International Credit Supply Shocks A. Cesa-Bianchi1 1
A. Ferrero2
A. Rebucci3
Bank of England and Center for Macroeconomics 2 Oxford University Johns Hopkins Carey Business School and NBER
3
18th Jacques Polak Annual Research Conference IMF - November 2-3, 2017
*The views expressed in this paper do not necessarily reflect the position of the Bank of England.
Introduction
1
Fact 1: Capital inflows are typically associated with expansions and asset price surges Cross-border Credit
House Price
-2
-1
0
+1
+2
+3
0 -5 -10 -3
-2
+1
+2
+3
-3
-2
-2
-1
0
+1
+2
+3
Current Account / GDP Pctg. Point
0
0
0 -2 -4
-5 -2
-1
0
+1
+2
+3
-3
-2
GDP
-1
0
+1
+2
+3
6 4 2 0 -1
0
+1
+2
+3
Pctg. Point
4 2 0 -3
-2
-1
0
+1
-2
-1
0
+1
+2
+3
Real Short-term Int. Rate
6
-2
-3
Consumption Percent
Percent
0
5
2
-3
-1
10 0 -10 -20 -30
Real Exch. Rate (USD) Percent
Percent
Real Eff. Exch. Rate
-3
Percent
Percent
Percent
0 -10 -3
Equity Price
5
10
+2
+3
5
0 -3
-2
-1
0
+1
+2
+3
All Economies
NOTE. Each panel plots the median across all boom-bust episodes, using a 6-year window that goes from three year before the peak to three years after the peak. In each panel, time 0 marks the peak of the boom-bust cycle in cross-border bank claim growth (i.e., the last period of a boom in which cross-border bank claims displays a positive growth rate), which is also depicted with a vertical line. All variables are expressed in percentage changes, with the exception of the short-term interest rate and the current account over GDP which are expressed in percentage points.
Introduction
2
Fact 2: Some countries seem more sensitive than others to the volatility of capital inflows Cross-border Credit
House Price
-2
-1
0
+1
+2
+3
0 -5 -10 -3
-2
+1
+2
+3
-3
-2
-2
-1
0
+1
+2
+3
Current Account / GDP Pctg. Point
0
0
0 -2 -4
-5 -2
-1
0
+1
+2
+3
-3
-2
GDP
-1
0
+1
+2
+3
6 4 2 0 -1
0
+1
+2
+3
All Economies
Pctg. Point
4 2 0 -3
-2
-1
0
+1
Advanced Economies
-2
-1
0
+1
+2
+3
Real Short-term Int. Rate
6
-2
-3
Consumption Percent
Percent
0
5
2
-3
-1
10 0 -10 -20 -30
Real Exch. Rate (USD) Percent
Percent
Real Eff. Exch. Rate
-3
Percent
Percent
Percent
0 -10 -3
Equity Price
5
10
+2
+3
5
0 -3
-2
-1
0
+1
+2
+3
Emerging Economies
NOTE. Each panel plots the median across all boom-bust episodes, using a 6-year window that goes from three year before the peak to three years after the peak. In each panel, time 0 marks the peak of the boom-bust cycle in cross-border bank claim growth (i.e., the last period of a boom in which cross-border bank claims displays a positive growth rate), which is also depicted with a vertical line. All variables are expressed in percentage changes, with the exception of the short-term interest rate and the current account over GDP which are expressed in percentage points.
Introduction
3
100
80
60
40
20
0
Introduction
100
80
60
ARG AUT CHN DNK FIN DEU GRC ITA JPN LUX MYS MLT PHL SGP CHE BGR NZL NOR BRA EST IDN PRT CAN ISR SWE AUS BEL CZE FRA ISL IRL LVA LTU MEX POL RUS ZAF ESP THA UKR USA
120 IND GBR
NLD
50
CHE COL HKG DEU JPN AUT FRA
60
COL HKG HUN KOR SVN URY
0 SGP AUS GBR ISL USA
90
80
70
ZAF NZL FIN DNK MEX ARG AUS CHL NLD PER GBR ISR IDN IND BRA SWE THA LUX IRL BEL PRT ITA GRC SVN ESP CZE ISL PHL MLT POL SRB RUS URY LVA EST NOR TWN BGR CHN SVK SGP HRV HUN LTU
NZL DNK CHE NLD
80
HRV
20
CHE DNK NZL SWE AUS CAN GBR NOR MLT CZE ZAF TWN SGP HKG POL CHN MYS KOR THA HUN ISR MEX UKR BRA IND IDN RUS SVK PHL ISL SRB LVA HRV CHL COL SVN EST PER ARG LTU MAR BGR URY
40
RUS SVN ARG BGR IDN PER UKR BRA POL CZE IND SVK LTU PHL MAR HRV HUN MEX CHN COL EST LVA ITA CHL GRC THA KOR ISR ZAF FRA TWN AUT BEL MLT MYS LUX FIN JPN ESP HKG CAN IRL DEU PRT NOR SWE
60
USA DEU ITA AUT ESP BEL FRA PRT FIN NLD GRC LUX IRL JPN
Fact 3: Countries differ in important dimensions, and the EMs vs. AEs divide may not be whole story Mortgage Debt / GDP 100
Home Ownership
Share of foreign currency debt 40
Max Loan to Value (LTV)
40
NOTE. Each bar corresponds to a country. The lighter (yellow) bars are classified as emerging markets and the darker (blue) bars as advanced economies. See the data appendix for variable definitions and data sources.
