
and Friederike Niepmanna
aFederal Reserve BoardbFederal Reserve Bank of New York
Domestic prudential regulation can have unintended effectsacross borders and may be less effective in an environmentwhere banks operate globally. Using U.S. micro-banking datafor the first quarter of 2000 through the third quarter of 2013,this study shows that some regulatory changes indeed spillover. First, a foreign country’s tightening of limits on loan-to-value ratios and local-currency reserve requirements increaseslending growth in the United States through the U.S. branchesand subsidiaries of foreign banks. Second, a foreign tighten-ing of capital requirements shifts lending by U.S. global banksaway from the country where the tightening occurs to theUnited States and to other countries. Third, tighter U.S. cap-ital regulation reduces lending by large U.S. global banks toforeign residents.
JEL Codes: F42, F44, G15, G21.
1. Introduction
In the period since the global financial crisis, policy discussionshave highlighted the potential need for the active use of macropru-dential instruments to support financial stability goals. But some
∗The authors thank Jacob Conway and Eric Parolin for excellent researchassistance. We also thank anonymous referees, Sirio Aramonte, Stijn Claessens,Valeriya Dinger, Kebin Ma, Marcus Pramor, Jana Ohls, Tim Schmidt-Eisenlohr,Judith Temesvary, and participants at the 2016 IBEFA summer meeting and theNorges Bank’s Financial Stability and Macroprudential Policy workshop for veryuseful feedback. The views expressed in this paper are solely those of the authorsand should not be interpreted as reflecting the view of the Board of Governors,the Federal Reserve Bank of New York, or the staff of the Federal Reserve System.
435
436 International Journal of Central Banking March 2017
macroprudential instruments might not work as intended and haveeffects that propagate across borders through the global linkages ofinternational financial institutions. In the presence of cross-borderbanking, domestic policies might not be effective, as they do notapply to the same degree to banks headquartered in foreign coun-tries. Changes in domestic prudential instruments might also spillover into foreign markets, because domestic banks affected by thepolicies adjust their operations globally.1
This paper analyzes these issues focusing on the United Statesand attempts to answer three questions. First, do changes in foreignprudential instruments affect lending growth in the United States?Second, do U.S. global banks adjust their foreign operations whenforeign prudential instruments change? Third, do U.S. regulatorychanges spill over into foreign countries via U.S. global banks? Wefind evidence of both spillovers of foreign regulatory changes into theUnited States and cross-border effects of U.S. prudential instrumentchanges.
The United States is an interesting case, as its banking sec-tor is markedly interconnected with the rest of the world. Foreignglobal banks expanded their operations in the United States inthe 2000s through local branches and through separately charteredbanks (Tarullo 2012). U.S. global banks have substantial exposuresto advanced economies and to emerging market countries throughcross-border lending, funding, and affiliates located abroad (Cetorelliand Goldberg 2006).
Our analysis uses regulatory reports filed by U.S. global banksand by the U.S. subsidiaries and branches of foreign banks. Thesebank-level data for 2000:Q1 through 2013:Q3 are combined with adatabase of prudential instruments newly constructed by the Inter-national Banking Research Network (IBRN) (see Cerutti et al. 2017for a description of the IBRN Prudential Instruments Database).The database has information on the use of seven different pruden-tial instruments by sixty-four countries. Our methodology largely
1Lim et al. (2011), Akinci and Olmstead-Rumsey (2015), Cerutti, Claessens,and Laeven (2015), and Vandenbussche, Vogel, and Detragiache (2015) analyzethe effectiveness of macroprudential policies in curtailing credit growth and houseprice inflation using cross-country data. Cross-border spillovers of prudential poli-cies are explored in Aiyar, Calomiris, and Wieladek (2014), Aiyar et al. (2014),and Danisewicz, Reinhardt, and Sowerbutts (2015).
Vol. 13 No. S1 Lessons from the United States 437
follows that described in Buch and Goldberg (2017) and is partof the joint research effort of the IBRN on cross-border prudentialpolicy spillovers.2
Our first specifications test whether U.S. global banks andU.S. branches and subsidiaries of foreign banks adjust their lend-ing in response to foreign prudential instrument changes. Wefind statistically significant effects for three instruments: capitalrequirements, local-currency reserve requirements, and limits onloan-to-value (LTV) ratios. The tightening of prudential instru-ments abroad increases loan growth in the United States. Higherforeign-country capital requirements abroad mainly affect U.S. loangrowth through U.S. global banks, while higher local-currencyreserve requirements and limits on LTV ratios mainly transmitthrough the lending of the U.S. branches and subsidiaries of foreignbanks.
Our second set of tests investigates whether U.S. global banks’exposures in foreign countries react to prudential instrument changesthere. The evidence is weaker in this case. Foreign changes in pru-dential instruments have a weak and mostly insignificant effect onU.S. banks’ claims on residents in the country where the changeoccurs.
Lastly, we explore whether changes in U.S. prudential instru-ments have effects across borders. While foreign economies haveused a combination of both cyclical and structural instruments, U.S.policymakers have favored structural regulations that are less corre-lated with the financial cycle and are not changed frequently (Elliott,Feldberg, and Lehnert 2013). As a result, the only U.S. instrumentchange recorded in the IBRN Prudential Instruments Database isrelated to the introduction of the Basel II.5 capital regulations in2013:Q1. Our results indicate that after this change the largest U.S.banks, those that are required to participate on annual stress tests
2The following studies are part of the IBRN study on the impact of prudentialinstrument changes on the activities of global banks: Auer, Ganarin, and Towbin(2017); Avdjiev et al. (2017); Baskaya et al. (2017); Bonfim and Costa (2017);Bussiere, Schmidt, and Vinas (2017); Caccavaio, Carpinelli, and Marinelli (2017);Damar and Mordel (2017); Frost, de Haan, and van Horen (2017); Gajewski andKrzesicki (2017); Hills et al. (2017); Ho and Wong (2017); Jara and Cabeza(2017); Levin-Konigsberg et al. (2017); Nocciola, Zochowski, and Franch (2016);Ohls, Pramor, and Tonzer (2017); Park and Lee (2017).
438 International Journal of Central Banking March 2017
or follow the Advanced Approaches capital framework, reduced theirforeign lending growth relative to the smaller banks.3
Taken together, and focusing on the response of U.S. globalbanks, our results indicate that U.S. prudential regulation reducesforeign lending, whereas tighter foreign prudential regulationincreases total lending and shifts this lending away from the hostcountries undertaking regulatory changes. In general, the magni-tudes of the identified spillovers across all the exercises appear tobe small. Changes in foreign capital requirements probably had themost significant economic effect: we calculate that stricter capitalrequirements abroad added a total of $249 billion in lending of U.S.global banks over the period from 2000:Q1 to 2013:Q3.
While our results are broadly consistent with the existing evi-dence on cross-border spillovers, there are some important differ-ences that we have identified. The effect of higher U.S. capitalrequirements are consistent with Aiyar et al. (2014), who documentthat tighter capital requirements for U.K. banks decreased thesebanks’ cross-border lending. In the U.S. data, cross-border spilloversof higher capital requirements work in both directions. Tighter capi-tal standards abroad increased lending growth in the United States,mainly through U.S. global banks. While banks may cut lendingat home and abroad to comply with higher capital standards, thechange of capital requirements in one country affects the relativeprofitability of lending in different parts of the global banking organi-zation. When capital requirements are higher abroad, domestic lend-ing might become relatively more profitable compared with foreignlending through foreign subsidiaries subject to the higher capitalrequirements. The fact that higher local-currency reserve require-ments and limits on LTV ratios abroad have positive effects on U.S.lending growth follows a similar logic.
The weak response of U.S. global banks’ lending to foreign pol-icy changes in the countries where the policy changes occur issomewhat consistent with the evidence on leakages presented by
3More information about the Advanced Approaches capital framework can befound at this link: https://www.federalreserve.gov/bankinforeg/basel/advanced-approaches-capital-framework-implementation.htm. Information about the U.S.stress tests conducted by U.S. bank supervisors can be found at this location:https://www.federalreserve.gov/bankinforeg/stress-tests-capital-planning.htm.
Vol. 13 No. S1 Lessons from the United States 439
Aiyar, Calomiris, and Wieladek (2014) and Reinhardt and Sower-butts (2015), who show that foreign bank lending expands when theregulation of domestic banks tightens. While we do not find thatU.S. banks expand their lending growth, we do not find them con-tracting their lending growth either, suggesting that foreign policychanges might not be able to impact these banks’ local operations.This result contrasts with those in Temesvary (2015), who finds sig-nificant responses of U.S. banks’ foreign activities to stricter bankregulation in host countries. Part of the divergence in these resultsmay be explained by the use of different cross-country regulatorydata and different methodologies for measuring the effect of changesin prudential instruments.
A related literature with contributions by Houston, Lin, andMa (2012) and Bremus and Fratzscher (2014) exploits a databasedeveloped by Barth, Caprio, and Levine (2013), which capturesdifferences in bank regulation and supervision across countries, toanalyze changes in global banking activities. Using information oncross-border bank flows, they find evidence for regulatory arbi-trage through cross-border lending. As opposed to our paper, theirtests rely on aggregate bank flows instead of bank-specific claims.In another cross-country study, Ongena, Popov, and Udell (2013)find effects of tighter home-country regulation on banks’ risk takingabroad.
The next section describes the data used in the various exer-cises testing the transmission of prudential policies through foreignbanks operating in the United States, and through U.S. global banks.Section 3 presents the empirical methodology and key empiricalresults. Section 4 concludes, emphasizing that despite limited realconsequences for the U.S. economy over the past decade, prudentialinstruments applied abroad have the potential to more significantlyinfluence U.S. loan growth in the future.
2. Data and Stylized Facts for the United States
Our analysis examines prudential policy spillovers internation-ally using four distinct bank panels. The first panel coversU.S.-headquartered global banks’ total lending and varies by bankand quarter. The second data set adds a country dimension to thebank and time dimension, capturing U.S. global banks’ claims in
440 International Journal of Central Banking March 2017
different locations through cross-border flows or through branchesor subsidiaries established in foreign markets. The two other micro-banking data sets cover foreign bank lending in the United States.One contains data on foreign-owned bank subsidiaries operating inthe United States, while the other consists of data on U.S. branchesof foreign banks. The data for U.S. global banks and for subsidiariesof foreign banks within the United States span the first quarter of2000 through the third quarter of 2013, while the U.S. branches offoreign banks data set spans the fourth quarter of 2002 through thethird quarter of 2013.4
2.1 Bank-Level Data
2.1.1 Data Sources
U.S. commercial bank data cover both U.S. global banks and theU.S. subsidiaries of foreign banks. Balance sheet, income statement,and select off-balance-sheet data for them are drawn from the Fed-eral Financial Institutions Examinations Council (FFIEC) 031 form,better known as the Call Report. Income statement, balance sheet,and selected off-balance-sheet data on U.S. bank holding compa-nies are drawn from the FR Y-9C form. The FFIEC 009 form onthe international exposures of U.S. reporting banks is the sourceof detailed information on the geographic distribution of U.S. bankclaims on foreign residents. A bank is defined as a U.S. global bankif it reports the FFIEC 009 and is headquartered in the UnitedStates. Capital and asset data for foreign bank holding companiesin our aggregated branch data set are drawn from the FR Y-7Qform. Balance sheet and off-balance-sheet data pertaining to U.S.branches and agencies of foreign banking organizations are drawnfrom FFIEC 002 filings, aggregated across U.S. branches to thelevel of the “top bank” within the global banking organization.5
National Information Center (NIC) data are used to connect com-mercial banks to their high holders. All of these data filings are
4We end the analysis in 2013:Q3 since the FFIEC 009 reporting form changedthe next quarter. The FR Y-7Q form used in branch regressions was not intro-duced until 2002:Q4.
