CLARENDON LECTURES in MANAGEMENT STUDIES 2014
The Architecture of Collapse:
The Global System in the 21st Century
Mauro F. Guillén
It’s an Honour
• I love “unplanned muddles” (John
Betjeman).
• Oxford University Press.
• Brasenose College:
– William Morris
– Michael Palin.
• John Ruskin, William Morris, and the
Oxford Movement.
Half Cooked
• This is thought in progress—not even work
in progress.
• I hope you enjoy the flow of consciousness.
• What can organizational theory add to our
understanding of global dynamics?
Benjamin Thompson
“In Oxford things are more
brilliantly formulated, in Cambridge
things are more seriously thought
through.”
Plan
• The global system:
– Precedents and intellectual lineages.
– Complexity and coupling.
– Data: many charts, most of which show an
upward trend.
• Two intriguing cases of complexity &
coupling:
– The EU vs the EZ.
– The U.S. / China relationship.
• Isomorphism, State Capacity, and
Institutional Diversity.
The Battle of
Alexander at Issus,
by Albrecht Altdorfer
1529
Alte Pinakothek,
Munich.
Lecture I
Complexity and Coupling
in the Global System
The Global System
• Intuition: It has become unwieldy, complex,
unpredictable, prone to failure and crisis.
• My goal is to theorize this intuition in terms
of:
– Interactive complexity.
– Tight coupling.
Source of data: Rogoff and Reinhardt. Note: Based on 70 countries.
Source of data: Rogoff and Reinhardt. Note: Based on 70 countries.
Theoretical Ancestry
•
•
•
•
•
•
World-system (Wallerstein).
World-society (Meyer).
Open-economy politics (Gilpin).
New international trade theory (Krugman).
Societal advantage theory (Biggart)
Normal accidents theory (Perrow).
Isomorphism Model
DiMaggio-Powell-Westney
•
•
•
•
Normative: “Cultural dupes.”
Coercive: “Against my will.”
Mimetic: “Birds of a feather…”
Emulative: “Follow the leader.”
Levels:
Units:
Nodes
Countries
Network
Dyads
System
Global System
Definitions
• Interactive Complexity: Many moving parts,
in intricate arrangement, interacting with one
another in non-linear ways.
• Tight Coupling: Extent to which the parts are
tightly related to one another, thus reducing
the buffers and/or degrees of freedom, the
tolerance, or the margin for error.
• Nota bene: Two parts may be inter-dependent but not
necessarily tightly coupled. For instance, Wallerstein’s core
and periphery are inter-dependent, but there are
considerable degrees of freedom as long as there are
multiple core and multiple peripheral countries (as
exemplified by Haggard’s (1990) analysis of bilateral
investor/investee power).
System Complexity =
Node Complexity & Network Complexity
System Coupling =
Node Coupling & Network Coupling
Key Arguments
• Do networks facilitate exchange during
normal periods?
• Are networks shock-absorbing or shockdiffusing?
– Complex networks are generally shockabsorbing.
– Complex networks that are also tightly coupled
tend to be shock-diffusing.
Number of
Countries
Trade in
Goods &
Services
Foreign
Direct
Investment
NETWORK
COMPLEXITY
Tourism
and
Migration
Information
Flows
# of Nodes: Member Countries
Trade (% of global GDP)
Mauro F. Guillén. Source of the data: World Development Indicators.
Unit: millions USD.
Source of the data: Dyadic trade data: http://www.correlatesofwar.org/COW2%20Data/Trade/Trade.html
Price index: http://www.minneapolisfed.org/community_education/teacher/calc/hist1800.cfm
Direct Investments 2012
Mauro F. Guillen. Source of the data: World Investment Report; World Investment Directory.
Why are these indicators of network
complexity but not necessarily of
network coupling?
• Growth of trade may help countries
specialize and diversify sources and
destinations.
• Direct investment may create:
– More permanent financing for countries.
– Real options for companies.
• Portfolio investment, by contrast, is an
indicator of coupling because it tends to be
“hot money.”
Key Contrasts
• Between portfolio and direct foreign investment.
• Between trade in widgets and trade in dollars:
“When we penetrate the fog of implausible assertions that
surrounds the case for free capital mobility, we realize that
the idea and the ideology of free trade and its benefits […]
have, in effect, been hijacked by the proponents of capital
mobility. They have been used to bamboozle us into
celebrating the new world of trillions of dollars moving about
daily in a borderless world, creating gigantic economic gains,
rewarding virtue and punishing profligacy. The pretty face
presented to us is, in fact, a mask that hides the warts and
wrinkles underneath.”