4
This paper
I
Traditionally, push-pull factor analysis of capital flows and their impact
I
This paper focuses on one particular push shock ⇒ A change in the leverage constraint of global banks that shifts the international credit supply
Introduction
5
This paper
I
Traditionally, push-pull factor analysis of capital flows and their impact
I
This paper focuses on one particular push shock ⇒ A change in the leverage constraint of global banks that shifts the international credit supply
I
Questions (1) What are the mechanisms through which capital inflows lead to macroeconomic booms? (2) What are the characteristics that account for the differences in sensitivity across countries?
Introduction
5
This paper: What we do & What we find I
What we do • Theory: Open economy model with international financial intermediation • Empirics: Heterogeneous panel VAR model for more than 50 countries
Introduction
6
This paper: What we do & What we find I
What we do • Theory: Open economy model with international financial intermediation • Empirics: Heterogeneous panel VAR model for more than 50 countries
I
Three main takeaways 1. Leverage shock is expansionary both in the model and in the data 2. In the average economy, the shock has sizable impact and explains a significant fraction of macroeconomic and asset price variance 3. In the cross-section, a stronger transmission is associated with higher max LTV ratios and shares of FX liabilities
Introduction
6
This paper: What we do & What we find I
What we do • Theory: Open economy model with international financial intermediation • Empirics: Heterogeneous panel VAR model for more than 50 countries
I
Three main takeaways 1. Leverage shock is expansionary both in the model and in the data 2. In the average economy, the shock has sizable impact and explains a significant fraction of macroeconomic and asset price variance 3. In the cross-section, a stronger transmission is associated with higher max LTV ratios and shares of FX liabilities
I
Important implication LTV ratios and shares of FX liabilities, which can be influenced by policy, are linked to final outcomes
Introduction
6
Selected related literature
I
Global financial cycle Rey (2013, 2016); Passari and Rey (2015); Bruno and Shin (2015a,b); Miranda-Agrippino and Rey (2015); Dedola, Rivolta, and Stracca (2015); Forbes, Reinhart, and Wieladek (2016); Cerutti, Claessens, Rose (2017); Aoki, Benigno, and Kiyotaki (2016); Boz and Mendoza (2014); Cetorelli and Goldberg (2011, 2012)
I
House prices and capital flows in the United States Aizenman and Jinjarak (2009); Gete (2009); Bernanke (2010); Justiniano, Primiceri and Tambalotti (2014); Favilukis, Ludvigson and Van Nieuwerburgh (2017); Ferrero (2015)
I
Sensitivity of consumption to asset price and credit shocks Jappelli and Pagano (1989); Almeida, Campello, and Liu (2006); Calza, Monacelli, and Stracca (2014); Berger, Guerrieri, Lorenzoni, and Vavra (2016); Mian, Sufi, and Verner (2016)
Introduction
7
The Model
Model
8
Overview of the model I
Model
Two-period, two-country, two-good, endowment economy with no uncertainty
9
Overview of the model I
Two-period, two-country, two-good, endowment economy with no uncertainty
I
Impatient Home household (i ∈ [0, n]) • Borrows in domestic currency (b) and foreign currency (f ) to consume and
purchase housing services (h1 )
• Subject to collateral constraint: b + s1 f ≤ θ qh1
Model
9
Overview of the model I
Two-period, two-country, two-good, endowment economy with no uncertainty
I
Impatient Home household (i ∈ [0, n]) • Borrows in domestic currency (b) and foreign currency (f ) to consume and
purchase housing services (h1 )
• Subject to collateral constraint: b + s1 f ≤ θ qh1 I
Patient Foreign household (i ∈ (n, 1]) • Saves via deposits (d) and equity (e) in a global bank • Subject to adjustment cost on equity position
Model
9
Overview of the model I
Two-period, two-country, two-good, endowment economy with no uncertainty
I
Impatient Home household (i ∈ [0, n]) • Borrows in domestic currency (b) and foreign currency (f ) to consume and
purchase housing services (h1 )
• Subject to collateral constraint: b + s1 f ≤ θ qh1 I
Patient Foreign household (i ∈ (n, 1]) • Saves via deposits (d) and equity (e) in a global bank • Subject to adjustment cost on equity position
I
Global bank • Channels funds from lenders to borrowers • Subject to capital requirement: e ≥ χ (b/s1 + f )
Model
9
Overview of the model I
Two-period, two-country, two-good, endowment economy with no uncertainty
I