5“Bank” in this context includes bank holding companies and commercialbanks.
Vol. 13 No. S1 Lessons from the United States 441
quarterly, with the exception of the FR Y-7Q.6 Although much ofthe bank-level data are publicly available, bank-level data from theFFIEC 009 report are confidential.7 Further details on data sourcesand variable construction are in table 7 in the appendix.8
2.1.2 Definition of Dependent Variables
Most of the dependent variables have bank and time dimensions,with ΔYb,t defined as the change in log loans by bank b at timet. For some specifications, these loans are divided by their location(U.S. versus foreign addressees).
For a more detailed analysis of the response of U.S. global banks’foreign lending to policy changes (outward analysis), a country jdimension is added, with ΔYb,j,t defined as the change in log claimsextended by bank b to counterparties in country j at time t.9 Theseclaims can be cross-border, in which case they are extended froma particular location to a counterparty external to that location, orlocal, in which case the global bank affiliate in a location extendsclaims to borrowers in that location.
2.1.3 Bank-Level Variables
As the composition of bank balance sheets may influence the effectsof prudential instruments, the data set also includes bank size as
6The FR Y7-Q is filed quarterly by foreign banking organizations (FBOs)whose activities are deemed to be effectively that of a financial holding company,and is filed annually by all other FBOs. Data from the FR Y-7Q are then lin-early interpolated in order to construct quarterly data for foreign bank holdingcompanies (BHCs).
7Most of the data collected on the FR Y-9C, FFIEC 031, FFIEC 002, and FRY-7Q are available to the public, but there are a small number of series that areconfidential.
8The data are trimmed to exclude or correct for potential reporting errors andnoise. First, we identify outliers and exclude these observations from all descrip-tive tables and analysis. Observations are identified as outliers if they satisfy atleast one of the following four criteria where applicable: (i) a change in log claimsor loans > 1 or < −1 (precluding most major mergers and acquisitions), (ii) atier 1, illiquid assets, core deposits, or international ratio which is > 100 percentor < 0 percent, (iii) not part of a consecutive string of bank-time observationsat least eight quarters in length, or (iv) their home country changes between ourcontemporaneous and lagged periods.
9The term “claims” includes loans and securities holdings of banks.
442 International Journal of Central Banking March 2017
captured by log of total real assets (LogTotalAssetsb,t−1), percent-age of a bank’s portfolio of assets that is illiquid (IlliquidAsset-Ratiob,t−1), percentage of the banking organization’s balance sheetfinanced with core deposits (CoreDepositsb,t−1), percentage of thebanking organization’s regulatory tier 1 risk-based capital-to-assetratio (Tier1Ratiob,t−1), percentage of the banking organization’s netdue to minus net due from head office relative to total assets (Net-DueTF b,t−1), and percentage of international activity as proxiedby the ratio of the banking organization’s foreign deposits plus totalclaims relative to total assets (InternationalRatiob,t−1).10 The analy-sis also utilizes information on the nationality of the foreign parentof branches and subsidiaries hosted in the United States.
2.1.4 Summary Statistics and Features of theU.S. Banking System
The sample of reporting banks and characteristics of balance sheetdata are summarized in table 1. The number of distinct reportingentities for each data set is provided in the first data row. The sec-ond row reports the number of observations used in the empiricalanalysis, combining information on the number of entities and thenumber of quarters for each entity. For the outward transmissionthrough global banks, the number of observations reflects a combi-nation of the number of global banks active throughout our sampleperiod and the number of countries in which each of these banksreports claims or local funding activity at each quarter.
These summary statistics provide a broad overview of the creditactivities of the financial institutions captured in our empiricalanalysis. In general, the United States is a financial center, both host-ing the offices of several foreign financial institutions and serving asthe headquarters location for a group of large global banks. The U.S.offices of foreign banks, branches, and subsidiaries account for 18 to23 percent of U.S. bank assets in our sample period, with their loansrepresenting between 12 and 17 percent of total loans in the UnitedStates. The largest foreign participants in the U.S. banking sectorare headquartered in advanced economies, particularly in Europe.
10Total assets are converted to 2012:Q1 dollars using GDP deflator data fromthe U.S. Bureau of Economic Analysis.
Vol. 13 No. S1 Lessons from the United States 443Tab
le1.
Sum
mar
ySta
tist
ics
onB
ank
Len
din
gan
dC
har
acte
rist
ics
Inw
ard
—U
.S.
Outw
ard
—U
.S.
Inw
ard
—U
.S.
Subsi
dia
ries
Inw
ard
—U
.S.B
ranch
esG
lobalB
anks
Glo
balB
anks
ofFore
ign
Banks
ofFore
ign
Banks
Enti
tyC
ount
59
59
102
137
Obse
rvati
on
Count
35,4
83
1,8
73
2,8
01
4,2
62
Vari
able
Mea
nM
edia
nSD
Mea
nM
edia
nSD
Mea
nM
edia
nSD
Mea
nM
edia
nSD
Bal
ance
She
etD
ata
(for
Eac
hBan
kb
and
Quar
ter
t[a
nd
Des
tinat
ion
Cou
ntr
yjfo
rO
utw
ard
Cla
ims]
)
Dep
enden
tVar
iable
s:Δ
Log
Loa
ns
(Cla
ims)
a0.
010
00.
311
0.00
80.
008
0.09
50.
023
0.01
60.
098
0.01
90.
005
0.20
8Δ
Log
Cro
ss-B
order
Cla
ims
0.00
70
0.33
5Δ
Log
Loc
alC
laim
s0.
011
00.
411
Bal
ance
Shee
tC
ompos
itio
n:
Tot
alA
sset
s(B
illion
s)63
3.2
197.
876
3.3
269.
866
.151
9.8
14.5
1.3
30.9
15.8
3.6
26.4
Tie
r1
Rat
io(%
)11
.210
.53.
411
.810
.94.
116
.812
.612
.510
.49.
54.
8Illiqu
idA
sset
sR
atio
(%)
57.3
60.7
21.9
64.0
72.9
21.9
70.3
74.9
17.7
34.6
36.2
28.1
Inte
rnat
ional
Act
ivity
11.5
5.0
13.8
18.6
8.6
21.5
Net
Due
To
(Hea
d0.
10.
00.
7−
0.5
0.0
6.4
2.8
0.0
8.2
8.0
11.0
46.8
Offi
ce)
(%)/
Ass
ets
Cor
eD
epos
its
Rat
io(%
)39
.740
.023
.050
.555
.421
.26.
0866
.124
.66.
00.
912
.2C
ycle
Var
iable
s:B
ISFin
anci
alC
ycle
3.0
3.0
16.0
1.8
0.9
5.4
1.4
0.6
15.2
3.6
3.5
15.3
BIS
Busi
nes
sC
ycle
−0.
1−
0.1
2.1
−0.
10.
01.
30.
0−
0.1
1.5
0.0
0.0
1.8
Note
s:T
his
table
pro
vid
essu
mm
ary
stati
stic
sfo
rbank
bala
nce
shee
tand
lendin
gdata
,su
mm
ari
zing
those
obse
rvati
ons
incl
uded
inour
base
line
regre
s-si
ons.
Data
are
obse
rved
quart
erly
from
2000:Q
1–2013:Q
3fo
rU
.S.glo
balbanks
and
U.S
.su
bsi
dia
ries
offo
reig
nbanks,
and
from
2002:Q
4to
2013:Q
3fo
rU
.S.bra
nch
esof
fore
ign
banks.
Bankin
gdata
sourc
esby
subse
tca
nbe
found
inta
ble
7and
are
report
edat
the
level
of
the
top
bank
wit
hin
the
glo
bal
bankin
gorg
aniz
ati
on
for
U.S
.glo
balbanks
and
for
the
U.S
.bra
nch
esoffo
reig
nbanks
(aggre
gate
dacr
oss
U.S
.bra
nch
esin
this
case
),and
at
the
subsi
dia
ryle
vel
for
the
U.S
.su
bsi
dia
ries
offo
reig
nbanks.
The
tier
1ass
etra
tio
report
edfo
rbra
nch
esis
that
ofth
isass
oci
ate
dpare
nt.
The
Net
Due
To
(or
Due
Fro
m)
vari
able
mea
sure
sfr
om
the
per
spec
tive
ofa
bank’s
hea
doffi
ceto
talnet
inte
rnalle
ndin
g(o
rborr
owin
g)
vis
-a-v
isall
its
rela
ted
dom
esti
cand
inte
rnati
onal
offi
ces.
Cycl
eva
riable
sin
the
“In
ward
U.S
.G
lobalB
ank”
sam
ple
are
const
ruct
edas
exposu
re-w
eighte
dav
erages
.aD
ue
todata
availability,
loans
are
use
din
all
inw
ard
regre
ssio
ns,
while
claim
sare
uti
lize
din
all
outw
ard
regre
ssio
ns.
Cla
ims,
cross
-bord
ercl
aim
s,and
loca
lcl
aim
shav
ea
countr
ydim
ensi
on
inth
eoutw
ard
regre
ssio
nsa
mple
.
444 International Journal of Central Banking March 2017
Similarly, U.S. global banks have a notable presence in foreignmarkets. Foreign claims, which are composed of cross-border claimsand claims originated at foreign offices, for the U.S. global banksin our sample average about 9 percent of total assets. Total claimsincreased from 8 to 10 percent of total assets, on average, between2002 and 2012. Most of this increase is accounted for by growthin affiliate local claims, which rose from 2 to 5 percent of totalassets during that period (cross-border claims dropped slightly from6 to 5 percent). By country of destination, between 2002 and 2012total claims to advanced foreign economies went up from 4 to 7percent and those to emerging market economies decreased from 4to 3 percent. The U.S. branches and subsidiaries of foreign bankshave higher U.S. lending growth rates, on average, compared withU.S. global banks. Variability in lending is highest for the U.S.branches of foreign banks. For U.S. global banks, the growth in for-eign claims by bank and by location is more volatile than lendingdomestically.
2.2 Data on Prudential Instruments
The prudential instruments included in the IBRN Prudential Instru-ments Database (Cerutti et al. 2017) are capital requirements,sector-specific capital buffers, limits on LTV ratios, concentrationratios, reserve requirements (local currency and foreign currency),and interbank exposure limits. Although the full database coverssixty-four countries, the only policies that enter into our regres-sion analysis are from those countries with banking entities in theUnited States or spanned by the claims of U.S. global banks. Forinward analysis through global banks, the prudential instrumentsare weighted aggregates across countries, with weights constructedon the basis of bank-specific information on country exposures ineach period.
