International Business

Article Review Assignment

Submitted by:Purnima Shrestha

4th semesterSchool of Management Tribhuvan University

Submitted to:Dr. Arhan Sthapit

School of Management Tribhuvan UniversityAugust, 2015

Causality between GDP, Export and Import in India (1950-2007): A Granger Causality Approach

This article titled “Causality between GDP, Export and Import in India (1950-2007): A

Granger Causality Approach” is authored by Rahul Ranjan and Abhishek Kumar Chintu

and was published in Sumedha Journal of Management (volume 2, January-March

2013).The study analyses the real GDP, real import and real export figures of India for

the period of 1950/51 to 2008/09 to test the whether there is long run equilibrium relation

between the GDP, export and import. Hence, the study period encompasses the ‘pre

reform’ (1970/71-1990/91) as well as ‘post reform period’(1991/93 -2008/09).

There are usually two strategies adopted by countries for economic growth; one is

‘import substitution’ and the other is ‘export based industrialization’. Before the

industrial policy of 1991, India followed import substitution strategy by imposing higher

tariffs and quotas on imports. However India gradually shifted towards export promotion

after the 1991 industrial policy. Tariff rates were reduced and quotas were also abolished

gradually. Financial incentives were provided in the form of tax exemption on exportable

commodities. Exclusive Export Processing Zones (EPZ) were established to attract

foreign direct investment and export promotion. Foreign firms, investing in EPZs, got

special preference and tax exemption facilities. Hence, in this manner India moved from

import substitution to export promotion. Export-led growth strategy is preferred because:

first, trade expansion will bring about enhanced productivity through increased

economies of scale in the export sector, positive externalities on non-exports and through

increased capacity utilization. Second, exports may affect productivity through

encouraging better allocation of resources driven by specialization and increased in

efficiency, which in turn generate dynamic comparative advantage via reduction in costs

for a country that facilitates exports. Third, through encounters with international

markets, trade will facilitate more diffusion of knowledge (especially in the process of

interaction with foreign buyers and learning by doing gains) and more efficient

management techniques which will have a net positive effect on the rest of economy and

enhance overall economic productivity. Fourth, export growth also promotes capital

accumulation and accumulation of foreign exchange and thus enables the importation of

capital and intermediate inputs necessary in the production of goods exports. Thus, this

study broadly examines the impact of export and import on GDP in view of India's

changing financial markets and policy by using simple Ordinary Least Square (OLS)

method.

While, the regression analysis deals with the dependence of one variable on the other

variables; it does not necessarily imply causation. However, the Granger Causality test is

used to test the causality relationship between the variables. That is, if event A happens

before event B, then it is possible that A is causing B. However, it is not possible that B is

causing A. In other words events in the past can cause events to happen today. Applying

the Granger causality test in for the concerned variables i.e. import, export and GDP, it is

found out that there is no long run equilibrium relationship between GDP, import and

export i.e. GDP does not cause export or export does not cause GDP and GDP does not

cause import or import does not cause GDP. It is usually assumed current context of

increasing world trade that import/export have significant impact on GDP (more

specifically import/export activities helps in GDP growth of a country) and vice versa.

Hence, the significance of this article is that it breaks this assumption that there is always

a causality relationship between import/export and GDP based on concerned data

analysis for a considerably long duration of time; 1950-2007.

.

Nepal's Trade Flows: Evidence fromGravity Model

This working paper titled “Nepal's Trade Flows: Evidence from Gravity Model” is

authored by Surya Bahadur Thapa and was published in NRB economic review. This

study is carried out to estimate the trade potentiality of Nepal using gravity model. The

gravity model simply explains that the volume of trade between pairs of countries is a

positive function of the size of two countries and negative function of the distance

between them. The model is popular for empirical research because it explains a very

large portion of actual trade flows observed in the world.

Considering the significance of trade in economic development, Nepal has been shifting

towards liberal and market-oriented trade policy since the mid-1980s that was

accompanied by various reform programs in 1992 .Under these reforms, the country has

introduced export-oriented policies in order to increase the volume of exports. Similarly,

import substitution policies have been removed. Thus, the general objective of the present

study is to estimate the gravity model of Nepal while the specific objectives are as

follows: (i) to evaluate the determinants of bilateral trade flows of Nepal and (ii) to

explain Nepal’s trade potential. The gravity model of international trade is a simple

empirical model for analyzing trade flows between countries. The model states that the

bilateral trade flows is directly proportional to the product of the economic size (GDP or

GNI) of country ‘i’ and ‘j’ and inversely proportional to the distance between the two

countries. The simplest form of the gravity model appears in the following form.

Tij = A (YiYj)/(Dij

Where,

Tij = Bilateral trade flows (exports plus imports) between country i and j.

Yi (j) = GDP or GNI of country i(j).

Dij = Distance between country i and j.

A = Constant of proportionality.

Here, GNI is taken as an independent variable because the product of GNI serves as a

proxy for the two countries’ economic size, both in terms of production capacity and the

size of the market. Similarly, distance is taken as another independent variable because

the distance between two countries serves as a trade barrier variable such as transport

cost, time and other such variables. This study covers Nepal’s 19 trading partners

namely; Australia ,Bangladesh, Brazil,

Canada ,China ,Denmark ,France ,Germany ,Hong

Kong ,India ,Italy ,Japan ,Malaysia ,Netherlands ,New Zealand ,Singapore,

Switzerland ,UK and USA .From the OLS method it is revealed that trade volume

between Nepal and her 19 trading partners is positively affected by economic size of the

countries while distance plays a negative role and the variable per capita income plays

insignificant role. Based on the gravity model estimation of the Nepal’s trade potential, it

shows that Bangladesh, Brazil, Denmark, France, Germany, Hong Kong, Italy, Japan,

and the Netherlands reveal potential for expansion of trade. Thus, to increase the trade

and exploit the trade gap with these countries Nepal needs to adopt suitable trade

promotional strategies. Similarly, the volume of trade with a particular country may be

increased in the future as a result of increase in the GNI in the future and reduction of

distance by adopting appropriate trade facilitation measures. Hence, it does not mean that

Nepal cannot extend the trade relations with the countries that exceeded her trade

potential at present.

All in all, the significance of this study is that it uses the gravity model to evaluate the

determinants of foreign trade of Nepal and contributes to the literature on the application

of gravity model in Nepal for the researchers, learners, policy makers in particular and for

all other interested parties. Moreover, it also evaluates whether Nepal still has some

untapped trade potential with its major trading partners. Furthermore, it provides useful

indicators for current negotiations for the country specific trade promotional policies and

bilateral trade as well. However, this study has been limited only to independent variables

including GNI, per capita GNI and distance. It could have included additional

explanatory variables such as openness indicator, trade complementary index etc. in the

model which would make the study more significant. Likewise, the study is based only

on cross section data of merchandise trade at an aggregate level, and not on product

specific disaggregated data. Hence, the study could have more weight if trade in other

areas such as services an intellectual property rights would have been included.