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European Integration and the Feldstein-Horioka
Puzzle
Margarita Katsimi and Gylfi Zoega
European Integration and the Feldstein-Horioka Puzzle
Margarita Katsimia and Gylfi Zoegab
December 10, 2015
Abstract
We apply the differences-in-differences method to study the effect of the European
single market in 1993 and the euro in 1999 on the Feldstein-Horioka equation where
countries outside the single market serve as a control group and those within as a
treatment group. We find structural breaks that coincide with both events, in addition
to the financial crisis in 2008. The results suggest that the correlation between
investment and savings depends on institutions, exchange rate risk and credit risk.
Furthermore, the pattern of capital flows within the single market leaves a significant
part of the flows unexplained by fundamentals.
9971 words.
Keywords: Feldstein-Horioka puzzle, European integration.
JEL Classification: E2
a Department of International and Economic Studies, Athens University of Economics and
Business, 76 Patision Avenue, 10434 Athens. CESifo, Munich, Germany, [email protected]
b Corresponding author. Department of Economics, University of Iceland, 2 Saemundargata,
101 Reykjavik, Iceland. Department of Economics, Mathematics and Statistics, Birkbeck,
University of London, Malet St, London WC1E 7HX, [email protected]. CESifo, Munich, Germany.
Tel: +354 525 5239. Fax: +354 552 1331. Email: [email protected].
We are grateful to two anonymous referees for their comments on an earlier draft.
0
1. Introduction
A large and growing literature has attempted to explain the findings of Feldstein and
Horioka (1980) that savings and investment are correlated across countries. In this
paper we take advantage of a natural experiment to test whether the beginning of the
European single market in 1993 and the introduction of the euro in 1999 coincided
with a structural break in the savings-investment relationship in the European
countries but not in the rest of our sample of 30 countries. We use the differences-indifferences method by using countries that are outside the single market as a control
group and assuming that the saving-investment relationship would have evolved in the
same manner in countries currently within and outside the single market if these steps
towards European integration had not been taken. We can then show how the effect of
the single market and the euro affected the relationship for various groups of
European countries, such as those within and outside the euro zone, the northern part
of the euro zone and its southern periphery.
The FH equation is the following
(1)
where I denotes gross capital formation, S is savings, Y denotes GDP, u is an error
term and j is a country index. If capital was perfectly mobile across countries we
would find the coefficient b to be close to zero because a fall in savings in one country
would not affect domestic interest rates or investment. However, Feldstein and
Horioka found that the estimated coefficient of the saving rate was 0.887 in a cross
section of industrialized countries for the period 1960 and 1974. In a world of capital
mobility the finding appears puzzling since a fall in savings in one country should not
affect domestic interest rates or investment. The authors attributed their finding to
barriers to capital mobility.1
1
Several authors have provided explanations for the FH puzzle. Coakley et al. (1996) use the fact that
the difference between saving and investment equals the current account surplus in the national
accounts to focus their explanation on current account imbalances. According to these authors,
excessive current account deficits may raise the interest rate faced by a country in international capital
markets making further borrowing difficult. Similarly, as argued by Tobin (1983) and Summers (1988),
governments may dislike deficits for financial stability reasons and surpluses since they indicate room
for expansionary policies. Katsimi and Moutos (2009) find that the FH result is impervious to the use
of a broader view (i.e., including human capital) of investment and saving. Bai and Zhang (2010) show
that financial frictions can explain the FH puzzle.
1
This paper makes two contributions in the Feldstein-Horioka literature: First, it
shows that capital mobility as measured by the coefficient of savings in the FeldsteinHorioka equation is both time-varying and not unidirectional and then uses the
Frankel (1992) theoretical framework for interpreting changes in the coefficient
taking place in Europe in the past two decades. Frankel points out that a zero saving
retention coefficient (the FH perfect capital null) requires both real parity to hold and
national saving to be uncorrelated with the error term in the FH regression.
The second contribution is that the paper attempts to explain factors affecting
capital flows in Europe by exploring the pattern of capital mobility before the
financial crisis of 2008. The results suggest that a large part of the pattern is
unexplained by fundamentals, suggesting that one of the unintended consequences of
European integration may have been a flow of capital from core to peripheral
economies that led to asset price bubbles and financial instability in the periphery.
We will estimate the FH equation 1960-2014 for a sample of 19 EU Single market
and 11 non-single-market countries in order to test for structural breaks in the
equation coinciding with steps towards European integration and the recent financial
crisis. We first use a rolling 10-year panel regression, which is novel in the FH
literature in showing the variability of capital mobility over time, especially in
Europe. This stands in contrast to the conventional treatment of using time-averaged
cross-sectional regressions. Next, we perform panel estimation for the whole sample
period and test for structural breaks in the FH coefficient. By not confining our
sample to the EU countries we can compare and contrast structural breaks between the
euro zone, member countries of the single market that do not use the euro and
countries that do not belong to the single market. Using the differences-in-differences
method allows us to find the effect of the single market and the euro on the FH
coefficient for European countries. We will then investigate the determinants of
current account imbalances, which by definition equal the difference between saving
and investment, and argue that one unintended consequence of increased capital
mobility within the EU may have been asset price bubbles and financial instability in
the periphery economies.
2
2. Theoretical framework
Frankel (1992) explains how the FH puzzle may arise if other variables affect both
savings and investment. Thus countries with low tax rates may have both high saving
and investment rates. There is also the possibility that real interest rates are not
equalized across countries due to a country premium, exchange rate premium or the
expected depreciation of the currency. In this case a fall in savings in one country may
make real interest rates rise and investment fall. For the saving-investment correlation
to be zero the real interest parity must hold. The real interest rate differential can be
written as
(2)
where
and
denote domestic and foreign nominal interest rates,
and
are
expected domestic and foreign inflation, fd is the forward discount on the domestic
currency and
is the expected depreciation of the domestic currency. The first term
on the RHS of equation (2) is the covered interest differential and is defined by
Frankel (1992) as the 'country premium' since it captures country specific factors that
may not allow real interest rates to be equal such as the possibility of capital controls
or default risk. The second and third terms represent the exchange risk premium and
the expected real depreciation and together they form the 'currency premium'. The
elimination of both the 'country' and the 'currency' premium implies that the real
interest parity holds.