For regression analysis of policy spillovers to yield convincingfindings, the specific prudential instruments used in each regressionmust have a sufficient level of variation. We screen for sufficientvariation by examining the counts of changes in each prudentialinstrument as relevant for the particular banking entities in eachdata subset, the number of countries associated with those changes,
Vol. 13 No. S1 Lessons from the United States 445
and the number of tightening and loosening observations. The pan-els of table 2 show this information for the four data sets. Whilethere is not a well-defined rule available for determining a sufficientdegree of variation for regressors in an econometric specification,we apply a judgmental approach to capture a sufficient numberof episodes and number of countries. As a result of this screeningwe exclude concentration ratios in our outward and inward trans-mission analysis for U.S. global banks, and exclude foreign reserverequirements, interbank exposure limits, and concentration ratiosfrom our inward transmission analysis for U.S. branches of foreignbanks.
2.3 Data on Country Business and Financial Cycles
The analysis introduces controls for country business cycles andcredit cycles. These controls are not only important to account forcredit demand conditions but also for assessment of whether theeffects of the prudential instruments vary over the cycle. Details onthe construction of the business cycle control (output gap) and thefinancial cycle control (credit-to-GDP gap) are described in Bankfor International Settlements (2014) and Drehmann, Borio, andTsatsaronis (2011), respectively.
3. Empirical Method and Regression Results
This section provides conceptual observations on how changes inprudential instruments might spill over internationally into lend-ing activity, presents the main empirical specifications, and reportsresults for the analysis on the impact of prudential regulations onbank claims both in the United States and abroad. Section 3.1focuses on the spillovers of foreign regulatory changes to U.S. lend-ing. Section 3.2 explores the effect of changes in foreign regulationson the activities of U.S. global banks in foreign locations. It alsoanalyzes the response of U.S. global banks’ foreign activities whenU.S. capital requirements change.
While more extensively discussed in Buch and Goldberg (2017),changes in capital requirements, reserve requirements, and loan-to-value ratios could spill over to bank lending through various channels
446 International Journal of Central Banking March 2017Tab
le2.
Sum
mar
ySta
tist
ics
onC
han
ges
inP
ruden
tial
Inst
rum
ents
Exposu
re-
Wei
ghte
dB
ase
Dat
a(B
efore
Aggre
gat
ing
toExposu
re-W
eighte
dM
easu
res)
Obse
rvat
ions
No.of
No.of
No.of
Countr
y-
Countr
y-
No.of
Countr
y-
Tim
eT
ime
Ban
k-
Pro
port
ion
Pro
port
ion
Tim
eC
han
ges
Chan
ges
Tim
eB
ase-
MP
PExpP
tIn
stru
men
tC
han
ges
(Tig
hte
nin
g)
(Loose
nin
g)
Chan
ges
Non-z
ero
Non-z
ero
Out
war
d—U
.S.Ban
ks
Pru
dent
ialIn
dex
502
329
173
1,40
00.
170.
89G
ener
alC
apital
Req
uire
men
ts64
640
258
0.03
0.24
Sect
or-S
pec
ific
Cap
ital
Buff
er69
5118
545
0.02
0.39
Loa
n-to
-Val
ueR
atio
Lim
its
8864
2468
90.
040.
16R
eser
veR
equi
rem
ents
:Fo
reig
n13
383
5080
90.
040.
19R
eser
veR
equi
rem
ents
:Loc
al26
912
414
51,
112
0.08
0.48
Inte
rban
kE
xpos
ure
Lim
it22
211
209
0.01
0.21
Con
cent
ration
Rat
io32
302
356
0.01
0.32
Inwar
d—U
.S.G
loba
lBan
ks
Pru
dent
ialIn
dex
506
333
173
1,46
90.
160.
69G
ener
alC
apital
Req
uire
men
ts64
640
307
0.03
0.15
Sect
or-S
pec
ific
Cap
ital
Buff
er68
5117
622
0.02
0.28
Loa
n-to
-Val
ueR
atio
Lim
its
8864
2483
30.
030.
37R
eser
veR
equi
rem
ents
:Fo
reig
n13
686
5093
20.
040.
43R
eser
veR
equi
rem
ents
:Loc
al27
012
514
51,
224
0.07
0.55
Inte
rban
kE
xpos
ure
Lim
it22
211
260
0.01
0.11
Con
cent
ration
Rat
io32
302
404
0.01
0.18
(con
tinu
ed)
Vol. 13 No. S1 Lessons from the United States 447
Tab
le2.
(Con
tinued
)
Exposu
re-
Wei
ghte
dB
ase
Dat
a(B
efore
Aggre
gat
ing
toExposu
re-W
eighte
dM
easu
res)
Obse
rvat
ions
No.of
No.of
No.of
Countr
y-
Countr
y-
No.of
Countr
y-
Tim
eT
ime
Ban
k-
Pro
port
ion
Pro
port
ion
Tim
eC
han
ges
Chan
ges
Tim
eB
ase-
MP
PExpP
tIn
stru
men
tC
han
ges
(Tig
hte
nin
g)
(Loose
nin
g)
Chan
ges
Non-z
ero
Non-z
ero
Inwar
d—U
.S.Su
bsid
iari
esof
For
eign
Ban
ks
Pru
dent
ialIn
dex
9574
2121
30.
08G
ener
alC
apital
Req
uire
men
ts22
220
550.
02Se
ctor
-Spec
ific
Cap
ital
Buff
er17
143
280.
01Loa
n-to
-Val
ueR
atio
Lim
its
3123
893
0.03
Res
erve
Req
uire
men
ts:Fo
reig
n1
10
10.
00R
eser
veR
equi
rem
ents
:Loc
al31
1417
390.
01In
terb
ank
Exp
osur
eLim
it10
100
180.
01C
once
ntra
tion
Rat
io6
60
100.
00
Inwar
d—U
.S.Bra
nche
sof
For
eign
Ban
ks
Pru
dent
ialIn
dex
227
176
5165
30.
15G
ener
alC
apital
Req
uire
men
ts37
370
128
0.03
Sect
or-S
pec
ific
Cap
ital
Buff
er36
288
890.
02Loa
n-to
-Val
ueR
atio
Lim
its
5847
1121
90.
05R
eser
veR
equi
rem
ents
:Fo
reig
n48
3513
790.
02R
eser
veR
equi
rem
ents
:Loc
al99
5643
237
0.06
Inte
rban
kE
xpos
ure
Lim
it14
140
480.
01C
once
ntra
tion
Rat
io17
170
410.
01
Sourc
e:IB
RN
.N
ote
s:T
his
table
show
ssu
mm
ary
stat
isti
cson
chan
ges
inth
epru
den
tial
inst
rum
ents
inhom
ean
d/o
rdes
tinat
ion
count
ries
ofban
kslo
cate
din
the
Unit
edSta
tes.
The
sam
ple
per
iod
for
U.S
.gl
obal
ban
ksan
dfo
rsu
bsi
dia
ries
offo
reig
nban
ksis
2000
:Q1
to20
13:Q
3.T
he
U.S
.bra
nch
esof
fore
ign
ban
ksdat
ase
tgo
esfr
om20
02:Q
4to
2013
:Q3.
Dat
aon
the
inst
rum
ents
com
efr
omth
eIB
RN
Pru
den
tial
Inst
rum
ents
Dat
abas
edes
crib
edin
Cer
utt
iet
al.(2
017)
and
are
onth
equ
arte
rle
vel.
The
table
isbas
edon
the
esti
mat
ion
sam
ple
.T
he
table
show
sth
eto
talnu
mber
ofch
ange
s,i.e.
,ti
ghte
nin
gor
loos
enin
g,fo
rea
chin
stru
men
tas
wel
las
the
pro
por
tion
ofnon
-zer
oen
trie
s.A
llhom
ean
d/o
rdes
tinat
ion
count
ries
ofban
kslo
cate
din
the
Unit
edSta
tes
are
incl
uded
.
448 International Journal of Central Banking March 2017
that depend on the institutions examined. Consider first a changein capital requirements abroad. U.S. global banks that operate for-eign subsidiaries need to finance their foreign assets with subsidiary-specific capital. When foreign capital requirements are tightened,U.S. parent banks may cut lending in these markets and employ theavailable funding for lending in a different location. In contrast, thedirection of effects of tighter capital requirements in foreign banks’home countries on their U.S. subsidiaries is less clear. On the onehand, tighter capital requirements in the foreign bank’s home coun-try imply that the bank must finance its balance sheet with morecapital on a consolidated basis. To achieve this, the parent bank mayreduce lending both at home and abroad. However, tighter capitalrequirements at home also mean that the relative costs of lending athome and abroad change, with lending abroad becoming relativelyless expensive.
As opposed to the stand-alone structure of subsidiaries, the assetsin branches of foreign banks are directly linked to parent banks’ bal-ance sheets. A reduction of lending in the U.S. branches should thushave the same effect on the parent bank’s tier 1 ratio as a reductionof lending in its home offices. One would therefore expect that highercapital requirements at home lead to a reduction in lending by U.S.branches of foreign banks, as the parent bank seeks to comply withhigher capital standards.
Local-currency reserve requirements used as prudential tools areput in place by national monetary authorities to control the growthin domestic credit. Higher reserve requirements imply that banksneed to hold a larger fraction of funds as reserves with the cen-tral bank and can lend out only a smaller fraction to local borrow-ers. Reserve requirements in local currency, however, do not con-strain the bank’s activities in other countries. Since local fundingbecomes more expensive, banks have an incentive to raise fundingabroad and could move operations to other locations. They could dothis by increasing lending of their foreign branches or their foreignsubsidiaries.
Limits on LTV ratios are aimed at reducing credit in the econ-omy and often are specifically targeted at counteracting a potentialreal estate bubble. Such limits apply to all banks that engage inmortgage lending in a given country by decreasing the pool of eligi-ble borrowers. A tightening of LTV limits should thus decrease the
Vol. 13 No. S1 Lessons from the United States 449
local lending opportunities for all banks and might induce a shift inlending to other markets.
Within regression specifications, the exact mechanisms throughwhich adjustments occur are not constrained by instrument and typeof entities considered. Some policy instruments affect all banks thatoperate in a given market, as is the case of loan-to-value ratios. Otherinstruments may differentially affect banks in relation to their modeof servicing a location, as could be the case with capital require-ments, or the structure of their balance sheets in the case of reserverequirements.
3.1 Inward Analysis: Spillovers into the United States fromForeign Prudential Policies
The inward transmission analysis investigates the consequences forlending in the United States of foreign prudential policies throughtwo channels. First, U.S. banks with large foreign activities mightrespond to changes in regulation abroad by reallocating activityacross foreign and domestic locations. Second, foreign banks thathave to comply with home-country regulation might adjust lendingby their U.S. subsidiaries or U.S. branches.11
3.1.1 Specifications
We run regressions separately for (i) U.S. global banks, (ii) U.S. sub-sidiaries of foreign banks, and (iii) U.S. branches of foreign banks.In each specification, we regress the log change in lending ΔYb,t byentity b in quarter t on a relevant measure of foreign prudentialpolicy changes, including several lagged bank characteristics Xb,t−1(see section 2.1 for details) as well as bank and quarter fixed effects.We also control for financial and business cycle variables. Effec-tively, these regressions show whether policy changes abroad hadan effect on lending growth by entity b, after controlling for a bank-specific time-invariant component in entity b’s lending growth anda quarter-specific shift in lending growth common to all entities inthe sample.
11U.S. credit could also be affected through foreign banks that do not haveU.S. affiliates but lend cross-border to U.S. firms.
