How Does Trade Evolve in the Aftermath of Financial Crises?

48 Pages·2014·0.9 MB·English

by  Petia Topalova

How Does Trade Evolve in the Aftermath of Financial Crises?

Abdul Abiad, Prachi Mishra, and Petia Topalova1
June 2014

Abstract
International trade collapsed in 2008-09, particularly in countries that experienced a financial
crisis. Was this collapse unique or part of a broader historical pattern? Using an augmented
gravity model and 179 episodes from 1970-2009, we find that financial crises are associated with
sharp declines in imports of the crisis country—19 percent, on average, in the year following a
crisis—and this decline is persistent, with imports recovering to their gravity-predicted levels
only after 10 years. In contrast, exports of the crisis country fall modestly and then remain close
to or even above the predicted level. The protracted drop in imports post-crisis is consistent with
evidence of a sustained depreciation of the exchange rate and impaired credit conditions
following crises.
JEL Classification Numbers: F10, G01
Keywords: trade, financial crisis
Authors’ E-Mail Addresses: [email protected] (corresponding author); [email protected],
[email protected]

1 IMF; 700 19th St NW, Washington, DC 20431, USA; [phone]. The views expressed in this paper are those
of the authors and do not necessarily represent those of the IMF or IMF policy. We are grateful to Olivier
Blanchard, Don Davis, Petya Koeva Brooks, David Romer, Philippe Martin, Andrei Levchenko, and seminar
participants at the World Bank, IMF, ITC, Hong Kong University of Science and Technology, Indira Gandhi
Institute for Development Research, ICRIER, and the Delhi School of Economics for helpful comments. We thank
Gavin Asdorian, Stephanie Denis, Lisa Kolovich, Andy Salazar and Yorbol Yakhshilikov for excellent research
assistance.
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I. INTRODUCTION
Financial crises have been a consistent feature of the economic landscape. As Reinhart and
Rogoff (2008, 2009a) document in their history of such crises, the occurrence of both debt and
banking crises over the past decades is merely a continuation of a pattern that extends back to at
least the start of the 19th century. It comes as no surprise, then, that the effects of financial crises
have been studied extensively. Cerra and Saxena (2008) and IMF (2009), for example, find that
financial crises are associated with large and persistent declines in output; Kaminsky and
Reinhart (1999) observe that problems in the banking sector are typically followed by a currency
crisis; and Reinhart and Rogoff (2009b) note that financial crises lead to deep and prolonged
asset market collapses, large declines in output and employment, and rising levels of government
debt.
However, what happens to international trade after a country goes through a financial
crisis has not been analyzed as extensively. The world witnessed a spectacular collapse of
international trade in the aftermath of the Great Recession. While the collapse of trade that
occurred  in  late  2008  and  the  beginning  of  2009  was  “sudden,  severe,  and  synchronized,”  as  
depicted in Figure 1, its recovery was uneven across countries, with an important distinction
being whether the country had a banking crisis. For countries that did not have a banking crisis,
real imports were on average back to their pre-crisis peak by the beginning of 2010. In contrast
for the 13 countries that underwent a systemic banking crisis, real imports were on average well
below their pre-crisis levels (Figure 2).
Is this part of a broader historical pattern? Have financial crises in the past led to similar
disruptions in a country’s  trade, and how long-lasting were these disruptions? Understanding the
behavior of trade is crucial as it is an important channel through which crises can affect
economic welfare and growth, and through which the effects of a crisis in one economy can spill
over to its trading partners.
To answer these questions, we examine episodes of banking and debt crises over the past
40 years and analyze the behavior of trade flows following such crises. More specifically, we
augment the gravity model of bilateral trade to examine whether, in the aftermath of a financial
crisis,  a  country’s  exports  and  imports  deviate  from  their  “natural”  level,  i.e., the level of trade
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that would have been predicted by standard determinants such as GDPs, bilateral distance, etc.
We find that, even after controlling for income and other gravity controls, crises are associated
with large and persistent declines in imports. On average, in the year following a crisis, imports
of the crisis country are 19 percent lower than the level predicted by the gravity framework;
