How Does Trade Evolve in the Aftermath of Financial Crises?

56 Pages·2010·1.31 MB·English

WP/11/3

How Does Trade Evolve in the Aftermath
of Financial Crises?

Abdul Abiad, Prachi Mishra, and Petia
Topalova
© 2010 International Monetary Fund WP/11/3

IMF Working Paper

Research Department

How Does Trade Evolve in the Aftermath of Financial Crises?

Prepared by Abdul Abiad, Prachi Mishra, and Petia Topalova1

Authorized for Distribution by Andrew Berg and Petya Koeva Brooks

January 2011

Abstract
We analyze trade dynamics following past episodes of financial crises. Using an augmented
gravity model and 179 crisis episodes from 1970-2009, we find that there is a sharp decline in a
country’s imports in the year following a crisis—19 percent, on average—and this decline is
persistent, with imports recovering to their gravity-predicted levels only after 10 years. In
contrast, exports of the crisis country are not adversely affected, and they remain close to the
predicted level in both the short and medium-term.
JEL Classification Numbers: F10, G01
Keywords: trade, financial crises
Author’s E-Mail Address: [email protected]; [email protected], [email protected]

This Working Paper should not be reported as representing the views of the IMF.
The views expressed in this Working Paper are those of the author(s) and do not necessarily
represent those of the IMF or IMF policy. Working Papers describe research in progress by the
author(s) and are published to elicit comments and to further debate.

