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International Financial
Integration and Crisis Intensity
Andrew K. Rose
UC Berkeley, NBER and CEPR
(collaborator with Mark Spiegel)
ASEAN Presentation, Seoul December 2010
1
What Caused the 2008-09 Crisis?
• Defining macroeconomic event of generations
– A recent “Natural Experiment”
• Did International Financial Integration play
any significant role?
– If so, multilateral or bilateral ties matter most?
– If bilateral, which country matters most for
exposure/insurance?
• Big Asian Economies: China; Japan; Korea.
• United States
ASEAN Presentation, Seoul December 2010
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Non-Structural Methodology
• MIMIC (multiple-indicator, multiple cause)
model explicitly incorporate difficulties in
observing relative crisis severity
– Treats crisis as a latent variable
– Observed with error as function of observable
manifestations
– Also do OLS, graphical analysis
• Sample is cross-section of 85 countries
ASEAN Presentation, Seoul December 2010
3
Crisis Performance is Latent Variable
Mapping Observable Causes to
Observable Manifestations
• 4 Manifestations from 2008-09: equity market
collapse, exchange rate devaluation, economic
growth, and change in creditworthiness
• Compare to 2006 vulnerabilities (causes)
– National causes
– International financial linkages
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Results, 1
• Plausible estimates of relative severity of crisis
– Ex: Iceland and Latvia identified as exceptionally bad
– Most Asians have mild crises
• Use literature to find three “national” crisis
causes (determinants from 2006)
1. Real Income (negative “progressive” effect”)
2. Financial Market Regulation (looser → worse crisis)
3. Current Account (% GDP) (deficit → worse)
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Results, 2
• Less success linking crisis to integration
variables
– No multilateral variables consistently enter at
statistically significant levels
– Most bilateral variables irrelevant too
– Little effect of: a) banking exposure; b) debt
denomination; c) Fed swap lines
– Asset exposure (CPIS) matters, but not strong
– More exposure to US → more mild crisis!
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Data
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Empirical Strategy
• Exploit recent international cross section
– “Great Recession” a “natural experiment”
• Don’t have to rely on time-series/panel data
– All information country-specific initially
– Then add linkages between countries
– National characteristics may influence
vulnerability to foreign shocks
• Medical analogy: common shocks vs. contagion
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Data Span
• As crisis hit all types of countries, include both
developed and EMEs
– All countries >$10,000 per capita GDP
– All countries >$4,000 per capita GDP, plus
population > 1 million (WB: upper middle income)
– Maximum of 85 countries in sample
• Use only publicly-available series available for
reasonable span of countries
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Sample of Countries
Argentina
Chinaa
Finland
Ireland
Lithuania
Norway
Singaporea
Armeniaa
Colombia
France
Israel
Luxembourg
Oman
Slovakia
Trinidad &
Tobago
Tunisia
Australiaa
Costa Rica
Georgiaa
Italy
Macedonia
Panama
Slovenia
Turkeya
Austria
Croatia
Germany
Jamaica
Malaysiaa
South Africa
UK
Barbados
Cyprus
Greece
Japana
Malta
Papua New
Guineaa
Paraguay
Spain
Ukraine
Belgium
Czech Rep
Guyana
Kazakhstana
Mauritius
Peru
Sri Lankaa
United Statesa
Botswana
Denmark
Hong Konga
Koreaa
Mexico
Poland
Uruguay
Brazil
Ecuador
Hungary
Kuwait
Morocco
Portugal
St. Kitts &
Nevis
Swaziland
Bulgaria
Egypt
Iceland
Kyrgyzstana
Namibia
Romania
Sweden
Canada
El Salvador
Indonesiaa
Latvia
Netherlands
Russia
Switzerland
Chile
Estonia
Iran
Lebanon
New Zealanda
Saudi Arabia
Thailanda
ASEAN Presentation, Seoul December 2010
Venezuela
a = Asian
10
Differences in Crisis Severity
(Manifestations/Consequences)
• Crisis intensity only observed with error [e.g.
Berg, et al (2004)]
– Abundant measurement error likely
• Initially model severity as a latent variable linked
to four observable indicators for 2008-09
1.
2.
3.
4.