—Jagdish N. Bhagwati, “The Capital Myth: The Difference
between Trade in Widgets and Dollars.” Foreign Affairs
(1998).
Trade and Coupling
• Trade leads to coupling and contagion when:
– High Cohesion with a small number of partners:
• A and B trade intensively with each other.
• A suffers a shock.
• The shock spreads from A to B.
– High Role Equivalence:
• A and B export the same goods to C.
• C suffers a shock.
• Both A and B suffer.
• There are few instances of extreme levels of:
– Cohesion: Mexico relative to the U.S.
– Role equivalence: Mostly on a regional basis.
Immigrants (% of population)
Mauro F. Guillén. Source of the data: World Development Indicators.
Internet
http://3.bp.blogspot.com/_dr3S8zqPnj4/TTHr0nY_LxI/AAA
AAAAAThw/zX1W0OkerF0/s1600/global-traffic-maplarge.png
International Phone Calls
http://www.telegeography.com/research-services/telegeography-report-database/index.html
The Skype Effect
http://www.telegeography.com/research-services/telegeography-report-database/index.html
Democracy
Checks &
Balances
Size of the
State
NODE
COMPLEXITY
State Failure
Industrial
Diversification
Democracy
• Rapid spread.
• Democracies have multiple points of entry
for interest groups to influence the political
process.
• Democracies are “messy.”
• Democracies create a more complex socioeconomic structure within nodes.
The Spread of Democracy
Anocracies:
Incoherent polities with a mix of autocratic
and democratic authority patterns
•
•
•
•
•
•
Russia.
Armenia
Bhutan.
Sri Lanka.
Cambodia.
Venezuela.
•
•
•
•
•
•
•
•
•
Algeria.
Morocco.
Mauritania.
Sudan.
Angola.
Chad.
Guinea.
Zimbabwe.
Madagascar.
Checks & Balances
Based on Witold Henisz’s polconiii measure. Democracies = 6-10 on the Polity scale.
Size of the State
• Makes nodes more complex.
• Indicators:
– Taxation.
– Spending.
Total Tax Revenue
(% GDP)
Mauro F. Guillén. Source of the data: World Development Indicators.
Public Spending
(General Gov’t Consumption, excluding investment, % GDP)
Mauro F. Guillén. Source of the data: World Development Indicators.
Number of Failed States
Mauro F. Guillén. Source of the data: Center for Systemic Peace.
Source of the data: Center for Systemic Peace.
Industrial Diversification
• Countries with one dominant industry are
less complex:
– Chile (mining).
– Venezuela (oil).
• Countries with a more diversified industry
structure are more complex.
• There are implications for the susceptibility
of policymakers to pressure.
Average Herfindahl Index of
Industrial Diversification (4-digit)
Mauro F. Guillén. Source of the data: UNIDO Industrial Statistics.
Most Importantly
• Node complexity may make:
– The node more impervious to global
isomorphic forces.
– The effect of network complexity and network
coupling less strong.
– The node less likely to contribute to contagion.
• More on this in Lecture III.
Current
Account
Imbalances
Foreign
Portfolio
Investment
Trade in
Intermediates
NETWORK
COUPLING
Currency
Trading
Cross-Border
Banking
Global imbalances:
Current account, % GDP
EMA: East and Southeast Asia. OCADC: Europe, excluding Germany.
Mauro F. Guillén. Data from the IMF, Global Economic Outlook.
Current accounts and capital flows
direction of capital flows
Mauro F. Guillén. Source of the data: World Development Indicators.
Trade in Intermediates (% GDP)
Source: WTO.
The Paradox of Trade in Intermediates
• CAGR 1962-2003 in real terms: +6.4%.
• But trade in final consumer and capital goods
has increased even faster: +8.7%.
• As a % of total: down from 70.8% to 56.1%.
• Much more sensitive to the business cycle.
• However:
– It has grown fastest for developing countries,
especially since 2001 (11% CAGR vs. 4%).
– It has grown fast in electronics and automobiles.
– The effect of double-counting gets bigger as
more value is added.
– Gereffi and Grossman are correct.
Source: Sturgeon and Memedovic, “Mapping Global Value Chains.” UNIDO WP 05/2010.
Example: The iPhone
iPhone-related
U.S. Trade Deficit
with:
China
Japan
Final
value
Value
added
-1901.2
0
-73.5
-685.0
South Korea
Germany
0
0
-259.0
-341.0
Rest of the world
0
-543.0
Note: mn USD. Source: http://www.wto.org/english/res_e/statis_e/miwi_e/background_paper_e.htm
Consequences of Global Value Chains
• Efficiency:
– Produce each component in the lowest-cost
location.