1 We are grateful to Andrew Berg, Olivier Blanchard, Don Davis, Petya Koeva Brooks, David Romer, Philippe
Martin, Andrei Levchenko, and seminar participants at the World Bank, IMF, 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. We thank Peter Pedroni for kindly providing the programs to
perform panel unit root and cointegration tests
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Contents Page
I. Introduction .......................................................................................................................4
II. Methodology .....................................................................................................................6
III. A First Look at the Data ....................................................................................................8
IV. Gravity Framework Results ..............................................................................................9
A. Main Findings ...............................................................................................................9
B. Robustness ..................................................................................................................13
V. Differences in Trade Dynamics Across Products, During Global Downturns, and Over
Time ................................................................................................................................18
A. Do Postcrisis Trade Dynamics Vary Across Products? .............................................18
B. Are Postcrisis Trade Dynamics Different During Global Downturns? ......................20
C. Do Postcrisis Trade Dynamics Vary Over Time? ......................................................21
VI. Conclusions .....................................................................................................................22
VII. Tables
Table 1. Sample Characteristics ......................................................................................24
Table 2. Imports and Exports Following Crises: Pooled Panel Gravity Estimates,
1970-2009 .......................................................................................................................25
Table 3. Tariff Equivalent Trade Costs ...........................................................................26
Table 4. Imports and Exports Following Crises: Robustness .........................................26
Table 5. Reverse Causality Issues ...................................................................................28
Table 6. Imports and Exports of Various Product Categories Following Crises ............30
VIII. Figures
Figure 1. Growth Rate of World Real Imports ..............................................................32
Figure 2. Evolution of Imports in Crisis and Non-Crisis Countries ...............................33
Figure 3. Distribution of Crises across Time and Regions .............................................34
Figure 4. Evolution of Imports and Exports Following Crises: A First Look ................35
Figure 5. Evolution of Imports and Exports Following Crises: Gravity Model .............36
Figure 6a. Evolution of Exchange Rates Following Crises ............................................37
Figure 6b. Why a Persistent Drop in Imports Following Crises? ...................................38
Figure 7. Evolution of Imports and Exports Following Crises: Robustness ...................39
Figure 8. Evolution of Imports and Exports Following Crises: Robustness ...................40
Figure 9. Evolution of Imports and Exports for Different Product Categories ..............41
Figure 10. Evolution of Imports and Exports Following Crises during Global
Downturns .......................................................................................................................42
Figure 11. Evolution of Imports and Exports Following Crises in Importer and
Exporter...........................................................................................................................43
Figure 12. Evolution of Imports and Exports Following Crises: Pre and Post- 1990 ....44
IX. References .......................................................................................................................45
X. Appendixes
Appendix 1. Data Sources...............................................................................................50
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Appendix 2. Time-series Properties of Imports and GDP ..............................................51
XI. Appendix Tables
Table A1. Summary Statistics to Main Variables ...........................................................52
Table A2. Panel Unit Root and Cointegration Tests .......................................................53
Table A3. Data Sources ..................................................................................................54
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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 three decades of relative
tranquility following the end of World War II were more the exception than the norm; since
the mid-1970s, both debt and banking crises have been relatively frequent, continuing a
pattern that extends back to at least the start of the 19th century. So it comes as no surprise
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 are followed by 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. Understanding the behavior of trade is crucial as it is
an important channel through which crises can affect economic welfare and growth.
Moreover, looking at the experience of the past can help us understand how trade might
evolve for economies that recently went through such crises.
This paper provides empirical evidence on trade dynamics following past banking and debt
crises. How has trade evolved in the past following banking and debt crises? Do such crises
have lasting effects on a country’s imports and exports? Do crises influence the behavior of
trade only through their effect on output and the standard gravity determinants of trade, or are
they followed by the rise of other impediments to trade?
Most of the literature on trade and crises has focused on what happens to trade following
global economic downturns, and especially on explaining the “Great Trade Collapse” that
followed the 2008-09 global economic crisis (see Baldwin, 2009 and references therein).
Taking a historical perspective, Freund (2009) finds that the decline in world trade following
four previous global downturns was almost five times bigger than the corresponding decline
in world GDP, and that while world trade growth resumes quickly following a global
downturn, it takes more than three years for pre-downturn levels of trade openness to be
reached. 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; this should thus be seen as a
complement to the existing literature.
The recent global downturn does, in fact, provide some suggestive evidence that trade
dynamics may be different for countries that suffered a financial crisis. While the collapse of
trade that occurred in late 2008 and early 2009 was “sudden, severe, and synchronized”
(Baldwin, 2009) as depicted in Figure 1, its recovery so far has been uneven across countries,
with an important distinction being whether a country recently had a banking crisis. For
countries that did not have a banking crisis (Figure 2, left panel), real imports were on
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average back to their precrisis peak by the first quarter of 2010. In contrast, for the thirteen
countries identified by Laeven and Valencia (2010) as having had a systemic banking crisis
from 2007 onwards, real imports were on average well below their precrisis peaks (Figure 2,
right panel).
The reason such evidence can only be suggestive at best is that, as has been documented in
the literature, output falls substantially following a financial crisis. So the differences
documented in Figure 2 may simply reflect the substantial differences in output dynamics
across these two groups. To find out whether trade behaves “abnormally” in the aftermath of
a financial crisis, one would need an analytical framework that accounts for output dynamics.
This paper uses the workhorse of the empirical trade literature—the gravity model of trade—
to gauge the extent to which trade behaves differently from “normal” following a financial
crisis.
Our empirical approach follows a growing body of literature that has used the gravity model
of trade to investigate the effects of various types of “shocks” to an economy on trade. 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, while 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, and find the tariff-equivalent cost of violence to be between 7 and 17
percent.2
To date, two other studies have used the gravity framework to analyze postcrisis trade
dynamics. Ma and Cheng (2003) use a smaller sample of 52 countries over the period 1981-
1998, and focus on short-term effects up to two years after a crisis. They find that banking
crises have a negative impact on imports and a positive effect on exports in the short run.
While their paper analyzes trade values, here we look at trade volumes. In addition to the
broader coverage of countries and years that we use, we also subject our results to a greater
number of robustness tests, and we examine whether the effects of crises vary across
different product categories, over time, and across global downturns. Berman and Martin
(2010) 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, and that the effect is larger for African exporters.

