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THE PERSISTENCE OF THE CURRENT ACCOUNT
SURPLUS FOLLOWING AN EXTERNAL SECTOR CRISIS
Juan Manuel Jauregui
Global Economics and Management
UCLA Anderson Graduate School of Management*
and
Business, Society and Economy
IAE Business School
May 2006
Abstract
This paper addresses empirically the duration of the period of current account surplus that follow a current
account reversal. Analyzing quarterly data from 1980 it identifies fast current account reversals –defined as
episodes of a reduction of more than one percentage point of GDP in the current account deficit in just one
quarter– effected simultaneously with a period of high distress in the foreign exchange market. Using a Cox
proportional hazards model in which the episodes are stratified by country it finds that GDP growth and the
change in international reserves both have an effect on the hazard rate. The effect is also of non trivial
magnitude: the hazard rate is reduced by 5% per each additional percentage point of GDP growth and by
9% per each additional percentage point in the reserves to GDP ratio. These surplus periods that follow
crises episodes reflect the rebalancing of the external position of countries. The amount of the correction
and the length of the period of surplus have not been addressed thoroughly in the literature. The results of
this paper suggest that countries are more likely to end the surplus period when the growth falters and when
the reserve accumulation weakens. This finding is in line with episodes of recovery with no outside credit called by Calvo et al (2006) Phoenix miracles- and presents the puzzle of why the regained access to
external finance is not accompanied with stronger growth. Somewhat surprising is that it is not a surge in
imports that drive the rebalancing to end.
1- Introduction
 This research was conducted with the financial support of IAE Business School and of UCLA
Anderson’s CIBER –Center for International Business Education and Research. I would like to thank Prof.
Sebastian Edwards for guidance, and Prof. Leamer, Prof. Chwe and Prof. Lieberman for helpful comments.
I am also grateful with Roberto Alvarez and Guillermo Tolosa for many insightful discussions.
*
110 Westwood Plaza, Suite C525, Los Angeles, CA 90095. Tel: +1-310-825-8207
Email: Juan.Manuel.Jauregui.2006@anderson.ucla.edu

Casilla de Correo No. 49, B1629WWA Pilar, Bs. As., Argentina.
Tel: +54-2322-48-1000. Email: JJauregui@iae.edu.ar
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External sector crises are at the center of academic and policy debates. This area
of research has been very fruitful and has helped policymakers to understand much better
how to prevent crises (see for example Edwards and Frankel, 2002). Since their effects on
the economy are remarkable in many cases, this proved to be a topic for research of great
relevance for the welfare of the societies. Edwards (2005a, 2004a, b) show how the cost
of crises is significant. Also Hong and Tornell (2005) find that after a crisis the level of
GDP remains permanently below its trend. Cerra and Saxena (2005) find similarly that
lost trend growth is not regained. Baldacci, de Mello and Inchauste also find that crises
have negative consequences on poverty, and in certain cases they also increase inequality.
They do so through a variety of channels: economic activity slowdown, relative price
changes and fiscal retrenchment, just to name a few.
From the understanding of their immediate consequences, crises management can
be improved. Much work has been done and continues to be done in this area. See for
example Dooley and Frankel (2002). Moreover, the analysis of the recovery after a crisis
is also being the focus of much attention. For example, Calvo et al (2006) recently
showed the patterns for growth and credit during the period of recovery after crises. My
paper aims at understanding better the period that follow a crisis.
In the center of the debate about crises are the current account reversals, and what
drives them. Edwards (2004a, b, 2002) has studied them in depth the causes and
consequences of them. Previously, a good analysis on their empirical regularities was
done by Milesi-Ferreti and Razin (2000). Furthermore, the debate about crises is related
to one of the most important political issues of these days: global imbalances. The world
economy is facing an unprecedented situation of imbalances between countries with high
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current account deficits, the US mainly, and countries with high current account
surpluses, mainly China. The risk of an abrupt correction, also called hard landing, posses
a serious threat to the stability of the global economy. Understanding deeply the current
account reversals is an issue of great importance. A thorough analysis of this issue can be
found in Edwards (2005b, c, d)
This objective of this paper is to increase our understanding about the recoveries
of the economies after the crises of the current account. Specifically, I study the
persistence of the periods of current account surplus that follow them. During them, the
countries undergo a process of rebalancing of the net international investment position.
