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S3H Working Paper Series
Number 05: 2020
The Effects of Merchandise Import and Export
Determinants on the Pakistan Trade Balance
Laila Yamin
Ayesha Javaid
Bahlol Khan Orakzai
Zafar Mahmood
August 2020
School of Social Sciences and Humanities (S3H) National University of Sciences and Technology (NUST)
Sector H-12, Islamabad, Pakistan
S3H Working Paper Series
Faculty Editorial Committee
Dr. Zafar Mahmood (Head)
Dr. Samina Naveed
Dr. Gulnaz Zahid
Dr. Ume Laila
Dr. Umar Nadeem
Ms. Fariha Tahir
S3H Working Paper Series
Number 05: 2020
The Effects of Merchandise Import and Export
Determinants on the Pakistan Trade Balance
Laila Yamin Graduate, School of Social Sciences and Humanities, NUST
E-mail: [email protected]
Ayesha Javaid Graduate, School of Social Sciences and Humanities, NUST
E-mail: [email protected]
Bahlol Khan Orakzai Graduate, School of Social Sciences and Humanities, NUST
E-mail: [email protected]
Zafar Mahmood Professor, School of Social Sciences and Humanities, NUST
E-mail: [email protected]
August 2020
School of Social Sciences and Humanities (S3H)
National University of Sciences and Technology (NUST) Sector H-12, Islamabad, Pakistan
iii
Table of Contents
ABSTRACT ........................................................................................................................................ vii
1. INTRODUCTION ......................................................................................................................... 1
Research Questions ......................................................................................................................... 3
Objectives ......................................................................................................................................... 3
2. LITERATURE REVIEW .............................................................................................................. 4
2.1. Theoretical Studies ................................................................................................................... 4
2.2. Empirical Studies ...................................................................................................................... 5
2.2.1. International Empirical Studies ....................................................................................... 5
2.2.2. National Empirical Studies .............................................................................................. 7
3. OVERVIEW OF THE ECONOMY .......................................................................................... 9
4. METHODOLOGY ...................................................................................................................... 14
4.1. Theoretical Framework: ........................................................................................................ 14
4.2. Variables Description ............................................................................................................ 14
4.3. Empirical Model ..................................................................................................................... 15
4.3.1. Export Function .............................................................................................................. 16
4.3.2. Import Demand Function ............................................................................................. 16
4.4.4. Trade Balance Function ................................................................................................. 17
4.4 Data and Econometric Procedure ....................................................................................... 18
5. RESULTS AND DISCUSSION ................................................................................................ 21
Real Export Model ........................................................................................................................ 22
Real Imports Model ....................................................................................................................... 25
6. CONCLUSION AND POLICY IMPLICATIONS ............................................................... 27
6.1. Conclusion ............................................................................................................................... 27
6.2. Policy Implications ................................................................................................................. 27
Appendix 1 .......................................................................................................................................... 28
REFERENCES.................................................................................................................................. 30
iv
List of Tables
Table 3.1. Pakistan’s Major Exports ............................................................................................... 10
Table 3.2. Major Export Markets .................................................................................................... 11
Table 3.3. Real Effective Exchange Rate of Pakistan ................................................................... 12
Table 3.4. Exports and Imports ....................................................................................................... 12
Table 3.5. Different Trade Statistics................................................................................................ 13
Table 4.1. List of Variables ............................................................................................................... 19
Table 5.1. Unit Root Test ................................................................................................................. 21
Table 5.2. Lag Length Criteria for Real Exports ........................................................................... 22
Table 5.3. ARDL Bounds Test for Real Exports .......................................................................... 22
Table 5.4. ARDL Co-integrating and Long-run form for Real Exports ................................... 23
Table 5.5. Breusch-Godfrey Serial Correlation LM Test ............................................................. 24
Table 5.6. Heteroskedasticity Test: Breusch-Pagan-Godfrey ...................................................... 24
Table 5.7. Lag Length Criteria for Real Imports ........................................................................... 25
Table 5.8. ARDL Bounds Test for Real Imports .......................................................................... 25
Table 5.9. ARDL Co-integrating and Long-run form for Real Imports ................................... 26
Table 5.10. Breusch-Godfrey Serial Correlation LM Test ........................................................... 27
Table 5.11. Heteroskedasticity Test: Breusch-Pagan-Godfrey .................................................... 27
v
List of Abbreviations
ADF Augmented Dickey-Fuller
ADRL Autoregressive Distributed Lag
AITIC Agency of International Trade Information and Cooperation
ATR Average Tariff Rate
BOP Balance of Payments
ES Exportable Surplus
FY Fiscal Year
GDP Gross Domestic Product
GMM Generalized Method of Moments
GNI Gross National Income
HLM Harberger-Laursen-Metzler Effect
IRM Imported Industrial Raw Material
OLS Ordinary Least Square
PBS Pakistan Bureau of Statistics
PES Pakistan Economic Survey
REER Real Effective Exchange Rate
SBP State Bank of Pakistan
VECM Vector Error Correction Model
WTO World Trade Organization
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Abstract
This study attempts to examine the relationship between export and import determinants and
their effect on the balance of trade for Pakistan using a time series data from 1980 to 2018. The
estimated import and export models were simultaneously tested with appropriate variables using
bounds testing approach to co-integration and long-run form developed within an autoregressive
distributed lag (ARDL) framework to investigate whether a long-run equilibrium relationship exists
between the dependent and independent variables. The results of bounds tests indicate that there is a
long-run relationship between exports and its determinants as well as imports and its determinants.