GDP growth (%)
Change in National Equity Markets (stocks, %)
Change in multilateral SDR exchange rate (%)
Change in Euromoney country credit rating
• March 2008 - March 2010
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Table 1: Crisis Manifestations
Stock
Market
-91.4
Euromoney
Credit Rating
-23.4
Price of
SDR
100.3
Real GDP
1
2008-09
changes in:
Iceland
2
Russia
-81.2
-1.6
22.2
-2.7
3
Bulgaria
-75.8
-6.4
1.7
.7
4
UAE
-69.9
-4.4
-.8
4.5
5
Cyprus
-66.9
-1.0
1.4
1.8
6
Macedonia
-64.3
-3.7
1.6
4.1
7
Slovenia
-64.1
-4.0
1.4
-4.6
8
Croatia
-61.7
5.2
1.3
-3.5
9
Greece
-58.3
-9.8
1.4
-.0
10
Bermuda
-57.3
-15.3
-.8
.4
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-5.6
12
Methodology
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MIMIC model
• MIMIC model consists of two sets of equations:
(1)
y    
i, j
j i
i
i   k xi ,k   i
(2)
where yi , j is crisis indicator, xi , k is an observation for potential crisis
cause;  i is latent variable representing severity of the crisis (or lack
thereof in our case), andi and  i are well-behaved disturbances
• Equation (1) links observable (2008-09) manifestations
of the crisis to latent variable
• Equation (2) links latent variable to (2006) crisis causes
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Characteristics of MIMIC Model
• Substitute (2) into (1), eliminate latent variable
• MIMIC model is then a system of J (=4) equations
with right hand sides restricted to be
proportional
• With normalization, system is identified
– Normalize on equity returns (Breusch)
• Desirable feature of MIMIC model is ability to
systematically address measurement error
• Estimate with STATA using GLLAMM model [RebeHesketh, et al (2004)]
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What Determinants are Associated
with Crisis Incidence?
• Survey literature (Rose and Spiegel 2009a,
2009b, 2010), find three determinants
• Use these as national controls throughout
1. Real Income (negative effect)
2. Credit Market Regulation (looser is worse)
3. Current Account, % GDP (higher is better)
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Sensitivity Analysis
1.
2.
3.
4.
Drop Exchange Rate Consequences
Restrict to Asian/Pacific Countries (and USA)
OLS with growth as dependent variable
OLS with stock market change as regressand
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MIMIC Estimates with Controls
Control
MIMIC
Default
Asian/
Pacific
OLS,
Growth
OLS,
Stocks
-12.6**
(4.36)
-2.5
(3.5)
Drop
Exchange
Rate
Conseq.
-13.5**
(4.4)
-2.0
(3.5)
Log 2006
real GDP pc
2006 Credit
Market
Regulation
2006
Current
Account,
%GDP
-6.0
(3.2)
-.4
(3.1)
-3.0**
(.8)
-2.2**
(.7)
-13.2**
(3.9)
-1.4
(2.8)
.56*
(.26)
.53*
(.26)
-.22
(.27)
.21**
(.06)
.53*
(.25)
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Findings consistent with Literature
• Real GDP per capita has negative, significant
effect (the “progressive” crisis)
• More Credit Market Regulation associated
with milder crisis (Giannone et al), but rarely
significant
• Current Account surpluses associated with
milder crises
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Crisis was Progressive
2008-09 Crisis Manifestations against Real Income
Depreciation against SDR
-50
-100
-50
0
0
50
50
100
100
Stock Market Change
7
8
9
10
11
7
9
10
11
GDP Growth Rate
-20 -10
-20 -10
0
0
10 20
10 20
Country Credit Rating Change
8
7
8
9
10
11
7
8
9
10
11
Log Real GDP per capita 2006
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Role of Current Account
2008-09 Crisis Manifestations against Current Account
Depreciation against SDR
-50
-100
-50
0
0
50
50
100
100
Stock Market Change
-40
-20
0
20
40
-40
0
20
40
GDP Growth Rate
-20 -10
-20 -10
0
0
10 20
10 20
Country Credit Rating Change
-20
-40
-20
0
20
40
-40
-20
0
20
40
Current Account % GDP 2006
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International Financial
Integration
ASEAN Presentation, Seoul December 2010
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Multilateral Financial Linkages
• Examine (6) imperfect multilateral proxies for
2006 financial integration, a)-e) as %GDP
– a) net foreign assets;
– b) external debt;
– c) short-term external debt;
– d) financing via international capital markets;
– e) international reserves.
– f) currency union dummy
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Unchanged Methodology
• Always include (3) national causes
• Same sensitivity analysis
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Role of Multilateral
Financial Linkages
Multilateral
Linkages
2006, %GDP
Net Foreign
Assets
Debt
Short-Term
Ext. Debt
Fin via Int’l
Capital Mkts
Reserves
Currency
Union
MIMIC
Default
-8.3
(6.3)
.11
(.31)
-1.0
(.8)
-.9
(1.1)
-.2
(.2)
-3.9
(7.5)
Drop Exch.
Rate
Conseq.