Two major institutional reforms increasing capital mobility have taken place in
recent decades. The first was the single European market in 1993 and the second the
introduction of the euro in 1999 (EMU). These may have affected the country and the
currency premium in equation (2). The introduction of the single market involved the
removal of capital controls with obvious implications for the country premium in
equation (2) above. The introduction of EMU may also have been important for the
currency premium. Regions within countries do not face currency risk when it comes
to intra-country capital movements. Thus regional authorities can be expected to be
less concerned about current account imbalances than national authorities. Real rates
of interest should also be the same across regions with given intra-country purchasing
power parity. Since the correlation between savings and investment should for this
reason be much higher between countries than between regions within a country, the
3
establishment of the euro zone in 1999 may have coincided with a structural break in
the coefficient of savings in the Feldstein-Horioka equation.2
Blanchard and Giavazzi (2002) studied current account balances, savings and
investment and found that the FH puzzle had disappeared in the euro zone. Telatar et
al. (2007) looked at nine EU countries for the 1970-2002 period and found that six of
these countries moved from a low to a high capital mobility regime with EMU.
Supportive evidence for a negative EMU effect on the saving retention coefficient has
also been found by Kumar and Rao (2009) in a sample of 13 OECD countries and
Choudhry and Kling (2014) in a sample of 252 countries. Smitz and von Hagen
(2011) find that current account imbalances widened significantly in the euro area
since the beginning of EMU while the current account balance of the euro zone as a
whole remained almost balanced. They find that capital flows follow differences in
capital endowments. These authors interpret their results as indicative of deepening in
financial market integration in the euro area and go so far as to claim that the
observed current account imbalances were a sign of the proper functioning of the euro
area. These studies do not look at differences between various groups of countries
within and outside the single market nor do they include the period of the recent
financial crisis. Choudhry and Kling find that capital mobility increased until the
beginning of the financial crisis and declined thereafter. Johnson and Lamdin (2014)
also find a positive impact of the financial crisis on the coefficient of the saving ratio
for the euro zone and non-euro countries of the EU. Specifically, they estimate the FH
equation for a sample of 40 OECD countries for the 1980-2012 period and find that b
increases (by 0.06) in the 2006-2012 period for the EU and euro zone countries while
for the rest of the countries the savings ratio coefficient remains unaffected. However,
somewhat surprisingly, they find that this effect comes from the 2006-2008 period
and disappears in the subsequent years.
Although the Feldstein-Horioka (FH) equation was initially estimated as a crosssection relationship, most recent studies use panel estimation techniques that allow
both for country heterogeneity and time-series variation. Many of these studies
involve testing for cointegration between savings and investment using a variety of
2
These results are supported by Helliwell (1998), Bayoumi and Rose (1993) for British regions,
Helliwell and McKitrick (1998) for Canadian regions and Sinn (1992) for U.S. regions.
4
standard or more sophisticated econometric techniques,3 while other studies attempt to
study the FH relationship using estimators that are consistent even in the absence of
cointegration.4
We depart from the earlier studies by classifying the 30 countries in our sample
into groups and then use the differences-in-differences method to find the effect of
institutional changes in Europe (single market and the euro) on the FH coefficient
using the countries outside the single market as a “control group”. One group of
countries includes the single market countries, another group has eurozone countries
in northern Europe, the fourth has eurozone countries in southern Europe and fifth and
final group has countries in the single market who are not a part of the eurozone.
Moreover, we extend the sample of observations to 2014 giving us six observations
for each country after the onset of the financial crisis in 2008.
In the following section we estimate a rolling ten-year window panel regression
for sub-groups of countries in order to describe the time series variation in the
coefficient of the saving rate in contrast with the static coefficient estimation from
long-run averaged cross-sectional regressions. This then provides a rationale for
investigating the time-series variation in the coefficient of savings, such as testing for
structural breaks due to institutional changes. We explore whether the FH coefficient
is sensitive to institutional changes, in particular the removal of capital controls in
Europe in the 1990s and EMU in 1999, and the financial crisis starting in 2008. One
could argue that the creation of the single market should decrease the 'country'
premium for participating countries while the fiscal crisis after 2008 must have
worked towards the opposite direction due to a rise in default risks. Also one would
expect the adoption of the common currency to reduce the 'currency premium' for
euro area countries.
3. Statistical results
We observe savings and investment for 30 OECD countries going back to 1960 and
ending in 2014. Unit-root tests and panel tests for cointegration between savings and
3
Miller (1988) is the first study using standard cointegration techniques while later studies such as
Caporale et al. (2005) employ various asymptotically efficient cointegration estimators. For a survey
see Apergis and Tsoumas (2009) and Kumar and Bhaskara (2009).
4
De Vita and Abbott (2002), Kollias et al (2008) and Coakley et al (2004).
5
investment show that over the period 1960-2014 many of the series have a unit root
and it is difficult to reject cointegration for the whole period, easier for the sub period
1993-2014 (see Table A1). The value of the LM test of Hansen (1992) rejects the null
of parameter stability for all countries but Belgium, Finland and Israel.
The figure below highlights the evolution of the FH coefficients from equation (1)
over time by plotting estimates for b using a "rolling window" of 10 observations.5, 6
Figure 1. The evolution of FH coefficients
1.2
1.0
euro zone
0.8
outside
single market
0.6
0.4
0.2
0.0
single market
- non-euro
-0.2
-0.4
1980
1985
1990
1995
2000
2005
2010
The coefficients are estimated using panel estimation with fixed effects, a moving ten-year sample and White cross-section
standard errors & covariance (d.f. corrected).
The figure shows that capital mobility increased more in the single-market countries
after 1993 than in the non-single market ones – the FH coefficient fell by more – and
that the subsequent fall in capital mobility after the financial crisis is strong in the
single market countries. It is interesting that capital mobility increased even more in
the non-euro single-market countries than in the euro zone after 1999. Also, note that
the FH coefficient has fallen in the past couple of years in the single market countries
– both within and outside the euro zone – indicating greater capital mobility.
Tables 1 and 2 show the results of (unbalanced) panel estimations of the FH
equation for all countries as well as groups of countries defined in the Appendix. In
5
6
For example the observation in 1980 is estimated using 1971-1980 data.