Impatient Home household (i ∈ [0, n]) • Borrows in domestic currency (b) and foreign currency (f ) to consume and
purchase housing services (h1 )
• Subject to collateral constraint: b + s1 f ≤ θ qh1 I
Patient Foreign household (i ∈ (n, 1]) • Saves via deposits (d) and equity (e) in a global bank • Subject to adjustment cost on equity position
I
Global bank • Channels funds from lenders to borrowers • Subject to capital requirement: e ≥ χ (b/s1 + f )
Capital ratio Model
9
Equilibrium: Graphical analysis I
Model
Equilibrium can be represented in the ‘quantity of credit – interest rate’ space
10
Equilibrium: Graphical analysis I
Equilibrium can be represented in the ‘quantity of credit – interest rate’ space 5.5
Non-binding region Binding region
5
B
4.5
4
3.5 Demand Supply (Binding)
3 0.566
Model
0.567
0.568
0.569
0.57
0.571
0.572
10
International credit supply shock I
Experiment Reduction of equity requirement for global banks (χ ↓) • A push shock from Home country’s perspective ↑
Model
11
International credit supply shock I
Experiment Reduction of equity requirement for global banks (χ ↓) • Credit flows into Home country, lending rate falls
(a) Lending Rate
6
B
0.9598
B' 4
3 0.566
B
s1
R
5
(b) Exch. Rate
0.96
0.9596
0.567
0.568
0.569
0.57
0.571
0.572
0.9594 0.566
(c) House Price
0.854
0.567
0.568
0.569
0.57
0.853
0.85 0.566
Model
B
c1
q
1.95
B 0.567
0.568
0.569
0.57
0.571
0.572
B'
1.945
B'
0.851
0.571
(d) Consumption
1.955
0.852
B'
0.572
1.94 0.566
0.567
0.568
0.569
0.57
0.571
0.572
12
International credit supply shock I
Experiment Reduction of equity requirement for global banks (χ ↓) • Real exchange rate appreciates
(a) Lending Rate
6
B
0.9598
B' 4
3 0.566
B
s1
R
5
(b) Exch. Rate
0.96
0.9596
0.567
0.568
0.569
0.57
0.571
0.572
0.9594 0.566
(c) House Price
0.854
0.567
0.568
0.569
0.57
0.853
0.85 0.566
Model
B
c1
q
1.95
B 0.567
0.568
0.569
0.57
0.571
0.572
B'
1.945
B'
0.851
0.571
(d) Consumption
1.955
0.852
B'
0.572
1.94 0.566
0.567
0.568
0.569
0.57
0.571
0.572
13
International credit supply shock I
Experiment Reduction of equity requirement for global banks (χ ↓) • House prices increase (if binding borrowing constraint)
(a) Lending Rate
6
B
0.9598
B' 4
3 0.566
B
s1
R
5
(b) Exch. Rate
0.96
0.9596
0.567
0.568
0.569
0.57
0.571
0.572
0.9594 0.566
(c) House Price
0.854
0.567
0.568
0.569
0.57
0.853
0.85 0.566
Model
B
c1
q
1.95
B 0.567
0.568
0.569
0.57
0.571
0.572
B'
1.945
B'
0.851
0.571
(d) Consumption
1.955
0.852
B'
0.572
1.94 0.566
0.567
0.568
0.569
0.57
0.571
0.572
14
International credit supply shock I
Experiment Reduction of equity requirement for global banks (χ ↓) • Consumption increases
(a) Lending Rate
6
B
0.9598
B' 4
3 0.566
B
s1
R
5
(b) Exch. Rate
0.96
0.9596
0.567
0.568
0.569
0.57
0.571
0.572
0.9594 0.566
(c) House Price
0.854
0.567
0.568
0.569
0.57
0.853
0.85 0.566
Model
B
c1
q
1.95
B 0.567
0.568
0.569
0.57
0.571
0.572
B'
1.945
B'
0.851
0.571
(d) Consumption
1.955
0.852
B'
0.572
1.94 0.566
0.567
0.568
0.569
0.57
0.571
0.572
15
Empirics
Model
16
A Heterogeneous Panel VAR model I
Objective Identify an international credit supply shock in the data (1) Transmission and relative importance for the average economy (2) Differential impact across countries
Empirics
17
A Heterogeneous Panel VAR model I
Objective Identify an international credit supply shock in the data (1) Transmission and relative importance for the average economy (2) Differential impact across countries
I
Reduced-form VAR for country i is
Xit = ai + bi t + ci t2 + F1i Xi,t−1 + uit , where
Xit =
Empirics
LEVt
KFit
Cit
HPit
RERit
CAit /Yit
17
A Heterogeneous Panel VAR model I
Objective Identify an international credit supply shock in the data (1) Transmission and relative importance for the average economy (2) Differential impact across countries
I
Reduced-form VAR for country i is
Xit = ai + bi t + ci t2 + F1i Xi,t−1 + uit , where
Xit = I
LEVt
KFit
Cit
HPit
RERit
CAit /Yit
LEVt : Leverage of US Broker-Dealer sector (Flow of Funds) • Empirical proxy for global banks’ leverage • Common to all countries
Empirics
17
A Heterogeneous Panel VAR model I
Objective Identify an international credit supply shock in the data (1) Transmission and relative importance for the average economy (2) Differential impact across countries
I
Reduced-form VAR for country i is
Xit = ai + bi t + ci t2 + F1i Xi,t−1 + uit , where
Xit = I
LEVt
KFit
Cit
HPit
RERit
CAit /Yit
KFit : Cross-border claims of BIS reporting banks on country i • All instruments, to financial and non-financial sectors
Empirics
18
A Heterogeneous Panel VAR model I