-8.6
(6.3)
.03
(.32)
-1.0
(.8)
-1.0
(1.1)
-.2
(.2)
-4.6
(7.5)
Asian/
Pacific
OLS,
Growth
OLS,
Stocks
3.9
(4.8)
.05
(.10)
-5.6**
(1.4)
-1.8*
(.8)
.3
(.2)
n/a
.29
(1.28)
.00
(.04)
-.36*
(.14)
.12
(.18)
-.00
(.03)
-.48
(1.41)
-9.0
(8.0)
.01
(.31)
-.98
(.55)
-1.11
(.86)
-.18
(.16)
-4.3
(4.4)
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Poor Multilateral Results
• Little effect of international financial
integration, after taking into account (3)
domestic factors
– 30 coefficients; one significantly different from
zero at 1%; two more at 5%.
– Short-Term External Debt/GDP consistently
negative effect (Blanchard et al)
• Significant 2/5 times
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Proceed on to Bilateral Linkages
• Exposure to Individual Countries
• Different Sectors:
– All External Assets (CPIS)
• Debt, Long-Term Debt as well
– Bank Loans (BIS)
– Debt Denomination (WB)
– Fed swap-lines
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(17) Measures of Bilateral
Financial Linkages
• Share of overseas assets held in USA (as
proportion of all overseas wealth)
– Also consider China, Japan, Korea
• Also consider debt, long-term debt
– BIS Consolidated banking data
• Available for Japan, USA
– PPG debt denominated in yen/$
– Finally, (endogenous) existence of Fed swapline
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CPIS: American Exposure Helps!
Bilateral
Linkages
(2006)
CPIS Asset
Share
CPIS Asset
Share
CPIS Asset
Share
CPIS Asset
Share
Exposure
to
MIMIC
Default
USA
.44**
(.12)
1.5
(1.2)
.26
(2.80)
4.7
(7.8)
Japan
Korea
China
Drop
Exchange
Rate
Conseq.
.48**
(.12)
1.9
(1.2)
.3
(3.1)
4.7
(7.8)
Asian/
Pacific
OLS,
Growth
OLS,
Stocks
.10
(.12)
.11
(.61)
4.7
(2.6)
1.5
(2.8)
.02
(.03)
.36
(.20)
-.18
(.61)
2.79**
(.56)
.48**
(.10)
1.9
(1.5)
.5
(2.9)
4.7
(4.2)
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Special Role of US
•
•
•
•
•
Crisis originated in US
Provider of International Reserves
Monetary Anchor (especially in Asia)
Dollar Appreciation in 2008
But exposure to US assets associated with
more mild crises
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Robust to Exact Asset Considered
Bilateral
Linkages
CPIS Debt
Share
CPIS Debt
Share
CPIS Debt
Share
CPIS Debt
Share
CPIS Long
Debt Share
CPIS Long
Debt Share
CPIS Long
Debt Share
CPIS Long
Debt Share
Exposure to
USA
Japan
Korea
China
USA
Japan
Korea
China
MIMIC
Drop Exch
Asian/
Default
Rate
Pacific
.39**
.43**
.17
(.11)
(.11)
(.14)
-.62
-.59
.0002
(1.27)
(1.34)
(.0007)
-.38
-.27
2.3
(2.56)
(2.54)
(2.1)
1.0
1.0
.4
(1.2)
(1.2)
(1.0)
.38**
.44**
.26
(.12)
(.12)
(.19)
-1.74
-1.6
.0001
(1.5)
(1.6)
(.0009)
.17
.30
2.4
(2.05)
(2.04)
(1.7)
1.1
1.0
2.0
(1.1)
(1.1)
ASEAN Presentation,
Seoul December(3.4)
2010
OLS,
Growth
.02
(.03)
.39
(.22)
-.10
(.41)
.40**
(.08)
.02
(.03)
.16
(.22)
-.08
(.30)
.43
(.07)
OLS,
Stocks
.44**
(.09)
-.60
(1.52)
-.2
(2.2)
1.06*
(.44)
.45**
(.10)
-1.6
(1.7)
.3
(1.6)
.98*
(.47)
31
Graphical Evidence: US Exposure
2008-09 Crisis Manifestations against Asset Exposure to USA
Depreciation against SDR
-50
-100
-50
0
0
50
50
100
100
Stock Market Change
0
20
40
60
80
0
40
60
80
GDP Growth Rate
-20 -10
-20 -10
0
0
10 20
10 20
Country Credit Rating Change
20
0
20
40
60
80
0
20
40
60
80
Percentage External Assets in USA, CPIS 2006
ASEAN Presentation, Seoul December 2010
32
Japanese Exposure
(note x-scales)
2008-09 Crisis Manifestations against Asset Exposure to Japan
Depreciation against SDR
-50
-100
-50
0
0
50
50
100
100
Stock Market Change
0
2
4
6
8
10
0
2
6
8
10
GDP Growth Rate
-20 -10
-20 -10
0
0
10 20
10 20