• Vulnerability due to coupling:
– Especially when just-in-time versus just-in-case®
supply management is implemented:
• Political disruptions.
• Weather and other transportation contingencies.
• Major catastrophes: Japanese tsunami.
Source: IMF, Coordinated Portfolio Investment Survey.
Source: IMF, Coordinated Portfolio Investment Survey.
Dyadic Portfolio Investment Network
Source: IMF, Coordinated Portfolio Investment Survey.
Source: Alan Taylor in IMF, Financial Crises (2014).
Daily Currency Trading
(% of global GDP ~72 trillion USD)
Source: Bank for International Settlements.
Currency Markets
• Largest and most liquid of all.
• Over 5 million daily transactions totaling over
$5.3 trillion.
• Relatively “safe” thanks to the CLS settlement
system, a bank-owned platform launched in 2002:
– CLS (Continuous Linked Settlement) settles
transactions instantaneously as “payment-versuspayment,” thus minimizing counterparty risk.
Weathered the financial crisis relatively well.
– This is known as “Herstatt Risk” after the German
bank that collapsed in June 1974 triggering huge
counterparty losses.
Limitations of CLS
• 63 member financial institutions.
• Settles only 2/3 of total transactions.
• 17 currencies (95% of total transactions):
AUD, CAD, DKK, EUR, HKD, ILS, JPY,
MXN, NZD, NOK, SGD, ZAR, KRW,
SEK, CHF, GBP, and USD.
• U.S.-centric: Regulated by the NY Fed.
• Temptation of bilateral settlement by banks
in order to avoid fees.
• What if the Renminbi becomes more
important?
Regional Crises
• Increasing levels of network coupling due
to portfolio investment and currency trading
related to regional crises?
– Europe in the 1970s and early 90s.
– Latin America in the 1990s.
– East Asia in the 1996.
• Combination of footloose capital &
currency speculation can be lethal.
• More on this issue in Lecture II.
International Bank Positions
Total claims of banks* by counterparty location
Source: BIS. *Using the residence criterion for banks, i.e. without consolidating at the banking group level.
Source: BIS.
Financial
Interconnectedness
http://www.imf.org/external/np/pp/eng/2010/100410.pdf
Cross-Border Bank Lending
(locational by residence)
Reproduced with permission. http://www.imf.org/external/pubs/ft/wp/2011/wp1174.pdf
Cross-Border Banking Assets Q4 1999 (immediate borrower basis)
Source: BIS.
Cross-Border Banking Assets Q4 2006 (immediate borrower basis)
Source: BIS.
Cross-Border Banking Assets Q3 2013 (immediate borrower basis)
Source: BIS.
Cross-Border Banking Assets Q3 2013 (IBB) Full Sample
Source: BIS.
Network of Cross-Border Banking Assets, 1999-Q32013
(Immediate Borrower Basis)
Unit: millions USD. Source: BIS.
Network Coupling  Node Coupling
• Cross-border banking generates
network coupling.
• But it can also generate node
coupling:
– Example of the Euro Zone (Lecture II).
Network Interconnectedness and
Financial Crises
• Measured by connectivity, centrality, and
clustering.
• Has increased fastest among developed
countries (the global “core”).
• It tends to decrease during and after
financial crises.
• The 2007-08 event was the most
pronounced.
http://www.imf.org/external/pubs/ft/wp/2011/wp1174.pdf
Capital Mobility and Banking Crises
Sample: N=66 countries.
Source: Carmen M. Reinhardt and Kenneth S. Rogoff, “This Time is Different.” NBER WP 13882 (2008).
The Great Recession
Proportion of OECD Countries
with at least two consecutive quarters of GDP decline
Source: Figure 2.2 in Guillen and Ontiveros, Global Turning Points (Cambridge University Press, 2012).
Population
Ageing
Public
Debt
Urbanization
NODE
COUPLING
Income
Inequality
Wealth
Inequality
World
Developed Countries
Source: Population Division, United Nations.
Less Developed Countries
Least Developed Countries
Source: Population Division, United Nations.
Millionaires
(“High-Net-Worth Individuals”)
Country:
# of millionaires
(thousands)
Millionaires
% Women
2011
2012
World 2008
24
USA
3,068
3,436
World 2010:
27
Japan
1,822
1,902
North America
37
Germany
951
1,015
Japan
31
China
562
643
Asia-Pacific ex Japan
24
UK
441
465
Europe
18
France
404
430
Latin America
18
Canada
280
298
Middle East
14
Switzerland
252
282
Australia
180
207
Italy
168
176
Brazil
165
165
South Korea
144
160
Source of data: Capgemini/Merrill Lynch Global
Wealth Management Advisor Surveys 2009, 2011.