The empirical results show that real effective exchange rate, foreign income, imported industrial raw
materials and exportable surplus are all positively correlated to estimated export function and hence,
they yield an improvement in the trade balance. However, in the case of imports, domestic income is
positive and highly significant which leads to an increased import demands causing Pakistan's trade
balance to deteriorate. On the other hand, the average tariff rate is borderline significant and inversely
related to the demand for imports thus, improves the balance of trade. The policymakers of Pakistan
should closely monitor international developments regarding income growth and relative exchange
rate to design strategic policies for the demand side of exports rather than purely facilitating supply-
side export growth to attain trade balance improvement.
Keywords: Exports, Imports, Real Effective Exchange Rate, Trade Balance, Pakistan
1
1. Introduction
From the days of the Silk Route, trade activities played an important role in the economic
development of nations around the globe. Over the years, with development and globalization, it has
evolved and embedded deeper into the economic structures of countries. It has become more
sophisticated with the formation of international bodies such as the World Trade Organization (WTO)
and the Agency of International Trade Information and Cooperation (AITIC). They are
intergovernmental organizations, embodying and concerned with the creation and regulation of trade
between nations.
Global integration of nations into the world economy has been one of the most significant
advancements in the last century. In 1960, aggregate exports contributed to 12% of the world GDP
and by 2015, this percentage rose to 30% (World Bank, 2018). While countries like Germany, USA,
and China have been the world’s largest exporters for decades, there are numerous cases of late
industrialization in the world economies. For instance, only four decades ago, South Korea and
Taiwan were poor economies but rose to the title of two Asian tigers owing to their GDP growth of
8.4% and 7.7%, respectively (Trindade, 2005). Kreuger (1985) attributed this growth to the export
promoting policies of the countries and major growth in manufacturing sector exports.
Exports provide an interface into the competitiveness of nations on a global scale. Similarly,
a booming export base prevents a country from facing a deteriorating current account balance.
Generally, exports help achieve economies of scale, increase employment, expand the foreign reserves
which facilitate imports financing, establish comparative advantage to allow effective resource
allocation, improvement in production process and efficiency through healthy competition and
innovate domestic system by allowing knowledge spill-over.
Countries seeking economic development and industrialization adopt differentiated strategic
trade policies that can be broadly split into two categories. In the wake of the great recession, many
developing countries such as Indonesia and Mayanmar adopted an import substitution policy
approach to protect their domestic industries against external forces. The fiscal authorities intervened
heavily and promoted import substitution and domestic industrialization to insulate the domestic
producers against global competition. Most developed nations, on the other hand, opted for export
promoting trade regimes. These countries aimed to increase efficiency and attract foreign direct
investment by creating favourable ties with other nations via foreign trade expansion and open-door
policies.
2
Export growth is seen as a key contributor to the economic development of many developing
nations (Balassa, 1985; and Vohra, 2001). Marin (1992) reiterated on the need for adoption of export
promotion policies especially for developing countries undergoing industrialization. Export
promoting trade policies targeting export-oriented growth have shown particularly encouraging results
for countries like Pakistan, Israel and Puerto Rico (Keesing, 1967).
Since the early 1980s, the Government of Pakistan adopted an extensive programme of
macroeconomic reforms including trade liberalisation and export promotion aside from macro-
economic management and stability.
Export growth depends on internal as well as external factors. The capacity of a country to
export relies on the world economic conditions. The international market provides opportunities and
threats to trade. The factors of production of a country such as its physical and human capital,
technology and natural resources allow it to gain a comparative advantage. Policymakers can easily
influence the performance of exports by introducing export subsidies or altering the exchange rate.