The list of countries belonging to each group is given in Appendix II. .
6
Table 1 we estimate equation (1) with OLS while in Table 2 we perform IV
estimations using the lagged savings ratio as an instrument in order to address a
possible endogeneity problem pointed out in the literature (see Feldstein and Horioka;
1980, Frankel; 1992). 7 In all estimations we use country fixed effects in order to
account for the remaining countries' characteristics. We allow for three time dummies
to test for structural breaks; one for the years 1993-98, another for 1999-2007 and the
third one for 2008-2014. The time dummies are also interacted with the saving rate to
test for structural breaks in the coefficient b in the equation above. A Wald test rejects
the hypothesis of a constant intercept term as well as a constant coefficient of the
saving rate across time.
Comparing the OLS coefficients in Table 1 to the IV coefficients in Table 2 one
can see that they are qualitatively quite similar. The values of the coefficients on the
saving ratio are somewhat higher in the IV regressions while the coefficients of the
interaction of savings with the time dummies have very similar values across
estimation methods in most cases.
For the whole sample of 30 countries we get a coefficient of 0.537 for the saving
rate in Table 1 (and of 0.638 in Table 2). The southern euro-zone countries seem to
have the lowest capital mobility over the whole sample period reflected in a
coefficient of 0.81 in OLS estimations and 0.86 in IV regressions, which is the highest
among the group of countries we examine. Countries outside the single market have a
coefficient lower than countries inside the single market (0.48 compared to 0.65 in
Table 1 and 0.56 compared to 0.75 in Table 2). To the extent that this difference
reflects lower capital mobility in the single market countries, it may also explain the
need for promoting free movement of capital through the creation of the single
market. Within the single market, the results from IV regressions indicate a similar
saving coefficient for the euro-zone and the non-euro countries whereas OLS
estimates point to a higher saving coefficient for countries using the euro.
Turning to the impact of the single market, the adoption of the euro and the
economic crisis, one can see in Table 1 that the coefficient of the saving rate for the
whole sample of countries shifts downwards in 1999-2007 to 0.076 and then back in
2008-2014 to 0.279. Similarly, in Table 2 the coefficient shifts downwards in 19997
We have also obtained similar results using alternative instruments such as the ratio of the population
aged 65+ and the benefit replacement rate. However, in order not to restrict our sample substantially
due to the availability of these instruments across countries and over time, we decided to perform the
IV regressions using the lagged savings ratio as an instrument. See, amongst others, Kasuga (2004).
7
2007 to 0.197 and then back in 2008-2014 to 0.424. This indicates greater capital
mobility in the 1999-2007 period, which is partly reversed during the crisis. In
contrast, both OLS and IV estimates indicate that the creation of the single market
does not seem to affect b when looking at the whole sample of countries.
In column (2) of Table 1 we see that, as expected, the creation of the single market
does affect b for the single-market countries. The coefficient of the saving rate falls
significantly from 0.648 to 0.443 in 1993-98 and further to -0.026 in 1999-2007.
About half of the fall in b is due to euro area creation is offset by the crisis after 2008
when it rises to 0.277. Interestingly, in Table 2 the effect of the single market was
more significant to the single-market countries that did not later adopt the euro. One
can see in column (4) for the non-euro single-market countries that the coefficient of
the saving rate falls significantly from 0.682 to 0.487 in 1993-98 and further to 0.039
in 1999-07. Again about half of the fall in b due to euro area creation is offset by the
crisis.
Although in countries outside the European single market capital mobility
appears not to be affected by the single market, euro zone creation seems to have
coincided with a decrease in the value of b in the whole sample. However, this effect
is much weaker for the non-single market countries (becomes statistically
insignificant in the OLS regressions) and much stronger for the euro zone. Column (3)
of Table 2 shows that the adoption of the euro coincides with a decrease of the
coefficient of the savings ratio for countries outside the single market to 0.376, which
is, however, five times higher than the same coefficient for single market countries
(0.078). The effect is greater within the euro zone as shown in column (5) of Tables 1
and 2 where the creation of the euro area decreases the value of the savings ratio
coefficient from 0.71 to -0.02 according to the OLS estimates and from 0.769 to 0.093
in IV regressions.
The financial crisis leads to a rise in the saving ratio coefficient throughout the EU
but it does not affect non-single market countries. The southern periphery of the euro
zone is affected more than its northern part and the single-market countries that do not
use the euro.
In lines 9-14 in Tables 1 and 2 we perform a differences-in-differences analysis to
show the results more clearly. This can be explained in terms of the equation below
where superscript E denotes a group of European countries (the treatment group),
8
NSM the group of countries outside the single market (the control group) and t
measures the time period; 60-92, 93-98, 99-07 or 08-14.
(3)
The equation calculates the difference in the change of the FH coefficient b between
time periods between a group of European countries, on the one hand, and the group
of non-single-market countries, on the other hand, which is equivalent to the
difference between time periods of the within-group difference. Thus we find whether
the coefficient of savings in equation (1) decreased more in the euro zone – or the
northern part of the euro zone, the southern part or the single-market countries that do
not have the euro – than in the control group, which has the non-single-market
countries.
As shown in lines 11-14 in Tables 1 and 2 the effect of the single market caused
the largest fall in b in the southern part of the euro zone and in the non-euro part of the
single market. The introduction of the euro has, as expected, the biggest effect in the
euro zone, especially in the northern countries. Finally, the financial crisis starting in
2008 raised the value of b similarly in the euro zone and non-euro zone single market
countries. Frankel's (1992) theoretical framework presented in equation (2) allows us
to understand better the rise in the saving ratio after 2008. The fiscal crisis after 2008
was a clear case of a rise in the 'country risk' reflected by the significant rise in default
risks. There is also the possibility of a euro exit creating currency risk in some of the
countries.
4.
Factors affecting capital flows
Increased capital mobility in the European single market starting in 1993 and in the
euro zone starting in 1999 may have increased economic efficiency; capital flowing to
equalize marginal rates of return. Differences in the age structure of the population
across countries, in output per capita and in growth prospects can thus be expected to
have played a role in affecting capital flows. There is also the possibility that the
capital flows have been destabilizing by generating unsustainable credit expansions
and asset price bubbles. Thus, capital flows have been blamed for the recent financial
crises in countries such as Greece, Iceland, Ireland and Spain.