2 There are a number of papers that investigate the trade impact of various policy regimes, such as exchange rate
regimes and currency unions (f.ex. Rose, 2000, Glick and Rose, 2002, Klein and Shambaugh, 2006), exchange
rate volatility (Thursby and Thursby, 1987), preferential trade agreements (f.ex. Frankel, Stein and Wei, 1996),
democracy (Yu, 2010) etc.
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We examine episodes of banking and debt crises over the past 40 years and track the changes
in imports and exports of a country following such crises. Even after controlling for output
and other standard gravity controls, we find that 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 to normal within one year. These findings are robust to
various alternative specifications and methodologies, such as including exporter and importer
fixed effects as well as their interaction to control for any bilateral time-invariant
characteristics; addressing omitted-variable and selection biases using the Helpman, Melitz
and Rubinstein (2008) framework; allowing the elasticity of trade with respect to GDP to
vary across the cyclical and trend components of outputs and across crisis and non-crisis
periods; introducing various additional controls such as exchange rates, domestic absorption,
prices, and time-varying multilateral resistance terms; isolating episodes of “pure” financial
crises that were not accompanied by large depreciations; and looking at aggregate rather than
bilateral trade patterns. In addition, we conduct some simple tests to address the potential
endogeneity of crises; these tests, though far from definite, show a very consistent picture
and support the main findings.
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 Section V
illustrates some additional findings. Section VI 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.3 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. We augment the conventional gravity model to include indicators of crisis in the
importing and exporting countries.
Our main estimating equation is specified as follows:

3 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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(cid:1864)(cid:1866)(cid:1839) (cid:3404)(cid:1503) (cid:3397)(cid:2024) (cid:3397)(cid:3533) (cid:1503) (cid:1855)(cid:1870)(cid:1861)(cid:1871)(cid:1861)(cid:1871) (cid:3397)(cid:3533)(cid:2010) (cid:1855)(cid:1870)(cid:1861)(cid:1871)(cid:1861)(cid:1871)
(cid:3036),(cid:3037),(cid:3047) (cid:3036)(cid:3037) (cid:3047) (cid:3038) (cid:3036),(cid:3047)(cid:2879)(cid:3038) (cid:3038) (cid:3037),(cid:3047)(cid:2879)(cid:3038)
(cid:3038) (cid:3038)
(cid:3397)(cid:2011) lnY (cid:3397)(cid:2011) lnY (cid:3397)(cid:2012) lny (cid:3397)(cid:2012) lny (cid:3397)(cid:2020)(cid:1850) (cid:3397)(cid:2013)
(cid:2869) (cid:2919)(cid:2930) (cid:2870) (cid:2920)(cid:2930) (cid:2869) (cid:2919)(cid:2930) (cid:2870) (cid:2920)(cid:2930) (cid:3036)(cid:3037)(cid:3047) (cid:3036),(cid:3037),(cid:3047)
(1)
Where ln(cid:1839) is the (log) imports of country (cid:1861) from exporter (cid:1862) at time (cid:1872), and (cid:1855)(cid:1870)(cid:1861)(cid:1871)(cid:1861)(cid:1871) and
(cid:3036),(cid:3037),(cid:3047) (cid:3036),(cid:3047)(cid:2879)(cid:3038)
(cid:1855)(cid:1870)(cid:1861)(cid:1871)(cid:1861)(cid:1871) are dummy variables indicating whether the crisis started in period (cid:1872) (cid:3398)(cid:1863) in the
(cid:3037),(cid:3047)(cid:2879)(cid:3038)
importer and exporter respectively. (cid:1503)  denotes importer-exporter pair dummies, which
(cid:3036)(cid:3037)
control for all possible time-invariant country-pair characteristics such as distance, common
language, common border, etc. 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).4 (cid:2024) represents time dummies, which capture factors that
(cid:3047)
affect all countries’ trade simultaneously, such as global downturns, or global changes in
commodity prices. Finally, (cid:1850) captures other importer-exporter time-varying controls such
(cid:3036)(cid:3037)(cid:3047)
as whether trading partners are part of a currency union or free trade agreement in time (cid:1872).
Since we find strong evidence of cointegration between imports and GDP, we estimate (1) in
levels.5
The coefficients of interest are (cid:1503)  and (cid:2010) . (cid:1503) captures the average effect of a crisis in
(cid:3038) (cid:3038) (cid:3038)
country (cid:1861) on its imports from country (cid:1862), (cid:1863) years after the beginning of a crisis in country (cid:1861); (cid:2010)
(cid:3038)
captures the average effect of a crisis in country (cid:1862) on country (cid:1861)’s imports from country (cid:1862)—or
equivalently, country (cid:1862)’s exports to country (cid:1861)—(cid:1863) years after the crisis. In other words, (cid:1503)
(cid:3038)
measures the average effect of a crisis on a country’s imports, and (cid:2010) 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, the
estimated coefficients on crisis indicators capture whether (cid:1863) 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.