Implications for:
- Financial markets?
- Consumer markets?
- Elections?
Sandro Botticelli, Venus and Mars, c 1483. Tempera on panel, 69 cm x 173 cm, National Gallery, London.
Urbanization
Source: United Nations Population Division, World Urbanization Prospects: The 2011 Revision.
World’s Largest Cities 1960
Source: United Nations Population Division, World Urbanization Prospects, the 2011 Revision.
World’s Largest Cities 1980
Source: United Nations Population Division, World Urbanization Prospects, the 2011 Revision.
World’s Largest Cities 2011
Source: United Nations Population Division, World Urbanization Prospects, the 2011 Revision.
World’s Largest Cities 2025
Source: United Nations Population Division, World Urbanization Prospects, the 2011 Revision.
Growth of Cities
• Pressure on water and food systems.
• Tendency towards duality:
– Countryside/city.
– Within the city.
Government Debt (% GDP)
Advanced: Australia, Canada, France, Germany, Italy, Japan, Korea, the United Kingdom, and the United States.
Emerging: Argentina, Brazil, China, India, Indonesia, Mexico, Russia, Saudi Arabia, South Africa, and Turkey.
Source of the data: IMF.
Income Inequality within Countries
(Gini Coefficients for Developed Countries)
Mauro F. Guillén. Data Source: All the Ginis Dataset, World Bank.
Income Inequality within Countries
(Gini Coefficients for Emerging Countries)
Mauro F. Guillén. Data Source: All the Ginis Dataset, World Bank.
Another Indicator:
The Top 1%
• During the Great Recession, the income and
wealth of the top 1% came under scrutiny.
• In the United States, the “one-percenters”
have:
– More than $394,000 in income.
– More than $8.4 million in wealth.
Income of the Top 1% as a Percent of Total Income
Mauro F. Guillén. Data Source: World Top Incomes Database.
Poverty in Europe and the U.S.
• In the United States, the government
calculates that:
– 46 million (16%) are under the poverty
threshold ($23,050 income for a family of
four).
– Nearly 4 million are in extreme poverty (<$2
per day).
• In the European Union, a similar proportion
(16% of the population) lives in poverty or
at risk of being poor.
The Causes of Rising Inequality
•
•
•
•
•
•
Technological change.
Trade.
Foreign investment.
Growth of the service sector.
Welfare state retrenchment.
Growth of wealth accumulation (capital
gains).
• Changes in taxation.
• Growth of emerging economies.
Inequality within Nodes
• Impact on consumer markets (and economic
growth).
• Undermines the “social contract.”
• Reduces degrees of freedom during times of
crisis and adjustment.
• Therefore, it increases coupling.
The Middle Class
• Internally: Economic, political, and social
stabilizer.
• Externally, it can add to tensions:
– Race for natural resources: energy, minerals,
water, and food.
– Emulative consumption.
– Environmental degradation.
– Global climate change.
Middle class defined as people with more than $10 per day to spend but less than $100 (using purchasing
power parities).
Source: Homi Kharas, The Emerging Middle Class in Developing Countries (Presentation at Brookings, 2011).
Reproduced by permission.
Source: Homi Kharas, The Emerging Middle Class in Developing Countries (OECD, 2010).
Reproduced by permission.
Growth of the Financial Sector
• While relevant, I am not emphasizing it as
part of my framework.
• The financial sector (FS) has grown in size.
• No correlation between FS growth and GDP
growth.
• Wages in the FS have grown relatively.
• The FS has become more skill intensive.
• FS growth cannot be explained by unit cost
increases.
Source: Thomas Philippon and Ariell Reshef, “An International Look at the Growth of Modern Finance.”
Journal of Economic Perspectives 27(2) (Spring 2013):73-96.
In Sum
• Increasing node and network complexity.
• Increasing node and network coupling.
• As a result, the global system is
increasingly complex and coupled.
• What role does this play in the occurrence
and unfolding of crises?