This process begins with a crisis, in a traumatic way, and very few things are known
about how long they last. This paper shows evidence about the factors that make these
periods last longer.
2- The Empirical Model
2-1- The beginning and end of the events
This paper analyzes the duration of the periods of rebalancing of the net
international investment position (NIIP) after a period of extreme market pressure in the
foreign currency market. The aim is to identify the factors that drive the length of the
time during which a country that was originally in deficit, that is, that had a deteriorating
NIIP, rebalances it, at least partially. The beginning of the time spell will be identified by
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three conditions: there has to be extreme market pressure in the currency market, the
current account balance has to be at a deficit in the previous period and there has to be a
reduction of the CAD to GDP ratio of at least one percentage point in just one quarter.
The end of the spell is chosen as the moment in which one of two things happens. Either
a current account deficit begins after having a surplus or, if the correction of the current
account deficit did not ever reach the surplus, an increase of the deficit begins. Therefore,
the episodes last from the moment of the crisis, when the country is not allowed to
continue its deficit at the same level and is forced to an abrupt correction, to the moment
in which it begins or increases its current account deficit (CAD).
2-2- The extreme market pressure index
The definition of market pressure is similar to the one used by Eichengreen, Rose
and Wyplosz (1995)1. In their paper, they use a weighted index that combines the
exchange rate changes, reserves changes and, and interest rate changes. For their index,
they use the differentials with respect to the center that they define to be Germany. I just
use the changes in the variables, not of the differentials, since the center may be different
at different times. Their study covers a shorter span of time than mine, and consequently
this was not a problem for them. As the volatilities of the three components of the index
are very dissimilar, being highest for reserves and the lowest for interest rates, they
weight the index so that the conditional volatility of each of them is equal. In this paper I
follow Wyplosz (2001) by weighting the index by the inverse of the standard deviation of
1
They in turn follow earlier work by Girton and Roper (1977).
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each component. Also, I define a crisis as a time in which the index is two standard
deviations above its mean, as Eichengreen et al (1995) do.
2-3- The Cox proportional hazards model
This periods of rebalancing are analyzed using a Cox proportional hazards model
(Cox 1972) in which the hazard rate is related to the explanatory variables xj in the
following way:
ht | x j   h0 t  exp x jt  x 
The hazard rate is defined as:
ht   lim t 0
Pr t  t  T  t | T  t  f t 
f t 


t
S t  1  F t 
Where S(t) is called the survival function and T is the duration of the event2.
This model does not make any assumption about the baseline hazard h0(t), and
this is a great advantage in this setting in which there is not any compelling evidence in
the literature about how this hazard should evolve through time. Moreover, there is not
any theoretical model widely accepted that we could use to assume a particular shape of
2
For a brief introduction of duration analysis see Greene (2000).
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h0(t). This model is very suited for the problem under study since, in fact, the baseline
hazard is left unestimated3. Our model will include time-varying covariates4.
The model was stratified by country, which means that it estimates a different
baseline hazard for each country5. In this way, it is recognized that country specific
effects make the hazard rates at each time different between countries even for the same
set of variables. It is not that one country faces a higher probability or even that this is
increasing, but that the whole shape can be different, because no restrictions are imposed
on the face of the baseline hazard. Therefore, the baseline hazards for the episodes j are
different for each country c:
ht | x j   h0c t  exp x jt  x 
The coefficients to be estimated are required to be the same for all events
regardless of the country. This analysis does not include time varying-coefficients. This is
feasible, but we saw no need to include this feature in our model6.
In the likelihood calculations, the Breslow (1974) approximation has been used
for the cases of tied failures. These are the cases in which two or more episodes fail at the
same time according to the data. The exact calculation can be computational intensive,
and consequently this approximation is typically used.
3
For a technical treatment of the estimation see Kalbfleisch and Prentice (2002).
For details about a Cox model with time-varying covariates see Wooldridge (2002).
5
For a further discussion about stratified analysis see Cleves et al (2004).
6
Also Cleves et al (2004) provides an explanation on this.
