Financial Integration, Monetary
Unions, and Symmetry
(Correlation of Cyclical Fluctuations)
API-119 Lecture 8:
Guest Lecture by Jeff Frankel
Recap: Financial Integration Pros & Cons
• Pros: In API-120 & API-119, we learned that functions
of international financial markets include:
– Consumption Smoothing
• break the timing between production & consumption
– Risk Diversification
• insurance again shocks
– Efficient Allocation of Capital
• capital is at its most productive use;
• investors earn a higher return.
• Cons:
– These come with costs, such as volatility & crises.
– Capital does not always seem to flow the right direction!
Evidence from International Data
• In previous API119 lectures we saw
many puzzles in the literature:
• The theoretical benefits of financial integration
do not match evidence from international data.
– Feldstein-Horioka Puzzle
• High saving-investment correlations
– Risk Sharing Puzzle
• Low consumption correlations
– Lucas Paradox
• Capital does not flow from rich to poor.
The FeldsteinHorioka Puzzle
Feldstein-Horioka regression:
(I/GDP) = α + β (NS/GDP) + v.
Feldstein (1980) argued that if capital were
perfectly mobile, he would find β = 0.
Instead, β was much closer to 1.
The coefficient (“saving retention”)
fell a bit subsequently, but still high.
*
* See Table 2,
Appendix I
in this powerpoint.
There are many critiques of Feldstein-Horioka
• (I) National Saving is endogenous
• The “intertemporal optimization” critique -Private saving varies with the business cycle,
– or with population or productivity growth.
– Often: “A theoretical model can be constructed in which capital mobility
is perfect and yet the saving-investment correlation is high.”
– Obstfeld, Summers, Tesar…
• The “maintained external balance” critique –
– Fiscal policy is endogenous: governments react to trade imbalances
– Tobin, Westphal, Caprio & Howard, Roubini, Bayoumi, Buiter.
• (II) The world real interest rate is endogenous
– = The “big-country” critique.
– Murphy, Tobin, Obstfeld.
– But that doesn’t help explain the cross-section findings.
• The most common critique is that NS is endogenous,
• which should call for an Instrumental Variable.
• IV for Public Saving (BS): military spending
• IV for Household Saving: dependency ratio.
• Yet the IV estimates of the F-H coefficient
(“saving retention”) are as high as the OLS estimates !
* See Table 3, Appendix I in this powerpoint.
Evidence from Intra-national Data
Studies of data among regions within a common currency do not
show the puzzles: current account deficits & surpluses are big
enough to allow saving and investment to go their separate ways
• Feldstein-Horioka tests on regions within a common currency
– Sub-regions within the UK:
• Bayoumi, Tamim, & Andrew Rose (1992), "Domestic Saving and Intra-National Capital Flows," European Economic Review.
– Provinces within Canada (for 1961-1990) :
• Bayoumi, Tamim, & Gabriel Sterne (1992), "Regional Trading Blocs, Mobile Capital and Exchange Rate Coordination," IMF.
– Prefectures of Japan:
• Dekle, Robert (1996) "Saving-investment associations and capital mobility: On the evidence from Japanese regional data," JIE, Aug.
• Iwamota & van Wincoop (2000): Estimated coefficient is 0.3 in cross section, 0.2 in panel.
“Intranational versus International Saving and Investment co-movements, ” in Intranational Macroeconomics, Hess & van Wincoop, eds..
– States within the US (1950s data):
• Sinn, Stefan (1992+), "Saving-Investment Correlations and Capital Mobility: On the Evidence from Annual Data," Economic Journal.
• The same for nations under the gold standard (Bayoumi, 1990).
• The finding is never a high positive correlation between NS & I
– as is standard in international studies.
The prediction of the full risk sharing model
also holds up better on intra-national data:
– Crucini & Hess (2000):
cross-region consumption correlations > output correlations.
• On data from US states, Canada provinces & Japan prefectures.
»
“International versus Intranational Risk Sharing,” in Intranational Macroeconomics, Hess & van Wincoop, eds.
– Kalemli-Ozcan, Sorensen & Yosha (AER, 2003):
intranational risk sharing >> international risk sharing.