Lecture II
Two Intriguing Cases
of Complexity & Coupling:
The EU vs. the EZ
The U.S. / China relationship
Complexity × Coupling
Table 1: Four System Configurations in terms of Complexity and Coupling
Complexity:
High
Low
Coupling:
Loose
Tight
Complex interactions
with built-in buffers
There is room to adapt in
response to deviations and
mishaps, even if systemic
Complex interactions
without buffers
Potential for disaster
Linear interactions
with built-in buffers
Very easy to manage
Linear interactions
without buffers
Deviations and mishaps not of
systemic nature
Source: Adapted from Charles Perrow, Normal Accidents: Living with High-Risk Technologies. New York: Basic Books, 1994.
System Complexity =
Node Complexity & Network Complexity
System Coupling =
Node Coupling & Network Coupling
The EU vs. the EZ
• The EU has become a more complex
network over time:
–
–
–
–
–
From 6 to 28 members.
Trade.
Foreign direct investment.
Tourism and migration.
Information flows.
• Each EU member has been compelled to
become more internally complex as well:
– Adopt democracy and checks & balances.
– Increase the size of the state.
The EZ is Tightly Coupled
• Network coupling:
–
–
–
–
–
Current account imbalances.
Trade in intermediates.
Portfolio investment, esp. government bonds.
Cross-border banking.
(Although not in terms of currency trading.)
• Node coupling:
–
–
–
–
Population ageing.
Public debt.
Income and wealth inequality.
European cities have not grown bigger but they
have become more dualistic.
Western Europe
Germany
Source: Population Division, United Nations.
France
UK
Source: Population Division, United Nations.
Spain
Italy
Source: Population Division, United Nations.
Public Debt (% GDP)
Source of the data: World Development Indicators.
Building Europe
• It was states pursuing their national interests
which built what we know today as the EU
(Moravcsik, The Choice for Europe).
• Gradually, they lost some sovereignty.
• The EZ represents a qualitatively different
type of integration:
– Gave the impression that countries could still
formulate their own fiscal and banking policies.
– Ultimately placed the weaker states between a
rock and a hard place.
– It increased node and network coupling.
Waves of Speculative Attacks on Currencies
1971
1973
USA
1
1
UK
1
1
Austria
1
1
Belgium
1
1
Denmark
1
France
1992
1994
South Africa
1
1997
1
Argentina
1
1
Brazil
1
1
1
Mexico
*
1
1
1
Peru
1
1
1
1
Venezuela
1
Germany
*
*
Italy
1
1
Netherlands
1
Norway
Taiwan
1
1
Hong Kong
1
1
1
Indonesia
1
1
1
1
South Korea
1
Sweden
1
1
Malaysia
1
Switzerland
1
1
Pakistan
1
1
Canada
Philippines
Japan
1
1
Singapore
Thailand
1
Finland
1
1
Greece
1
1
Vietnam
1
1
Czech Republic
1
Iceland
*
1
Ireland
1
Portugal
1
Spain
1
Australia
1
1
1 means currency suffered speculative attack
New Zealand
1
1
* Denotes first currency to be attacked
1
1
Hungary
1
Poland
1
Canada
1
1
*
1
1
1
Source: Reuven Glick and Andrew K. Rose, “Contagion and Trade. Why are Currency Crises Regional?”Journal of International Money and Finance 18 (1999):603-617.
Famous Instances of
Coupling-Induced Troubles
•
•
•
•
•
France in 1981.
Mexico in 1994-95.
The Asian Flu of 1997.
Argentina in 2001-02.
The Eurozone in 2009.
Stanley Hoffman criticizes integration
• “The logic of integration deems the uncertainties of
the supranational function process creative; the logic
of diversity sees them as destructive past a certain
threshold.” […] “As for methods, there was a gamble
on the irresistible rise of supranational functionalism.
[…] It assumed […] that the dilemma of governments
having to choose between pursuing an integration
that ties their hands and stopping a movement that
benefits their people could be exploited in favor of
integration by men representing the common good,
endowed with the advantages of superior expertise,
initiating proposals, propped against a set of
deadlines, and using for their cause the technique of
package deals.”
Source: Stanley Hoffman, “Obsolete or Obstinate?” (1966).
Tony Judt’s Skepticism
• “I am enthusiastically European; no informed
person could seriously wish to return to the
embattled, mutually antagonistic circle of
suspicious and introverted nations that was the
European continent in the quite recent past.
But it is one thing to think an outcome
desirable, quite another to suppose it is
possible. It is my contention that a truly united
Europe is sufficiently unlikely for it to be
unwise and self-defeating to insist upon it. I
am thus, I suppose, a Euro-pessimist.”
Source: Tony Judt, A Grand Illusion? (1996).
Taxes & Spending
• High levels of taxation and spending imply
tighter coupling within nodes.
• Levels are especially high in Europe.
