(FX) lending

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17th Dubrovnik Economic Conference
June 28-July 2, 2011, Dubrovnik, Croatia
Organized by the Croatian National Bank
Credit Euroization in CESEE:
The „Foreign Funds“ Channel at Work
Peter R. Haiss and Wolfgang Rainer
Vienna University of Economics and Business
Department of Global Business and Trade
The opinions expressed are the authors‘ personal views
AGENDA






Stylized facts on foreign currency (FX) lending
Motivation
Literature review
Model, method and data
Results
Conclusions & policy recommendations
Stylized facts on foreign
currency (FX) lending
• Rapid credit growth & rising FX-lending are specific features
of the CESEE convergence path
Supported economic growth & transition at cost ofhigher
volatility
FX lending not uniform (share, sectors, FX, timing, regulation)
role of FX asymmetric for loans & deposits
SEITE 3
Total loans (to non-banks)
as % of GDP
Source: Raiffeisen RESEARCH, 2010
FX lending share (2010)
in private sector in CESEE
Percentage of total loans
Source: Hake, Cuaresma and Fidrmuc (2011)
FX loans as a share of total
loans, 2009
Source: Author‘s own calculations, data from local central banks;
Note: Due to data restraints, the figures do not include FX indexed loans for Croatia and Macedonia.
SEITE 6
Currency denomination of FX-loans
in selected CESEE countries, 2009
Source: Author‘s own calculations, data from local central banks;
Note: Share of FX-loans in total private sector loans according to currency denomination; Macedonia: banking
sector assets in foreign currency; For Hungary and Serbia other currencies consist mostly of CHF.
Dynamic development
100%
Albania
100%
80%
80%
60%
60%
40%
40%
20%
20%
0%
0%
non-financial corporations
100%
Hungary
non-financial corporations
household
Latvia
100%
80%
household
Slovenia
80%
60%
60%
40%
40%
20%
20%
0%
0%
non-financial corporations
household
SEITE Author‘s
8
Source:
own calculations, data from local central banks
non-financial corporations
household
High level
100%
Estonia
100%
80%
80%
60%
60%
40%
40%
20%
20%
0%
0%
non-financial corporations
100%
household
Romania
non-financial corporations
100%
80%
80%
60%
60%
40%
40%
20%
20%
0%
0%
non-financial corporations
Lithuania
household
SEITE Author‘s
9
Source:
own calculations, data from local central banks
household
Moldova
non-financial corporations
household
Low level
100%
Czech Republic
80%
60%
40%
20%
0%
non-financial corporations
100%
household
Russia
100%
80%
Poland
80%
60%
60%
40%
40%
20%
20%
0%
0%
non-financial corporations
household
SEITE Author‘s
10
MKO-PROJEKTSEMINAR
PLANUNG
SOSEcentral
2010 banks
Source:
own calculations, data
from local
non-financial corporations
household
Motivation for the paper
• Rise of FX lending as regional feature
Materialization of risks
Reasons? Findings controversial, funding underrepresented
SEITE 11
Motivation
 Rise of FX lending across most of the region
 depreciation  Increased interest & redemption payments for
unhegded borrowers (though leverage rather low)
 Household loans mainly for mortgage/real estate
 double exposure (though uneven across region)
 Materialization of risks
 Significant depreciation of CESEE currencies against EUR and
CHF 2007-2009 in HU, PL, RO, AL, SR, UA
 Banks had to increase provisions for impairment losses by