• On data from US states, Canada provinces, Japan prefectures,
UK regions, Italian regions, & Spanish regions
• Summary:
– Regions that are known to share a common currency and to be highly integrated with
respect to their goods markets pass the Feldstein-Horioka and risk sharing tests, while
standard international data fail the tests.
– Also, recall that tests by price-based criteria such Covered Interest Parity, financial
markets are highly integrated.
– An implication: exchange rate variability or other sources of imperfect integration of
goods markets may be the source of real interest differentials and quantity-based
findings of “low capital mobility”
– although this is not necessarily the authors’ interpretations of their own results.
Optimal Currency Areas
• Symmetry of GDP fluctuations is one of the main
criteria for Optimal Currency Areas (OCA).
• It goes back to Mundell (1961).
• OCA theory says that the benefits of a common
currency outweigh the costs if:
–
–
–
–
the shocks and cycles are similar
the countries are open to trade with each other
the degree of labor mobility is high
a system of risk-sharing is in place
• through stabilizing fiscal transfers
• or through stabilizing private capital flows.
Endogeneity – “Lucas Critique”
• OCA theory talks as if trade patterns and other parameters are
exogenous and unchanging.
• But the original motivation for currency unions such as EMU
was to promote trade within the region!
– Rose (2000) showed that countries with a common currency do
indeed trade more, as much as x2 or x3.
• An application of Lucas Critique:
you cannot rely on ex ante statistical estimates to analyze
the outcome of a change in regime (joining), because the
“parameters” will change after the new regime is in effect!
– You do not know in advance if it is optimal or not.
– One would have to derive everything from deeper parameters that
don’t change.
If intra-regional trade is endogenous
with respect to MU decision,
then cyclical correlations are likely to be as well.
(I) Eichengreen-Krugman hypothesis
on the sign of the endogenous effect of on correlations.
• Krugman (1993): when MU boosts intra-regional trade,
– countries specialize according to comparative advantage.
– So trade shocks become more idiosyncratic (asymmetric).
– Countries share production risk via integrated capital markets.
• More specialization in production induces a higher
degree of asymmetry (lower correlation of cycles)
– => Even if countries appear to satisfy OCA criterion ex ante,
• they may fail it ex post.
(II) Frankel-Rose hypothesis
on the sign of the endogenous effect of on correlations.
• Once countries are in EMU and trade more
– it leads to a lower degree of asymmetry,
– more highly correlated business cycles.
– => Even if countries appear to fail OCA criterion ex ante,
• they may satisfy it ex post.
• FR: empirically, more trade leads to more symmetry
• Frankel-Rose (1998), “The Endogeneity of
the Optimum Currency Area Criteria,” Econ.J.
Frankel-Rose Regression
• Corr (GDPi, GDPj) = a + b Tradeij + controls + error
– i-j are countries (pair-wise regression);
– Cross-section estimated over 5 year window
• b is estimated to be positive
with strong statistical significance,
– even when endogeneity of trade is handled by IV
• from the gravity model (proximity of pair, size, etc.).
– Supports F-R hypothesis over Eichengreen-Krugman.
Frankel-Rose:
Both OCA criteria, not just intra-union trade but also
symmetry, are more likely to hold ex post than ex ante.
Trade
OCA criterion
line
Countries should adopt
common currency
Countries
should float
Correlation of Business
Cycles Across Countries
“symmetry” of shocks
Evidence on the Competing Channel:
Building Block I
• Kalemli-Ozcan, Sorensen & Yosha (2003):
more capital market integration => more specialization,
using data from US states
– Regression: Spec i = a + b fin.integration i + error
– Spec i is a state/region within a country
– Spec i measures how much i’s production differs from
the rest of states within the country
– Integration i measures how financially integrated is i
with the rest of the states within the country.
– Estimate of b is positive and significant.
Evidence on Competing Channel:
Building Block II
• Kalemli-Ozcan, Sorensen, Yosha (2001) (KSY):
more specialization => less asymmetry.
• Recall FR Regression:
– Corr (GDPi, GDPj) = a + b Tradeij + controls + error.