Objective Identify an international credit supply shock in the data (1) Transmission and relative importance for the average economy (2) Differential impact across countries
I
Reduced-form VAR for country i is
Xit = ai + bi t + ci t2 + F1i Xi,t−1 + uit , where
Xit =
LEVt
KFit
Cit
HPit
RERit
CAit /Yit
I
All variables are in real terms (except LEVt and CAit /Yit ) and in log-levels (except CAit /Yit )
I
Mean group estimator [Pesaran and Smith (1995); Pesaran (2006)] over 1985:Q1-2012:Q4 sample period
Empirics
19
Identification of international credit supply ‘push’ shock in the data I
Empirics
In the model shocks to leverage shift global supply of cross-border bank credit
20
Identification of international credit supply ‘push’ shock in the data I
In the model shocks to leverage shift global supply of cross-border bank credit
I
In the data LEVt arguably is exogenous to conditions in individual country
i
• Unlikely to be driven by country-specific ‘pull’ factors • Drop US from sample
Empirics
20
Identification of international credit supply ‘push’ shock in the data I
In the model shocks to leverage shift global supply of cross-border bank credit
I
In the data LEVt arguably is exogenous to conditions in individual country
i
• Unlikely to be driven by country-specific ‘pull’ factors • Drop US from sample
I
Empirics
Implementation with country-by-country Cholesky factorization with LEVt ordered first Shocks
20
Identification of international credit supply ‘push’ shock in the data I
In the model shocks to leverage shift global supply of cross-border bank credit
I
In the data LEVt arguably is exogenous to conditions in individual country
i
• Unlikely to be driven by country-specific ‘pull’ factors • Drop US from sample
I
Implementation with country-by-country Cholesky factorization with LEVt ordered first Shocks
I
Robustness • Control for globally synchronized pull shocks • Drop ‘not so small’ open economies
Empirics
20
Transmission consistent with model and stylized facts on boom-bust episodes in cross-border credit Leverage 6
Percent
Cross-border Credit
Consumption 0.4
2
0.3
1.5 4 1
0.2
2
0.5
0.1
0
0
0
5
10 15 20 25 30 35 40
5
House Price
10 15 20 25 30 35 40
5
Real Exch. Rate
10 15 20 25 30 35 40
Current Account
0
1
Percent
0 -0.2 0.5
-0.1
-0.4 -0.6
0 5
10 15 20 25 30 35 40
Quarters
Empirics
-0.2
-0.8 5
10 15 20 25 30 35 40
Quarters
5
10 15 20 25 30 35 40
Quarters
21
The shock explains a substantial fraction of the forecast error variance of domestic variables Leverage
100
30
Cross-border Credit
Consumption
20
Percent
15 20 50
10 10 5
0
0 5
10 15 20 25 30 35 40
House Price
25
Percent
20
10 15 20 25 30 35 40
Real Exch. Rate
20
5
10 15 20 25 30 35 40
Current Account
15
15 10
15 10 10
5 5
5 0
0 5
10 15 20 25 30 35 40
Quarters
Empirics
0 5
0 5
10 15 20 25 30 35 40
Quarters
5
10 15 20 25 30 35 40
Quarters
22
Understanding cross-country heterogeneity
I
Error bands for IRFs and FEVDs are relatively wide ⇒ Significant differences across countries
I
Does heterogeneity follow specific patterns?
Empirics
23
Understanding cross-country heterogeneity
I
Error bands for IRFs and FEVDs are relatively wide ⇒ Significant differences across countries
I
Does heterogeneity follow specific patterns?
I
Conjecture Transmission affected by country characteristics. Focus on two characteristics that have a clear counterpart in the model • Maximum LTV limit (θ i ) • Share foreign currency liabilities (ψi )
I
Empirics
Compare theoretical predictions with data
23
Loan-to-Value ratios I
Prediction 1 A larger LTV ratio (higher θ ) implies a higher sensitivity of Ci , HPi , and RERi to shocks to χ • If constraint binds, higher θ leads to higher house price response, and hence
larger collateral effect and amplification • Higher θ leads to higher credit and demand, and hence larger real exchange
rate response
Empirics
24
Loan-to-Value ratios I
Prediction 1 A larger LTV ratio (higher θ ) implies a higher sensitivity of Ci , HPi , and RERi to shocks to χ • If constraint binds, higher θ leads to higher house price response, and hence
larger collateral effect and amplification • Higher θ leads to higher credit and demand, and hence larger real exchange
rate response
House Price
Consumption
IRs (Max)
1 0.5 0
IRs (Max)
4
1.5
IRs (Max)
Real Exch. Rate 0
2 0
40
60
80
(Home Ownership) x (max LTV)
-2 -3
Correlation: 0.4 t-Statistic: 2.9
Correlation: 0.3 t-Statistic: 2.0
-0.5
-1
40
60
80
(Home Ownership) x (max LTV)
Correlation: -0.2 t-Statistic: -1.3
40
60
80
(Home Ownership) x (max LTV)
NOTE: LTV is maximum LTV weighted by homeownership rate.