450 International Journal of Central Banking March 2017
We estimate the following equation on the sample of fifty-nineU.S.-headquartered banks with sizable exposures in foreign countries(global banks):
ΔYb,t = α0 +2∑
k=0
αk+1ExpPb,t−k + α4Xb,t−1 + α5Zb,t
+ fb + ft + εb,t, (1)
where ExpPb,t−k stands for the foreign-exposure-weighted index andcaptures the extent to which policies are tightened or loosened incountries where entity b has exposures in quarter t−k.12 To controlfor foreign-country financial and economic developments, the regres-sion also controls for exposure-weighted credit-to-GDP and outputgap variables Zb,t.13 Different prudential policies are explored usingthis specification and for this bank panel. Prudential policy effectscan be immediate (k = 0) or appear over the next two quarters(k = 1, 2). Standard errors are robust.
The regression equation for the 102 U.S. subsidiaries of foreignbanks and 137 U.S. branches of foreign banks is given by
ΔYb,j,t = α0 +2∑
k=0
αk+1HomePj,t−k + α4Xb,t−1 + α5Zj,t
+ fb + ft + εb,j,t, (2)
where HomePj,t−k indicates whether regulation tightened or loos-ened in home country j of entity b in quarter t − k. Zj,t includes
12The exposure-weighted prudential index for bank b at time t is calculatedusing this formula:
ExpPb,t =∑
j �=USA
PPjt · ϕjb,t−1, where · ϕjb,t−1 =
∑t−1t=t−4 claimsbjt
∑j �=USA
∑t−1t=t−4 claimsbjt
.
The term PP jt in the formula above stands for any of the indexes that measurethe change in one of the prudential instruments (e.g., limits on LTV ratios, capi-tal requirements, etc.) by regulators across all countries spanned by j. The termclaimsbjt represents bank b’s claims on country j at time t through the FFIEC009 reports.
13The exposure-weighted cycle variables are constructed in parallel to theexposure-weighted prudential index. For details, see footnote 12.
Vol. 13 No. S1 Lessons from the United States 451
country-specific measures of the home country’s credit-to-GDP gapand output gap. Standard errors are clustered at the country level.
3.1.2 Spillovers into the United States
Table 3 presents the results of the inward transmission through U.S.global banks, U.S. subsidiaries of foreign banks, and U.S. branchesof foreign banks. We only display results for those prudential instru-ments for which we find significant effects for at least one of thesethree types of entities. The table presents estimates of contempo-raneous effects and two periods of lagged effects. It also displaystests of the sum of effects, with the presentation columns organizedboth by instrument and entity type. Three instruments show signif-icant inward spillovers: capital requirements, local-currency reserverequirements, and LTV limits. Tighter foreign capital requirementsincrease the lending of U.S. global banks and of U.S. subsidiaries offoreign banks (the evidence for subsidiaries is weaker though), butdo not significantly affect lending by the U.S. branches of foreignbanks. In contrast, tighter foreign limits on LTV ratios and local-currency reserve requirements cause U.S. subsidiaries and branchesof foreign banks to increase their lending. We do not find significanteffects on lending of foreign changes in sector-specific capital buffers.The PruC index, which aggregates prudential policy changes over allinstruments, has largely insignificant effects, probably because theconsequences for lending growth vary substantially by prudentialinstrument and are more appropriately evaluated in isolation.14
Interestingly, both bank-specific characteristics and country con-ditions drive quarterly lending growth rates. Lending growth by U.S.affiliates of foreign banks follows home-country financial and eco-nomic conditions. In particular, lending growth by U.S. subsidiariesis relatively strong when the home country has slower growth, whilelending growth by U.S. branches is stronger when the credit-to-GDPgap is higher in the home country (implying a larger gap betweenthe credit-to-GDP ratio and its long-term trend). In contrast, the
14The effects of changes in concentration ratios were not analyzed because oflimited variation in foreign policies in all three samples. For the same reason, theeffects of changes in exposure limits and foreign reserve requirements were notexplored for U.S. affiliates of foreign banks.
452 International Journal of Central Banking March 2017
Tab
le3.
Inw
ard
Spec
ifica
tion
Cap
ital
Req
uir
emen
tsR
eser
ve
Req
uir
emen
ts:Loca
lLoan
-to-V
alue
Rat
io
Glo
bal
Glo
bal
Glo
bal
Ban
ks
Subs
Bra
nch
esB
anks
Subs
Bra
nch
esB
anks
Subs
Bra
nch
es(1
)(2
)(3
)(4
)(5
)(6
)(7
)(8
)(9
)
Pt
0.03
6∗∗
0.01
6−
0.01
3−
0.00
30.
016∗
∗0.
024
0.04
3−
0.01
30.
018∗
∗
(0.0
18)
(0.0
09)
(0.0
23)
(0.0
08)
(0.0
07)
(0.0
14)
(0.0
31)
(0.0
09)
(0.0
09)
Pt−
10.
009
0.00
8−
0.00
9−
0.00
10.
014
0.00
2(0
.008
)(0
.007
)(0
.019
)(0
.011
)(0
.014
)(0
.011
)P
t−2
−0.
005
0.02
6∗∗∗
0.00
8−
0.01
00.
021∗
∗0.
007
(0.0
07)
(0.0
04)
(0.0
10)
(0.0
10)
(0.0
10)
(0.0
14)
Log
Tot
alA
sset
s t−
1−
0.06
6∗∗∗
−0.
039∗
∗∗−
0.01
8−
0.06
7∗∗∗
−0.
040∗
∗∗−
0.01
8−
0.06
7∗∗∗
−0.
040∗
∗∗−
0.01
8(0
.015
)(0
.009
)(0
.013
)(0
.015
)(0
.009
)(0
.013
)(0
.015
)(0
.009
)(0
.013
)T
ier
1R
atio
t−1
0.00
2∗∗
0.00
0−
0.00
00.
002∗
∗0.
000
−0.
000
0.00
2∗∗
0.00
0−
0.00
0(0
.001
)(0
.001
)(0
.001
)(0
.001
)(0
.001
)(0
.001
)(0
.001
)(0
.001
)(0
.001
)Illiq
uid
Ass
ets
Rat
iot−
1−
0.00
0−
0.00
1∗∗∗
−0.
002∗
∗∗−
0.00
0−
0.00
1∗∗∗
−0.
002∗
∗∗−
0.00
0−
0.00
1∗∗∗
−0.
002∗
∗∗
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Net
Due
To t
−1
−0.
003
0.00
0−
0.00
0−
0.00
30.
000
−0.
000
−0.
003
0.00
0−
0.00
0(0
.003
)(0
.001
)(0
.000
)(0
.003
)(0
.001
)(0
.000
)(0
.003
)(0
.001
)(0
.000
)C
ore
Dep
osits
Rat
iot−
10.
001
−0.
000
0.00
00.
001
−0.
000
0.00
00.
001
−0.
000
0.00
0(0
.000
)(0
.000
)(0
.001
)(0
.000
)(0
.001
)(0
.001
)(0
.000
)(0
.000
)(0
.001
)B
ISFin
anci
alC
ycle
t−
0.00
1∗∗∗
0.00
1∗0.
001∗
∗∗−
0.00
1∗∗
0.00
1∗0.
001∗
∗∗−
0.00
1∗∗
0.00
1∗0.
001∗
∗∗
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(con
tinu
ed)
Vol. 13 No. S1 Lessons from the United States 453
Tab
le3.
(Con
tinued
)
Cap
ital
Req
uir
emen
tsR
eser
ve
Req
uir
emen
ts:Loca
lLoan
-to-V
alue
Rat
io
Glo
bal
Glo
bal
Glo
bal
Ban
ks
Subs
Bra
nch
esB
anks
Subs
Bra
nch
esB
anks
Subs
Bra
nch
es(1
)(2
)(3
)(4
)(5
)(6
)(7
)(8
)(9
)
BIS
Bus
ines
sC
ycle
t0.
000
0.00
5∗∗∗
0.00
20.
000
0.00
5∗∗∗
0.00
20.
000
0.00
5∗∗∗
0.00
1(0
.003
)(0
.002
)(0
.004
)(0
.003
)(0
.002
)(0
.003
)(0
.003
)(0
.002
)(0
.004
)In
tern
atio
nalA
ctiv
ity t
−1
0.00
1∗0.
001∗
0.00
1∗
(0.0
01)
(0.0
01)
(0.0
01)
Obs
erva
tion
s1,
873
2,80
14,
262
1,87
32,
801
4,26
21,
873
2,80
14,
262
R2
0.19
60.
191
0.10
00.
195
0.19
30.
100
0.19
70.
193
0.10
0A
djus
ted
R2
0.14
10.
142
0.05
90.
140
0.14
30.
059
0.14
10.
143
0.05
9N
o.of
Ban
ks59
102
137
5910
213
759
102
137
Pro
por
tion
ofP
tN
on-z
ero
0.14
50.
020
0.03
00.
549
0.01
40.
056
0.37
00.
033
0.05
1P
tC
oeffi
cien
tSu
m0.
001
0.05
0∗∗∗
0.02
30.
031
0.02
20.
027∗
p-va
lue
[0.9
14]
[0.0
00]
[0.2
46]
[0.2
70]
[0.2
63]
[0.0
67]
Note
s:T
his
table
repor
tsth
eeff
ects
ofch
ange
sin
capit
alre
quir
emen
ts,
loca
l-cu
rren
cyre
serv
ere
quir
emen
ts,
and
LT
Vlim
its.
The
sam
ple
per
iod
for
U.S
.gl
obal
ban
ksan
dfo
rsu
bsi
dia
ries
offo
reig
nban
ksis
2000
:Q1
to20
13:Q
3.T
he
U.S
.bra
nch
esof
fore
ign
ban
ksdat
ase
tgo
esfr
om20
02:Q
4to
2013
:Q3.
Col
um
ns
1,4,
and
7sh
owth
ere
sult
sbas
edon
the
sam
ple
ofU
.S.gl
obal
ban
ks.C
olum
ns
2,5,
and
8ar
efo
rU
.S.
subsi
dia
ries
offo
reig
nban
ks,an
dco
lum
ns
3,6,
and
9ar
efo
rU
.S.bra
nch
esof
fore
ign
ban
ks.In
spec
ifica
tion
s(1
)to
(3),
the
vari
able
Pt
stan
ds
for
Exp
Pb
,t,th
eex
pos
ure
-wei
ghte
din
dex
.In
spec
ifica
tion
s(4
)to
(9),
Pt
stan
ds
for
Hom
ePj,t,th
epru
den
tial
index
that
captu
res
pru
den
tial
pol
icy
chan
ges
inen
tity
b’s
hom
eco
unt
ryj.For
mor
edet
ails
onth
eva
riab
les,
see
table
7in
the
appen
dix
.B
IScy
cle
vari
able
sar
esi
milar
lyco
nst
ruct
edas
expos
ure
-wei
ghte
dav
erag
esin
spec
ifica
tion
s(1
)to
(3).
All
spec
ifica
tion
sin
clude
tim
ean
dban
kfixe
deff
ects
assp
ecifi
edin
the
low
erpar
tof
the
table
.Sta
ndar
der
rors
are
robust
for
glob
alban
ks,an
dcl
ust
ered
byco
unt
ryfo
raffi
liat
ere
gres
sion
s.**
*,**
,an
d*
indic
ate
sign
ifica
nce
atth
e1
per
cent
,5
per
cent
,an
d10
per
cent
leve
l,re
spec
tive
ly.