9
In this section we explore to which extent observed current account imbalances
can be explained by differences in the population age structure of different countries
and by differences in growth rates and output per capita, on the one hand, and to
which extent they are unexplained hence possibly causing asset price bubbles and
financial instability, on the other hand.
The life-cycle hypothesis (see Modigliani, 1975) and the national account identity
imply that the age structure of the population should affect current-account balances
so that a country with proportionately more young and old people should have deficits
and a country with proportionately more middle-aged people should have current
account surpluses. Studies of the relationship between the age structure and the
current account go back to the work of Leff (1969) who regarded dependency rates as
the determinant of saving rates.8
In addition, we include variables measuring economic growth defined as the rate
of growth of output per capita, the level of output per capita and budget balances for
the government as a ratio to GDP. Economic growth is included because in the
medium to long term higher growth rates may reflect differences in the rate of
technological progress which may coincide with an inflow of capital. A country
having high rates of technological progress could be expected to have a greater
demand for capital that would be expected to generate a capital inflow and current
account deficits. The level of GDP per capita is included because a lower level of
output per capita may reflect a higher marginal product of capital in a given country if
its steady-state output per capita is the same as elsewhere. Thus Schmitz and von
Hagen (2011) find that the elasticity of net capital inflows with respect to output per
capita increases significantly after the adoption of the common currency for euro zone
countries. Finally, government budget balances may be related to the current account
since the sum of private and public savings net of investment has to equal the current
account surplus. While the presence of such “twin deficits” does not prove prima
facie evidence for causality, the link between the two may be stronger within a single
currency area.
8
A relationship between age structure variables and domestic savings has been found by many authors,
such as Fry and Mason (1982), Mason (1987, 1988), Higgins (1998), Lindh (1999), Herbertsson and
Zoega (1999), Bloom et al., (2010) and Gudmundsson and Zoega (2014). In an interesting paper,
Taylor and Williamson (1994) explain the capital flow from Britain to Australia, Canada, the U.S. and
Argentina in the late 19th century, early 20th century by high youth dependency ratios in the colonies.
10
Table 3 reports the results for the sample of 30 countries for the period 1981 to
2007.9 We end the sample in 2007 so as not to allow the financial turbulence of the
years 2008-2011 to affect our estimates. The dependent variable is the current account
surplus as a share of GDP (in per cent). Among regressors we include two age groups,
0-24 and 65+ (in percentage of total population) in addition to the annual rate of
growth of output per capita (in percentage), the level of output per capita (US
thousands of dollars per capita at 2005 prices) and the budget balance as a share of
GDP (in percentage).
We start by introducing time dummies; the first takes the value one for each year
since the start of the single market in 1993 and zero for all earlier years and another
that takes the value one for each year since the start of the euro zone in 1999 and zero
for all other years. We report the results of the pooled estimation in column (1) and
the fixed effect estimation in column (2) using annual data. In columns (3) and (4) we
then remove the time dummies and replace them with a dummy for the single market
countries and a dummy for the euro zone countries. 10 The effect of each of the
variables can then be found by looking at three coefficient estimates when the relevant
variable is interacted with each dummy variable. Thus if one were interested in the
effect of having a higher budget surplus on the current account surplus in column (4)
for a euro zone country, one would add up the three coefficients of that variable that
are statistically significant – the coefficient of the budget surplus variable, the
coefficient of the variable interacted with the dummy variable for membership of the
single market, and the coefficient of the variable interacted with membership of the
euro zone. In this case the only significant coefficient is that of the variable interacted
with the dummy variable for the single market, which is 0.29, implying a positive
effect on the current account – a 1% budget surplus goes with 0.29% current account
surplus.
The results show that current account surpluses tend to be associated with
government budget surpluses in the single market and high level of GDP per capita,
the latter effect especially strong in the euro zone. High growth rates have a negative
coefficient in the last time period (1999-2007) when time dummies are used but in the
9
Korea excluded because of missing data on government budget balances.
When a single-market country enters the euro zone the value of the single-market dummy remains
equal to one while the value of the euro zone dummy changes from zero to one. If a country remains in
the single market and does not enter the euro zone (Sweden for example) then the single market
dummy also remains equal to one.
10
11
euro zone high growth and current account surpluses appear to go together. Thus it is
the output per capita and the budget surplus variables that most clearly affect current
account surpluses in the expected way.
The relationship between the current account and the demographic variables is
such that the higher the proportion of the old, the smaller the current account surplus
or the larger the deficit in the period 1999-2007 when fixed effects are used.
However, this relationship does not appear in the fixed effect estimation for the euro
zone in column (4). As shown by Gudmundsson and Zoega (2014) this should not
come as a surprise because based on the age structure Germany, Austria, Belgium and
Denmark should have smaller surpluses while the age structure cannot fully explain
the current account deficits of Greece, Portugal and Spain. Somewhat surprisingly, the
higher the proportion of the young, the larger the current account surplus. Again, this
shows that the age structure of the population cannot explain the pattern of current
account surpluses in this sample of countries.
Looking closer at the results using time dummies in columns (1) and (2), the
growth variable has a negative and statistically significant coefficient during the
period 1999-2007 implying that a 5% increase in the rate of growth (as from 1% to
6%) reduces the current account by 1.15% of GDP (using the coefficient estimate 0.23 = -0.33 + 0.10 from the fixed effect estimation). Note that the sign of the
coefficient is positive before 1999. Output per capita has a positive and statistically
significant coefficient in all periods using the fixed effect estimation. Finally, the
budget surplus has a positive and significant coefficient after 1993 under the fixed
effects estimation and for the period after 1999 using the pooled estimator, implying
that a 5% increase in the budget surplus (as a fraction of GDP) will make the current
account improve by 1.15% of GDP using the fixed effect estimator.
The variable measuring the share of the population over 65 (old) is statistically
significant and negative in the post 1999 period. During this period the current
account surplus is smaller the greater the proportion of old people in the population.
