Asymmetric response of the US–India trade balance to exchange rate changes: Evidence from 68 industries

• DOI: http://doi.org/10.1111/twec.12521
• Author: Mohsen Bahmani‐Oskooee,Sujata Saha
• Date: 01 October 2017
• Published date: 01 October 2017

ORIGINAL ARTICLE

Asymmetric response of the US–India trade balance

to exchange rate changes: Evidence from 68

industries

Mohsen Bahmani-Oskooee

1,2

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Sujata Saha

1,2,

*

1

The Center for Research on International Economics, The University of Wisconsin-Milwaukee, Milwaukee, WI, USA

2

Department of Economics, The University of Wisconsin-Milwaukee, Milwaukee, WI, USA

1

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INTRODUCTION

Interest in the link between the trade balance and the real exchange rate keeps growing, mostly

due to Magee’s (1973) introduction of the J-curve phenomenon, which basically attempts to distin-

guish the short-run and the long-run effects of exchange rate changes on the trade balance. The

trade balance may deteriorate in the short run but can improve in the long run due to a devaluation

or depreciation. Bahmani-Oskooee and Hegerty (2010) and Bahmani-Oskooee and Ratha (2004),

who reviewed the empirical literature, showed that a majority of the studies have used aggregate

trade flows between one country and the rest of the world. These studies were criticised by Rose

and Yellen (1989) for suffering from aggregation bias. To reduce the bias, they recommended dis-

aggregating trade data by trading partners and using trade flows at the bilateral level. Their effort

in trying to detect the short-run J-curve effect, or even a long-run relationship between the US

trade balances with its six major partners and bilateral real exchange rates, was futile.

Rose and Yellen’s (1989) approach was recently criticised by Bahmani-Oskooee and Faridita-

vana (2016) for assuming the effects of real bilateral exchange rate changes to be symmetric. Once

Bahmani-Oskooee and Fariditavana (2016) argue for asymmetric effects and introduce non-linear

adjustment of the real exchange rate into the bilateral trade balance model, they demonstrate that

in most cases, indeed, currency depreciation or appreciation could have significant short-run and

long-run asymmetric effects. They then recommend the asymmetry analysis to be applied to the

experiences of other pairs of countries.

Following the recommendation of Bahmani-Oskooee and Fariditavana (2016), recently Bahmani-

Oskooee and Saha (2017) considered the asymmetry experiences of India’s bilateral trade balances

with her 14 major trading partners and provided relatively more support for the J-curve effect which

was attributed to separating depreciations from appreciations and introducing non-linear adjustment

of the exchange rate. However, in the trade balance with the USA, one of the two largest trading part-

ners of India, with more than 8% trade share, long-run asymmetric effects wer e insignificant.

1

We

*Valuable comments of two anonymous reviewers are greatly appreciated. Remaining errors, however, are our own.

1

The other largest partner is China with 9% trade share.

DOI: 10.1111/twec.12521

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©2017 John Wiley & Sons Ltd wileyonlinelibrary.com/journal/twec World Econ. 2017;40:2226–2254.

wonder whether poor results in the case of trade with the USA could be due to using aggregate bilat-

eral trade flows between the two countries. To determine the answer, we disaggregate the trade flows

by commodity and consider bilateral trade balances of 68 3-digit SITC industries that trade between

the two countries. These 68 industries conduct close to 71% of trade between the USA and India and

they are the industries for which continuous time-series data were available. To compare our findings

to previous studies, we first use the linear ARDL approach of Pesaran, Shin, and Smith (2001) where

symmetry assumption is maintained. We then apply the non-linear ARDL approach of Shin, Yu, and

Greenwood-Nimmo (2014) to identify industries which benefit from currency depreciation in the

non-linear model if not in the linear model. To that end, we introduce the models and both the meth-

ods in Section 2. Our empirical results are presented in Section 3 with a summary and conclusion in

Section 4. Finally, data definitions and sources are provided in an Appendix.

2

2

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THE MODELS AND THE METHODS

Since we are building upon and extending the results of Bahmani-Oskooee and Saha (2017), we

adopt their specification with some changes in notation so that the model conforms to the com-

modity-level data. As such, the following long-run model is adopted:

LnTBj;t¼aoþa1LnIPINDIA

tþa2LnIPUSA

tþa3LnREXtþet;(1)

where TB

j

is a measure of industry j’s trade balance and is defined as the ratio of imports

from the USA over exports to the USA by Indian industry j. As a measure of economic acti v-

ity, we include the Index of Industrial Production for both the countries and denote them by

IP

INDIA

and IP

USA

, respectively. Given these definitions, we expect an estimate of a

1

to be pos-

itive and an estimate of a

2

to be negative.

3

As the Appendix shows, the real bilateral exchange

rate is defined in a manner in which a decline reflects a depreciation of rupee and if a depreci-

ation is to improve the trade balance of Indian industry j, an estimate of a

3

is expected to be

positive.

4

An estimate of (1) by any method only yields the long-run effects of all the three exogenous

variables on the trade balance of industry j. To assess their short-run effects, especially the short-

run effects of the real bilateral exchange rate, the common practice is to convert (1) to an error-

correction model. To this end, an approach that yields short-run and long-run estimates in one

specification and in one step is Pesaran et al.’s (2001) ARDL approach. Following their approach,

the error-correction model takes the following form:

2

Studies related to India were reviewed by Bahmani-Oskooee and Saha (2017). Those who used aggregate trade flows of

India with rest of the world included: Bahmani-Oskooee (1985, 1989), Bahmani-Oskooee (1991), Bahmani-Oskooee and

Malixi (1992), Buluswar, Thompson, and Upadhyaya (1996), Himarios (1989), Ratha (2010) and Suri and Shome (2013)

who mostly found no evidence of the J-curve effect. On the other hand, Arora, Bahmani-Oskooee, and Goswami (2003)

and Dash (2013) used bilateral data between India and several partners and provided some significant results. None of these

studies engaged in asymmetry analysis.

3

Note that India’s income elasticity could also be negative due to substitution effect. As India grows, if it produces more

import-substitute goods, it will import less (Bahmani-Oskooee, 1986).

4

For a theoretical derivation of models like (1), see Rose and Yellen (1989).

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