~100%-200% (2008/2009)
 FX loans still attractive, >60% of FX borrowers say “did well”
(Beckmann, Scheiber and Stix, 2011)
 Findings controversial, funding underrepresented
Literature review
• Qualitative surveys vs econometric investigations
Foreign banks vs foreign funds channel
SEITE 13
Surveys
 ECB (2006)






Interest rate advantage
Fixed exchange rate regime
Expectation to join the Euro Area soon
Lack of risk awareness
Herd behaviour
Appreciation trend of the local currency
 OeNB (Dvorsky et al 2008, Fidrmuc et al 2011)




FX loan is cheaper
My bank advised me to take out an FX loan
More stable interest rate in FX
Plan for more FX loans
Econometric models I
 Interest rate differential: Rosenberg and Tirpák 2008 (+), Basso et al
2011 (+), Brown et al 2011 (~/+), Zettelmeyer et al 2010 (+), Epstein &
Tzanninis 2005 (+), Arteta 2005 (~), Bednarik 2007 (-)
 Foreign currency deposits: EBRD 2010 (+), Luca and Petrova 2008
(+), Arteta 2005 (+), Barajas 2003 (+), Calvo 2001 (+)
 Loan to deposit ratio: Rosenberg and Tirpák 2008 (+)
 Openness of the economy: Luca and Petrova 2008 (+), Rosenberg and
Tirpák 2008 (+), Basso et al 2007 (+ for corporates), Keloharjy and
Niskanen 2001 (+)
 Inflation (expectations): Zettelmeyer et al 2020 (+), Honig 2009 (high
past inflation +, time series variable -), Brown et al 2008 (~), Arteta
2005 (max. hist. inflation +)
SEITE 15
Econometric models II
 Exchange rate regime: Arteta 2005 (~), Honig 2009 (~)
 Exchange rate: Brzoza-Brzezina 2007 (appreciation +), Luca and
Petrova 2007 (~depreciation -), Epstein and Tzaninis 2005 (~)
 Economic development: Honig 2009 (~), Rosenberg and Tirpák
2008 (~), Brzoza-Brzezina 2007 (GDP +)
 Government quality: Honig 2009 (-)
 Foreign banks: Steiner 2011 (~/+), Brown and De Haas 2010
(~/+), Backer and Gulde 2010 (+), Haiss et al 2009 (~), Brown et
al 2008 (+/~), Rosenberg and Tirpak 2008 (~)
SEITE 16
Do foreign banks drive FX
lending?
Note: Share of foreign bank assets in total banking assets (in %)
Source: Author, data from EBRD, RZB Group (2009)
SEITE 17
Foreign bank channel
 Rationale
 European Commission (2004): Cross-ownership in the banking sector
contributes to the high level of FX (Euro) loans in the new Member
States
 Calvo (2002): Foreign banks have better access to FX (refinancing)
via parent bank
 Empirical evidence
 Asset share of foreign banks (market share) correlated with credit
euroization?
 Backer and Gulde, 2010: large part of FX loans funded by foreign
banks
 Haiss et al (2009), Rosenberg and Tirpák (2008): not significant;
Steiner (2011, households): not significant
 Brown et al (2011): scarce evidence of positive correlation
using (SME) firm-level data (EME, not CESEE); Brown and De Haas
(2010): corporate borrowers (~/+), households (~)
SEITE 18
Foreign funds channel
Foreign
borrowings (in
FX)
FX deposits from
clients
Increased FX
share of bank
liabilities
Tight restrictions
on open foreign
exchange
positions
Lending in DC and
hedging of
exposure
Active promotion
of FX loans
Foreign funds channel = Degree to which FX loans are financed from abroad
(and not with FX deposits from residents)
Proxied by FX loan to FX deposit ratio FXLFXDR
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Model, Method and Data
Results and Conclusions
SEITE 20
Model
