The volatility of world trade in the 21st century: Whose fault is it anyway?

• DOI: http://doi.org/10.1111/twec.12826
• Author: Daniel Lederman,Federico Bennett,Samuel Pienknagura,Diego Rojas
• Published date: 01 September 2019
• Date: 01 September 2019

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wileyonlinelibrary.com/journal/twec World Econ. 2019;42:2508–2545.

© 2019 John Wiley & Sons Ltd

Received: 30 June 2017

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Revised: 25 January 2019

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Accepted: 12 February 2019

DOI: 10.1111/twec.12826

ORIGINAL ARTICLE

The volatility of world trade in the 21st century:

Whose fault is it anyway?

FedericoBennett1

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DanielLederman2

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SamuelPienknagura3,4

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DiegoRojas2

1Duke University, Durham, North Carolina

2The World Bank, Washington, District of Columbia

3International Monetary Fund (IMF), Washington, District of Columbia

4Facultad de Ciencias Sociales y Humanisticas (FCSH), ESPOL, Guayaquil, Ecuador

KEYWORDS

economic development, trade liberalisation, volatility

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INTRODUCTION

The volatility of international trade flows gained prominence in the aftermath of the global financial

crisis of 2008–09. This event motivated analyses about the causes of the collapse of world trade.

Eaton, Neiman, Kortum, and Romalis (2016) is a prominent contribution that focuses on demand and

supply‐side factors that can explain why trade declined more than global GDP. In previous years, as

the developing world opened up to international trade during the 1990s, the literature on international

business cycle synchronisation driven by trade flows flourished (Calderón, Chong, & Stein, 2007;

Kose, Prasad, & Terrones, 2003). Thus, the literature has treated international trade both as a conduit

for the transmission of volatility across countries and as the recipient of shocks emanating from coun-

try‐specific factors.

The above discussion suggests that understanding the factors affecting the volatility of inter-

national trade flows is of interest in itself, not just because it can affect other economic out-

comes. Yet, as far as we know, the literature studying the sources of volatility of international

trade flows per se is rather limited.1

In an attempt to contribute to the understanding of the forces

driving the volatility of trade, this paper follows the methodology proposed by Koren and

Tenreyro (2007) combined with the gravity model of trade. This approach allows us to decom-

pose trade volatility into six factors that have received attention in the literature—a common

1 Di Giovanni and Levchenko (2002) is one of the few papers exploring this issue. However, as will be argued later, the

authors focused exclusively on the link between the composition of a country's export basket and export volatility.

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(global) term, a country‐specific term, a trading‐partner term, a sectoral ter m, a resistance term

and an error term.2

Broadly speaking, the discussion over trade volatility has focused around four potential forces that

are related to the above‐mentioned factors. First, there is a conventional wisdom view that emphasises

the role of growing trade and financial globalisation as a cause of volatility and business cycle syn-

chronisation. To be sure, the evidence prior to the global financial crisis of 2008–09 provided limited

support to the idea that globalisation leads to business cycle synchronisation (Kose et al., 2003). Yet,

the great degree of co‐movement observed since the global financial crisis brought the attention back

to globalisation as a potential source of volatility. Underlying this conventional view is the idea that

there are shocks that are common across countries and sectors of the economy, that is, that are global

or common factors that help to explain trade volatility.

A second source of volatility identified in the literature is related to country‐specific shocks. For

instance, Koren and Tenreyro (2007) argue that country‐specific risks, which they interpret as domes-

tic policy risks, explain a large share of GDP volatility. Relatedly, Raddatz (2007) shows through a

VAR exercise that internal factors (as opposed to external factors such as commodity prices) are the

main source of fluctuations in low‐income countries. In these papers, country‐specific shocks cut

across all sectors in the economy.

A third source of volatility is related to trade connections and the identity of trading partners of a

given economy. More specifically, the literature has stressed the role of trade linkages as a channel

through which shocks are propagated (Frankel & Rose, 1998; Calderón et al., 2007; Jansen, Lennon,

& Piermartini, 2016). This suggests that deeper trade linkages increase a country's exposure to shocks

emanating from their partners. However, the extent to which trade linkages are an important driver of

volatility is related to the magnitude of these shocks. Hence, the intensity of a country's trade linkages

and the identity of the partners with whom these linkages are established may be important drivers of

volatility.

Finally, the literature has emphasised the role of product or sectoral composition as a factor af-

fecting volatility. In particular, Imbs and Wacziarg (2003) and Klinger and Lederman (2004, 2006)

find that poorer countries, which tend to display higher export volatility, have more concentrated

production and export baskets. In addition, Koren and Tenreyro (2007) show that poorer countries are

concentrated in sectors that are more volatile.