However, it is positive in the period 1993-1998. The coefficient for the young is, in
contrast to what was expected, positive after 1999 (-0.39+0.64=0.25) when using the
fixed effects estimator, albeit smaller than the coefficient of the old.
Now turning to columns (3) and (4) where the time dummies are replaced by
dummy variables for the single-market countries and the euro zone countries we find
that within the euro zone high output per capita has a positive effect on the current
12
account surplus. This implies that within the euro zone current account deficits – that
is capital inflows – coincide with low GDP per capita. Budget surpluses are also
associated with current account surpluses within the single market. What is surprising,
however, is the current account surpluses within the euro zone are not explained by
the population under 25 and over 65 years of age. There is even a positive relationship
between the share of the population in these age groups and the current account
surplus within the single market.11
The R-square of the pooled estimate in column (1) of Table 3 is 0.43 while the
fixed effect estimate has an R-square of 0.76. This implies that a significant share of
the capital flows is unexplained by the factors considered here. The residuals from the
four regressions show that Germany, Austria, Canada, Norway, Sweden and
Switzerland developed unexplained current account surpluses in the 2000s while
Belgium, Estonia, Greece, Ireland, Iceland, Italy, New Zealand, Portugal, Spain and
the U.K. had unexplained deficits during this period. This opens the possibility that
speculative capital flows from northern European countries to the southern periphery
of the euro zone, Estonia, Ireland, and Iceland may have caused the financial crises
that hit these countries in the late 2000s. Investors may thus have wrongly assumed
that the country premium (credit risk) in equation (2) was permanently lowered in all
EU economies whereas it returned with a vengeance during the financial crisis.
In Figure 2 we take the average value of the residuals for 2001-2007 from the
fixed effect estimation of our equation in column (4) in Table 3 and plot them against
the actual current account surpluses.
12
Note that the countries with the largest
unexplained deficits suffered financial crises in 2008-2009 while the ones with the
unexplained surpluses did not have a crisis. The current account deficits reflect a
capital inflow that preceded the crises, which went through the banks in the case of
Iceland, Ireland and Spain and the sovereign in the case of Greece and Portugal.13
11
Using a 55 country sample used by Gudmundsson and Zoega (2014) we find a stronger effect of the
age structure in the predicted direction.
12
Australia (aut), Austria (aus), Belgium (bel), Canada (can), Chech Republic (cze), Denmark (den),
Estonia (est), Finland (fin), France (fra), Germany (ger), Greece (gre), Iceland (ice), Ireland (ire), Italy
(ita), Japan (jap), Netherlands (net), Norway (nor), New Zealand (nze), Poland (pol), Portugal (por),
Poland (pol), Slovenia (slove), Slovakia (slova), Spain (spa), Sweden (swe), Switzerland (swi), UK
(uk) and the US (us).
13
A major financial crisis hit Belgium in 2008 when two large banks, Fortis and Dexia, encountered
liquidity as well as solvency problems. At the same time British banks had problems requiring the
government to offer a rescue package intended to restore confidence in the banking system. The
bursting of a house price bubble made the Irish banks insolvent requiring the government to stabilise
them by taking on large liabilities. A housing bubble also burst in Spain in. The Icelandic banks failed
13
Figure 2. The current account and its unexplained component
15
current
account
(%)
10
nor
swi
net
5
ger
den
aus can
isr
chi
slove
fra
uk ita ire
pol cze
nz aut
us
slova
spa
gre
est por
-5
ice
-10
swe
jap
bel
0
fin
-15
-6
-4
-2
0
2
4
6
residual from Table 3
We next reduce the sample of countries to the six surplus countries (Austria,
Canada, Germany, Norway, Sweden and Switzerland) and ten deficit countries
(Belgium, Estonia, Greece, Ireland, Iceland, Italy, New Zealand, Portugal, Spain and
the U.K.). In Table 4 we estimate the FH equation presented in Tables 1 and 2 and
discussed in the previous section for these six surplus and the ten deficit countries. As
in Tables 1 and 2, the IV estimations produce in general higher coefficients than OLS.
One can see that the creation of the single market reduced the coefficient for the
saving rate more in the deficit countries than in the surplus countries. As a result of
the single market creation deficit countries seem to have experienced a higher rise in
capital mobility than the surplus countries reflected in a savings rate coefficient of
0.26 in OLS estimations and of 0.44 in IV estimations instead of 0.38 and 0.52
respectively. In contrast, the creation of the euro area seems to have led to a slightly
stronger decrease in the savings coefficient for the surplus countries. The financial
crisis led to a decrease in capital mobility in both groups however, although the
impact was stronger for the surplus countries. The rise in the saving rate coefficient
for the surplus countries was roughly as high as its initial fall due to the creation of the
in October 2008. Greece and Portugal had a sovereign debt crisis in 2010 and. The Baltics also had a
crisis when domestic credit expansion came to an end.
14
single market while it was much smaller for the deficit countries. Specifically the
financial crisis increased the coefficient to 0.33 in surplus countries and to 0.16 in
deficit countries according to the OLS estimates.14
Finally, we explore further whether the explanatory variables can account for the
pattern of current account surpluses and deficits by repeating the estimation in Table 3
for this narrower set of countries. The results are shown in Table A2 in Appendix I.
The R-square of both the pooled as well as the panel regressions in columns (1) to (4)
tend to be lower than before in Table 3. Moreover, the residuals show the same
pattern of rising surpluses in the first group of countries as before, most importantly in
Germany, while the residuals in the second group, such as in the crisis countries of
Iceland, Ireland, Portugal, Spain and Greece, show rising deficits in the 2000s. The
model thus does not help explain the pattern of surpluses and deficits in the 2000s
based on fundamentals leading up to the financial crises in the deficit countries.
5. Conclusions
Frankel (1992) pointed out that for investment and savings to be perfectly
uncorrelated requires real interest rates to be equalised across countries – thus a zero
country and currency premium. The single market could be expected to have reduced
the country premium by making its country commit to the free flow of capital and the
euro would by definition have abolished the currency premium. Finally, the financial
crisis has increased the country premium and even raised the currency premium
through the threat of euro exit by some members of the euro zone.