Empirics
24
Share of foreign currency debt I
Prediction 2 A larger share of foreign currency debt (higher ψ) may imply a higher sensitivity of Ci , HPi , and RERi to shocks to χ • Higher ψ implies larger collateral and endowment valuation effects (↑), and
larger debt valuation effect (↓) • Depending on which effect dominates, higher ψ can lead to both
higher/lower amplification
Empirics
25
Share of foreign currency debt I
Prediction 2 A larger share of foreign currency debt (higher ψ) may imply a higher sensitivity of Ci , HPi , and RERi to shocks to χ • Higher ψ implies larger collateral and endowment valuation effects (↑), and
larger debt valuation effect (↓) • Depending on which effect dominates, higher ψ can lead to both
higher/lower amplification
House Price
Consumption
IRs (Max)
1 0.5 0 Correlation: 0.5 t-Statistic: 4.8
-0.5 0.2
0.4
0.6
0.8
Share of foreign currency debt
IRs (Max)
4
1.5
IRs (Max)
Real Exch. Rate 0
2 0
-1 -2 -3
Correlation: 0.6 t-Statistic: 5.1
-2 0.2
0.4
0.6
0.8
Share of foreign currency debt
Correlation: -0.4 t-Statistic: -3.7
0.2
0.4
0.6
0.8
Share of foreign currency debt
NOTE: Share of foreign currency liabilities computed using BIS banking data.
Empirics
25
Robustness checks
I
Control for synchronized pull shocks
Go
• Augment vector of endogenous variables with world GDP
I
Drop ‘not so small’ economies that can affect global credit supply
Go
• Japan, Switzerland, UK, and Germany
I
Exclude lagged country variables from the leverage equation
I
Scatter plots vs. VARs on sub-groups
I
VAR vs. Local Projections
Empirics
Go
Go
Go
26
Conclusions I
Theory • Expansionary push shock triggered by changes in leverage of global banks
I
Empirics • Identified shock to US broker-dealers’ leverage explains a significant share of
domestic variance • Transmission consistent with model (both time series and cross-section)
Conclusions
27
Conclusions I
Theory • Expansionary push shock triggered by changes in leverage of global banks
I
Empirics • Identified shock to US broker-dealers’ leverage explains a significant share of
domestic variance • Transmission consistent with model (both time series and cross-section)
I
Policy implications • Max LTV ratios and shares of FX liabilities associated with sensitivity to shock • Macro-pru can try to influence them and hence affect final outcome
I
Next on agenda: Quantitative model and policy analysis
Conclusions
27
Appendix: Event Study
Appendix
28
Event study: Methodology
I
Event study follows Mendoza and Terrones (2008)
I
Boom (Bust) = At least 3 consecutive years of ∆ ln KFit > 0 (< 0)
I
134 boom, 81 bust, and 50 boom-bust episodes
I
Observe economy’s behavior around boom-bust cycles’ peak
Appendix
29
Event Study: Summary Statistics Mean Across Episodes Boom
Number Duration Max Min Amplitude
Bust
Boom-bust
ALL
AE
EM
ALL
AE
EM
ALL
AE
EM
2.4 7.3 32.6 5.0 131.6
2.5 8.8 28.5 3.7 130.1
2.3 6.1 35.9 5.9 132.8
1.4 4.4 -4.2 -20.4 -53.2
1.1 3.7 -4.6 -17.5 -36.9
1.6 4.8 -4.1 -21.9 -61.3
0.9 12.7 36.3 -21.8 103.5
0.8 13.4 29.5 -19.2 115.7
0.9 12.4 40.5 -23.5 96.0
Median Across Episodes Boom
Number Duration Max Min Amplitude
Bust
Boom-bust
ALL
AE
EM
ALL
AE
EM
ALL
AE
EM
2.0 6.0 28.5 3.0 105.5
2.0 8.0 26.0 2.0 121.0
2.0 5.0 31.0 4.0 84.0
1.0 4.0 -3.0 -18.0 -42.0
1.0 3.0 -3.0 -15.0 -30.0
2.0 4.0 -3.0 -19.0 -51.5
1.0 12.0 29.0 -19.0 80.5
1.0 13.0 27.0 -18.0 106.0
1.0 12.0 31.0 -20.0 39.0
NOTE. Number is number of episodes; Duration is length of episodes in years; Max and Min are maximum and minimum growth rate of cross-border credit during episode, respectively; Amplitude is cumulative sum of growth rate of cross-border credit over episode.
Appendix
30
Appendix: Data
Appendix
31
Data
I
Global variable • Global banks’ leverage: US Broker-Dealers’ leverage (LEVt )
I
Country-specific variables • International credit: cross-border claims of BIS reporting banks (KFit ) • Macro variables: private consumption (Cit ) and current account to GDP
(CAit /Yit )
• Asset prices: house prices (HPit ) and real exchange rate vis-a-vis the US
dollar (RERit )
I
Sample: 57 countries between 1977 and 2012 (unbalanced) Data sources
Appendix
32
International credit claims I
Cross-border total claims (all instruments, to financial and non-financial sectors) of BIS reporting banks on country i
KFit =
N
∑
j=1(j6 =i)
KFij,t
I
Important role of banks in international financial intermediation in the run up to the global financial crisis
I
Three examples Argentina
300
Brazil
150
200
100
100
50
Ireland
100
50
0
0 1980
Appendix
1990
2000
2010
0 1980
1990
2000
2010
1980
1990
2000
2010
33
Leverage of US Broker-Dealers I
Leverage is defined as Assets/Equity of the US broker dealer sector from the Federal Reserve’s Flow of Funds
I
Empirical proxy for global banks’ leverage • [Bruno and Shin (2015); Rey (2013)]
30
Leverage
25 20 15 10 1985
Appendix
1989
1993
1997
2001
2005
2009
34
Data sources: Countries I
24 Advanced Economies: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Japan, Luxembourg, Malta, Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, UK, and US
I
33 Emerging Economies: Argentina, Brazil, Bulgaria, Chile, China, Colombia, Croatia, Czech Republic, Estonia, Hong Kong, Hungary, India, Indonesia, Israel, Korea, Latvia, Lithuania, Malaysia, Mexico, Morocco, Peru, Philippines, Poland, Russia, Serbia, Singapore, Slovakia, Slovenia, South Africa, Taiwan, Thailand, Ukraine, and Uruguay
I
Sample: 1970:Q1–2012:Q4 (subject to data availability)
Back
Appendix
35
Data sources: Quantities I
Cross-border banking flows. Foreign claims (all instruments, in all currencies, locational by residence) of all BIS reporting banks vis-` a-vis all sectors deflated by US consumer price inflation. Source: BIS.