454 International Journal of Central Banking March 2017
negative and significant coefficients on the exposure-weighted credit-to-GDP gap indicate that the lending growth of U.S. global banksis lower when the credit-to-GDP gap in the countries where thesebanks operate is higher. This is likely because these banks refocustheir lending toward foreign countries and away from domestic lend-ing when foreign demand for credit is strong, a hypothesis that issupported by the positive coefficient on the credit-to-GDP gap inthe outward exercise.
Bank-level characteristics also help explain lending growth. Aftercontrolling for bank fixed effects on lending growth, U.S. globalbanks with higher tier 1 ratios (in the previous quarter) havestronger lending growth. This also holds for their foreign activities,as shown later in the outward exercise, and is consistent with previ-ous results in the literature.15 Tier 1 capital ratios do not appear asdrivers of foreign-owned bank lending growth in the United States.Instead, lending growth is stronger when illiquid asset ratios arelower.
Below we discuss the regression results of table 3 in more detailand evaluate the economic impact on loan growth in the U.S. fromchanges in capital requirements, local-currency reserve requirements,and limits on LTV ratios abroad.
3.1.3 Capital Requirements
The conjecture that foreign capital requirements could shift globalbank activity away from the host country is supported by theregression results. We find a significant positive effect of tightercapital requirements abroad on total lending by U.S. global banks(see column 1 of table 3).16 We also used as the dependent vari-able total lending minus loans to foreign banks, commercial andindustrial loans to foreign addressees, and loans to foreign gov-ernments and official institutions. Results based on these alterna-tive dependent variables show that the effects on lending growthare not limited to U.S. lending. U.S. banks increase domestic and
15See, e.g., Bernanke and Lown (1991) and Berrospide and Edge (2010).16Lagged values of the capital requirement index are dropped in the regressions
displayed in columns 1–3, since these were never significant.
Vol. 13 No. S1 Lessons from the United States 455
third-country lending growth in response to higher foreign capitalrequirements.17
With regards to the lending of foreign-owned subsidiaries, theregression results indicate that our substitution effect from tighterhome capital requirements (lending abroad becomes relatively lessexpensive than home lending) can dominate the effect associatedwith the consolidated entity’s increased capital needs and give parentbanks a net incentive to expand subsidiary operations in the UnitedStates. However, overall the support for this effect is relatively weak:the estimated coefficient shown in column 2 is significant only at the11 percent level. The point estimate related to branch lending is notsignificant at conventional levels (see column 3).
How large is the positive effect on loan growth from tighter cap-ital requirements abroad? If there were a change in capital require-ments in all countries in which a U.S. bank holds claims, then thatbank’s lending growth would be 3.6 percentage points higher accord-ing to the estimated coefficient in column 1. This corresponds toaround 38 percent of one standard deviation of the dependent vari-able. The average value of the exposure-weighted index is 0.028 inthe sample, implying an average positive effect on a bank’s lendinggrowth rate of 0.1 percentage point.
We conduct a basic experiment to illustrate the magnitudes ofpotential spillovers from past capital requirement changes: (i) wecalculate the effect on a bank’s lending growth in each quarter, mul-tiplying the capital requirement index in each period with the esti-mated coefficient; (ii) we convert the effect on the bank’s lendinggrowth rate to a U.S. dollar value, taking into account the lendingvolume of the bank in the previous period; and (iii) we aggregatethe calculated U.S. dollar value over all banks. It is important tonote that the estimated coefficients often have large confidence inter-vals, so the resulting dollar amounts are rough estimates of potentialspillover effects.
Most of the regulatory changes in the sample occurred in thefirst quarter of 2012 and 2013 when several industrialized coun-tries introduced Basel II.5 and Basel III, respectively. In some of
17Detailed estimates are shown in table 8 in the appendix. As noted later, theoutward analysis shows that U.S. banks do not increase lending growth in thecountries where capital requirements are changed.
456 International Journal of Central Banking March 2017
these countries, U.S. banks have large operations—for example, inCanada, Hong Kong, and Switzerland. Accordingly, the effect onaggregate lending of U.S. global banks is notable. Based on ourcalculations, the introduction of Basel II.5 or Basel III in 2012:Q1in twenty-eight countries led U.S. global banks to increase lendingby around 2.4 percentage points ($119 billion). Summed over allquarters, additional lending due to changes in capital requirementsabroad totaled $249 billion.
3.1.4 Local-Currency Reserve Requirements
The conjecture that higher local reserve requirements in the homecountry will make operations by foreign-owned affiliates in theUnited States relatively more attractive is supported by the regres-sion results, as can be seen in column 5 of table 3. Higher local reserverequirements in the home country increase a U.S. subsidiary’s lend-ing growth rate by a total of 5 percentage points over half a year(beta coefficient of 0.07). The contemporaneous and lagged coeffi-cients in the branch regression (column 6 of table 3) are not jointlysignificant at standard levels, but there is some weak evidence thatbranch lending responds as well since the coefficient on the con-temporaneous prudential variable is significant at the 11 percentlevel. Banks should not prefer to move activity to subsidiaries or tobranches in particular, since the impact of local reserve requirementsis not related to the bank’s organizational structure as discussedearlier.
U.S. global banks do not seem to respond at all to local reserverequirement changes abroad. In principle, changes in local reserverequirements in a market could also affect U.S. global banks thatoperate there. However, U.S. global banks do not fund themselvesto a significant extent in foreign/local currencies and are probablylittle affected by these types of regulatory changes.
We investigated whether banks respond symmetrically to tight-ening versus loosening reserve requirements. In terms of magnitudes,the effects appear to be similar but the timing of responses differs.The effect of a tightening unfolds immediately, while responses to aloosening of reserve requirements occur with a lag of half a year.
Figure 1 illustrates the aggregate effects of reserve require-ment changes abroad on lending by U.S. subsidiaries of foreign
Vol. 13 No. S1 Lessons from the United States 457
Figure 1. Home-Country Local-Currency ReserveRequirements and Lending by U.S. Subsidiaries
of Foreign Banks
Notes: The chart shows the effect of changes in home-country local-currencyreserve requirements on lending by U.S. subsidiaries of foreign banks. Calcula-tions follow the methodology described in the text and are based on the estimatedcoefficients shown in column 5 of table 3. The figure plots by date the addi-tional lending by subsidiaries in U.S. dollar values due to observed changes inlocal-currency reserve requirements in these entities’ home countries.
banks following the methodology described earlier. The largest effectoccurred in 2012. On January18, 2012, the European Central Banklowered the reserve requirement ratio from 2 percent to 1 percent.India and China, which were parent countries for U.S. subsidiaries in2012, also lowered their local reserve requirements in this year. Sum-ming the U.S. dollar changes in lending from 2012:Q1 to 2012:Q3over subsidiaries suggests that the reduction in local reserve require-ments in this period led to roughly $7 billion lower lending by theseentities, a bit less than half a percent of their total lending over thesame period.
3.1.5 Limits on Loan-to-Value Ratios
The regression results in columns 8 and 9 of table 3 support theconjecture that banks headquartered abroad redirect activity to the
458 International Journal of Central Banking March 2017
Figure 2. Home-Country Limits on LTV Ratios andLending by U.S. Subsidiaries and Branches of
Foreign Banks
Notes: The chart shows the effect of changes in home-country limits on LTVratios on lending by U.S. subsidiaries (dashed line) and branches (solid line) offoreign banks. Calculations follow the methodology described in the text and arebased on the estimated coefficients shown in columns 8 and 9 of table 3. Thefigure plots by date the additional lending by subsidiaries and branches in U.S.dollar values due to observed changes in limits on LTV ratios in these entities’home countries.
United States in response to tightened LTV limits in their homecounties. Lending by both U.S. branches and subsidiaries of foreignbanks expands in response to these changes.18
If tightening occurs in the parent country, lending growth byU.S. subsidiaries and U.S. branches of foreign banks increases by2.2 and 2.7 percentage points, respectively, based on estimates incolumns 8 and 9 (sum of contemporaneous and lagged coefficients).Figure 2 shows the aggregate effects of past changes in LTV limitsby quarter. The volatility of aggregate effects over time is mainly areflection of tightening and loosening in foreign countries. For sub-sidiaries, the switching signs on the contemporaneous versus lagged
18We did not find evidence for differential effects of tightening versus looseningLTV limits.
Vol. 13 No. S1 Lessons from the United States 459
effects of policy changes (see column 8) also play a role. Most changesin LTV limits occurred after the 2007–08 financial crisis in advancedeconomies like Sweden, Canada, Norway, and the Netherlands butalso in developing countries like China and Brazil. Summing theeffects of past LTV changes over the sample period and over bothtypes of entities suggests that U.S. branches and subsidiaries lentout an additional $15 billion from 2003:Q3 to 2013:Q3 due to policychanges in their home countries. Subsidiaries contributed around 45percent, and branches around 55 percent, to the increase.19 Overallthe additional lending over the sample period is small, reflecting atiny fraction of these entities’ total lending (0.04 percent).20
3.2 Outward Analysis: International Response of U.S. GlobalBanks to U.S. and Foreign Prudential Policies
The outward transmission exercise assesses the effects of foreign pru-dential policies on the growth of U.S. banks’ claims to foreign coun-tries, including on the reallocation of U.S. banks’ external claimsacross foreign markets. The analysis also explores the impact of U.Sregulation on U.S. banks’ claims abroad.
3.2.1 Impact of Foreign Prudential Instruments onU.S. Banks’ Foreign Claims
First, we consider the impact of different prudential instrumentsused by the destination country on U.S. bank claims abroad. Eachof the prudential instrument measures enters the regression specifi-cation with its contemporaneous value and two lags. Formally, weestimate the regression equation:
ΔYb,j,t = α0 + (α1DestPj,t + α2DestPj,t−1 + α3DestPj,t−2)
+ α4Xb,t−1 + α5Zj,t + fj + ft + fb + εb,j,t, (3)
19The larger contribution of branches to this expansion stems from a largerimpact of an LTV ratio change on branch lending, compared with subsidiarylending, and the fact that more local reserve requirement changes occurred inthe home countries of U.S. branches.
20In 2013:Q3, total lending of branches in our data set was $518 billion versus$595 billion of subsidiaries.
460 International Journal of Central Banking March 2017
where the prudential instrument changes are captured by DestP j,t,which records the changes in the prudential instruments of countryj in which U.S. bank b has exposures at time t. The dependent vari-able is the change in logs of U.S. bank b’s claims on countryj at timet evaluated on an ultimate risk basis.
Table 4 summarizes the main results for individual prudentialinstruments on the foreign claim growth of U.S. banks. Only two pru-dential instruments have some statistically significant coefficients:LTV ratio limits and interbank exposure limits. However, the sumof coefficients on these two measures for all lags is not significant,suggesting only a weak effect of prudential regulation in the des-tination countries on U.S. bank foreign claims. The weak resultshave two interpretations. First, while some of these policies havebeen actively used across U.S. counterparty countries, especially inemerging markets, exposures of U.S. global banks to emerging mar-kets are smaller than exposures to advanced economies; it may bethat global banks just choose to absorb the costs of the extra regu-lation. Alternatively, it may be that these policies are ineffective inchanging the growth of foreign claims at U.S. banks.