• KSY Regression:
– Corr (GDPi, GDPagg) = a + b Fin.Integrationi + controls + error
– Dependent Variable ≡ correlation of i with the aggregate
– (country i is in)
To Summarize
Trade
Finance
Policy
Knowledge
MORE
MORE
Frankel & Rose
Intra-Industry
LESS
Inter-Industry
Kalemli-Ozcan, Sorenson & Yosha
MORE
Fluctuations Asymmetry
LESS
LESS
Which one dominates?
• Empirical papers above show both are important.
• No study yet runs a horse race
between the two channels
– which would require pair-wise data
both on trade linkages and on financial linkages
• But we have an experiment to evaluate
– European Crisis: 2010-…..
Joining Euro Zone
• One of the arguments made in favor of Euro
zone in the past is that even when member
countries are hit by asymmetric shocks, they still
do not need independent monetary policies
• Even if output shocks are asymmetric,
consumption will not be, thanks to integrated
capital markets!
• Sure enough, the periphery countries ran huge
CA deficits after joining: NS << I .
After the formation of the Euro, current account imbalances rose sharply
Current Crisis
• But the current euro crisis is a clear
indication that such insurance has not
been achieved among Euro zone countries!
Smoothing Fluctuations: Evidence
• US Smoothing (1999-2005):
– Capital Markets: 55%
– Federal Government: 15%
– Credit Markets: 30%
• Euro Zone Smoothing (1999-2005):
– Capital Markets: 10%
– Euro Zone Government: 0% (there is no such gov)
– Credit Markets: 35%
Euro Zone Fluctuations and Smoothing
• Clearly capital markets did not do the job,
whether because:
– Not integrated enough
– Not enough time passed since common currency
– Markets still segmented
– with different laws and jurisdictions
– Or maybe capital flows are procyclical
– contrary to theory !
• And of course this is not a fiscal union
– so there are supposed to be no fiscal transfers.
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Spreads over German Bunds show
integrated markets
1400
Big question:
why did markets
think these
periphery
countries were as
safe as Germany
upon joining euro?
Greece
Portugal
Ireland
600
500
400
300
Spain
200
Italy
100
Maastricht Criteria
• Many viewed that convergence according to
Maastricht criteria will prepare the countries
for OCA. Most important criteria:
– Debt levels < 60% of GDP
– All countries violated
European Debt Levels
Why it is a political problem in a
currency area with no fiscal union:
Exposure to Greek Debt
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
ECB (bought in open market)
Greek banks (held as collateral by the ECB)
Greek pension funds and insurance comp.
French banks
German banks
UK banks
Portuguese banks
US banks
Dutch banks
Italian banks
Austrian banks
Swiss banks
Belgian banks
Japanese banks
Spanish banks
Others (insurance, hedge funds)
55.0
40.0
30.0
56.9
28.3
14.7
10.2
8.7
5.2
4.5
3.3
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20.0
Frankel Appendices on Measuring
International Capital Mobility
1.
Feldstein-Horioka for developing countries.
2.
Interest Rate Parity: Country premium
•
•
vs. currency premium for Latin America in 1994.
Periphery euro countries versus emerging markets 2006-10.
Appendix 1:
The FeldsteinHorioka coefficieint
(“saving retention”)
appears no higher
for developing
countries than
for industrialized
countries –
the opposite of what
one would expect if
measured barriers to
capital mobility.
• IV for Public Saving (BS):
military spending
• IV for Household Saving:
dependency ratio.
ˡ
• Yet the IV estimates of
the F-H coefficient
(“saving retention”)
are as high as the
OLS estimates !
ˡ
Appendix 2:
Measuring factors in interest differentials
• Sometimes the effect of capital controls can be
isolated by offshore-onshore interest differentials
– including by the covered interest differential
to take out currencies difference (for countries with forward markets),
– or differential in local $-linked bonds vs. US T-bills.
• Sometimes currency premia can be decomposed.
• The effect of default risk can be isolated by the
sovereign spread on bank loans or bonds (EMBI).
Total interest
differential
(Local – US )
= (Currency
premium)
+ (country
premium)
= (Δse +
exchange
risk premium)
+ (country
premium)
On the eve of the Mexican peso crisis
Sovereign interest rates, in 3 crises
Source: IMF
Worst mis-pricing: Greece’s sovereign spreads 2003-08