4
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2-4- The economic factors
The literature about the determinants of the current account is very broad (for a
general review see Obstfeld and Rogoff, 1997). Based on this and on the previous
academic work about crises, the economic factors to be analyzed are the following:
a) GDP growth
b) Exports
c) Imports
d) Foreign direct investment (FDI)
e) Domestic credit
f) Fiscal surplus
g) International reserves
h) Interest rate
i) Exchange rate
j) Initial CA / GDP ratio
The exports and imports are obviously important variables to include in the model
for their impact on the current account. Typically, the current account reversal occurs
because of a sudden reduction in imports that is followed by a surge in exports. The
relative size of the adjustment that comes from each of the variables allows a
characterization that separates between countries whose exports make most of the
correction and those whose imports are the responsible for the current account
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improvement (see Guidotti, Sturzenegger and Villar, 2004). In any case, one could expect
that the component that changed most during the reversal could be reverting back and so
bringing the current account surplus period to an end. Along this line, Desai and Mitra
(2004) find that the pre-crisis difference in export sector strength between Argentina and
Thailand provides a significant explanation for the post-crisis difference in the interest
rate and exchange rate movements between the two countries. This points to the strength
and flexibility of the exporting sectors, and consequently, to exports as an important
factor.
The rate of growth of GDP is also important. Kaminsky, Reinhart and Vegh
(2004) show that net capital flows are pro-cyclical. We can expect that the current
account deficit will be higher in the presence of healthy growth. Moreover, since most of
the external sector crises happen in emerging markets, this dynamic of the current
account turning to deficit in good times and to surplus in bad times is of great importance
for this study. One line of reasoning goes as follows: emerging countries are credit
constrained and whenever they are favored by international capital inflows this eases this
constrain and allows them to increase investment and consequently output. Good times
come with the ability to borrow and propel GDP. Also, crises are periods of current
account surplus and they are related to large falls in GDP. Whenever GDP recovers one
can expect the times coming back to normal, with increased access to international
financial markets.
However, there is also a view that is opposite to the one just mentioned. Based on
the economic success experienced by some Asian countries, and on the fact that they are
export oriented, there is the idea that growth can be stronger and sustained for longer
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periods of time when industrial exports are high. Healthy growth and current account
surpluses come together in this theory. Furthermore, it has been recently observed that
many countries that face sudden stops and crises have GDP growth recover without
credit. Calvo (2005) discusses this issue extensively.
Foreign direct investment has been found to be the most stable type of capital
inflow. It is long term, highly illiquid and also related to technological spillovers. It has
been a good indicator of the quality of the capital inflows and there has been empirical
evidence that the higher the levels of FDI, the lower are the chances of having a crisis and
the less negative the impact of the crisis is. It is natural to expect that this component of
the capital account will have an impact in the duration of the surplus period. It may be an
indicator of increased foreign interest in the assets of the country in question and a
predictor of a forthcoming deficit period.
Interest rates are also affected heavily by the capital inflows. The times of inflows
are also times of low interest rates and we could expect that if the current account deficit
is about to begin, the interest rates should be falling in the presence of increased inflows.
Arbitration in the money market is very fast, and interest rates should be a great predictor
of the foreign currency availability for the future times. Also, if capital inflows increase
and the government decides to intervene to sustain a high exchange rate, it may decide to
sterilize the purchases of foreign currency. By doing so, the interest rates show go up, and
they should go down whenever the government changes its policy. Therefore, a fall in
interest rates can be preceding the end of the surplus period.
Similarly related to the capital inflows, the international reserves can be going up
if the governments choose to keep the level of the nominal exchange rates and capital
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inflows begin to increase. Consequently, we can expect that they would go up at the end
of the surplus period. However, this variable is certainly reflecting complex forces. The
reserves can also go up at the beginning of the surplus period because this happens just
after the crisis and at that time, reserves may be too low and they need to be
reconstituted. Also, the exchange rate surely overshoots in the crises, and may stabilize at
a level that is higher than the equilibrium level, allowing some reserve accumulation at
the beginning. Finally, during all of the surplus period, policy makers will be naturally
concern about the possibilities of future crises, and they use reserve accumulation as an
insurance against future capital outflows. Hence, we can observe some reluctance
towards nominal exchange rate appreciation and policies favorable to international
reserves accumulation. Moreover, the perspectives of coming back to a current account
deficit may not be so appealing to the leaders of a country that had serious problems to
sustain a deficit in the very recent past.