I
GDP. Real index. Source: OECD, IMF IFS, Bloomberg.
I
Consumption. Real private final consumption index. Source: OECD, IMF, IFS, Bloomberg.
I
Current account to GDP ratio. Current account balance divided by nominal GDP. Source: OECD, IMF IFS, Bloomberg.
Back
Appendix
36
Data sources: Prices I
House prices. Nominal house prices deflated by consumer price inflation. Source: Cesa-Bianchi et al (2015, JMCB)
I
Short-term interest rates. Short-term nominal market rates. A real ex-post interest rate is obtained by subtracting consumer price inflation. Source: OECD, IMF, IFS, Bloomberg.
I
Consumer prices. Consumer price index. Source: OECD, IMF IFS, Bloomberg.
I
Equity prices. Equity price index deflated by consumer price inflation. Source: OECD, IMF IFS, Bloomberg.
I
Exchange rate vis-` a-vis US dollar. US dollars per unit of domestic currency. A real exchange rate is obtained with US and domestic consumer price inflation. Source: Datastream.
I
Real effective exchange rate. Index (such that a decline of the index is a depreciation). Source: IMF IFS, BIS, Bloomberg.
Back Appendix
37
Cross-border credit: Banks vs. non-Banks
US Dollars (Trillions)
30 25
Banks Non-banks Total
20 15 10 5 0 1977
1981
1985
1989
1993
1997
2001
2005
2009
2013
Back
Appendix
38
Appendix: Model
Appendix
39
Households I
Home country (starts with zero initial credit)
max
{c1 ,c2 ,h1 ,f }
u(c1 ) + βu(c2 ) + v(h1 )
with β ∈ (0, 1) and h0 given, subject to
c1 + qh1 − b − s1 f c2 where
ct ≡ I
= pH1 y + qh0 = pH2 y − Rb b − s2 Rf
α c1 − α cHt Ft α α (1 − α )1− α
Collateral constraint
b + s1 f ≤ θqh1
Appendix
40
Households I
Foreign country (1 > β∗ > β)
max u(c1∗ ) + β∗ u(c2∗ )
{c1∗ ,c2∗ ,d,e}
subject to
c1∗ + d + e + ψ(e) c2∗
∗ ∗ y = pF1 ∗ ∗ = pF2 y + Rd d + Re e + Π
with ψ0 , ψ00 > 0, and ∗
c∗ α c∗1− α c = ∗ α ∗ H F ∗ 1− α ∗ α (1 − α ) ∗
∗
Appendix
41
Global financial intermediaries I
Balance sheet Assets Loans (H currency): Loans (F currency):
I
Profits
Π = Rf +
Liabilities b/s1 f
Deposits (F currency):
d
Equity (F currency):
e
Rb b − Rd d − Re e − φ s2
b s1
where φ(·) is cost of swapping loans in Foreign currency (with φ0 , φ00 > 0) I
Leverage constraint (capital requirement)
e≥χ Appendix
b +f s1
42
Equilibrium: Analytical characterization I
Take limit for n → 0 ⇒ Home becomes small open economy
I
Abstract from intermediaries portfolio problem • Fix the ratio between domestic and foreign currency liabilities (η )
I
All households are risk-neutral and housing (land) is in fixed supply
I
Then, we can solve analytically • Terms of trade from goods market equilibrium (⇒ Real exchange rate) • Credit demand and credit supply
I
Represent the equilibrium in the {f , R} space
Appendix
43
Parameters
Parameter
Description
β β∗ κ λ θ η χ y = y∗
Country H discount factor Country F discount factor Normalized marginal utility of housing Degree of openness LTV ratio Share of foreign debt Capital requirement Endowments
Value
0.9 0.99 0.85 0.79 0.92 0.43 0.1 1
I
Adjustment cost parameters pin down equity and loans risk premia
I
In turn, the level of risk premia will determine whether the equilibrium lies in the unconstrained/constrained region
Appendix
44
Appendix: Identification
Appendix
45
Estimated international credit supply shock I
Orthogonalized leverage innovations for each of the country-specific models (light solid lines) can differ slightly across countries • Lagged feedback from the rest of the system to leverage equation • Models are estimated over different sample periods (depending on data
availability)
20
Percent
10 0 -10 -20 -30 1985
1989
1993
1997
2001
2005
2009
NOTE. The light solid lines are the orthogonalized leverage innovations for each of the country-specific models. The dark solid line is the cross-country average of the country-specific leverage innovations. The dotted lines are the average of the one-standard deviation bands, equal to 7.5 percent per quarter.