 Model I – private non-financial sector
 Model II – non-financial corporations
 Model III - households
SEITE 21
Method & Data
 Method
 Panel data estimations
 Heteroscedasticity  robust standard errors
 Strong autocorrelation  First difference
estimations
 Data
 13 countries (AL, BG, HR, CZ, EE, HU, LV, LT, MD, PL,
RO, RU, SK)
 1999-2007
SEITE 22
Results
Dependent variable = FX-Loans as % of
total laons to…
R^2
Foreign currency deposits
Model I
Model II
(corporations)
Model III
(households)
Private nonfinancial sector
Non-financial
corportions
households
0,75
0,64
0,50
0,95***
(Foreign currency deposits)^2
2,07***
0,94***
-1,49***
FX-loan to FX-deposit ratio
0,26***
0,29***
0,23***
(FX-loan to FX-Deposit Ratio)^2
-0,33***
-0,04***
-0,02***
DC-loan to DC-deposit ratio
-0,47***
-0,48***
-0,28***
(DC-loan to DC-deposit ratio)^2
0,07***
-0,07***
0,05***
Trade with Eurozone countries (as % of GDP)
0,40***
0,24**
Manufacturing industry as % of GDP
0,55**
Loan to deposit ratio
-1,52**
Inflation
0,002**
Interest rate differential to Euro zone
-0,01***
EU
membership
dummy
SEITE
23
0,03***
Conclusions
 No direct relationship between the asset share of
foreign banks and FX lending
 Foreign funds channel appears to be a main source
of supply with foreign capital and a driver of credit
euroization
 Credit euroization of corporate lending seems to be,
at least partly, driven by the desire of firms to
hedge foreign currency inflows arising from export
activities
 Banks appear to fund FX loans to households to a
greater extent with FX deposits, while FX loans to
corporations appear to be financed to a higher
degree from abroad (i.e. direct cross-border
lending)
SEITE 24
Policy Recommendations
 Policy makers should educate the public about the
risks of FX lending
 In some situations, central banks might decide to
take restrictive measures to curb FX loan growth
 Policy makers would be advised to increase people’s
trust in the domestic economy, currency and capital
markets in order to decrease loan and deposit
euroization
 Neither CESEE nor CIS are homogenous regions –
the countries should be treated separately
SEITE 25
Dr.Habil Peter R. Haiss
WU Vienna University of Economics and Business
Department of Global Business and Trade
Althanstrassd 51
A-1090 Wien
Austria / European Union
Peter.haiss@wu.ac.at
http://ssrn.com/author=115752
Wolfgang Rainer
WU Vienna University of Economics and Business
EuropeInstitute
Althanstrasse 39-45
A-1090 Wien
Austria / European Union
Wolfgang-rainer@gmx.at
SEITE 26
Details & Back-up
SEITE 27
FX-Lending Relevance (2010)
Source: UniCredit (2011), CEE Banking Aoutlook Jan 2011, 20
FX usage
lending & deposits asymmetric
Source: Backer and Gulde (2010), IMF WP 10/130
FX loan funding
foreign banks vs. domestic deposits
Source: Backer and Gulde (2010), IMF WP 10/130
FX loans still attractive
Source: OeNB Euro Survey as reported in Beckmann, Scheiber & Stix (2011)
Market share of foreign banks
Market concentration
SEITE 33
MKO-PROJEKTSEMINAR PLANUNG SOSE 2010
Total banking assets
SEITE 34
MKO-PROJEKTSEMINAR PLANUNG SOSE 2010
Total loans
SEITE 35
MKO-PROJEKTSEMINAR PLANUNG SOSE 2010
Nonperforming loans
SEITE 36
MKO-PROJEKTSEMINAR PLANUNG SOSE 2010
Loan to Deposit Ratio
SEITE 37
MKO-PROJEKTSEMINAR PLANUNG SOSE 2010
Loan to deposit ratio for