Closely related to this discussion about the role of international reserves is the
level of the exchange rate. Basically, it is the same phenomenon, but the other side of the
coin. One would expect an appreciation when capital inflows resume and the deficit may
be about to begin.
Domestic credit is also a very important factor to consider. Excessive creation can
be the source of a crisis of the sort of the ones called of the first generation (Krugman,
1979). It also grows notably in the periods of exuberance that can lead to crises of the
second and third type7. The crisis then come with an abrupt contraction in domestic
credit, a contraction that can begin before the crises unleashes. This low credit can
continue during quite a long time (see Calvo et al 2006). Later, domestic credit would
7
For a reference on the models of crises see Edwards and Frankel (2002).
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recover whenever capital inflows resume. However, in a case in which the government is
interested in not letting the nominal exchange rate to fall, the sterilization of the capital
inflows can lead to an increase in the interest rates and prevent domestic credit from
recovering. In a different mechanism, one could expect that if domestic credit recovers,
this will increase domestic aggregate demand, fostering imports, and bringing down the
surplus. In any case, this factor certainly is related to the events under study and we can
expect that it would increase at the end of the surplus period.
Edwards (2004a) showed that the current account to GDP ratio was the most
important factor affecting the probability of facing a CA reversal if we consider both
statistical significance and magnitude of the effect. Hong and Tornell (2005) find in a
different study that the pre-crisis expansion and the reserve inadequacy are closely related
to the extent of the post-crisis recession. These two results suggest that in a current
account reversal, the initial level of the deficit may have lasting consequences. Therefore,
we will include this variable in the study of the persistence of the surplus period as we
expect that the higher the original imbalance, the larger the adjustment needed and the
longer the period of rebalancing will be.
3- Empirical Results
3-1- The Dataset
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This empirical research is done with a very large and new dataset from the
International Financial Statistics, of the International Monetary Fund. Quarterly data from
1980 to 2005 is used. However, due to a lack of reliable data from the early years, only a
few events under study are from the 1980s are included.
3-2- Findings
The empirical findings can be seen in tables 1 to 58. A number of Cox
proportional hazards models with different specifications for the vector of independent
variables where estimated. The analysis was stratified by country, that is, the baseline
hazards were allowed to differ by country.
In table 1, equation (1), we see the main empirical result of the paper. In this
study, the events begin when the current account reversal occurs and they end when a
deficit begins. The hazard rate for this period to end is affected negatively by the GDP
growth and by the change in the international reserves to GDP ratio. It is shown that the
hazard ratios are 0.95 and 0.91, respectively. For each additional percentage point of
growth of GDP the rate decreases by 5% and it does by 9% for each additional
percentage point of change in the international reserves to GDP ratio. Both effects are
statistically significant at the 5% level. This means that the higher GDP growth and the
higher the change in reserves, the longer we can expect the current account surplus to
last. In table 1, equation (1), the coefficient estimates for the same model are reported.
8
I only report selected results due to space considerations. All the results commented in the paper are
available upon request.
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They are -0.0492 for GDP growth and -0.0881 for the change in the international reserves
to GDP ratio.
In this basic model we include GDP growth, the change in the international
reserves to GDP ratio, the percentage change in the exchange rate and the percentage
change in the interest rate. These episodes begin when a current account reversal occurs
simultaneously with a moment of high external market pressure. This is measured as
anytime during which a weighted average of the last three variables is two standard
deviations above the mean. Consequently, there is a need to control for the values of
these variables during the event under study. These variables put the events into
existence, they may influence their duration. One of them proves to be significant, but the
other two not. A model with only GDP growth can be estimated. The result in table 1,
equation (2), shows that it is statistically significant at the 5% level and the hazard ratio is
0.97. In table 1, equation (3), we see the results for including only the variables that were
significant from the base model. Not controlling for changes in interest rates and in the
exchange rates makes the changes in reserves lose their significance. It is natural to think
that the three of them belong to the model together since together were used to identify
the periods of high distress.
In table 2, equations (5) and (6), we see that if we include the ratios of imports to
GDP and exports to GDP they do not have any statistical significance. In table 2,
equation (7), they are included only with the variables of the base model that were
statistically significant, with similar results. When the change in the ratio imports to GDP
is included, it was not significant either.