imports recover slowly, taking roughly 10 years to return to normal. In contrast, exports of the
crisis country are not as adversely affected. On average, exports are 4 percent below predicted in
the year of the crisis and return close to or even above levels predicted by the gravity model in
subsequent years. Importantly, we find evidence which suggests that the sharp and persistent
import losses are associated with a sustained depreciation of the exchange rate and impaired
credit conditions following financial crises.
Our main finding of long-lasting import losses is robust to the following: (i) alternative
econometric methodologies, such as estimating a model with bilateral time-invariant
characteristics (instead of country-pair fixed effects), accounting for omitted-variable and
selection biases, and estimating a model with aggregate rather than bilateral trade; (ii) more
flexible specifications, such as allowing the elasticity of trade to vary with respect to the various
components of GDP (i.e., trend vs cyclical), with respect to crisis and non-crisis periods and
allowing for time-varying multilateral resistance terms; (iii) introducing alternative controls such
as domestic absorption; and (iv) excluding the most recent episode of financial crises.
Our empirical approach follows a growing body of literature that has used the gravity
model to investigate the effects on trade of  various  types  of  “shocks”  to  an  economy.  Glick  and  
Taylor (2010) and Martin, Mayer, and Thoenig (2008) use the gravity model to estimate the
effects of war on bilateral trade and find very large and persistent trade losses between
belligerents following war. Qureshi (2009) studies the impact of war on trade of neighboring
countries. Similarly, Blomberg and Hess (2006) estimate the contemporaneous effect of different
forms of violence (terrorism, revolutions, interethnic fighting, and external wars) on trade. The
gravity framework has also been used extensively to quantify the trade impact of various policy
regimes, such as exchange rate regimes, free trade agreements, and currency unions (e.g., Rose,
2000, Glick and Rose, 2002, Klein and Shambaugh, 2006, Baier and Bergstrand, 2007),
exchange rate volatility (Thursby and Thursby, 1987), preferential trade agreements (e.g.,
Frankel, Stein and Wei, 1996), and democracy (Yu, 2010).
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To date, only two other studies have used the gravity framework to analyze post-crisis
trade dynamics. Ma and Cheng (2005) use a smaller sample of 52 countries over the period
1981-1998, and focus on short-term effects (up to two years) of banking crises. They find that
during the latter half of their sample, banking crises had a negative impact on imports and a
positive effect on exports in the year following the crisis, whereas both imports and exports
decline two years after the crisis. In addition to the broader coverage of countries and years that
we use, we analyze the evolution of trade over a longer time horizon following crises (up to 10
years), and we subject our results to a battery of robustness tests. Importantly, we also examine
how the effects of crises vary across different product categories, and during global downturns,
and we try to identify the channels through which a crisis impacts trade. Berman and Martin
(2012) also use a bilateral gravity framework to investigate the effects of financial crises on
trade. Their focus, however, is on the effect of financial crises on the exports of trading partners,
and specifically on the vulnerability of Sub-Saharan African economies to financial crises in
advanced economies. They find that a financial crisis in a trading partner has a moderate but
long-lasting effect on exports, especially for African exporters.
Our study contributes to the large literature inspired by the “Great  Trade Collapse.”2 This
literature focuses on understanding the causes of the sudden, severe and synchronized collapse in
trade that characterized the 2008-09 global financial crisis. The emerging consensus is that the
great trade collapse was mostly a demand shock, with trade falling substantially more than
output due to compositional effects (see e.g., Levchenko, Lewis, and Tesar, 2010, Eaton et al.
2011, Bems, Johnson, and Yi, 2010) and synchronicity because of the rise in vertical supply
chains. Supply side factors, such as the disruption of trade credit (Chor and Manova 2012, Amiti
and Weinstein, 2011, Iacovone and Zavacka, 2009) or a rise in protectionism (Evenett, 2010)
were found to have some, but not a very large, role in the collapse in trade. Our study
complements this literature by taking a step back and documenting whether the collapse of trade

