International Journal of Economic Practices and Theories, Vol. 3, No. 3, 2013 (July), e-ISSN 2247–7225

www.ijept.org

192

Exports Performance under the Role of Foreign Direct Investment in Pakistan: An

ARDL Approach

by

Muhammad Ayaz, Muhammad Umair Yousuf, Muhammad Asghar

Lecturer, Department of Economics,

University of Baluchistan, Quetta, Pakistan

M.Phil Research Fellow, Applied Economics Research Centre,

University of Karachi, Karachi, Pakistan

M.Phil Research Fellow, Applied Economics Research Centre,

University of Karachi, Karachi, Pakistan

ayaz.economics@uob.edu.pk, umair.aerc@hotmail.com, m.asghar.ly@gmail.com

Abstract: Foreign Direct Investment (FDI) is the largest source of inflow of foreign earnings for the countries of the

developing world. This study examines the short and long run association between FDI, exports and growth for Pakistan by

employing the Autoregressive and Distributed Lags (ARDL) approach in the time series framework from 1975 to 2011.

Augmented Dickey Fuller (ADF) test is applied for checking the stationarity of data, while ARDL technique is applied for

the presence of cointegration; long run relationship and short run relationship among macroeconomic variables in case of

Pakistan. The ARDL model found cointegration at level among the variables while the Error Correction Term (ECT) is

insignificant at 1% significance level. The positive relationship between FDI and exports in the short run as well as in the

long run is predicted by the parameters of ARDL. The study suggests that government should attract FDI in those sectors

which mainly contribute to exports directly (like textile manufacturing) or indirectly (like power generation sector) to make

exports competitive in the international market.

Key Words: ARDL, exports, foreign direct investment (FDI), terms of trade.

JEL Classification: F14, F21

1 Introduction

The importance of exports and FDI has been

increasing with the passage of time. We are

living in the age of globalization and those

nations who are recognized as the world leaders

in the prevailing times are improving their

economies through increasing trade for mutual

benefits. This current structure of nations to

trade with other countries is not an instant

process. Different countries experienced

different situations with international trade

depending upon their factor endowments. As

occurred in the history of the developing world,

countries had Import Substitution policies in the

late 1950s as well as in the early 1960s are

considering international trade between nations

(on the basis of their incomplete specialization)

significantly and optimistically. They are

reaping advantages of mutual gain, promotions

of relations, reasonable prices and market

expansions. Exports and FDI are considered as

the major growth enhancing factors for the

development of the economy. FDI is one of the

most important tools which make nations

especially the developing ones to achieve the

investment levels beyond their levels of saving

because every country has limited opportunities

to grow and save in autarky condition. In this

era, it is almost impossible for every nation to

close their boundaries for international trade

The impacts of these factors are

multidimensional and they have influences on

common man whether they are social,

economical, political or cultural. World Trade

Organization (WTO) has now become an

international trading system with a framework

of principles and laws between the trading

partners. Pakistan (like other developing

nations) having problems of low productivity

and under utilization of resources due to non-

specialization and diseconomies of scale in

different sectors of the economy like agriculture

etc. There are different classical theories, which

193

favor the positive impact of international trade

and FDI inflows. The increasing globalization

all over the world has led to the increasing

competition to attract FDI in the developing

countries. Export led growth (ELG) hypothesis

states that exports are one of the most important

growth accelerating factors for the economy.

FDI allows the nations to get more benefits

(compared to others) by efficient use of their

productive resources, whether they are natural

resources, human capital etc. At the same time,

the host countries also enjoys the benefits in the

form of advanced technology (particularly from

the developed to the developing world),

improved production levels, up gradation of

physical and human capital as well, but also

have ambiguous impacts (in favor of or against)

on the social and cultural values.