Country Credit Rating Change
4
0
2
4
6
8
10
0
2
4
6
8
10
Percentage External Assets in Japan, CPIS 2006
ASEAN Presentation, Seoul December 2010
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Korea
(note x-scales)
2008-09 Crisis Manifestations against Asset Exposure to Korea
Depreciation against SDR
-50
-100
-50
0
0
50
50
100
100
Stock Market Change
0
1
2
3
4
5
0
1
3
4
5
GDP Growth Rate
-20 -10
-20 -10
0
0
10 20
10 20
Country Credit Rating Change
2
0
1
2
3
4
5
0
1
2
3
4
5
Percentage External Assets in Korea, CPIS 2006
ASEAN Presentation, Seoul December 2010
34
China
(note x-scales)
2008-09 Crisis Manifestations against Asset Exposure to China
Depreciation against SDR
-50
-100
-50
0
0
50
50
100
100
Stock Market Change
0
.5
1
1.5
2
0
1
1.5
2
GDP Growth Rate
-20 -10
-20 -10
0
0
10 20
10 20
Country Credit Rating Change
.5
0
.5
1
1.5
2
0
.5
1
1.5
2
Percentage External Assets in China, CPIS 2006
ASEAN Presentation, Seoul December 2010
35
BIS Consolidated Banking Claims,
Debt Denomination, Fed Swaplines
Linkage
(2006)
Exposure to
Default
Drop Exchange
Rate
Consequence
Euromoney,
not II
Condition on
C/acc (%GDP),
not size
Condition on NFA
(%GDP), not size
BIS Consolidated
Banking Share
USA
191.
(122.)
202.
(122.)
-224.
(212.)
-13.6
(18.8)
207.**
(69.)
BIS Consolidated
Banking Share
Japan
59.
(48.)
57.
(49.)
-18.
(33.)
10.0**
(3.8)
57**
(18.)
% PPG Debt
in $
USA
.11
(.24)
.08
(.23)
n/a
-.01
(.04)
.07
(.25)
% PPG Debt
in yen
Japan
.15
(.50)
.12
(.50)
-.11
(.27)
.10
(.09)
.10
(.28)
USA
7.2
(8.1)
7.2
(8.2)
-1.7
(7.0)
-.8
(1.6)
7.5
(6.7)
Federal Reserve
Swap Line
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36
Outliers Important for Japanese BIS
consolidated banking data
2008-09 Crisis Manifestations against Bank Exposure to Japan
Depreciation against SDR
-50
-100
-50
0
0
50
50
100
100
Stock Market Change
0
10
20
30
40
50
0
10
30
40
50
GDP Growth Rate
-20 -10
-20 -10
0
0
10 20
10 20
Country Credit Rating Change
20
0
10
20
30
40
50
0
10
20
30
40
50
Percentage Banking Assets in Japan, BIS 2006
ASEAN Presentation, Seoul December 2010
37
American Analogue
2008-09 Crisis Manifestations against Bank Exposure to USA
Depreciation against SDR
-50
-100
-50
0
0
50
50
100
100
Stock Market Change
0
5
10
15
20
0
10
15
20
GDP Growth Rate
-20 -10
-20 -10
0
0
10 20
10 20
Country Credit Rating Change
5
0
5
10
15
20
0
5
10
15
20
Percentage Banking Assets in USA, BIS 2006
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38
Some Sensitivity, Bigger Mystery
• Why does exposure to America (most likely
epi-center of 2008 crisis) seem to help?
– Special Advantage of “Exorbitant Privilege”?
– Interesting Future Research topic
• Still, results not very strong
– Most measures insignificant
• No evidence that Asian links helped in crisis
ASEAN Presentation, Seoul December 2010
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Summary and Conclusion
ASEAN Presentation, Seoul December 2010
40
Examine causes and consequences
of 2008-09 Financial Crisis
• MIMIC Methodology explicitly confronts fact
that “crisis severity” observed with error
• Account for national crisis causes that work in
literature
• Cross-sectional focus: only trying to explain
relative incidence, not timing
ASEAN Presentation, Seoul December 2010
41
Message
• Financial Integration across countries not very
important in understanding crisis incidence
• Seems to provide little insurance (though may
also limit contagion)
• Multilateral measures especially weak
• Bilateral American Financial Influence:
Enduring Impact
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