Total Tax Revenue
(% GDP)
Mauro F. Guillén. Source of the data: World Development Indicators.
Public Spending
(General Gov’t Consumption, excluding investment, % GDP)
Mauro F. Guillén. Source of the data: World Development Indicators.
Super-Mario (Draghi)
Government-Bank Coupling
• Initially across nodes, i.e. cross-border.
• After the crisis exploded it became withinnode, i.e. domestic.
EU Banks’ Exposure to Sovereign Debt in 2008-2009
Source: Adrian Blundell-Wignall and Patrick Slovik, “The EU Stress Test and Sovereign Debt Exposures.” (OECD, August 2010).
Sovereign Bond Holdings
Source: Bruegel.
Sovereign Bond Holdings
Source: Bruegel.
Sovereign-Bank Risk
CDS Spreads for a Basket of European Countries and Banks
(basis points, weighted by gross debt)
500
Sovereign
450
Bank
400
350
300
250
200
150
100
50
0
J-08
J-09
Source: AFI.
J-10
J-11
J-12
J-13
Low Actual Labor Mobility
% of the population
that changes residence
each year
USA, inter-state
EU-15, cross-border
EU-15, cross-border ex Luxembourg
2.3
0.2
0.1
EU new members, cross-border
EU-15, cross-border commuting
EU-15, within-country inter-regional
0.2
0.6
1.0
Source of the data: European Commission, Geographic Mobility in the European Union (2008).
Germany vs. Europe:
An example of tight coupling
•
•
•
•
Europe is tightly integrated.
Europe is dependent on Germany.
Germany is dependent on Europe.
Coupling has become tighter over time,
especially in the wake of the crisis.
Intra-Bloc Exports
EU
Euro Zone
NAFTA
Asia
Latin America
Source of the data: European Central Bank.
% total
exports
68
48
48
49
22
European Commission, Current Account Balances in the EU (2012). Reproduced by permission.
European Commission, Current Account Balances in the EU (2012). Reproduced by permission.
European Commission, Current Account Balances in the EU (2012). Reproduced by permission.
Implications
• The EZ will remain unstable for the
foreseeable future.
• The relationship between Germany and the
rest of the EZ is crucial.
The U.S./China Relationship
• Interactive complexity.
• Tight coupling.
The U.S.-China Relationship
• Complex:
– Trade and foreign direct investment.
• Tightly coupled:
– Portfolio investment: government bonds.
– Mutual hostage taking that leaves little room
for error.
– Neither country can put unlimited pressure on
the other (unlike the U.S.-Japan relationship in
the 1930s or in the 1980s).
• Notorious implications for the global
system: trade, capital flows, and reserves.
U.S. / China Trade
• China: Less than half of its trade surplus is
with the U.S.
• U.S.: Less than half of its trade deficit is
with China.
U.S. vs China
United States trade deficit
2013
bn USD
China’s trade balance
2011
bn USD
China
-318
United States
+202
European Union
-125
European Union
+145
of which, with Germany
-67
India
+27
Taiwan
-90
-68
South Korea
-80
of which, with Saudi Arabia
-33
Japan
-46
of which, with Venezuela
-19
ASEAN
-22
Euro Zone
OPEC
-104
Japan
-73
Mexico
-54
Canada
-31
South Korea
-21
India
-20
Russia
-16
Sum of all trade deficits
-719
Trade deficit
-689
Foreign Holdings of U.S. Gov’t Securities
Bottom Line
• There is some tight coupling between the
U.S. and China using conventional
indicators.
• The U.S. / China dyad poses a different
kind of tight coupling in the world.
Quiz
1800s-1914
Largest
economy
Largest
trading
country
Largest
navy
Dominant
reserve
currency
1945-1990s
2000s-
Answers
1800s-1914
1945-1990s
2000s-
Largest
economy
China until
1888, then
USA
USA
USA for now,
China soon
Largest
trading
country
UK
USA
China (since
2007 in
merchandise,
since 2012 in
both goods &
services
Largest
navy
UK
USA
USA
Dominant
reserve
currency
Pound
Sterling
Dollar
Dollar (and
Euro)
Biggest Economies
•
•
•
•
•
1 - ca.1500: India.
ca. 1500 - ca.1888: China.
ca. 1888 - present: United States
2020? onwards: China.
The UK never was the largest economy. It
was the second largest 1820-1872. Before
1820 France was bigger, and after 1872 the
U.S. was bigger. Germany became bigger
than the UK in 1908.
• Western Europe as a bloc was the largest
economy ca. 1840-1942.