The performance of exports shows the nation’s

capability to sell goods and services produce in

a domestic country to other nations in the

world. FDI inflows to the developing world

having positive externalities and may be

considered as an important component in the

development strategies made by the policy

makers because of its spillover effect on the

exports (Ahmad, Alam and Butt, 2003). Import

Substitution policies in the 1950s and 1960s

which were followed by Exports Promotion

policies in the 1970s, improved resource

allocation and increase productivity through

technological development and economies of

scale (Shirazi and Manap, 2004). There is also a

big impact of political integration between the

countries to attract FDI. Pakistan should

improve its relationship with economically

strong countries of the world on the basis of

bilateral gains and benefits (Khan, 2011).

1.1 FDI compared to other foreign financial

flows to the developing world

According to Migration and Remittances Fact

book (2011), FDI inflows are considered as the

largest source of overseas receiving for the

developing economies if compared with other

financial flows like workers’ remittances,

Official Development Assistance (ODA) and

Private Debt and Portfolio Equity (PD&PE).

Figure-1of appendix-d shows that the

developing countries are having different

sources of foreign earnings but FDI remains the

largest one since 1994. They continued to be

increasing from 1993 to 2008 then declined due

to global crises but improving with the

recovery. These financial flows help the

developing economies to deal with the problems

of financial constraints, low investment

opportunities etc.

Figure 1. FDI and Other Resource Flows to the

developing countries (1991-2009) Source: Migration and

Remittances Fact book (2011), World Bank, pp. 17.

1.2 Pakistan’s exports structure

Pakistan had been promoted from low income

group in 2008 to middle income group in 2011.

(World Bank’s Country Classifications, World

Bank, 2010). The structure of Pakistan exports

is presented in Figure-2 of appendix-d, which

shows that the exports of Pakistan are divided

into primary (17%); manufactured (74%) and

semi manufactured (9%) products. At the time

of independence 99% of Pakistan’s GDP share

was agriculture products and raw material but

today agriculture contributes only 23% in the

gross domestic product. Small portion of

exports belong to semi manufactured and

primary or raw materials. The manufactured

exports have the lion share of intermediate and

furnished textile products.

Figure 2. Structure of Pakistan Export. Source: economic

survey report of Pakistan, 2009-10

194

Figure 3 presents major exports of Pakistan’s

exports. More than half of Pakistan’s exports

belong to textile manufacturing; agro food

exports contribute 17 percent. Both of which

consist of 70 percent of total exports. Although

Pakistan remained under world economic and

political influence and subject to follow the

policies imposed by world leading economies

such as economic sanctions of 1998, issue of

9/11, political interruption by the west to

mitigate terrorism, capital flight and various

other factors contributed to economic slowdown

of Pakistan economy but in last decade Pakistan

improved its balance of payment by increasing

its manufactured export. The export structure is

presented in following figure:

Figure 3. Major products of Pakistan’s exports. Source:

Trade development authority of Pakistan, 2009-10

1.3 Significance and objectives of the study

This study will examine FDI and exports

performance for the period 1976-2011 for

Pakistan. It also investigates whether the

expansion of FDI has had any significant effect

on the exports performance of Pakistan. Further

it will help in identifying the key sectors where

Pakistan should attract FDI in order to increase

the exports performance. Theoretically it seems

that FDI significantly impact on the exports

performance, however we need to check this

phenomenon in the context of Pakistan’s

economy. Besides this, there is a need to do the

sector analysis of exports to understand and

interpret the empirical results.

With the help of empirical analysis, the aim is

to answer the following research questions.

To what extent FDI is more important in

determining the exports performance?

To find out the important sectors for

attracting FDI and formulating policies that

would yield the highest economic returns

for Pakistan.

Rest of the paper consists of review of the

related literature, data and methodology,

empirical results and discussion of the results

and finally we may draw some conclusions and

have some policy measures in this regards.