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A very interesting result can be observed in table 3, equation (12), when a dummy
variable for recessions is included to the base model. Since GDP growth is significant,
one can expect that the recession episodes are different. The coefficient on recessions is
not significant, but it is suggestive the fact that precision over the two significant
variables is increased and also the hazard ratios drop for both of them. In this setting,
each percentage point of change in reserves decreases the hazard by 11% and each
additional point of growth in GDP does so by 9%.
In table 3, equations (9), (10) and (11), we see the result of the model when we
include the percentage change in domestic credit. Something similar happens than when
we included the recession indicator. It is also the same result when both of them are
included. It is surprising that domestic credit is not statistically significant, since we
would expect it to have a positive effect on aggregate demand and consequently in the
current account deficit. It is also to be expected that domestic credit can be correlated
with increased capital inflows. So the current account deficit period should come with a
domestic credit increase. Also, Hong and Tornell (2005) find a close relationship between
pre-crisis credit expansion and reserve inadequacy and the extent of the post-crisis
recession. All these induced us to expect some correlation between domestic credit and
the duration, but the data does not seem to confirm that. The level of domestic credit did
not show any clear result, but also contributed to change the coefficients over the
significant variables in a similar way as the change in credit.
Also the fiscal surplus was included in some specification of the model, but it did
not show any explanatory power. This was also a surprise due to the correlation between
fiscal balance and current account balance (Agenor and Montiel, 1999).
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A somewhat unexpected result is presented in table 4, equations (13) and (14) in
models that include the ratio of FDI to GDP ratio and the proportion of FDI in the current
account. It does not show any statistically significant effect, even when it has been shown
that it plays an important role in the genesis of crises (Frankel and Rose, 1996), since FDI
is a more reliable and less volatile type of foreign investment.
When the exports to GDP ratio is included on top of the base model, results do
not change much (see table 2, equation (6)). When the ratio of imports to GDP is
included, the change in the reserves loses significance (see table 2, equation (6)). The fact
that both exports and imports have no significant impact is a big surprise. One reason is
that we would expect that they would be of importance since the events that we are
studying are based on the current account. Other reason is that the episodes of current
account reversal are typically associated with specific behaviors of these variables. To be
more specific, the literature refers to episodes of adjustment that come through a
reduction of imports as being different than those that come through an increase in
exports. Guidotti et al (2004) find that they are qualitatively distinguishable in the sense
that countries characteristics influence which ones adjust in one way or the other. Also,
the required adjustment of the exchange rate, the magnitude of the fall of GDP, and the
length of the time required to recover GDP levels according to the pre-crisis periods is
affected by how much exports contribute to the adjustment of the current account. It
could be expected that these variables are also playing a role in the persistence of the
current account surplus. But this is not the case, according to the results presented here.
For example, in table 2, equation (8), we see that when including imports and exports
with quadratic terms they do not have any explanatory power.
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Finally, in table 4, equation (15), we observe the result when the initial level of
the current account to GDP ratio is included. This variable has been identified as the
single most important one in the probability of facing a reversal (Edwards, 2004a). Also,
the higher the imbalance, the larger the adjustment is likely to be, and it well could be
expected that the longer the period of surplus would be. However, this variable is not
significant, contrary to what we expected.
4- Robustness and specification tests
The results presented in the previous subsection are quite robust. The inclusion of
other variables in the model did not affect significantly the results. Also the model seems
to be correctly specified9. Quadratic and interactive terms were included to test for non
linearity. None of these variables had any explanatory power. For example, in table 5,
equations (17), (18), (19) and (20), we see the estimates with interactive and quadratic
variables of the base model. Also a link test following Tukey (1949) and Pregibon (1979,
1980) was conducted. This test estimates the coefficients for the following expression of
the log relative hazard (LRH):
 ^ 
 ^ 
LRH  1  x  x    2  x  x 




2
9
The brief explanations about the tests performed and the calculations involved are based on Cleves et al
(2004) and Stata (2005).
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Under the assumption that xx is the correct specification, 1 = 1 and 2 = 0. This
last equality has been tested and the specification of our model was not rejected.
Moreover, interactions of all the variables with the analysis time were tested, since in a
correctly specified model they should not be statistically significant. In the general form,
the tests are:
LRH  x x  1 x1t 
And then we tested the hypothesis 1 = 0
Another test on the proportional hazards assumption that was conducted was
based on the generalization by Grambsch and Therneau (1994). This one is a test of
nonzero slope in a generalized linear regression of the scaled Schoenfeld (1982) residuals
on time. This test is equivalent to test that the log hazard ratio function is constant over
time. Thus, rejection of the null hypothesis indicates a deviation from the proportional
hazards assumption.