US and China: GDP Projection to 2020
Actual data 1980-2012. Assumes 7% growth rate in China, and 3% in the US.
Mauro F. Guillén. Source of data: World Development Indicators.
Biggest Merchandise Exporters
Mauro F. Guillén. Source of the data: World Development Indicators.
Biggest Exporters of Goods & Services
Mauro F. Guillén. Source of the data: World Development Indicators.
Largest Navies
Aircraft carriers
USA
11
Russia
1
China
0
Japan
0
UK
1
Missile submarines
Attack submarines
Total warships
18
53
341
16
32
282
6
52
239
0
18
109
4
8
100
Total personnel (‘000)
324
140
250
46
37
http://military-navy-army-airforce.blogspot.com/2012/10/list-of-top-10-largest-navies-in-world.html
Currency Allocation of Reserves
Mauro F. Guillen. Source of the data: IMF.
Source: Multipolarity: The New Global Economy (The World Bank, 2011).
MAURO F. GUILLEN
3455 S. Broad Street
Philadelphia, PA 19234
Cash
One dollar 00/100
November 25, 2013
1.00
SALVADOR DALÍ
214 Cadaqués St.
New York, NY 10001
Le Cirque
Three hundred and fifty-one dollars 27/100
May 21, 1968
351.27
The Dalí Principle
• Until when do you think Salvador Dalí was
able to enjoy a free lunch?
China’s Aspirations
“Chinese officials see renminbi
internationalization as advantageous for
their banks and firms, as part of the
broader process of rebalancing the
Chinese economy, and as a way of
reducing their dependence on the dollar.
In addition, renminbi internationalization
is integral to their vision for reforming the
international monetary system.”
—Barry Eichengreen, “Number One Country, Number one Currency?” World Economy 36(4):363-374.
China’s Challenges
“China faces significant challenges as it pursues renminbi
internationalization. While China may be a large
economy, it remains a poor one. Its financial markets lack
depth and liquidity. Encouraging international use of the
renminbi will require substantial liberalization of the
current account, in the course of which many things can
go wrong. As growth slows, China will face economic,
political and social tensions. There may then be pressure
for officials to slow or reverse the external financial
liberalization, state enterprise […] Finally, China’s
political system may be an obstacle to renminbi
internationalization. Foreigners will feel comfortable
holding financial instruments in China only if they believe
that their investments are secure.”
—Barry Eichengreen, “Number One Country, Number One Currency?” World Economy 36(4):363-374.
Money
• Means of exchange.
• Unit of account.
• Store of value.
Issuing the Reserve Currency
• Benefits:
– Lower transaction costs in trade.
– Lower interest rates.
– Prestige.
– Power & influence.
– You become an indispensable
country.
There’s also requirements…
•
•
•
•
•
•
Currency convertibility.
Free capital flows.
Rule of law.
Large and liquid market for securities.
Predictable government policymaking.
Fiscal responsibility.
Remember the
Spider-Man Principle
“With great power comes great responsibility.”
In Conclusion
• The EZ will remain inherently unstable for a
long time to come.
• The U.S. / China relationship can be seen as:
– Stabilizing: Two complementary countries
driving growth and providing an anchor to the
global trading and financial system.
– Destabilizing: China and the U.S. may develop
different agendas, and different degrees of
influence over global affairs. Plus there will
always be the temptation of the tertius gaudens.
Lecture III
Isomorphism, State Capacity,
and Institutional Diversity
Global Dynamics:
Isomorphic Pressures
Dynamic:
Mechanism:
Examples:
Normative
Shared ideologies, worldviews,
frameworks, or templates
Keynesianism, neoliberalism, democracy,
legal tradition
Coercive
Power, dependency
Hegemonic states,
multilateral agencies,
multinational firms
Mimetic
Frequency-based imitation to
cope with uncertainty and/or
secure legitimacy
Bandwagons, fads,
fashions
Emulative
Trait-based imitation driven by
the legitimacy of the source
Hegemonic states, states
considered to be
successful or innovative
Competitive Performance
Markets
Empirical Examples
Topic:
Drivers:
ISO 9000
certification
Coercive (state, MNEs), normative (cohesion in trade),
competitive (role equivalence in trade)
Central bank
independence
Coercive (trade, MNEs, IMF), normative (cohesion in trade),
competitive (role equivalence in trade)
Market reforms
Coercive (IMF), normative (cohesion), competitive (role
equivalence in trade)
Internet use
World-system status, competition, democracy,
cosmopolitanism
Stock markets
Normative (religion, legal tradition, economics), coercive
(IMF), competitive (role equivalence), imitation (regional)
Shareholder
capitalism
Normative (democracy, economics), coercive (IMF),
imitation (region), emulation (USA)
Sovereign debt
defaults
Normative (cohesion in trade), competitive (role equivalence
in trade)
Convergence and
differentiation
Little evidence of convergence; some within-cluster
convergence; increasing cross-cluster divergence
State Capacity
• “The ability of state institutions to effectively
implement official goals” (Hanson and Sigman
2013:2).