2 Literature review

The ambiguous results of different time series,

cross sectional and panel data analysis have

been analyzed in the literature. The relationship

between FDI, exports and output for Pakistan is

investigated by Ahmad et al (2003). The time

series data for the period 1972-2001 found that

there exists a long run relationship between

FDI, exports and domestic output. The

association between FDI inflows and growth for

Pakistan is analyzed by Falki (2009). These

inflows act as the growth enhancing catalyst for

countries of the developing world. However, the

positive impact of the FDI on growth is

productive through different channels like

increase in the domestic investment and human

capital with the transmission of the

technological factors.

Zhang and Song (2000) analyze the role of FDI

inflows to China from 1986 to 1997. In the

provincial panel data analysis, the role of FDI

on the exports of the country has been linked

and the conclusion of this study is that these

foreign inflows have direct impact on exports of

the manufacturing sector. Franco (2012)

analyzes the productivity spillover effects of the

foreign investment flows on the recipient

countries. This study uses data from 1990 to

2001 to evaluate the impact of the US FDI on

the exports strength at different sectors in 16

OECD countries. The conclusion of this study is

that FDI inflows positively influence the

exports performance of the host countries.

Javed et al (2012) finds out the link between

four South Asian economies (India, Pakistan,

Bangladesh and Sri Lanka) with panel data

analysis of 38 years (1973-2010). By employing

Generalized Method of Moments (GMM), this

study concludes the direct relation between

exports and growth in all the four major

195

economies while ambiguous relationship with

FDI.

Dritsaki, Dritsaki and Adamopoulos (2004)

analyze the long run relationship between FDI,

growth and trade. The time series analyses for

Greece from 1960 to 2002 also justify causal

relationship between the said variables and

conclude that growth, FDI and trade have

amalgamated affect on the country.

FDI and workers’ remittances are among the

two major sources of foreign earnings for many

developing countries. These foreign earnings

may lead to appreciation of real exchange rate

for Pakistan [Rehmen, Jaffri and Ahmed

(2010)]. Yousaf et al (2011) examines the

influence of FDI on the growth of Pakistan from

1980 to 2009. The important aspects to increase

economic growth through foreign investment

are favorable exports policies, local

infrastructure and production capacity with

improved human capital. Siddiqui and Ahmad

(2012) investigate the linkage between FDI and

current account by utilizing Johansen Juselius

cointegration technique and Granger causality

test on quarterly data of Pakistan from 1976 to

2005 and found long run relationship with the

unidirectional causality respectively. Vural and

Zortuk (2011) discuss the case study of Turkey

from 1982 to 2009 to find relationship between

FDI and exports. The data analysis of Turkish

economy shows that exports growth is

comparatively greater than the GDP growth and

FDI is one of the important factors that can

increase Turkish exports. No short run causality

is seen between FDI and current account. It also

suggests exports based investment flows are

valuable if profit outflows are less.

Mahmood and EhsanUllah (2011) explore the

impact of different macroeconomic variables

(population, import duties, political structure,

and manufacturing sector, exchange rate,

exports and education level) on FDI for

Pakistan from 1972 to 2005. By employing

ADF test and OLS regression analysis, this

study suggests that the size of the economy,

democracy and increasing education are the pull

factors of FDI while all the other variable shave

negative impact on the inflows of FDI. Rabiei

and Masoudi (2012) study the panel data of

eight Islamic developing countries including

Pakistan. The data set from 1980 to 2009

strongly supports FDI as the growth enhancing

factor. FDI inflows work as one of the vital

factor to boost economic growth and

development of the countries. Technological

transfer, efficient allocation of scarce

productive resources and employment

opportunities in the recipient countries are some

of the important long run benefits of these

foreign inflows. The directions of FDI should

be diverted from the services sector to the

exports oriented sectors to get real advantages

of these earnings [Muhammad et al (2010)].

Jayachandran and Seilan (2010) explore the

causal relation between FDI, trade and growth.

The analysis from 1970 to 2007 for India

exposes the long run relationship between the

macroeconomic variables which jointly

strengthen the benefits with the open-door

policy.