Alternative definitions of reversals of reversals were considered. When we study
those reversals that began in a situation in which there is not extreme currency market
pressure, the results are not very different. However it is important to remember that
these episodes may be qualitatively different than the ones analyzed previously. In a
model of only GDP growth and change in international reserves, the last is statistically
significant at the 10% level, while the first one is at the 1% level. The magnitude of the
effects, though, is smaller: both reduce the hazard by 2%. When we control for the
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percentage change in the interest rate and in the exchange rates GDP growth continues to
be significant, but the change in reserves not any longer.
The model was also estimated under a definition of current account reversal that
considered a different threshold. Requiring an adjustment of only 0.75% of GDP gave the
results posted in table 5, equation (20). They are almost exactly the same as with 1%
adjustment.
5- Magnitude, Economic Significance and Policy Implications
In the previous section I have addressed the issue of the statistical significance of
the political economy variables included in the model. But more important than that is the
economic significance of the results. So, in this section I move from the issue of which
variables are statistically significant and the estimated value of the coefficients to the
more relevant one of what economic impact these results have, what do they mean and
what policy implications do they have10.
5- 1- Magnitude of the Effects
The economic magnitude of the effects is important for both GDP growth and the
change in the international reserves to GDP ratio. The coefficients were -0.0492 and 0.0881 for the GDP growth and the change in the international reserves to GDP ratio,
10
See Ziliak and McCloskey (2004) for a detailed discussion about economic significance.
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respectively, representing a hazard ratio of 0.95 and 0.91, as reported in the previous
section. This means that for each additional percentage point of GDP growth, the hazard
rate is reduced by 5% and that for each additional percentage point in the change of the
reserves to GDP ratio, it is reduced by 9%. Both effects are nontrivial. A country that
grows at a 6% rate faces a hazard rate that is almost 20% lower than if it grew at 2%.
However, for a change in the rate of growth of international reserves the effect is milder:
a country that increases reserves at a rate of 1.5% of GDP per quarter will have its hazard
rate 9% lower than one that does it only at 0.5%. Nonetheless, the effect remains
important.
5-2- Economic Significance
It is particularly suggesting that the imports did not have a statistically significant
coefficient. We are considering episodes in which a crisis occurs, something that we
observe in the variable constructed to detect extreme pressure in the foreign currency
market, and an important current account reversal is effected, measured as a reduction of
one percent of GDP in the current account deficit in just one quarter. These are major
events. We study the current account surplus periods that follow, during which the
external position of the countries is partially recomposed. In many cases these current
account reversals are effected more by a sharp decrease in imports than a surge in exports
(see Guidotti et al 2004 and Lee and Rhee, 2002). And in most cases, imports fall sharply
during the reversals to recover after some time. Therefore, it is natural to think that the
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current account deficit, should it happen after a reconstitution of the external position of
the country, will come hand in hand with an increase in imports. However, in this study,
imports did not play any significant role in the estimations.
With respect to international reserves, the fact that their change plays such an
important role is worth analyzing. A decrease in the current account surplus should come
together with a real exchange rate appreciation. If this were to happen through a nominal
appreciation, it would be reflected in the coefficient of the change in the nominal
exchange rate. But this did not happen in our estimations. In the case of government
intervention that does not let the exchange rate change freely, this appreciation should
come with an increase in reserves. And this may be the mechanism through which
reserves increases prolong the current account surplus. A similar picture could be seen if
simultaneously capital inflows grow.
Another interesting issue is raised by the result that GDP growth has an effect that
seems counterintuitive at first sight. A country that is under a current account deficit and
is required to recompose its external position through a current account surplus is very
likely to be constrained in its credit. If this were not the case, one could expect that the
correction in the current account would have been smooth and with no pressure in the
foreign currency market. Therefore, if credit constrained, one would expect that
whenever foreign capital inflows resume, growth would show renewed strength. Despite
this, we observe exactly the opposite: healthy growth would prolong the surplus, and
whenever it falters, the hazard rate of beginning the deficit increases. We are presented
with a case of recovery in output with no foreign credit, something in the line of what has
been presented in the literature by Calvo et al (2006) as Phoenix miracles. These
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recoveries without credit have also been found by Hong and Tornell (2005). In their
study of the stylized facts of currency crises they find that the credit crunch problem is
more persistent than the reduced growth rate.