Among other drivers of total claim growth of U.S. global banks,the financial cycle variable has the expected signs in most cases,though the effects seem to be economically small. The negative andsignificant coefficient on the international ratio suggests that the for-eign claim growth is smaller for more diversified banks (banks withmore international activities). Core deposits are negatively relatedto total claims growth, reflecting the fact that U.S. banks withsmaller shares of core deposits on their balance sheets (and thus moredependent on wholesale funding) lend more to foreign residents. Thepositive and significant coefficient on both the illiquid assets ratioand the net due to ratio suggest that less liquid banks and bankswith more net internal borrowing from their parents exhibit a highergrowth rate in their foreign claims.
3.2.2 Impact of U.S. Prudential Instruments on U.S. Banks’Foreign Claims
Second, we test for the impact of changes in U.S. prudential instru-ments on U.S. banks’ foreign claims. The use of prudential instru-ments in the United States between 2000 and 2013 is essentially
Vol. 13 No. S1 Lessons from the United States 461
Tab
le4.
Outw
ard
Tra
nsm
issi
onof
Des
tinat
ion-C
ountr
yP
ruden
tial
Pol
icy
Sec
tor-
Res
erve
Res
erve
Cap
ital
Spec
ific
Loan
-to-
Req
uir
e-R
equir
e-In
terb
ank
Pru
den
tial
Req
uir
e-C
apit
alV
alue
men
ts:
men
ts:
Exposu
reIn
dex
Cm
ents
Buffer
Rat
ioFore
ign
Loca
lLim
its
(1)
(2)
(3)
(4)
(5)
(6)
(7)
Pt
0.00
5−
0.00
8−
0.00
20.
012
−0.
005
0.00
6−
0.00
2(0
.006
)(0
.014
)(0
.010
)(0
.010
)(0
.005
)(0
.009
)(0
.018
)P
t−1
0.00
7−
0.00
9−
0.00
3−
0.01
5∗0.
001
0.01
1−
0.03
7∗∗
(0.0
05)
(0.0
13)
(0.0
09)
(0.0
09)
(0.0
11)
(0.0
08)
(0.0
18)
Pt−
20.
009∗
−0.
014
0.01
30.
016∗
0.00
20.
007
0.01
3(0
.005
)(0
.011
)(0
.014
)(0
.010
)(0
.005
)(0
.006
)(0
.012
)Log
Tot
alA
sset
s t−
1−
0.00
6−
0.00
6−
0.00
6−
0.00
6−
0.00
6−
0.00
6−
0.00
6(0
.007
)(0
.008
)(0
.008
)(0
.008
)(0
.008
)(0
.007
)(0
.008
)T
ier
1R
atio
t−1
0.00
10.
001
0.00
10.
001
0.00
10.
001
0.00
1(0
.001
)(0
.001
)(0
.001
)(0
.001
)(0
.001
)(0
.001
)(0
.001
)Illiq
uid
Ass
ets
Rat
iot−
10.
001∗
∗0.
001∗
∗0.
001∗
∗0.
001∗
∗0.
001∗
∗0.
001∗
∗0.
001∗
∗
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
01)
(0.0
00)
(0.0
00)
(0.0
00)
Inte
rnat
iona
lA
ctiv
ity t
−1
−0.
002∗
∗∗−
0.00
2∗∗∗
−0.
002∗
∗∗−
0.00
2∗∗∗
−0.
002∗
∗∗−
0.00
2∗∗∗
−0.
002∗
∗∗
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
Net
Due
To t
−1
0.00
2∗0.
002∗
0.00
2∗0.
002∗
0.00
2∗0.
002∗
0.00
2∗
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(con
tinu
ed)
462 International Journal of Central Banking March 2017
Tab
le4.
(Con
tinued
)
Sec
tor-
Res
erve
Res
erve
Cap
ital
Spec
ific
Loan
-to-
Req
uir
e-R
equir
e-In
terb
ank
Pru
den
tial
Req
uir
e-C
apit
alV
alue
men
ts:
men
ts:
Exposu
reIn
dex
Cm
ents
Buffer
Rat
ioFore
ign
Loca
lLim
its
(1)
(2)
(3)
(4)
(5)
(6)
(7)
Cor
eD
epos
its
Rat
iot−
1−
0.00
1∗∗∗
−0.
001∗
∗∗−
0.00
1∗∗∗
−0.
001∗
∗∗−
0.00
1∗∗∗
−0.
001∗
∗∗−
0.00
1∗∗∗
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
BIS
Fin
anci
alC
ycle
t0.
000∗
∗0.
000∗
∗0.
000∗
∗0.
000∗
∗0.
000∗
∗0.
000∗
∗0.
000∗
∗
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
BIS
Bus
ines
sC
ycle
t0.
003
0.00
40.
004
0.00
40.
004
0.00
40.
004
(0.0
02)
(0.0
02)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
02)
Obs
erva
tion
s25
,986
25,9
8625
,986
25,9
8625
,986
25,9
8625
,986
R2
0.02
30.
022
0.02
30.
023
0.02
20.
023
0.02
3A
djus
ted
R2
0.01
60.
016
0.01
60.
016
0.01
60.
016
0.01
6
Des
tP(t
)C
oeffi
cien
tSu
m0.
021∗
−0.
030
0.00
80.
013
−0.
002
0.02
3−
0.02
6p-
valu
e[0
.091
][0
.266
][0
.669
][0
.243
][0
.917
][0
.150
][0
.427
]
Note
s:T
his
table
repor
tsth
eeff
ects
ofch
ange
sin
des
tinat
ion-c
ount
ryre
gula
tion
and
firm
char
acte
rist
ics
onlo
gch
ange
sin
tota
llo
ans
bydes
tinat
ion
count
ry.T
he
dat
aar
equ
arte
rly
from
2000
:Q1
to20
13:Q
3fo
ra
pan
elof
ban
khol
din
gco
mpan
ies.
Des
tPre
fers
toth
ech
ange
sin
regu
lati
onin
the
des
tinat
ion
count
ryof
the
loan
.For
mor
edet
ails
onth
eva
riab
les,
see
table
7in
the
appen
dix
.Eac
hco
lum
ngi
ves
the
resu
ltfo
rth
ere
gula
tory
mea
sure
spec
ified
inth
eco
lum
nhea
dline.
All
spec
ifica
tion
sin
clude
fixe
deff
ects
assp
ecifi
edin
the
low
erpar
tof
the
table
.Sta
ndar
der
rors
are
clust
ered
byco
unt
ry.**
*,**
,an
d*
indic
ate
sign
ifica
nce
atth
e1
per
cent
,5
per
cent
,an
d10
per
cent
leve
l,re
spec
tive
ly.
Vol. 13 No. S1 Lessons from the United States 463
related to the stricter regulation mandated by the Dodd-Frank Actand the Basel standards on capital regulation, in particular theBasel II.5 standards implemented in January 2013 and the Basel IIIstandards that became effective in January 2014. These regulatorychanges are captured in the IBRN Prudential Instruments Databasein the capital requirements index. Since our sample ends in 2013:Q3,only the implementation of Basel II.5 can be captured in our empiri-cal analysis. Given this setting, we use the cumulative change in thecapital requirement index for the United States as the variable ofinterest. This indicator is equal to one from the first quarter in 2013until the end of the sample, and zero otherwise. This approach makesthe empirical test a de facto difference-in-difference estimation. Moreformally, we use the following regression specification:
ΔYb,j,t = α0 + α1UScum CapReqt + α2Xb,t−1
+ α3UScum CapReqt ∗ Xb,t−1 + α4Zj,t
+ fj + fb + εb,j,t, (4)
where the prudential instrument is captured by UScum CapReqt,which records the cumulative changes in U.S. capital requirements.We also include interaction terms between this instrument and somebank characteristics in vector Xb,t−1 to complete the difference-in-difference analysis. As before, the dependent variable is the changein logs of U.S. bank b’s claims on country j at time t evaluatedon an ultimate risk basis. In this specification, the U.S. prudentialinstrument varies only by time and thus we only include bank andcountry fixed effects. We also use specifications that include country-time fixed effects to account for loan demand at the country level. Inthese cases, UScum CapReqt is absorbed by the country-time fixedeffect and thus we focus our attention only on the interaction ofUScum CapReqt and bank-specific characteristics.
Most of the recent regulatory changes in the United States havefocused on the systemic global banks which are subject to the FederalReserve’s stress tests, known as the Comprehensive Capital Analysisand Review (CCAR) and, among these banks, those that follow theso-called Advanced Approach capital rules.21 Therefore, we test for
21CCAR BHCs are generally global U.S. BHCs with total consolidated assetsabove $50 billion. As of 2013:Q3, there were thirty CCAR BHCs, twenty-three
464 International Journal of Central Banking March 2017
a differential impact of the stricter U.S. regulation on the growth intotal and cross-border claims for CCAR/non-CCAR and AdvancedApproach/non-Advanced Approach banks. To this end, we includeinteractions between UScum CapReqt and dummy variables that takethe value of one for CCAR or Advanced Approach banks and zerootherwise. We expect that if there is any negative effect of the newcapital regulations on the growth in foreign bank claims, it shouldbe significant for the group of large global banks.22
This expectation is supported by the results presented in table5. The first four columns of the table examine the changes in totalclaims and cross-border claims to all countries. Columns 5–8 exam-ine the changes in cross-border claims to advanced foreign andemerging economies. In almost all cases, the interaction of UScum
CapReqt and indicator variables for CCAR and Advanced Approachbanks is negative and significant. This finding confirms that the newBasel capital regulations reduced the growth in foreign claims at thelargest U.S. banks subject to the Federal Reserve’s stress tests com-pared with smaller institutions not subject to these stress tests. Forexample, taking into account that the difference in growth ratesbetween CCAR and non-CCAR banks before 2013 was on average0.4 percentage points (the growth rate was 1 percent for CCARbanks and 0.6 percent for non-CCAR banks), our estimates indicatethat the difference in growth rates between the two groups of banksand across the two periods should have been –5.5 percentage points(the difference-in-difference estimate). The growth rate differentialobserved in the data is –5.2 percentage points. Thus, most of thereduction in the growth rate of CCAR banks relative to non-CCARbanks could be attributable to the change in U.S. capital regulationfollowing the implementation of Basel II.5.
We explore further whether the negative impact of the strictercapital regulation is influenced by bank-specific characteristics. Tothat end, we include interaction terms between the cumulativecapital requirements index and three bank-specific characteristics:
of which had foreign claims in the fifty-nine countries in our sample. AdvancedApproach BHCs are CCAR BHCs with total assets above $250 billion and foreignexposures larger than $10 billion.
22Our estimates likely provide a lower bound to the total effects of regulatorychanges, as the banks may have adapted their portfolios as early as 2011.
Vol. 13 No. S1 Lessons from the United States 465
Tab
le5.
Impac
tof
Chan
ges
inU
.S.C
apital
Reg
ula
tion
onFor
eign
Cla
imG
row
thby
Type
ofC
laim
and
Des
tinat
ion
Cou
ntr
y
Adva
nce
dFore
ign
All
Countr
ies
Countr
ies
Em
ergin
gM
arket
s
Tota
lC
laim
sC
ross
-Bord
erC
laim
sC
ross
-Bord
erC
laim
sC
ross
-Bord
erC
laim
s
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
US c
um
Cap
Req
t*C
CA
Rt
−0.
055∗
∗∗−
0.07
4∗∗∗
−0.
078∗
∗−
0.07
2∗∗∗
(0.0
12)
(0.0
18)
(0.0
33)
(0.0
19)
US c
um
Cap
Req
t*−
0.04
8∗∗∗
−0.