Back Appendix
46
Brokers-Dealers’ leverage innovations and their underlying determinants I
Leverage is exogenous in our model, but in the data various factors can affect the leverage of US Broker-Dealers xt ∆FFRt
(1)
(2)
(3)
-2.477** [-2.364]
eMP
(5) -2.613** [-2.536]
-0.0497 [-0.650]
RLt − Rt
-0.900 [-1.642]
VIXt Obs. Adj. R2
(4)
111 0.049
91 0.005
111 0.024
-0.00182** [-2.057]
-0.00195** [-2.252]
111 0.037
111 0.091
NOTE. The Table reports a regression of the leverage innovations (average across countries) on their possible determinants:
eLEV = βxt . ∆FFRt is the first difference of the real (ex-post) federal fund rate; eMP is Romer and Romer (2004) monetary t
policy shock; RL t − Rt is the slope of the US yield curve; VIXt is the VIX index. The regressions also include a constant and world GDP (not reported).
Back Appendix
47
Appendix: Identification Robustness
Appendix
48
Identification robustness: controlling for globally synchronized ‘pull’ shocks I
Small open economy assumption rules out local factors can drive LEVt • No single country can affect leverage of global banks
I
But LEVt could be affected by globally synchronized factors
I
Synchronized shocks should affect world GDP • Augment vector of endogenous variables with world GDP
Xit =
I
Ytw
LEVt
KFit
Cit
HPit
RERit
CAit /Yit
Shock to leverage of US broker-dealers still identified with Cholesky Back
Appendix
49
IRFs to leverage shock (Identification robustness) Leverage
Cross-border Credit 1.5
4
1
2
0.5
0.2
Percent
6
Consumption
0.1
0
0 0 5
10 15 20 25 30 35 40
5
House Price
10 15 20 25 30 35 40
5
Quarters Current Account
Real Exch. Rate
0.8
0
0.6
-0.2
0.4
-0.4
10 15 20 25 30 35 40
0.1 0 -0.1
0.2
-0.6
0
-0.8 5
10 15 20 25 30 35 40
Quarters
-0.2 5
10 15 20 25 30 35 40
Quarters
5
10 15 20 25 30 35 40
Quarters
Back
Appendix
50
Variance decomposition (Identification robustness) Leverage
100
20
Cross-border Credit
Consumption
15
Percent
15 10
50
10
5
5 0
0 5
10 15 20 25 30 35 40
House Price
20
0 5
10 15 20 25 30 35 40
Real Exch. Rate
15
5
10 15 20 25 30 35 40
Quarters Current Account
15
15 10
10
5
5
10 5 0
0 5
10 15 20 25 30 35 40
Quarters
0 5
10 15 20 25 30 35 40
Quarters
5
10 15 20 25 30 35 40
Quarters
Back
Appendix
51
Identification robustness: World equity prices I
World GDP might not have enough forward looking component to capture globally synchronized pull shocks
I
Estimate a VAR with world equity prices (world MSCI index) instead of GDP
I
Results are robust qualitatively, but a bit weaker quantitatively • World equity prices incorporate information, like risk premia, also captured
by the leverage variable
Back
Appendix
52
Identification robustness: World equity prices I
Impulse responses Leverage
Cross-border Credit
Consumption
1.5
0.2
6
Percent
1 4 0.5 2
0.1 0
0 0
-0.1 5
10 15 20 25 30 35 40
House Price 0.6
5
10 15 20 25 30 35 40
Real Exch. Rate
0.2
5
10 15 20 25 30 35 40
Quarters Current Account
0.1
0 0
0.4
-0.2
0.2
-0.4
0
-0.1
-0.6 -0.2
-0.2 5
10 15 20 25 30 35 40
Quarters
5
10 15 20 25 30 35 40
Quarters
5
10 15 20 25 30 35 40
Quarters
Back Appendix
53
Identification robustness: World equity prices Forecast error variance decompositions Leverage
80
Cross-border Credit
Consumption 10
10
60
Percent
I
40 5
5
20 0
0 5
10 15 20 25 30 35 40
0 5
House Price 15
10 15 20 25 30 35 40
5
10 15 20 25 30 35 40
Quarters Current Account
Real Exch. Rate 10
10
5
5
10
5
0
0 5
10 15 20 25 30 35 40
Quarters
0 5
10 15 20 25 30 35 40
Quarters
5
10 15 20 25 30 35 40
Quarters
Back Appendix
54
Appendix: VAR Robustness
Appendix
55
VAR robustness: Drop large countries (IRF) Leverage
Percent
6
Cross-border Credit
Consumption 0.4
2
0.3 4
0.2
1 2
0.1 0
0
0 5
10 15 20 25 30 35 40
5
House Price
10 15 20 25 30 35 40
5
Real Exch. Rate
10 15 20 25 30 35 40