Is it valid to infer that the deficits in post-crisis countries are used to finance
consumption and not investment? That seems a reasonable conjecture given what was
expressed earlier. But we cannot be conclusive. First of all, it is important to distinguish
between what we observe in the after crisis period and what may happen during normal
times of current account deficits. Second, there could be a recovery in consumption after
a large fall in during the aftermath of the crisis. Third, there may be good reasons for
having lower investment in the nontradable sector, among which can be: depressed prices
of nontradables after the necessary real exchange rate surge of the reversal and
overcapacity due to the pre-crises exuberance that leads to overinvestment.
5-3- Policy Implications
How much of the results are reflecting the fact that governments may be
prolonging the current account surplus periods by artificially keeping the exchange rates
high after a crises? This is the main policy question that can be extracted from the present
study. It would be interesting to verify if actually this is the case. Not less interesting
would be to explore the reasons why would governments behave in this way. Are they
trying to build up reserves as an insurance mechanism against future crises? Rodrik
(2006a) seems to agree. Even the cost of doing so does not seem to be so high, according
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to him. Are they trying to achieve higher growth through exports led industrialization?
Again, Rodrik (2006b) seems to agree. Even when it is explicitly warned that a high
exchange rate is not a good industrial policy, it can be of help to industrial exporters.
Hausmann, Hwang and Rodrik (2005) support the idea that sophisticated exports can be a
component of a successful industrial policy that creates a path to development. However,
the question of why faltering growth would increase the likelihood of returning to a
current account deficit does not have a straightforward answer.
6- Conclusion
This paper studies the duration of the periods of current account correction that
follow a current account reversal. For an episode to be included in the analysis, it was
required that the country had an abrupt reversal measured as a reduction in the current
account deficit of one percentage point of GDP in one quarter, and also to be under
extreme pressure in the foreign currency market. This last was measured with a weighted
average of the losses of international reserves, of the depreciation of exchange rate and of
the increase in the interest rates. Extreme pressure was defined as two standard deviations
above the mean. The length of the period of current account recomposition following
these reversals was analyzed using a Cox proportional hazards model and it was found
that the hazard rate was decreased by 5% per each additional percentage point of GDP
growth and by 9% per each additional percentage point in the change of the reserves to
GDP ratio.
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The effect of the reserves accumulation is something that can be expected: if the
government is trying keep a high exchange rate and aims to build reserves as an
insurance against future negative shocks. This can be especially true after a crisis. Also,
fearful of future sudden stops, it may be willing to prolong the current account surplus
and foster investment in the tradable sector following an export oriented approach to
growth. Under this circumstances, the reserve accumulation may decrease whenever the
surplus is about to end.
However, it is somewhat surprising that the imports do not have a clear effect on
the hazard, since it could be expected that the current account deficits are more likely
when a surge in imports occur. The data did not support this hypothesis.
What is surprising is that higher GDP growth decreases the likelihood of the
current account surplus to end. Or to put it differently, the deficits come back usually
with a decrease in growth. This is surprising because the deficit reflects that the economy
is again able to benefit from foreign savings, and this should favor growth. Especially if
we consider that these countries were running deficits at the beginning of the episodes
that we study and that they needed to correct the deficits abruptly facing a crisis, this
seems to suggest that they would benefit from regaining access to international capital
markets. However, what we observe is that they are likely to grow without capital inflows
and that they may begin to have inflows again when growth is not as strong as during the
recovery. This effect is in line with what Calvo et al (2006) called Phoenix miracles.
They found that during the recoveries after abrupt falls in GDP due to external sector
crises, GDP recovers without neither external nor internal credit growth.
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Finally, the effects are of important economic magnitude. For example, a country
that grows at a 2% rate faces a hazard rate that is almost 23% higher than if it grew at
6%. Even higher is the effect of the change in reserves. A country that increases its
reserves at a rate of 1.5% of GDP per quarter instead of 0.5% implies a reduction in the
hazard rate of 9%.