4 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. As a robustness
check, we allow the multilateral resistance terms to vary across decades (see Section IV. B for details).
5 Under cointegration, standard panel techniques produce superconsistent estimates of slope coefficients (the
rate of convergence is faster in the panel than in the time series case); we get precise estimates even in small
panels and even if regressors are endogenous (see e.g. Pedroni, 2000). See Appendix for details.
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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 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.
Crisis dates are taken from Laeven and Valencia (2008, 2010). They identify 129 episodes of
systemic banking crises—defined as situations in which the financial sector experiences a
large number of defaults, nonperforming loans increase sharply, and all or most of the
aggregate banking system capital is used up—since 1970. They also identify 60 episodes of
sovereign debt crises—defined as an episode of sovereign debt default and/or restructuring
—over the same time period.6 We focus here on banking and debt crises (henceforth referred
to as “financial” crises or simply “crises”) in part because the most recent crises have been
systemic banking crises, and because the prospect of a sovereign debt crisis in a number of
economies has been increasing.7
Figure 3 shows the distribution of financial crises across regions and time. The 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. It is worth noting that 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.
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 IMF’s World Economic Outlook
(WEO) database. Country-pair variables including distance, a common land border, island

6Of the banking and debt crises in the Laeven-Valencia data set, there are ten cases where the two coincide. An
analysis of these “twin banking and debt crises” suggests that trade dynamics following these episodes was
qualitatively similar to those with only one type of crisis, although the effects were slightly more accentuated.
However, these findings should be interpreted with caution given the limited number of observations.
7 We do not focus on currency crises in the 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. Nevertheless, in the
analysis below we investigate the role of the exchange rate—both changes in its level and its volatility. In
addition, we control for bilateral exchange rates in the regression analysis, and also isolate the effect of “pure”
financial crises by excluding crisis episodes which were preceded by a currency crisis.
9
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 from Glick and Rose (2002), which we extend until 2009. Further details of all
the data used in the empirical analysis are outlined in Appendix I.
Table 1 presents some summary statistics on the 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.
Thus, each country-pair which trades in both directions is represented twice: once for the
imports from (cid:1862) to (cid:1861) and once for the imports from (cid:1861) to (cid:1862). 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. Summary statistics of all the variables used in
the empirical analysis are provided in Table A1. Unlike war (see Glick and Taylor, 2010),
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 4 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.
In the next section, we analyze more formally whether, within the gravity framework of
trade, crises continue to have lasting effects on imports and little effect on exports.
IV. GRAVITY FRAMEWORK RESULTS
A. Main Findings
Table 2 presents estimates from the augmented gravity model of trade, using our preferred
specification, equation (1). To account for potential autocorrelation and heteroskedasticity in
the error term, standard errors are clustered at the importer*exporter level. Since the baseline
specification includes importer*exporter fixed effects, the usual gravity time-invariant
country-pair controls, such as distance, etc., are not included. We include the
contemporaneous and lagged crisis indicators in the importer and exporter countries. The