2 See among others, Baldwin (2009) and references therein, Alessandria, Kaboski and Midrigan (2010), Bems,
Johnson and Yi (2010), Levchenko, Lewis and Tesar (2010), Eaton et al. (2011), and Chor and Manova (2012).
There is also a rising literature that provides micro-evidence on trade adjustment following large depreciations in
emerging economies (e.g., Gopinath and Neiman, 2011 and Alessandria, Kaboski, and Midrigan, 2011).
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is also a feature of past financial crises.3 Our paper also contributes to the extensive literature on
the macroeconomic effects of crises. Most recently, Gourinchas and Obstfeld (2012) evaluate the
behavior of various macroeconomic and financial variables around crisis events. Although the
focus of their paper is on the predictors of crisis, one of their findings consistent with ours is a
significant improvement in the current account in the aftermath of defaults and debt crises,
especially for emerging market economies.
The rest of the paper is organized as follows. Section II presents the empirical
methodology. Section III describes the data. Section IV presents the empirical results and their
robustness. Section V provides a discussion of the likely mechanisms behind the main findings,
while Section VI illustrates some additional patterns surrounding trade and crises. Section VII
concludes.
II. METHODOLOGY
The effects of crises on international trade are estimated using a standard gravity model of
international trade. The gravity model offers a well established framework with theoretical
underpinnings to analyze the determinants of trade flows between countries.4 It relates the level
of bilateral trade flows to characteristics of the importing and exporting countries (most notably
size and level of development) as well as to country-pair characteristics such as distance between
the two countries and whether they share a common border, language, or currency. Variations of
the gravity model have been used extensively in recent studies as benchmarks from which to
assess the trade impact of various economic disturbances, policy regimes, and political events
(see, for instance, Glick and Taylor, 2010, and references therein). We augment the conventional
gravity model to include indicators of whether the importing or exporting country experiences a

3 Freund (2009) also takes a historical perspective by examining the decline in world trade following four previous
global downturns. In this paper we focus not on global trade dynamics, but on what happens to trade of individual
economies that experience a banking or debt crisis.
4 The framework can be derived formally from a general equilibrium model of production, consumption, and trade,
as in Anderson and van Wincoop (2003). See also Baldwin and Taglioni (2006) for a survey of the use of gravity
models in the literature, as well as the pitfalls one faces in estimating them.
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financial crisis. Each observation in the regressions we run represents, for a particular year, an
importer-exporter pair (a dyad).5
Our main estimating equation is specified as follows:
lnM =∝ +𝜋 +∑ ∝ 𝑐𝑟𝑖𝑠𝑖𝑠 +∑ 𝛽 𝑐𝑟𝑖𝑠𝑖𝑠 +𝛾 lnY +𝛾 lnY +𝛿 lny +
(cid:2919),(cid:2920),(cid:2930) (cid:3036)(cid:3037) (cid:3047) (cid:3038) (cid:3038) (cid:3036),(cid:3047)(cid:2879)(cid:3038) (cid:3038) (cid:3038) (cid:3037),(cid:3047)(cid:2879)(cid:3038) (cid:2869) (cid:2919),(cid:2930) (cid:2870) (cid:2920),(cid:2930) (cid:2869) (cid:2919),(cid:2930)
𝛿2lnyj,t+𝜇𝑋𝑖,𝑗,𝑡+𝜀𝑖, 𝑗,𝑡 (1)
where ln𝑀 is the natural logarithm of imports of country 𝑖  from exporter 𝑗 at time 𝑡, lnY is
(cid:3036),(cid:3037),(cid:3047) (cid:2919),(cid:2930)
the natural logarithm of county i’s real GDP (a proxy for market size), lny is the natural
(cid:2919),(cid:2930)
logarithm of country i’s real GDP per capita (a proxy for its level of development), and
𝑐𝑟𝑖𝑠𝑖𝑠 and 𝑐𝑟𝑖𝑠𝑖𝑠 are dummy variables indicating whether the crisis started in period
(cid:3036),(cid:3047)(cid:2879)(cid:3038) (cid:3037),(cid:3047)(cid:2879)(cid:3038)
𝑡−𝑘 in the importer and exporter respectively.
The 𝜋 in eq. (1) represent  time  dummies,  which  capture  factors  that  affect  all  countries’  
(cid:3047)
trade simultaneously, such as global downturns, global changes in commodity prices or
uncertainty. 𝑋 captures other importer-exporter time-varying controls such as whether trading
(cid:3036),(cid:3037),(cid:3047)
partners are part of a currency union or free trade agreement in time 𝑡.
The coefficients of interest are ∝  and 𝛽 . ∝ captures the average effect of a crisis in
(cid:3038) (cid:3038) (cid:3038)
country 𝑖  on its imports from country 𝑗, 𝑘 years after the beginning of a crisis in country 𝑖; 𝛽
(cid:3038)
captures the average effect of a crisis in country 𝑗  on country 𝑖’s  imports  from  country  𝑗—or
equivalently, country 𝑗’s  exports  to  country  𝑖—𝑘 years after the crisis. In other words, ∝
(cid:3038)
measures  the  average  effect  of  a  crisis  on  a  country’s  imports,  and  𝛽 measures the average
(cid:3038)
effect  of  a  crisis  on  a  country’s  exports.  Since  the  empirical  specification  controls  for  standard  
gravity determinants as well as year and importer*exporter fixed effects (see below), the
estimated coefficients on crisis indicators capture whether 𝑘 years after the crisis the imports or
exports of a country are statistically different from what output, external demand/supply and
other determinants of trade would predict.