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Table 1
GDP growth
Eq. (1)
Eq. (1)
Eq. (2)
Hazard Ratio
Coefficients
Eq. (3)
0.9520
-0.492
0.9749
0.9637
0.025*
0.025*
0.048*
0.024*
Change in int’l
0.9157
-0.881
0.9298
reserves / GDP
0.029*
0.029*
0.0055
Change in the
1.0254
0.251
exchange rate
0.300
0.300
Change in the
1.0026
0.025
interest rates
0.819
0.819
Note:
Cox proportional hazards model. Stratified by country. Breslow method for ties.
Hazard ratios and P>|z| reported. *: statistically significant at 5% level.
48 events. 169 observations. Quarterly data.
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Table 2
Eq. (5)
GDP growth
Eq. (6)
Eq. (7)
Eq. (8)
0.9512
0.9496
0.9633
0.9541
0.027*
0.019*
0.027*
0.047*
Change in int’l
0.9279
0.9187
0.9425
0.9321
reserves / GDP
0.115
0.065
0.157
0.150
Change in the
1.031
1.034
1.0251
exchange rate
0.239
0.179
0.362
Change in the
1.005
1.004
1.0012
interest rate
0.654
0.712
0.927
Exports / GDP
0.9626
0.9497
0.9793
1.1172
0.452
0.278
0.636
0.616
0.9999
0.9999
1.0000
0.604
0.529
0.801
Imports / GDP
(Exports/GDP)2
0.9968
0.502
Note:
Cox proportional hazards model. Stratified by country. Breslow method for ties.
Hazard ratios and P>|z| reported. *: statistically significant at 5% level.
48 events. 169 observations. Quarterly data.
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Table 3
Eq. (9)
GDP growth
Eq. (10)
Eq. (11)
Eq. (12)
0.9629
0.9462
0.9091
0.9141
0.022*
0.019*
0.019*
0.018*
Change in int’l
0.9296
0.9058
0.8896
0.8967
reserves / GDP
0.053
0.019*
0.016*
0.019*
Change in the
1.050
1.053
1.0362
exchange rate
0.210
0.211
0.232
Change in the interest
1.0016
1.0013
1.0029
rate
0.887
0.905
0.796
Change in domestic
1.0061
0.9696
0.9755
credit
0.803
0.441
0.570
Recession
0.1674
0.1716
0.143
0.126
Note:
Cox proportional hazards model. Stratified by country. Breslow method for ties.
Hazard ratios and P>|z| reported. *: statistically significant at 5% level.
48 events. 169 observations. Quarterly data.
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Table 4
Eq. (13)
GDP growth
Eq. (14)
Eq. (15)
0.9526
0.9515
0.9518
0.026*
0.0024*
0.028*
Change in int’l reserves /
0.9176
0.9145
0.9150
GDP
0.036*
0.027*
0.038*
Change in the exchange
1.0219
1.0260
1.0258
rate
0.399
0.289
0.318
Change in the interest
1.0030
1.0034
1.0021
rate
0.786
0.768
0.890
FDI / GDP
0.9011
0.698
FDI / CA
1.0178
0.765
Initial CA / GDP
1.0044
0.960
Note:
Cox proportional hazards model. Stratified by country. Breslow method for ties.
Hazard ratios and P>|z| reported. *: statistically significant at 5% level.
48 events. 169 observations. Quarterly data.
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Table 5
Eq. (17)
Eq. (18)
Eq. (19)
Eq. (20)
Only .75%
GDP growth
0.9884
0.9498
0.9483
0.9521
0.025*
0.025*
0.027*
0.025*
Change in int’l
0.9083
0.9095
0.9147
0.9161
reserves / GDP
0.028*
0.028*
0.054
0.028*
Change in the
1.0327
1.0293
1.0332
1.0252
exchange rate
0.237
0.256
0.227
0.303
Change in the interest
0.9989
0.9986
0.9984
1.0025
rate
0.936
0.920
0.906
0.819
Exch. rate change x
1.0003
1.0003
1.0003
interest rate change
0.599
0.633
0.544
Interest rate change x
0.9996
int’l reserves change
0.744
Exch. rate change x
0.9996
int’l reserves change
0.747
Note:
Cox proportional hazards model. Stratified by country. Breslow method for ties.
Hazard ratios and P>|z| reported. *: statistically significant at 5% level.
48 events. 169 observations. Quarterly data.
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