Our results confirm changes to the coefficient of savings in the FH equation that
coincide with the single market, the introduction of the euro and the financial crisis
beyond the changes observed in the control group of countries outside the single
market. We find that the increase in the FH measure of capital mobility coincides with
the start of the European single market in 1993 and the introduction of the euro in
1999. We find that the former effect occurs in single-market countries that remain
outside the euro zone whereas the latter is greater in the euro zone countries. The
increased capital mobility within the euro zone consists of capital coming from
nations with a higher output per capita and government budget surpluses. Also, the
financial crisis that started in 2008 has led to a fall in the FH measure of capital
14
The difference is smaller when the IV estimator is used.
15
mobility in the single market. This recent development has occurred in both the
member states of the single market that use the euro as well as in those countries that
use their own currencies. However, capital mobility has increased in the past couple
of years in the single market, both within and outside the euro zone. In contrast, the
financial crisis has not affected the magnitude of the savings ratio coefficient in nonsingle market countries significantly.
We conclude that the institutional changes that followed the Maastricht treaty that
created the single market in capital and eventually the introduction of the euro
increased capital mobility in the member countries beyond what was observed in
countries outside the euro zone. The financial crisis also reduced capital mobility
more in these countries. Lastly, we cannot account fully for the pattern of current
account surpluses, which suggests that the capital flows may have had destabilising
effects within the single market.
Acknowledgements
We gratefully acknowledge comments by Ron Smith and Jerry Coakley and seminar
participants at Athens University of Economics and Business and the Central Bank of
Turkey on an earlier draft. This work was supported by the Icelandic Research Fund
(IRF – grant number 130551-052) and the University of Iceland Research Fund.
16
Table 1. Panel estimation : OLS with F.E.
All countries
Single market
Non-single market
Euro zone
Euro zone - north
Euro zone - south
(3)
16.577***
(5.87)
Single market noneuro
(4)
12.968***
(9.30)
(1)
15.342***
(9.00)
(2)
10.982***
(11.11)
(5)
9.437***
(6.54)
(6)
10.211***
(6.82)
(7)
7.155**
(3.53)
c93-98
-0.835
(-0.61)
1.583
(1.17)
-0.790
(-0.68)
1.379
(0.76)
-0.128
(-0.05)
-1.952
(-0.63)
4.696***
(2.85)
c99-07
8.538***
(3.44)
13.210***
(5.02)
2.604
(0.80)
10.728**
(2.42)
14.628***
(4.67)
7.980*
(1.81)
12.672***
(2.81)
c08-14
1.941
(1.15)
4.153***
(3.31)
-0.639
(-0.24)
2.375**
(2.05)
5.315***
(3.23)
5.450
(1.37)
6.923***
(4.67)
S/Y
0.537***
(8.21)
0.648***
(15.80)
0.476***
(4.60)
0.505***
(7.71)
0.710***
(12.03)
0.688***
(9.89)
0.810***
(10.13)
d93-98*s
-0.057
(-0.86)
-0.205***
(-3.12)
0.020
(0.50)
-0.220**
(-2.36)
-0.119
(-0.91)
-0.049
(-0.33)
-0.317***
(-3.61)
d99-07*s
-0.461***
(-4.38)
-0.674***
(-6.14)
-0.215*
(-1.81)
-0.593**
(-3.54)
-0.726***
(-4.93)
-0.487**
(-2.41)
-0.517**
(-2.03)
d08-14*s
-0.258***
(-3.73)
-0.057
-0.404
0.203
-0.077
-0.169
0.067
30
1127
0.658
-0.371***
(-7.40)
-0.205
-0.469
0.303
-0.225
-0.234
0.167
18
669
0.624
-0.079
(-0.87)
0.020
-0.235
0.136
8
349
0.744
-0.288***
(-5.46)
-0.220
-0.373
0.305
-0.240
-0.138
0.169
5
201
0.655
-0.423***
(-7.18)
-0.119
-0.607
0.303
-0.139
-0.372
0.167
11
428
0.601
-0.441**
(-3.03)
-0.049
-0.438
0.046
-0.069
-0.203
-0.090
7
265
0.584
-0.450***
(-7.68)
-0.317
-0.2
0.067
-0.337
0.035
-0.069
4
163
0.641
6.22(0.00)
7.49(0.00)
8.44(0.00)
18.89(0.00)
1.02(0.44)
2.00(0.20)
2.15(0.24)
11.03(0.02)
13.03(0.00)
31.98(0.00)
2.65(0.14))
5.80(0.03)
15.49(0.02)
824(0.00)
Constant
Difference: 60-92 and 93-98
Difference: 93-98 and 99-07
Difference: 99-07 and 08-14
Differences in differences 93-98/60-92
Differences in differences 99-07/93-98
Differences in differences 08-14/99-07
Countries (clusters)
Observations
R squared
Wald test
F: c93-98= c99-07= c08-12=0
F: d93-98= d99-07= d08-12=0
Standard errors clustered by country d.f. corrected. t-ratios in parentheses. Significance denoted by stars: *** at the 1% level, ** at the 5% and * at the 10% level of significance.
17
Table 2. Panel estimation, IV with F.E.