5 We follow the majority of the empirical literature on the gravity model by focusing only on the non-zero trade
flows. However, our findings are not sensitive to the exclusion of zero flows.
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Following Glick and Rose (2002), we include in eq. (1) a full set of importer-exporter
pair dummies, ∝ . These dummies control for all possible time-invariant country-pair
(cid:3036)(cid:3037)
characteristics such as distance, common language, common border, etc. The inclusion of the
import-exporter dummies implies that the effect of crises on imports is identified controlling for
the average level of imports of country 𝑖 from country 𝑗.
Importantly, the importer-exporter pair dummies also proxy for the time-invariant
component of the unobserved multilateral trade resistance effects in Anderson and van Wincoop
(2003). Anderson and van Wincoop (2003) argue that bilateral trade is determined not only by
bilateral trade costs, but by broader multilateral trade costs as well. For example, Australia and
New Zealand have large trade flows not only because they are close to each other, but because
they are far from the rest of the world. Based on the micro foundations of the gravity model, the
multilateral trade resistance  reflects  the  countries’  CES  ideal  price  indices—these can constitute
an important source of bias in the estimated coefficients for standard gravity models. The
standard in the gravity literature is to use importer-time and exporter-time fixed effects in panel
gravity setting, to capture multilateral resistance that is time varying (see e.g. Baldwin and
Taglioni, 2006). We cannot do this in our framework, because importer-time and exporter-time
effects would absorb the crisis dummies which are the regressors of interest here. Thus, while the
bilateral time-invariant importer-exporter dummies completely eliminate the cross-sectional
correlation between the estimated coefficients and unobserved multilateral resistance term, they
do not address the time series component of the bias. In order to address the latter source of bias,
we allow the importer-exporter pair dummies to vary across decades, and even across 5-year
periods (see Section IV.B for details). This strategy can attenuate the time series component of
the bias, to the extent that the variation in price indices over time occurs at lower than annual
frequency for a large number of countries.
III. A FIRST LOOK AT THE DATA
Our sample consists of 153 advanced, emerging, and developing economies, covering the
period 1970–2009. Bilateral import and export flows are  obtained  from  the  IMF’s  Direction of
Trade Statistics (DOTS) database. These are reported in current U.S. dollars and are deflated
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using the world import and export price deflators, respectively, from the International Financial
Statistics (IFS)  database,  to  get  each  country’s  real  imports  and  exports.6
Crisis dates are taken from Laeven and Valencia (2008, 2010). They identify 129 episodes
of systemic banking crises since 1970. The banking crisis definition combines quantitative
indicators measuring banking sector distress, such as a sharp increase in nonperforming loans,
large number of defaults, bank runs and a decline in the aggregate banking system capital, with
subjective assessment of the situation. Laeven and Valencia (2008) also identify 60 episodes of
sovereign debt crises—defined as episodes of sovereign debt default and/or restructuring—over
the same time period. The majority of countries in our sample have been involved in a banking
or debt crisis over the sample period. Of the 153 countries in our sample, about three-quarters
(119) had a crisis at some point during the sample period. Banking crises are quite dispersed
across regions. There are 13 episodes of banking crisis during 2007-08, which were concentrated
in the advanced economies. Debt crises have been mostly concentrated in Latin America (34
percent) and Sub-Saharan Africa (41 percent), with two-thirds of them occurring during the
1980s. We do not focus on currency crises in the baseline analysis, as trade dynamics following
such crises are fundamentally different—the most important characteristic of currency crises is,
by definition, a large exchange rate depreciation, which greatly influences the post-crisis
dynamics of both imports and exports. 7
Other standard variables used to estimate the gravity model include real GDP, population,
and various country-pair characteristics, such as distance and colonial ties. Real GDP and real
GDP per capita in U.S. dollars are obtained from the IMF’s  World Economic Outlook (WEO)
database. Country-pair variables including distance, a common land border, island and
landlocked status, common legal origin, language, and colonial ties are from Glick and Taylor
(2010), while indicators for whether countries belong to a currency union or a free-trade area are