3 Data sources

Our study is based on four major

macroeconomic variables; export (LEXP),

foreign direct investment (LFDI) and

productivity (LGDP) along with terms of trade

(LTOT). Variables are expressed in logarithmic

form for the ease of interpretation. Data for all

variables has been taken from 1975 to 2011

annually. Data on terms of trade has been taken

from various issues of Economic Survey of

Pakistan while all other variables are sourced

from World Development Indicators.

4 Methodological frameworks

Theoretically; export of goods and services is

related to the number of macroeconomic

variables. But for the sake of simplicity, we

hypothesize that export is a function of gross

domestic product, foreign direct investment and

terms of trade. Mathematically:

, , (1)LEXP f LGDP LFDI LTOT

1 2 3 4 (2)t t t t tLEXP LGDP LFDI LTOT

The expected signs of coefficients of gross

domestic product and foreign direct investment

196

are positive while exports are negatively related

with the terms of trade. There are numbers of

methods available for the estimation of short as

well as long run relation among these variables.

Among these methods some are like Angel-

granger (1987) test, Johansen (1991) test and

OLS based autoregressive and distributed lag

(ARDL) model. First two tests that is Angel-

granger and johansen tests are of low power

because both of these tests are subject to

stationarity test, if for example at 5%

significance level we test the stationarity of a

variable. There is 5% chance of making type-I

error, that is making an incorrect conclusion of

placing stationary series as a non-stationary. As

a result the test based on such data stationarity

test will also be of low power that is there is a

high chance of making an incorrect conclusion.

In case of ARDL model there is no need pre

testing for data stationarity. In johansen and

Angel-granger test it is necessary for all series

to be I(1) in order to test the cointegation

among variables but in case of ARDL it is not

necessary, we can test the presence of

cointegration among variables of different order

of integration. In our case one variable that is

FDI is not I(1) but is only a trend stationary. For

the above two reasons we have used ARDL

technique for analysis in this study.

4.1 Estimation

The ARDL framework of equations addresses

three basic questions. Firstly; is there exist any

long run relation among the variables? This

question is addressed by the following equation

(3):

In above equation αi, βi, ϒi, and ɳi are short run

coefficients while λi are long run coefficients.

P1, p2, p3, and p4 are number of lags used for

each variable like LEXP, LGDP, LFDI and

LTOT respectively. We used Akaike

information criteria (AIC) for the determination

of lag structure of each variable. The null

hypothesis in equation (3) is:

It means that all variables do not have any long

run relation. Alternatively;

There exists a long run relationship among the

variables. Secondly: we will calculate the long

run equation based on level of variables, if we

first find the existence of cointegration among

variables. We calculated the long run equation

which is normalized by coefficient of export

(LEXP). The long run model based on level of

variables can be estimated by equation (4):

where βi, ϒi, αi and ɳi are long run coefficients of

export, output, FDI and terms of trade

respectively. Finally the short run dynamics

were captured by estimating the equation (5),

which consists of only difference term and error

correction term (ECT) as given below:

In the above equation; αi, βi, ϒi, and ɳi are

representing short run coefficients, while θ1 is

an adjustment coefficient. It depicts the speed

and direction of change toward equilibrium in

the long run. Some diagnostic techniques were

applied to check the suitability of the model

1 2 3 4

0 1 1

1 0 0 0

2 1 3 1 4 1

(3)p p p p

t i t i i t i i t i i t i t

i i i i

t t t t

LEXP LEXP LGDP LFDI LTOT LEXP

LGDP LFDI LTOT

0 1 2 3 4H : 0

A 1 2 3 4H : 0

1 2 3 4

0

1 0 0 0

(4)p p p p

t i t i i t i i t i i t i t

i i i i

LEXP LEXP LGDP LFDI LTOT

1 2 3 4

0 1 1

1 0 0 0

(5)p p p p

t i t i i t i i t i i t i t t

i i i i

LEXP LEXP LGDP LFDI LTOT ECT

197

used. They suggest that there is no serial

correlation, violation of normality assumption

and none of the problems associated with

functional form. The reader may verify all

results presented in appendix C.