households
SEITE 38
MKO-PROJEKTSEMINAR PLANUNG SOSE 2010
Results Model I
• Linear regression
•
•
•
•
Number of obs =
F( 7,
97) =
Prob > F
=
R-squared
=
Root MSE
=
104
45.63
0.0000
0.7508
.03114
• -----------------------------------------------------------------------------•
|
Robust
•
D.fxl |
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
• -------------+---------------------------------------------------------------•
fxd |
•
D1. |
.9503634
.0955588
9.95
0.000
.7607056
1.140021
•
fxlfxdr |
•
D1. |
.2585564
.025644
10.08
0.000
.2076601
.3094527
•
fxlfxdr2 |
•
D1. | -.0330813
.0052314
-6.32
0.000
-.0434642
-.0226984
•
dcldcdr |
•
D1. | -.4747195
.0598861
-7.93
0.000
-.5935768
-.3558621
•
dcldcdr2 |
•
D1. |
.0704588
.0150505
4.68
0.000
.0405878
.1003298
•
trade_eur |
•
D1. |
.4045047
.0978392
4.13
0.000
.2103211
.5986883
•
indu |
•
D1. |
.5493155
.2698742
2.04
0.045
.0136899
1.084941
Note: FLX = FX loans as % of total loans to the private sector, FXD = FX deposits as % of total deposits, FXLFXDR = FX
loan to FX deposit ratio, DCLDCDR = DC loan to DC deposit ratio, TRADE_EUR = Trade with Euro zone countries (as %
of GDP), INDU = Manufacturing industry as % of GDP
Source: Author
SEITE 39
MKO-PROJEKTSEMINAR PLANUNG SOSE 2010
Results Model II
• Linear regression
•
•
•
•
Number of obs =
F( 6,
98) =
Prob > F
=
R-squared
=
Root MSE
=
104
30.27
0.0000
0.6398
.03783
• -----------------------------------------------------------------------------•
|
Robust
•
D.fxl_c |
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
• -------------+---------------------------------------------------------------•
fxd2 |
•
D1. |
.9402007
.1388543
6.77
0.000
.6646488
1.215753
•
fxlfxdr |
•
D1. |
.2857607
.0366806
7.79
0.000
.2129693
.3585522
•
fxlfxdr2 |
•
D1. |
-.040741
.006897
-5.91
0.000
-.0544279
-.0270541
•
dcldcdr |
•
D1. | -.4840679
.0786829
-6.15
0.000
-.6402115
-.3279243
•
dcldcdr2 |
•
D1. |
.0720704
.0192152
3.75
0.000
.0339384
.1102023
•
trade_eur |
•
D1. |
.2399445
.0921379
2.60
0.011
.0570999
.422789
• -----------------------------------------------------------------------------Note: FLX _C= FX loans as % of total loans to corporations , FXD = FX deposits as % of total deposits, FXLFXDR = FX
loan to FX deposit ratio, DCLDCDR = DC loan to DC deposit ratio, TRADE_EUR = Trade with Euro zone countries (as %
of GDP),
Source: Author
SEITE 40
MKO-PROJEKTSEMINAR PLANUNG SOSE 2010
Results Moel III
• Linear regression
Number of obs =
104
•
F( 10,
94) =
12.64
•
Prob > F
= 0.0000
•
R-squared
= 0.4980
•
Root MSE
= .05124
• -----------------------------------------------------------------------------•
|
Robust
•
D.fxl_h |
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
• -------------+---------------------------------------------------------------•
fxd |
•
D1. |
2.072722
.5368726
3.86
0.000
1.006749
3.138696
•
fxd2 |
•
D1. | -1.486093
.5629664
-2.64
0.010
-2.603876
-.3683099
•
ldr |
•
D1. | -.1519483
.0620158
-2.45
0.016
-.2750821
-.0288145
•
fxlfxdr |
•
D1. |
.2272738
.0494145
4.60
0.000
.1291602
.3253874
•
fxlfxdr2 |
•
D1. |
-.021062
.0072405
-2.91
0.005
-.0354382
-.0066859
•
dcldcdr |
•
D1. | -.2837331
.0701481
-4.04
0.000
-.4230138
-.1444525
•
dcldcdr2 |
•
D1. |
.0486925
.0119713
4.07
0.000
.0249232
.0724618
•
infl |
•
D1. |
.0021769
.0007027
3.10
0.003
.0007817