All countries
Single market
Non-single market
Single market noneuro
Euro zone
Euro zone - north
Euro zone - south
(1)
8.505***
(12.12)
(2)
5.549***
(5.53)
(3)
10.094***
(10.66)
(4)
6.900***
(4.33)
(5)
8.652***
(4.97)
(6)
2.038
(0.92)
(7)
5.574
(1.63)
c93-98
-2.271*
(-1.79)
0.063
(0.04)
-1.013
(-0.64)
1.325
(0.80)
-4.313
(-1.54)
-5.649*
(-1.67)
6.318
(0.72)
c99-07
8.127***
(7.08)
13.313***
(8.75)
1.893
(1.30)
11.954***
(5.66)
13.681***
(6.51)
5.006
(1.62)
12.710***
(3.03)
c08-14
1.133
(1.07)
3.690***
(2.62)
-0.291
(-0.21)
3.164
(1.61)
3.214
(1.33)
-1.235
(-0.22)
5.422
(1.30)
S/Y
0.638***
(17.95)
0.753***
(15.16)
0.559***
(11.12)
0.682***
(7.89)
0.769***
(10.47)
0.830***
(9.48)
0.860***
(5.66)
d93-98*s
0.014
(0.24)
-0.125*
(-1.84)
0.030
(0.39)
-0.195**
(-2.55)
0.081
(0.64)
0.124
(0.83)
-0.388
(-0.93)
d99-07*s
-0.441***
(-9.05)
-0.675***
(-10.42)
-0.183***
(-3.03)
-0.643***
(-7.86)
-0.676***
(-7.29)
-0.371***
(-2.84)
-0.504**
(-2.56)
d08-14*s
-0.214***
(-4.72)
0.014
-0.455
0.227
-0.016
-0.242
0.139
30
1086
0.650
-0.335***
(-5.57)
-0.125*
-0.55
0.34
-0.155
-0.337
0.252
18
649
0.593
-0.095
(-1.62)
0.030
-0.213
0.088
8
334
0.739
-0.317***
(-3.97)
-0.195
-0.448
0.326
-0.235
-0.235
0.238
5
194
0.619
-0.299***
(-2.82)
0.081
-0.757
0.377
0.051
-0.544
0.289
11
416
0.567
-0.134
(-0.55)
0.124
-0.495
0.237
0.094
-0.282
0.149
7
258
0.495
-0.315
(-1.48)
-0.388
-0.116
0.189
-0.418
0.097
0.101
4
158
0.610
69.38(0.00)
97.72(0.00)
89.50(0.00)
17.353(0.00)
3.38(0.34)
10.83(0.01)
34.33(0.00)
65.43(0.00)
72.23(0.00)
68.61(0.00)
7.48(0.06)
10.91(0.01)
1.39(0.01)
6.63(0.08)
Constant
Difference: 60-92 and 93-98
Difference: 93-98 and 99-07
Difference: 99-07 and 08-14
Differences in differences 93-98/60-92
Differences in differences 99-07/93-98
Differences in differences 08-14/99-07
Countries (clusters)
Observations
R squared
Wald test
F:
F:
Standard errors clustered by country d.f. corrected. t-ratios in parentheses. Significance denoted by stars: *** at the 1% level, ** at the 5% and * at the 10% level of significance.
18
Table 3. The current account and fundamentals (1981-2007)
Periods
Constant
Young
Old
Growth
Output per capita
Budget surplus as
share of GDP
(1)
Pooled
0.20
(0.05)
-0.09
(1.51)
0.12
(1.22)
(2)
F.E.
-28.52*
(3.02)
0.64*
(3.07)
0.16
(0.85)
0.20*
(2.11)
0.001*
(6.15)
0.10*
(2.30)
0.002*
(3.40)
Growth
0.05
(0.88)
0.001
(0.01)
Budget surplus as share
of GDP
1993-1998
Constant (93-09)
Young
Old
Growth
Output per capita
Budget surplus as
share of GDP
Young
Old
Growth
Output per capita
Budget surplus as
share of GDP
Cross sections
Observations
R-squared
Young
Old
Output per capita
0.09
(1.06)
0.001*
(12.45)
0.14*
(2.91)
0.002*
(3.29)
0.06**
(1.70)
0.02
(0.43)
-27.24*
(6.82)
0.31*
(3.58)
1.42*
(12.26)
-0.65*
(4.51)
-0.003*
(2.25)
0.39*
(6.95)
-17.73*
(3.53)
0.34*
(3.06)
0.73*
(4.55)
-0.27*
(2.46)
-0.002**
(1.82)
0.29*
(4.90)
-7.79
(0.80)
0.04
(0.24)
-0.72*
(2.06)
0.82*
(5.06)
0.54*
(18.69)
0.01
(0.08)
29
586
0.49
-22.81*
(2.62)
0.20
(1.29)
0.41
(1.38)
0.34*
(2.48)
0.04*
(6.91)
0.15
(0.35)
29
586
0.76
Single market countries
-12.62*
(2.91)
0.11
(1.41)
0.74*
(5.60)
-0.19
(1.06)
-0.001*
(2.64)
0.11
(1.17)
-4.05
(0.63)
0.04
(0.29)
0.47*
(2.99)
0.05
(0.54)
-0.001*
(2.97)
0.13**
(1.89)
1999-2007
Constant (99-09)
Constant
Participation in European
integration
(3)
(4)
Pooled
F.E.
2.64
-12.44**
(1.24)
(1.92)
-0.16*
0.22**
(3.79)
(1.70)
0.10*
0.16
(1.98)
(1.09)
Constant (93-09)
Young
Old
Growth
Output per capita
Budget surplus as share
of GDP
Euro zone countries
7.26
(1.49)
-0.01
(0.17)
-0.38*
(2.63)
-0.75*
(4.51)
0.0003*
(2.41)
0.48*
(5.64)
29
586
0.43
24.87*
(3.68)
-0.39*
(2.96)
-0.76*
(3.92)
-0.33*
(2.55)
0.001
(4.87)
0.23*
(2.71)
29
586
0.76
Constant (99-09)
Young
Old
Growth
Output per capita
Budget surplus as share
of GDP
Cross sections
Observations
R-squared
White cross-section standard errors & covariance (d.f. corrected p). t-ratios in parentheses.
Significance denoted by stars: * at the 5% and ** at the 10% level of significance.