6 The results discussed below are robust to using the nominal dollar values of trade and GDP instead.
7 Trade dynamics following currency crises (as defined by Laeven and Valencia, 2008) are qualitatively similar to
trade dynamics following banking crises, but with a much deeper initial fall in imports followed by a faster recovery
to gravity-predicted levels. In the analysis below, we also investigate the role of the exchange rate—both changes in
its level and its volatility.
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from Glick and Rose (2002), which we extend until 2009. Further details of all the data used in
the empirical analysis are outlined in the appendix and summarized in Table A1.
Table 1 presents some summary statistics on the number of observations and frequency of
crises. Our full sample contains 372,060 bilateral importer*exporter*year observations. Notice
that instead of constructing trade flows by averaging exports and imports for each country pair,
we use the unidirectional trade value and introduce both importer and exporter fixed effects and
their interaction. Thus, each country-pair which trades in both directions is represented twice:
once for the imports from 𝑗 to 𝑖 and once for the imports from 𝑖 to 𝑗. This gives us 20,003
importer*exporter pairs involving 153 countries. The bulk (two-thirds) of these observations is in
the later sample period from 1990-2009, reflecting the greater geographical diversification of
trade flows as many developing countries embarked on the process of trade liberalization.
Summary statistics of all the variables used in the empirical analysis are provided in Table A2.
Crisis is not an infrequent occurrence in the data. Almost 7 percent of the observations in the
sample involve a contemporaneous crisis in either the importing or exporting country.
Before proceeding to the gravity framework, we examine how imports and exports evolve
following financial crises. Figure 3 presents a first look at the data: it plots the coefficients on the
importer and exporter crisis indicators and their lags from a simple regression of bilateral trade
flows on these indicators, importer*exporter and time dummies. On average, imports fall by
about 11 percent in the crisis year. An additional drop of about 13 percent occurs the following
year. Imports recover slowly in subsequent years, so that even 10 years after the crisis, they are
about 5 percent below what would have been predicted in the absence of a crisis. The effect on
exports is smaller and often statistically indistinguishable from zero. There is no sharp drop in
exports in the short term; exports drop by only 3 percent on average at the onset of a crisis, and
they  recover  quickly  to  their  “normal”  level  within  two  years  following  the  crisis.
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In the next section, we analyze more formally whether this sharp and long lasting
reduction  in  imports  simply  reflects  the  change  in  the  country’s  fundamentals  in  the  aftermath  of  
a crisis (such as, for example, the decline in income), or a disruption in trade flows, away from
their gravity predicted levels.
IV. GRAVITY FRAMEWORK RESULTS
A. Main Findings
The estimates from the augmented gravity model of trade, using our preferred
specification, equation (1), are presented in Table 2. To account for potential autocorrelation and
heteroskedasticity in the error term, standard errors are clustered at the importer*exporter level
(see Bertrand, Duflo and Mullainathan, 2004). The impact of the usual gravity time-invariant
country-pair controls, such as distance, is captured by the importer-exporter fixed effects. We
include the contemporaneous and lagged crisis indicators in the importer and exporter countries.
The number of lags was chosen by a top-down approach (Pedroni, 2004): we include lags of the
crisis indicators until the estimated coefficients on crisis in the importing country become
statistically insignificant. This occurs at the 10th lag of the indicator for crisis in the importing
country. For brevity, the coefficients on the year and importer*exporter fixed effects are not
reported.
Not surprisingly, the gravity model fits the data well, explaining about 87 percent of the
variation in bilateral trade flows. The estimated coefficients on most of the importer- and
exporter-time varying control variables such as GDP, currency union and free trade agreements
(FTA) are plausible and similar to what has been found in the literature (see for example, Rose
(2000), and Glick and Taylor (2010)).8
The key variables of interest are the importer and exporter crisis dummies and their lags,
which  capture  the  effect  a  crisis  has  on  a  country’s  imports  and  exports  during  its  onset  and  in  

8 In the baseline specification, we include only the current value of the dummy for FTA. However, as Baier and
Bergstrand (2007) have shown, FTAs can have strong cumulative effects on trade (we thank an anonymous referee
for pointing this out). In order to address this issue, we estimate an alternative specification where we include
current as well as five lags of the FTA variable. The coefficients on the importer and exporter crisis variables remain
very similar to the baseline.