• State capacity is different from state goals or policy
priorities (Levi 1988; North 1981). Rather, it is the
infrastructure that enables states to pursue certain
goals or priorities, to get things done (Mann 1984).
• As Skocpol (1985:17) put it in an influential essay,
states have “capacities” related to their “territorial
integrity, financial means, and staffing.”
• Similar to “Weberianness” (Evans and Rauch 1999).
State Capacity and Isomorphism
• High levels of state capacity make adoption
of new models more likely in response to
normative, mimetic or emulative
isomorphism.
• States with more capacity have the means to
identify and evaluate alternatives proposed
or adopted elsewhere in the world, assess
their impact, and conduct follow-up studies
after implementation takes place.
State Capacity and Imperviousness
• Greater state capacity and greater state
spending shields countries from the vagaries
of global markets (Katzenstein 1985;
Rodrik 1998).
• State capacity makes countries more
impervious to coercive isomorphism.
Examples
• Central Bank Independence:
– Adoption of independent central banks driven
by isomorphic forces.
– Has resulted in a shift of power within the state.
– Critics abound, but it is the only effective actor
in the wake of the crisis.
• Shareholder Rights: What on earth is going
on?
Minority Shareholder Protections
Stock Market Cap as a % of GDP
by level of Minority Shareholder Protections
Highest Levels of de iure
protection of shareholders
•
•
•
•
•
•
•
•
Kazakhstan.
Russia.
Uzbekistan.
South Korea.
Mauritius.
Poland.
United Kingdom.
Japan.
State Capacity and SHRs
• State capacity increases SHR adoption.
• State capacity magnifies the effect of:
– Normative isomorphism: The effect of both
democracy and the professions is enhanced.
– Coercive isomorphism: State capacity does not
act as a shield but as a sponge.
– No significant interaction effect with mimetic
isomorphism.
Decoupling
• Coercion drives adoption but not outcomes:
– Stock markets (Weber et al. 2009): Coercive
adoption reduces stock market development.
– Shareholder capitalism:
• The main effect of SHR adoption increases market
cap and value of stocks traded, though not stocks
turnover.
• The interaction effect of SHR adoption with
coercive pressure reduces market cap and the value
of stocks traded.
Is the World
Getting Smaller?
“Certainly,” returned Ralph. “I agree with Mr.
Fogg. The world has grown smaller, since a
man can now go round it ten times more
quickly than a hundred years ago.”
—Gauthier Ralph and Phileas Fogg in Jules
Verne’s Around the World in Eighty Days
(1873, p. 19).
Dimensions
(a)
(b)
(c)
(d)
Minimum Volume Ellipsoid
Source: Heather Berry, Mauro F. Guillen, and Arun S. Hendi, “Is there Convergence across
Countries? A Spatial Approach.” Journal of International Business Studies, forthcoming, 2014.
Size of the World: Results
• The world has not evolved significantly
smaller in volume since 1960.
• Subcomponents such as core-periphery or
trade blocs exhibit increasing internal
convergence, and increasing divergence
between one another.
Source: Heather Berry, Mauro F. Guillen, and Arun S. Hendi, “Is there Convergence across
Countries? A Spatial Approach.” Journal of International Business Studies, forthcoming, 2014.
In a Nutshell…
• There is resilience to isomorphism.
• There is continuing diversity.
• There is decoupling between adoption and
outcomes.
Institutional Diversity
• Offers alternatives.
• Increases complexity.
• Reduces coupling, both internally and
externally.
• Contributes to the stability of the global
system.
Three Paradoxes
• Paradox of predictability:
– The global system is highly structured and predictable
(Wallerstein, Krugman).
– It is also prone to unpredictable disruptions, crises, and even
systemic breakdown.
• Paradox of coupling:
– There is increasing institutional decoupling between
adoption dynamics and outcomes (Meyer).
– Tight coupling within and among system components,
especially financially, economically, environmentally, and
demographically (Gilpin).
• Paradox of differentiated convergence:
– Pressures towards conformity and convergence (Meyer).
– Differentiation and specialization (Biggart, Krugman).