.0035722
•
ird_eur |
•
D1. | -.0052033
.0018254
-2.85
0.005
-.0088276
-.001579
•
eu |
.0296685
.0092484
3.21
0.002
.0113056
.0480315
Note: FLX _H= FX loans as % of total loans to households, FXD = FX deposits as % of total deposits, FXLFXDR = FX
loan to FX deposit ratio, DCLDCDR = DC loan to DC deposit ratio, INFL = Inflation, IRD_EUR = Interest differential to Euro
zone lending
rate, EU = EU membership
SEITE 41
MKO-PROJEKTSEMINAR
PLANUNG dummy
SOSE 2010
Source: Author
Descriptive statistics I
Variable
FXL
FXL_C
FXL_H
FXD
FXD2
LRD
FXLFXDR
FXLFXDR2
DCLDCDR
DCLDCDR2
LNRB
ASFB
AS5LB
ASAB
INFL
SEITE 42
Description
Foreign currency loans (share of total loans)
Foreign currency loans to non-financial
corporations (share of total loans to
corporations)
Foreign currency loans to households (share
of total loans to households)
Foreign currency deposits
= (FXD)^2
Loan-to-deposit ratio
FX loan to FX deposit ratio
= (FXLFXDR)^2
Dc-loan to dc-deposit ratio
= (DCLDCD)^2
Loans of non-resident banks
Asset share of foreign banks
Asset share of 5 largest banks
Asset share of Austrian banks
Inflation
Obs
117
117
Mean
0,47047
0,51718
Std. Dev
0,22289
0,21543
Min
0,08804
0,14681
Max
0,86486
0,88513
117
0,32168
0,28839
0,00000
0,89822
117
117
117
117
117
117
117
117
117
117
40
117
0,34084
0,14295
0,88282
1,28939
2,40162
0,86968
1,17846
0,12985
0,66247
0,66916
0,28849
5,74696
0,16433
0,12813
0,40352
0,86341
3,47115
0,65250
2,09001
0,10342
0,27082
0,14686
0,17975
11,04567
0,09808
0,00962
0,09423
0,20264
.041063
0,02664
.000710
0,01078
0,07419
0,41241
0,00000
-3,1670
0,76461
0,58463
2,56416
4,28685
18,3770
3,77213
14,2289
0,55294
0,99375
0,99446
0,61345
84,3900
Descriptive statistics
Variable
ER_EUR
RER
IRD_EUR
RDI
IRV
NIS
REMIT
GDP_PC
EXP_GDP
EXIM_GDP
TRADE_EUR
FDI
INDU
FLOAT_PEG
ERMII
EU
EBRD
SEITE 43
HLR
Description
Exchange rate LCU / EUR
Real effective exchange rate
Interest differential local to euro area lending
rate
Real domestic interest rate
Interest rate volatility
Net interest spread
Remittances / GDP
GDP per capita
Exports / GDP
(Exports + Imports) / GDP
Trade with euro area countries and countries
with a currency peg to the euro
Foreign direct investment inflow as a share
of GDP
Manufacturing industry as a share of GDP
Dummy variable for floating (0) or pegged
(1) exchange rate regime
Dummy variable for participation in the
ERM II
Dummy EU member
EBRD index of banking sector development
Household FX loan restrictions
Obs
117
117
117
Mean
-0,0143
118,349
7,95159
Std. Dev
0,10048
22,51345
9,71843
Min
-0,5859
57,9893
-0,5904
Max
0,15456
174,511
60,6401
117
117
117
117
117
117
117
117
0,05475
17,1399
6,73253
0,04253
10874
0,37436
0,87848
0,30729
0,05410
20,44795
4,24437
0,07258
4935
0,16487
0,31257
0,12587
-0,2476
0,73940
1,86700
0,00015
1404
0,06921
0,35215
0,09911
0,22056
120,243
26,0340
0,34670
24340
0,77003
1,54960
0,67192
117
0,06015
0,04340
0,00897
0,29622
117
117
0,30676
0,41880
0,05683
0,49549
0,16776
0,00000
0,41134
1,00000
117
0,11966
0,32596
0,00000
1,00000
117
117
117
0,25641
3,23932
0,92308
0,43853
0,63054
0,26762
0,00000
1,70000
0,00000
1,00000
4,00000
1,00000
CESEE exchange rate
developments against EUR and
CHF 06/2008 – 04/2009
Source: Author’s own calculation, data from EIU Country Data
SEITE 44
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