19
Table 4. Panel estimation, OLS and IV with F.E.: Surplus and Deficit Countries
Surplus countries
(OLS)
11.422***
(6.60)
Surplus countries
(IV)
5.361***
(2.67)
Deficit countries
(OLS)
9.213***
(6.35)
Deficit countries
(IV)
4.577**
(2.49)
c93-98
3.206
(1.71)
2.737
(1.62)
5.943***
(3.29)
4.810**
(2.02)
c99-07
9.672**
(3.43)
9.742***
(5.17)
11.788*
(1.95)
11.040***
(3.39)
c08-14
2.604
(0.89)
2.962
(1.26)
6.077**
(2.79)
3.946*
(1.67)
S/Y
0.631***
(9.53)
0.733***
(10.63)
0.681***
(9.53)
0.791***
(8.37)
d93-98*s
-0.248**
(-3.19)
-0.214***
(-2.74)
-0.416***
(-4.43)
-0.345***
(-2.91)
d99-07*s
-0.562***
(-5.07)
-0.565***
(-7.11)
-0.551
(-1.76)
-0.482***
(-2.94)
d08-14*s
-0.302**
(-3.51)
-0.248
-0.314
0.26
6
294
0.648
-0.321***
(-3.47)
-0.214
-0.351
0.244
6
285
0.636
-0.517***
(-3.66)
-0.416
-0.135
0.034
10
357
0.620
-0.338***
(-2.67)
-0.345
-0.137
0.144
10
342
0.586
3.95(0.07)
10.43(0.01)
30.80(0.00)
53.16(0.00)
4.99(0.03)
13.46(0.00)
12.00(0.00)
12.14(0.01)
Constant
Difference: 60-92 and 93-98
Difference: 93-98 and 99-07
Difference: 99-07 and 08-14
Countries (clusters)
Observations
R squared
Wald test
F:
F:
Standard errors clustered by country (d.f. corrected). t-ratios in parentheses. Significance denoted by
stars: *** at the 1% level, ** at the 5% and * at the 10% level of significance.
Appendix I
Table A1. Panel cointegration test (Pedroni)
Null Hypothesis: No cointegration
1993-2014
Panel v-Statistic
Panel rho-Statistic
Panel PP-Statistic
Panel ADF-Statistic
Observations:
Cross-sections:
Statistic
-0.91
2.30
1.41
-0.86
Prob.
0.972
0.989
0.921
0.195
Weig.St.
-1.71
1.21
-0.27
0.14
682
30 (1 dropped)
1960-2014
Prob.
0.96
0.89
0.39
0.56
Statistic
0.34
-2.66
-2.33
-5.61
Prob.
0.366
0.004
0.010
0.000
Weig.St.
0.241
-7.08
-6.44
-5.93
1705
30 (1 dropped)
Trend automatic lag length selection based on AIC with lags from 1 to 9: Deterministic intercept and
trend. Newey-West automatic bandwidth selection and Bartlett kernel.
20
Prob.
0.405
0.000
0.000
0.000
Table A2. The current account and fundamentals (1981-2007) – Narrow sample
Periods
Constant
Young
Old
Growth
Output per capita
Budget surplus as
share of GDP
1993-2007
Constant (93-09)
Young
Old
Growth
Output per capita
Budget surplus as
share of GDP
(1)
Pooled
3.73
(1.03)
-0.16
(2.73)*
0.04
(0.41)
0.21
(2.02)*
-0.0001
(0.23)
0.12
(1.66)**
(2)
F.E.
-3.89
(0.29)
0.39
(1.41)
-0.67
(1.99)*
0.18
(2.28)*
-0.01
(1.75)**
0.19
(2.71)*
-24.05
(5.63)*
0.39
(4.94)*
0.91
(6.96)*
-0.44
(2.15)*
0.0005
(0.66)
0.06
(0.61)
-34.00
(4.44)*
0.67
(4.19)*
1.10
(5.51)*
-0.16
(1.17)
0.0002
(0.26)
0.00
(0.05)
1999-2007
Constant (99-09)
Young
Old
Growth
Output per capita
Budget surplus as
share of GDP
Cross sections
Observations
R-squared
Constant
Young
Old
Growth
Output per capita
Budget surplus as share
of GDP
Single market countries
Constant (93-09)
Young
Old
Growth
Output per capita
Budget surplus as share
of GDP
Participation in European
integration
(3)
(4)
Pooled
F.E.
8.34*
57.24*
(2.84)
(5.57)
-0.22*
-0.69*
(3.33)
(3.78)
-0.11
-2.19*
(1.36)
(7.40)
0.14
0.17*
(1.34)
(2.33)
-0.001
-0.01*
(1.00)
(3.78)
0.16*
0.24*
(3.60)
(4.71)
-48.40*
(7.92)
0.58*
(5.31)
2.23*
(8.78)
-0.98*
(3.28)
-0.0002
(0.16)
0.41*
(4.62)
-65.87*
(5.64)
1.01*
(4.84)
2.40*
(6.46)
-0.55*
(3.14)
0.001*
(2.15)
0.14**
(1.72)
-14.23
(1.52)
0.10
(0.51)
-0.63*
(2.06)
0.95*
(3.27)
0.61*
(21.69)
-0.39*
(2.54)
16
383
0.54
-43.87*
(3.33)
0.40
(1.63)
1.21*
(2.94)
0.51*
(2.67)
0.35*
(7.19)
-0.30**
(1.72)
16
383
0.73
Euro zone countries
20.90
(1.99)*
-0.32
(1.45)
-0.66
(2.49)*
-0.66
(2.74)*
-0.003
(2.49)*
0.78
(8.27)*
16
383
0.39
22.38
(2.55)*
-0.42
(2.22)*
-0.49
(2.20)*
-0.37
(2.86)*
0.0004
(0.28)
0.44
(5.43)*
16
383
0.71
Constant (99-09)
Young
Old
Growth
Output per capita
Budget surplus as share
of GDP
Cross sections
Observations
R-squared
White cross-section standard errors & covariance (d.f. corrected). t-ratios in parentheses.
Significance denoted by stars: * at the 5% and ** at the 10% level of significance.
21
Appendix II
EU- single market: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland,
Italy, Netherlands, Norway, Portugal, Spain, Sweden Switzerland, U.K.
Non single market: Australia, Canada, Chile, Israel, Japan, Korea, New Zealand, U.S.
EU- euro: Austria, Belgium, Finland, France, Germany, Greece, Ireland, Italy, Netherlands, Portugal,
Spain.
EU-euro-north: Austria, Belgium, Finland, France, Germany, Ireland and the Netherlands
EU-euro-south: Greece, Italy, Portugal, Spain
Single market – non euro: Iceland, Norway, Sweden, Switzerland, the U.K.
Data
Gross capital formation as a share of GDP. Source: World Bank.
Gross national saving as a share of GDP. Source: World Bank
General government net lending/borrowing. Source: IMF.
Real GDP per capita in US collars. Calculated as the ratio of output-side real GDP at
chained PPPs (in mil. 2005US$) and population in millions. Source: Penn-World
Tables.
Share of population under age 25 and 65 and older. Source: World Bank.
22
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