046∗
∗−
0.04
2−
0.05
3∗∗
Adv
ance
dA
ppro
ach t
(0.0
14)
(0.0
19)
(0.0
28)
(0.0
20)
Log
Tot
alA
sset
s t−
1−
0.00
6−
0.00
3−
0.00
7−
0.00
4−
0.01
4−
0.01
20.
003
0.00
5(0
.011
)(0
.011
)(0
.011
)(0
.011
)(0
.015
)(0
.015
)(0
.016
)(0
.016
)T
ier
1R
atio
t−1
0.00
3∗∗
0.00
3∗∗
0.00
3∗∗
0.00
3∗∗
0.00
5∗∗∗
0.00
5∗∗∗
0.00
10.
001
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
Illiq
uid
Ass
ets
Rat
iot−
10.
001∗
0.00
1∗0.
001
0.00
10.
002∗
∗0.
002∗
∗.0
001
.000
1(0
.000
)(0
.000
)(0
.001
)(0
.001
)(0
.001
)(0
.001
)(0
.001
)(0
.001
)In
tern
atio
nalA
ctiv
ity t
−1
−0.
002∗
∗∗−
0.00
2∗∗∗
−0.
002∗
∗∗−
0.00
2∗∗∗
−0.
003∗
∗∗−
0.00
3∗∗∗
−0.
001∗
−0.
001∗
(0.0
01)
(0.0
01)
(0.0
00)
(0.0
00)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
Net
Due
To t
−1
0.00
20.
002
0.00
20.
002
0.00
30.
003
0.00
50.
005
(0.0
02)
(0.0
02)
(0.0
03)
(0.0
03)
(0.0
02)
(0.0
02)
(0.0
19)
(0.0
19)
Cor
eD
epos
its
Rat
iot−
1−
0.00
3−
0.00
4−
0.00
1−
0.00
1−
0.00
1∗−
0.00
2∗−
0.00
4−
0.00
1(0
.001
)(0
.001
)(0
.001
)(0
.001
)(0
.001
)(0
.001
)(0
.001
)(0
.001
)
Obs
erva
tion
s35
,483
35,4
8331
,114
31,1
1414
,809
14,8
0916
,305
16,3
05R
20.
120.
120.
130.
130.
10.
10.
150.
15A
djus
ted
R2
0.03
0.03
0.03
0.03
0.02
0.02
0.04
0.04
Cou
ntry
-Tim
eFix
edE
ffec
tsYes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Note
s:T
his
table
repor
tsth
eeff
ects
ofch
ange
sin
the
inte
ract
ion
ofch
ange
sin
U.S
.pru
den
tial
pol
icy
wit
hin
dic
ator
vari
able
sfo
rC
CA
Ror
Adva
nce
dA
ppro
ach
ban
ksan
dfirm
char
acte
rist
ics
onlo
gch
ange
sin
tota
llo
ans
bydes
tinat
ion
count
ry.
CC
AR
ban
ksar
eban
khol
din
gco
mpan
ies
(BH
Cs)
incl
uded
inth
eye
arly
stre
ss-t
est
exer
cise
conduct
edby
the
Fed
eral
Res
erve
.A
dva
nce
dA
ppro
ach
ban
ksar
eC
CA
RB
HC
sw
ith
tota
las
sets
abov
e$2
50billion
and
fore
ign
expos
ure
sla
rger
than
$10
billion
.T
he
dat
aar
equ
arte
rly
from
2000
:Q1
to20
13:Q
3fo
ra
pan
elof
BH
Cs.
For
mor
edet
ails
onth
eva
riab
les,
see
table
7in
the
appen
dix
.Eac
hco
lum
ngi
ves
the
resu
ltfo
rth
eco
unt
ryan
dcl
aim
type
spec
ified
inth
eco
lum
nhea
der
.Spec
ifica
tion
sin
allco
lum
ns
incl
ude
ban
kan
dco
unt
ry-t
ime
fixe
deff
ects
.Sta
ndar
der
rors
are
clust
ered
byban
k.**
*,**
,an
d*
indic
ate
sign
ifica
nce
atth
e1
per
cent
,5
per
cent
,an
d10
per
cent
leve
l,re
spec
tive
ly.
466 International Journal of Central Banking March 2017
size, the tier 1 capital ratio, and the core-deposits-to-total-liabilitiesratio.23 Table 6 shows the regression results. The estimations in thefirst two columns include US cum CapReqt as a stand-alone vari-able and separate country, time, and bank fixed effects. The changein U.S. capital regulation seems to reduce the growth in foreignclaim of U.S. global banks, as suggested by the negative coeffi-cient on US cum CapReqt, but this effect is not statistically signif-icant. However, balance sheet characteristics appear important toexplain bank reactions to the change in capital requirements, asindicated by the three significant interaction terms between US cum
CapReqt and size, tier 1 capital ratio, and the core-deposit-to-total-liabilities ratio in column 2. For example, the negative impact of thestricter regulation is stronger for larger banks; in contrast, bankswith more capital (tier 1 capital ratio) and core deposits are able toincrease their claims after the new regulations are implemented. Col-umn 3 shows that the significance of the interaction terms betweenUS cum CapReqt and size and core deposits is robust to account-ing for the foreign demand for credit through country-time fixedeffects.
To better control for the effect of bank size, and to verifythat the impact of the new regulations on foreign claims occursmainly through the largest global banks, we estimate the same spec-ifications, splitting our sample by CCAR and non-CCAR banksand by Advanced Approach and non-Advanced Approach banks.These results are shown in columns 4–7. As expected, the coeffi-cients on the interaction terms are mostly significant for CCARand Advanced Approach banks. The interaction terms with coredeposits for Advanced Approach banks, and with both tier 1 cap-ital and the core deposits ratio for CCAR banks, are positive andsignificant, indicating that large banks with more regulatory cap-ital and core deposits are able to offset the impact of the strictercapital regulation. Recent evidence shows that large U.S. banks sub-ject to the stress tests have been increasing their regulatory capitaland their deposits base (International Monetary Fund 2015). Our
23These three interaction terms have the only significant coefficients in thespecifications that include interactions between the cumulative changes in theU.S. capital requirements and all bank characteristics.
Vol. 13 No. S1 Lessons from the United States 467
Tab
le6.
Impac
tof
Chan
ges
inU
.S.C
apital
Reg
ula
tion
onTot
alFor
eign
Cla
imG
row
th
Adv.
Non-A
dv.
CC
AR
Non-C
CA
RA
ppro
ach
Appro
ach
All
Banks
Banks
Banks
Banks
Banks
(1)
(2)
(3)
(4)
(5)
(6)
(7)
UScum
CapR
eqt
−0.0
05
0.0
57
(0.0
09)
(0.0
82)
UScum
CapR
eqt*Log
−0.0
06
∗∗
−0.0
08
∗∗
−0.0
06
0.0
08
−0.0
11
−0.0
03
Tota
lA
sset
s t−
1(0
.003)
(0.0
03)
(0.0
06)
(0.0
07)
(0.0
08)
(0.0
04)
UScum
CapR
eqt*T
ier
1R
ati
ot−
10.0
05
∗∗
0.0
03
0.0
07
∗−
0.0
04
0.0
07
.0002
(0.0
02)
(0.0
02)
(0.0
03)
(0.0
03)
(0.0
04)
(0.0
03)
UScum
CapR
eqt*C
ore
0.0
01
∗∗
∗0.0
01
∗∗
0.0
01
∗∗
.0001
0.0
01
∗∗
.0001
Dep
osi
tsR
ati
ot−
1(0
.000)
(0.0
00)
(0.0
00)
(0.0
01)
(0.0
00)
(0.0
01)
Log
Tota
lA
sset
s t−
1−
0.0
14
−0.0
16
−0.0
08
−0.0
12
0.0
2−
0.0
35
0.0
08
(0.0
13)
(0.0
14)
(0.0
11)
(0.0
12)
(0.0
24)
(0.0
24)
(0.0
17)
Tie
r1
Rati
ot−
10.0
03
∗0.0
02
0.0
02
0.0
01
0.0
03
∗0.0
05
0.0
01
(0.0
02)
(0.0
02)
(0.0
01)
(0.0
03)
(0.0
02)
(0.0
04)
(0.0
02)
Illiquid
Ass
ets
Rati
ot−
10.0
01
∗∗
0.0
01
∗∗
0.0
01
0.0
01
0.0
01
0.0
01
0.0
01
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
Inte
rnati
onalA
ctiv
ityt−
1−
0.0
02
∗∗
∗−
0.0
02
∗∗
∗−
0.0
02
∗∗
∗−
0.0
02
∗∗
∗−
0.0
02
∗∗
∗−
0.0
03
∗∗
−0.0
02
∗
(0.0
01)
(0.0
01)
(0.0
00)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
Net
Due
Tot−
10.0
01
0.0
01
0.0
02
0.0
02
0.0
04
0.0
01
0.0
04
∗
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
03)
(0.0
02)
(0.0
02)
Core
Dep
osi
tsR
ati
ot−
1−
.0004
−0.0
01
−0.0
01
−0.0
01
.0002
−0.0
01
−0.0
01
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
BIS
Fin
anci
alC
ycl
e t0.0
03
∗∗
∗0.0
04
∗∗
∗
(0.0
01)
(0.0
01)
BIS
Busi
nes
sC
ycl
e t.0
002
.0001
(0.0
00)
(0.0
00)
Obse
rvati
ons
31,7
33
28,4
64
31,8
57
21,9
81
9,8
76
17,0
71
14,7
86
R2
0.0
10.0
10.1
30.1
80.3
0.2
20.2
2A
dju
sted
R2
0.0
05
0.0
10.0
40.0
50.0
30.0
50.0
3
Countr
y-T
ime
Fix
edEffec
tsN
oN
oYes
Yes
Yes
Yes
Yes
Note
s:
This
table
report
sth
eeffects
of
changes
inU
.S.pru
denti
alpolicy,th
ein
tera
cti
on
of
changes
inU
.S.pru
denti
alpolicy
wit
hch
anges
indest
inati
on-c
ountr
yre
gula
tion,and
firm
chara
cte
rist
ics
on
log
changes
into
tallo
ans
by
dest
inati
on
countr
y.T
he
data
are
quart
erl
yfr
om
2000:Q
1to
2013:Q
3fo
ra
panelofbank
hold
ing
com
panie
s.For
more
deta
ils
on
the
vari
able
s,se
eta
ble
7in
the
appendix
.Each
colu
mn
giv
es
the
resu
ltfo
rth
esu
bse
tofbanks
specifie
din
the
colu
mn
hea
der.
CC
AR
banks
are
BH
Cs
inclu
ded
inth
eyearl
yst
ress
-test
exerc
ise
conducte
dby
the
Federa
lR
ese
rve.A
dvanced
Appro
ach
banks
are
CC
AR
BH
Cs
wit
hto
talass
ets
above
$250
billion
and
fore
ign
exposu
res
larg
er
than
$10
billion.Specific
ati
ons
inall
colu
mns
inclu
de
bank
fixed
effects
,w
ith
the
firs
ttw
ocolu
mns
inclu
din
gcountr
yfixed
effects
.C
ountr
y-t
ime
fixed
effects
are
use
das
indic
ate
din
the
lower
part
ofth
eta
ble
.Sta
ndard
err
ors
are
clu
stere
dby
bank.***,**,and
*in
dic
ate
signific
ance
at
the
1perc
ent,
5perc
ent,
and
10
perc
ent
level,
resp
ecti
vely
.