5 Empirical results and discussion

In ARDL framework it is important to test the

data for stationarity in order to determine short

run dynamics. We applied ADF (1979) and

Philip Perron (1988) tests for testing data

stationarity. The outcomes are included in

appendix A. Table (1) shows that all variables;

output, terms of trade and export are I(1) except

foreign direct investment which becomes

stationary after de-trending it and hence it is

denoted by LFDIT.

Next part of the analysis examines the estimate

of ARDL framework of equations. The study

provides evidence in the support of existence of

long run relationship among the variables.

Because F-statistics value is almost high and the

null of no long run relationship is rejected

significant at 1% level of significance. Akaike

information criteria suggested a long run model

of order (3,3,3,3) is given in the appendix. (B)

The normalized form of the model is given in

table-1:

Table.1. Long run equation of LEXPD.

=Variable Coefficients t-statistics Probability

C

LFDIt-2

LFDIt-3

LGDPt-3

LTOT

LTOTt-3

MA(3)

-0.839420

0.059798

-0.110348

1.262984

-0.550944

-0.224639

0.92964

-0.536597

2.048613

-4.009872

7.340525

-4.426146

-1.887577

16.78285

0.5975

0.0499

0.0007

0.0000

0.0003

0.0737

0.0000

R2 =

0.994522

AIC = -

2.813760

F-stat =

453.8760

Prob =

0.000000

DW =

2.058455

RSS =

0.054747

Log

likelihood

=49.79952

The equation above depicts that output is

positively correlated with foreign direct

investment upto 2nd

lag but negatively from 3rd

lag. It suggests that profit patriot investors don’t

re-invest their profit in host country due to some

problems faced while conducting profitable

operations of business. The study also favors

growth driven hypothesis. Due to increase in

income; the demand for exportable goods

directly influences the large scale production

which enhances the exports. The coefficient of

terms of trade is negatively correlated. It shows

that as the export prices goes on increasing, it

will cause to reduce the demand for exportable

commodities. Akaike information criteria

suggested a short run model with ECT of order

(2,4,2,3) and results are presented in table-2:

Table.2. Short run equation with error correction term

(DLEXPD).

Variable Coefficients t-statistics Probability

C

ΔLEXPt-1

ΔLEXPt-2

LFDITt-1

LFDITt-3

LFDITt-4

ΔLGDPt-2

ΔLTOT

ΔLTOTt-3

ECTt-1

-1.3643

0.3201

0.2277

0.0868

-0.0940

0.0749

-0.7110

-0.4073

-0.5720

-0.9293

-3.814486

1.875666

1.384320

2.628093

-2.644217

1.801374

-0.843503

-2.364415

-3.009933

-4.001668

0.0013

0.0770

0.1832

0.0171

0.0165

0.0884

0.4100

0.0295

0.0075

0.0008

R2 =

0.689335

AIC = -

2.117191

F-stat =

4.437797

Prob =

0.003490

DW =

2.011981

RSS =

0.096603

Log

likelihood =

39.64068

The short run and long run coefficients of

foreign direct investment and terms of trade

shows the analogous relationship with export

and are positively correlated, while there exists

negative relation with output and is not

significant. Output does not have any impact on

export in short run suggested by ARDL

equation; the coefficient of output is statistically

insignificant in that equation. The coefficient of

ECTt-1 is large and highly significant. The sign

of error correction term shows that when there

is any disequilibrium from normal situation it

will converge back to equilibrium. The speed of

adjustment is fast as the magnitude of

coefficient of ECTt-1 is very large; it suggests

that 93% of adjustment towards equilibrium

will occurs within one year. Generally speaking

our estimates provide evidence in the support of

short run as well as long run relationship among

the variables.