Our decomposition looks at the contribution these four factors have in explaining trade volatility.

Additionally, a resistance term is also analysed. This additional term is included to take into account

that bilateral resistance (e.g., distance, free trade agreements, among others) varies over time and

across sectors when explaining trade flows. For example, Berthelon and Freund (2008) find that 25%

of traded goods have experienced an increase in their elasticity with respect to distance and that dif-

ferentiated goods have a lower distance elasticity compared to homogeneous goods. This suggests that

changes in search and transportation costs driven from technological change may favour some prod-

ucts more than others. As a result, countries with export baskets concentrated in goods experiencing

more drastic changes in their distance elasticities are more prone to experiencing volatility stemming

from this channel.

2 The global term reflects the volatility of shocks that change world average trade flows. The trading‐partner term refers to the

volatility of international trade flows that can be attributed to shocks that stem from trading partners. The sectoral term refers

to the volatility that can be attributed to shocks that stem from sectors that are present in a country's trade basket. The

resistance term refers to the volatility that can be attributed to changes in the geography and economic characteristics of

trading partners and changes in the elasticity of trade to these attributes. Finally, the error term is the volatility that cannot be

attributed to the aforementioned elements.

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Throughout the paper, export (import) volatility is defined as the variance over time of the growth

rate of real exports (imports). Following this definition, the results of the empirical exercise presented

in this paper are threefold. First, a decomposition of trade volatility over the past 25years points to two

factors as main drivers of trade growth volatility over that period. The largest contribution can be at-

tributed to the volatility of the common factor and the resistance term. When the two are taken to-

gether (i.e., when their correlation is taken into account), they explain close to 70% of the volatility of

exports of the average country.3

The second largest contribution comes from the country‐specific and

the error terms, which taken together account for close to 30% of the overall volatility of exports. In

contrast, the product and partner effects do not appear to add significantly to trade volatility, beyond

the effect captured by the common factor.

Second, the volatility decomposition presented in this paper provides a useful methodology to un-

derstand the evolution over time of the six components of volatility. In particular, the paper performs

additional decompositions using 10‐year rolling windows to study changes over time of the elements

of interest. The results of this exercise highlight two important trends among the factors contributing

to trade volatility. On the one hand, the common effect and the product effect experienced a sharp in-

crease in volatility since 2009, after years of relatively flat volatility profiles. In contrast, the country‐

specific and error terms show a steady downward trend throughout the period of analysis, especially

until 2008. Hence, the results suggest that the decline in trade volatility observed prior to 2009 was

mainly driven by a gradual decline in country‐specific risk. Moreover, the decline in the volatilities of

the country‐specific and error terms relative to that of the common effect was not reversed after the

global financial crisis. This shows that, on average, countries were able to maintain lower variances

of the country‐specific term relative to the early periods even as total trade volatility increased since

2008. In contrast, the post‐2009 spike in trade volatility appears to be driven mainly by a sudden rise

in the volatility of common factors and, to a lesser extent, in sectoral volatility.

Finally, the paper explores one potential force driving the decline in the volatility of the coun-

try‐specific term described above—trade diversification. We do so by pursuing three alternative ex-

ercises. First, the paper shows that the variance of the country‐specific term is negatively correlated

with the initial number of product–partner pairs of a country. Moreover, we show that this negative

correlation is not driven by other variables that are linked to both diversification and volatility, such

as a country's GDP per capita or population. Second, we use a fixed‐effects approach to highlight that

as countries become more diversified, they experience a significant reduction in the variance of the

country‐specific term. Lastly, we study the effect of trade diversification on country‐specific trade

volatility by exploiting differences in the timing of trade liberalisation. Kose, Prasad, and Terrones

(2005) and Cadot, Carrère, and Strauss‐Kahn (2013) provide evidence of an increase in the degree

of diversification following periods of trade liberalisation. This implies that countries that liberalised

trade more recently should have had bigger gains in terms of diversification compared to those that

liberalised earlier, and, as a result, experienced greater reductions in the volatility of the country‐spe-

cific term. We test this hypothesis by analysing the evolution of the volatility of the country‐specific

term in two groups of countries: (a) those that liberalised trade prior to 1985 (early liberalisers) and

(b) those that liberalised trade between 1985 and 1998 (recent liberalisers). The results show signifi-

cant differences between the two sets of countries. Regarding the initial levels of volatility, countries

with recently liberalised trade regimes have higher levels of volatility in the country‐specific term

compared to countries with more established liberalised trade regimes. However, the difference in

3 Bennett et al. (2016) study the determinants of the volatility of both export and import growth and find that the results are

very similar. For the sake of conciseness, the discussion throughout this paper focuses exclusively on the results obtained

from a decomposition of the variance of export growth.