468 International Journal of Central Banking March 2017
results indicate that this trend may help them withstand the tougherregulations.
These results are consistent with previous findings in the lit-erature suggesting a reduction in cross-border activities caused bystricter prudential policies (e.g., Aiyar et al. 2014). This is espe-cially the case for the largest global banks subject to higher capitalrequirements that apply to the consolidated entity.
4. Concluding Remarks
The 2007–08 financial crisis has led many countries around the worldto review their use of microprudential and macroprudential policyinstruments. In a financially integrated world in which banks areglobal and run large cross-border operations, two questions natu-rally arise. First, have prudential policies taken by national regula-tors affected risk taking and credit growth beyond national borders?Second, can domestic prudential policies be effective in containingrapid domestic credit growth and addressing excessive risk taking?The U.S. experience is useful since the country is home to a numberof globally active banks, many of which are systemically important,and simultaneously hosts many foreign banks engaged in lending inthe United States through both subsidiaries and branches. We focusprimarily on the response of credit growth through these bankingentities.
We find clear evidence that lending in the United States isaffected by foreign policy changes. A tightening of foreign prudentialinstruments leads to an increase in U.S. lending by both domesti-cally owned global banks with significant foreign operations and bythe U.S. affiliates of foreign banks. Specifically, lending growth riseswith tighter foreign capital requirements, limits on LTV ratios, andlocal-currency reserve requirements enacted in foreign economies.The capacity of foreign and U.S. global banks to lend appears toshift, at least in part, from the foreign countries, where it is beingconstrained, to the United States.
We also find that the largest U.S. global banks, those that aredeemed systemic and thus have been required to finance a largerproportion of their balance sheets with capital, appear to cut creditabroad relatively more than the smaller banks in response to tightercapital requirements in the United States. Although the intent of
Vol. 13 No. S1 Lessons from the United States 469
these capital requirements was not to reduce the supply of credit,the short-term effect points to lower foreign claims growth as a resultof the stricter requirements. In contrast, we find that the use of pru-dential instruments by foreign authorities does not have a significantimpact on the activities of U.S. banks in those foreign countries.
While the international spillovers from past prudential policytightening were moderate, our results highlight the challenges thatpolicymakers face today. Effective control of domestic credit can becomplicated by the prudential policies implemented in foreign juris-dictions. At the same time, calibration of domestic policies will needto take into account the spillovers of prudential policy changes inforeign countries and their cross-border effects. Despite limited realconsequences for the U.S. economy over the past decade, prudentialinstruments applied abroad have the potential to more significantlyinfluence loan growth in the future through a variety of bankingchannels.
470 International Journal of Central Banking March 2017A
ppen
dix
Tab
le7.
Con
stru
cton
ofB
alan
ceShee
tV
aria
ble
s
U.S
.B
ranch
es
of
Report
Form
Outw
ard
/In
ward
—U
.S.
U.S
Subsi
dia
ries
of
Fore
ign
Banks:
Vari
able
Nam
eD
esc
ripti
on
Glo
balB
anks:
Sourc
eFore
ign
Banks:
Sourc
eSourc
eN
ote
s
ΔY
Outw
ard
:lo
g(T
ota
lC
laim
s t)
–lo
g(T
ota
lC
laim
s t−
1)
Inw
ard
:lo
g(T
ota
lLoans t
)–
log(T
ota
lLoans t
−1)
FFIE
C009
FC
EX
C918,C
919,
C920,C
922,8593,
8577,8578,8579,
C915,C
916,C
917
FR
Y-9
C,FFIE
C031
BH
CK
and
RC
FD
2122
FFIE
C002
RC
FD
2122
Illiquid
Ass
ets
Rati
o{(
Loans
hel
dfo
rsa
le+
Loans
net
of
unea
rned
inco
me
and
allow
ance
sfo
rlo
an
and
lease
loss
es(A
.L.L
.)+
Hel
d-t
o-
matu
rity
MB
S,A
BS,
and
stru
cture
dfinanci
alpro
duct
s(a
mort
ized
cost
)+
Ava
ilable
-for-
sale
MB
S,A
BS,and
stru
cture
dfinanci
al
pro
duct
s(f
air
valu
e))/
Ass
ets}
*100
FR
Y9-C
,FFIE
C031
BH
CK
and
RC
FD
5369,B
529,B
838,
B841,B
842,B
845,
B846,B
849,B
850,
B853,B
854,B
857,
B858,B
861,G
300,
G303,G
304,G
307,
G308,G
311,G
312,
G315,G
316,G
319,
G320,G
323,G
324,
G327,G
328,G
331,
K142,K
145,K
146,
K149,K
150,K
153,
K154,K
157,1698,
1703,1709,1714,1718,
1733,1702,1707,
1713,1717,1732,1736
FR
Y9-C
,FFIE
C031
BH
CK
and
RC
FD
5369,B
529,B
838,
B841,B
842,B
845,
B846,B
849,B
850,
B853,B
854,B
857,
B858,B
861,G
300,
G303,G
304,G
307,
G308,G
311,G
312,
G315,G
316,G
319,
G320,G
323,G
324,
G327,G
328,G
331,
K142,K
145,K
146,
K149,K
150,K
153,
K154,K
157,1698,
1703,1709,1714,1718,
1733,1702,1707,
1713,1717,1732,1736
FFIE
C002
RC
FD
G483,
1754,1773,
2122,2170,
3195
Str
uct
ure
dfinanci
al
pro
duct
sav
ailable
on
the
FR
Y9-C
report
form
start
ing
2009:Q
2.
Log
Tota
lA
sset
sLog
(Tota
lass
ets
*(G
DP
Defl
ato
r 2012/
GD
PD
eflato
r))
FR
Y9-C
,FFIE
C031,
BEA
BH
CK
2170,R
CFD
2170
FR
Y9-C
,FFIE
C031,
BEA
BH
CK
2170,R
CFD
2170
FFIE
C002,
BEA
RC
FD
2170
Nom
inalass
ets
are
conver
ted
to2012
dollars
usi
ng
the
GD
Pim
plici
tpri
cedefl
ato
rse
ries
from
the
BEA
.
(con
tinu
ed)
Vol. 13 No. S1 Lessons from the United States 471Tab
le7.
(Con
tinued
)
U.S
.B
ranch
es
of
Report
Form
Outw
ard
/In
ward
—U
.S.
U.S
Subsi
dia
ries
of
Fore
ign
Banks:
Vari
able
Nam
eD
esc
ripti
on
Glo
balB
anks:
Sourc
eFore
ign
Banks:
Sourc
eSourc
eN
ote
s
Core
Dep
osi
tsR
ati
o{(
Tota
ltr
ansa
ctio
nacc
ounts
+Sav
ings
dep
osi
ts(M
MD
As,
etc.
)+
Tota
lti
me
dep
osi
tacc
ounts
wit
hbala
nce
sle
ssth
an
$100,0
00)/
Lia
-bilit
ies}
*100
FR
Y9-C
,FFIE
C031
BH
CB
2210,2389,
3187,6648,B
HO
D3187,3189,2389,
6648,R
CO
N2215,
2385,2604,B
HC
Kand
RC
FD
2948
FFIE
C031
RC
ON
2215,2385,
2604
FFIE
C002
RC
ON
1653,
2385,2604,
RC
FD
2950
Tie
r1
Rati
o(T
ier
1ri
sk-b
ase
dca
pit
al/
Ris
k-
wei
ghte
dass
ets
(net
ofallow
ance
sand
oth
erded
uct
ions)
)*
100
FR
Y9-C
,FFIE
C031
BH
CA
and
RC
FD
8274
,A
223
FR
Y9-C
,FFIE
C031
BH
CA
and
RC
FD
8274,A
223
FR
Y-7
QFB
OQ
8274,
A223
Lin
ear
inte
rpola
tion
isuse
dfo
rFR
Y-7
Qdata
.
Net
Due
To
((N
etdue
toow
nfo
reig
noffi
ces,
edge
and
agre
emen
tsu
bsi
dia
ries
,and
IBFs
–N
etdue
from
own
fore
ign
offi
ces,
edge
and
agre
emen
tsu
bsi
dia
ries
,and
IBFs)
/A
sset
s)*
100
FFIE
C009,FR
Y-9
C,
FFIE
C031
FC
EX
8595,B
HC
Kand
RC
FD
2170
FFIE
C031
RC
ON
2941,2163,
RC
FD
2170
FFIE
C002
RC
FD
2170,
2154,2944
Fro
mth
eper
spec
tive
ofth
eco
mm
erci
al
bank
hea
doffi
cevis
-a-v
isow
nfo
reig
noffi
ces,
edge
and
agre
emen
tsu
bsi
dia
ries
,and
IBFs.
Inte
rnati
onalA
ctiv
ity
((Fore
ign
Ass
ets
+D
eposi
tsin
fore
ign
offi
ces,
edge
and
agre
emen
tsu
bsi
dia
ries
,and
IBFs)
/A
sset
s)*
100
FFIE
C009,FR
Y-9
C,
FFIE
C031
FC
EX
C918,C
919,
C920,C
922,8577,
8578,8579,B
HD
M6631,6636,R
CFN
2200,B
HC
Kand
RC
FD
2170
FR
Y-9
C,FFIE
C031
BH
DM
and
RC
FN
6631,6636
Note
s:Bank-leveldata
collecte
don
the
FFIE
C009
are
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472 International Journal of Central Banking March 2017
Table 8. Additional Results on the Effectof Capital Requirements: Split between Domestic and
Foreign Lending
Capital Requirements
All Loans Domestic Foreign(1) (2) (3)
Pt 0.036∗∗ 0.030 0.202∗
(0.018) (0.020 (0.115)Log Total Assetst−1 −0.066∗∗∗ −0.077∗∗∗ −0.092
(0.015) (0.019) (0.060)Tier 1 Ratiot−1 0.002∗∗ 0.001 −0.003
(0.001) (0.002) (0.005)Illiquid Assets Ratiot−1 −0.000 −0.000 0.001
(0.000) (0.001) (0.001)Net Due Tot−1 −0.003 0.012 −0.008∗∗
(0.003) (0.017) (0.004)Core Deposits Ratiot−1 0.001 −0.000 0.000
(0.000) (0.001) (0.003)BIS Financial Cyclet −0.001∗∗ −0.001∗ 0.001
(0.000) (0.001) (0.003)BIS Business Cyclet 0.000 0.002 −0.003
(0.003) (0.009) (0.018)International Activityt−1 0.001∗ 0.000 −0.001
(0.001) (0.001) (0.002)
Observations 1,873 1,871 1,778R2 0.196 0.126 0.101Adjusted R2 0.141 0.067 0.037No. of Banks 59 59 58Proportion of Pt Non-zero 0.145 0.145 0.151
Notes: This table reports the effects of changes in capital requirements, splittingtotal loans into loans to U.S. (column 2) and foreign (column 3) residents. The sampleperiod is 2000:Q1 to 2013:Q3. All specifications include time and bank fixed effects.Standard errors are robust for global banks. ***, **, and * indicate significance atthe 1 percent, 5 percent, and 10 percent level, respectively.
Vol. 13 No. S1 Lessons from the United States 473
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