Current Account
0
Percent
1
0
-0.2
-0.1
-0.4
0.5
-0.6 0
-0.2
-0.8 -0.3 5
10 15 20 25 30 35 40
Quarters
5
10 15 20 25 30 35 40
Quarters
5
10 15 20 25 30 35 40
Quarters
Back Appendix
56
VAR robustness: No feedback from SOE I
Block exogenous VAR: no feedback from endogenous variables in country i to Broker-Dealers’ leverage
I
VAR for country i (abstracting from constant and time trend) is
I
LEVt xi,t
=
F11,i F21,i
0
F22,i
LEVt−1 xi,t−1
+
B11,i B21,i
0
B22,i
eLEV t exi,t
Identification: Cholesky decomposition as in the baseline
Back
Appendix
57
VAR robustness: No feedback from SOE (IRF) Leverage
Cross-border Credit
Consumption
8 3
0.4
Percent
6 0.3
2 4
0.2 1
2
0.1
0
0 5
10 15 20 25 30 35 40
House Price 1.5
0 5
10 15 20 25 30 35 40
Real Exch. Rate
0
Percent
10 15 20 25 30 35 40
Current Account 0
-0.2 1
5
-0.4
-0.1
-0.6 0.5
-0.2 -0.8
0
-1 5
10 15 20 25 30 35 40
Quarters
-0.3 5
10 15 20 25 30 35 40
Quarters
5
10 15 20 25 30 35 40
Quarters
Back Appendix
58
VAR robustness: No feedback from SOE (FEVD) Leverage
100
60
Cross-border Credit
Consumption
40
Percent
30 40 50
20 20 10
0
0 5
10 15 20 25 30 35 40
House Price
50
0 5
10 15 20 25 30 35 40
Real Exch. Rate
30
5
10 15 20 25 30 35 40
Current Account
30
Percent
40 30 20
20
20
10
10
10 0
0 5
10 15 20 25 30 35 40
Quarters
0 5
10 15 20 25 30 35 40
Quarters
5
10 15 20 25 30 35 40
Quarters
Back Appendix
59
VAR robustness: Local Projections Leverage
Cross-border Credit
Consumption
Percent
6 2
0.4
1
0.2
4 2 0 0
0 1
2
3
4
5
6
7
8
9 10
1
2
House Price
3
4
5
6
7
8
9 10
Real Exch. Rate
1
2
3
4
5
6
7
8
9 10
Current Account
0.1
0.5
Percent
0 1
0.5
0
-0.1
-0.5
-0.2 -0.3
-1 -0.4
0 1
2
3
4
5
6
Quarters
7
8
9 10
1
2
3
4
5
6
Quarters
7
8
9 10
1
2
3
4
5
6
7
8
9 10
Quarters
Back Appendix
60
VAR robustness: Local Projections (with REER) Leverage
Cross-border Credit
Consumption
3
Percent
6
0.4 2
4 2
1
0
0 1
2
3
4
5
6
7
8
9 10
0.2
0 1
2
House Price
3
4
5
6
7
8
9 10
1
2
Real Exch. Rate
3
4
5
6
7
8
9 10
Current Account 0.1
0.2
0
Percent
1 0
-0.1 -0.2
0.5
-0.2
0
-0.4
-0.3
1
2
3
4
5
6
Quarters
7
8
9 10
-0.4 1
2
3
4
5
6
Quarters
7
8
9 10
1
2
3
4
5
6
7
8
9 10
Quarters
Back Appendix
61
VAR estimated on ‘bins’: High and low share of foreign currency liabilities Leverage
Percent
6
Cross-border Credit
Consumption
2
0.4
1
0.2
4 2 0
0
0 5
10 15 20 25 30 35 40
5
House Price
10 15 20 25 30 35 40
5
Real Exch. Rate
10 15 20 25 30 35 40
Current Account
0 0
Percent
1
-0.2 -0.1
-0.4
0.5
-0.2
-0.6 0
-0.8 5
10 15 20 25 30 35 40
Quarters
-0.3 5
10 15 20 25 30 35 40
Quarters
5
10 15 20 25 30 35 40
Quarters
Back Appendix
62
VAR estimated on ‘bins’: High and low maximum Loan-to-Value Leverage
Consumption
2
0.4
1.5
0.3
1
0.2
2
0.5
0.1
0
0
6
Percent
Cross-border Credit
4
5
10 15 20 25 30 35 40
0 5
House Price
10 15 20 25 30 35 40
5
Real Exch. Rate
10 15 20 25 30 35 40
Current Account
0 0
Percent
1 -0.2
-0.1
-0.4
0.5
-0.6
-0.2
-0.8
0
-0.3 5
10 15 20 25 30 35 40
Quarters
5
10 15 20 25 30 35 40
Quarters
5
10 15 20 25 30 35 40
Quarters
Back Appendix
63
Appendix: Cross-Section
Appendix
64
Other characteristics I
Focus on share of foreign currency liabilities (1/(1 + η )) and the maximum LTV limit (θ ) as they have a clear counterpart in the model
I
But other characteristics might be relevant • Exchange rate flexibility • Controls on capital inflows • Mortgage credit over GDP
Max Loan to Value Foreign currency liability Exch. Rate flexibility Capital controls (inflows) Mortgage debt / GDP
Consumption
House Price
Exch. Rate
0.32 0.53 -0.40 0.23 -0.31
0.44 0.54 -0.41 0.32 -0.42
-0.21 -0.39 0.16 -0.28 0.25
NOTE. Correlation between the peak impulse response of selected variables (columns) and country characteristics (rows). See the appendix on data definition and sources.
Back Appendix
65