198

6 Conclusion and policy recommendations

This study analyzed the impact of FDI on

exports using annual times series data from

1970 to 2011 by employing ARDL technique.

The results conclude that there is short run as

well as long run positive relationship between

exports and FDI, whereas output has positive

impact on FDI in the long run but statistically

no significant impact in the short run. All

variables are non-stationary at their level except

FDI, which is trend stationary at level. The

model shows that there is quick adjustment

towards equilibrium in case of any

disequilibrium from equilibrium level.

The study advocates that exports may be

increased due to enlarging FDI. The policy

makers should make policies to attract FDI in

prominent exports sectors (textile

manufacturing) or in those which indirectly

contribute to exports (power generation) to

make it competitive in the international market.

The work also proposes that law and order

conditions should be improved in the country to

attract comparatively more FDI. This inflow of

FDI in manufacturing sector can be helpful to

increase exports and economic growth which

will lead to prosperity in the country. Increase

in FDI leads to stabilization of the deficit in

balance of payment in two ways that is directly

due to inflow of foreign exchange and indirectly

due to increase in export receipts.

The study suggest that in order to remove

deficit in balance of payment and get rid of

IMF, instead of foreign assistance government

should focus on economic policies like

attracting foreign direct investment by bringing

betterment in law and order situation and

attractive investment opportunities for

foreigners.

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200

Appendix. A. Unit Root test results

Augmented-Dicky Fuller Test Phillips Perron Test

Variable t-statistic (At level) Probability t-statistic (At level) Probability

LEXP -2.833048 0.1955 -2.890946 0.1772

LTOT -1.606945 0.7691 -1.606945 0.7691

LGDP -1.042354 0.9249 -1.518186 0.8045

LFDIT -5.423436 0.0004 -5.704175 0.0002

t-stat(1st Difference) t-stat( 1st

Difference)

LEXP -6.139081 0.0000 -6.134945 0.0000

LTOT -5.258778 0.0001 -5.241003 0.0001

LGDP -4.526907 0.0009 -4.538719 0.0009

LFDI

@5% level of significance; the critical value for t-stat is (1) At Level =-3.548490 (2) At first difference

=-2.948404

Appendix. B. Long run equation coefficient equation

Dependent Variable: LEXPD, Non normalized long run ARDL equation

Variable Coefficients t-statistics Probability

C

LEXP t-1

LEXPt-3

LFDIt-2

LFDIt-3

LGDPt-3

LTOT

LTOTt-3

MA(3)

-

0.839420

0.417162

-

0.387040

0.058298

-

0.107348

1.225984

-

0.534944

-

0.218639

0.898964

-0.536597

4.470446

-4.086462

2.048613

-4.009872

7.340525

-4.426146

-1.887577

16.78285

0.5975

0.0002

0.0006

0.0499

0.0007

0.0000

0.0003

0.0737

0.0000

R2 = 0.994522

AIC = -2.813760

F-stat = 453.8760

Prob = 0.000000

DW = 2.058455

RSS = 0.054747

Log likelihood

=49.79952

Appendix .C

C.1 Diagnostic checking results

TEST PROBABALITY

Ramsy’s functional form 0.3564

Normality 0.9685

Serial correlation LM TEST 0.4364

ARCH TEST 0.2714

Heterosedacity 0.7754

201

C.2 Recursive residuals

C.3 Cusum test

C.4 Cusum square test

-.20

-.15

-.10

-.05

.00

.05

.10

.15

.20

1990 1992 1994 1996 1998 2000 2002 2004 2006

Recursive Residuals ± 2 S.E.

-15

-10

-5

0

5

10

15

1990 1992 1994 1996 1998 2000 2002 2004 2006

CUSUM 5% Significance

-0.4

0.0

0.4

0.8

1.2

1.6

1990 1992 1994 1996 1998 2000 2002 2004 2006

CUSUM of Squares 5% Significance

202

C.5 Recursive coefficients test t