Export prices play a deterministic role in the export share of a country in the international market.
The prices of exports reflect the domestic cost of production which is subsequently dependent on the
country’s productivity and nominal inflation situation.
The world market can either provide opportunities or can raise trade barriers. Supply of labour,
natural resources and capital, level of human skills and technology can determine the comparative
advantage of a country. On the Policy front, exports incentives and exchange rate changes influence
the export performance. The export share in the international market depends on the export prices,
which reflects the domestic cost of production that in turn depends on the productivity and price
inflation affecting the prices of inputs and labour.
The economy of Pakistan has been facing persistent trade deficits due to its decreased export
earnings. While Pakistan’s export share has decreased, shares of its competitors in the world market
have depicted a substantial increase. A comparison of Pakistan with its competitors points out the
weaknesses of the trade regime being followed by the government especially in the last 10 years. The
most alarming trend is the continuous fall in the export-to-GDP ratio in Pakistan relative to other
developing countries. In 2016, despite governments support package to boost its export industry,
Pakistan experienced an overall decrease in its exports1.This highlights that there are deep institutional
and structural issues behind Pakistan’s sluggish export performance faced by the country due to
1 Mahmood (2019).
3
inherent structural problems and lack of good governance. Pakistan’s stagnant export growth requires
serious reforms which have been developed previously but not yet implemented actively.
Within the above perspective, the present study aims to investigate and analyse the key
determinants that bring about changes in exports and imports of Pakistan. The factors incorporated
by our study are; real effective exchange rate (REER), imported industrial raw materials (IRM),
domestic income (Y), foreign income (Y*), Average tariff revenue (ATR) and exportable surplus (ES).
Available research found the real exchange rate to be among the key determinants. Its impact, direction
and intensity of influence continue to be debated upon depending on the development level of
economies. Researches also examined the relationship between export and import variables, to assess
the sustainability of trade deficits. Based on the long-run relationship between these variables, the
studies aid policymakers in bringing exports and imports to equilibrium. In other words, the existence
of a long-run relationship between exports and imports determinants provides for the efficacy in
economic policies in correcting the trade deficits. Not only this, but the co-integration of exports and
imports models is also vital for evaluation and reformulation of economic policies to correct the trade
imbalances.
Many developing countries impose a high tariff on their imported goods to protect their export
industry and increase their competitiveness. Pakistan's domestic industry is currently facing 3 per cent
to 20 per cent imports tariffs on industrial raw materials and heavy equipment which has increased
the cost of inputs, especially for its export-based industries.
This has caused industrial sector difficulty in upgrading machinery and technology which is
necessary for the production of value-added products and in gaining efficiency in the international
market. Pakistan faced a 170% increase in its exports as a result of trade liberalization from 20% in
2001 to 9% in 2014. However, the policy was reversed in 2014 causing the exports to decline2.
Research Questions
1) What is the effect of real effective exchange on Pakistan’s imports and exports?
2) In the case of Pakistan, is the export function supply or demand-driven?
3) Is imported industrial raw material a significant variable in determining Pakistan’s export
performance?
Objectives:
The objectives of this study are to:
2 Ahmad, I. (2019, November) ‘ICCI for reducing import tariff on industrial raw materials, machinery’. The Nation. Retrieved from nations.com.pk/
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1) determine whether Pakistan's exports are demand or supply-driven,
2) examine whether real currency depreciation affects the exports or imports of Pakistan, and
3) assess the importance of imported industrial raw materials for their direct or indirect effects on
the performance of exports and hence, for the trade balance.
The rest of the study is organized as follows. Section 2 discusses the previous literature
available on trade balance based on international and national studies. Section 3 provides the
theoretical and empirical models that are further discussed in section 4 in terms of estimation
procedures along with the data obtained from different sources. Empirical results and findings are
analyzed and discussed used in section 5. Finally, section 6 draws conclusion and policy implications.
2. Literature Review
There are several studies published on the determinants of exports and imports of a country
and their subsequent aggregate impact on the trade balance, which attests the importance of this issue
playing a crucial role in trade and economic development. Owing to this significance, the focus has
been made in examining and analyzing whether exports of a country are supply or demand determined.
This section discusses available literature on the effect of export and import determinants on the
balance of trade. It has been divided into two subsections. Firstly, it aims to focus on the review of
theoretical studies on the trade balance and its determinants, and then to study the empirical aspects
of it. The second section has been further bifurcated into studies based on International analysis and
those investigating the issue of trade balance in Pakistan. Most studies conclude with various policy
measures and instruments that the researchers believe a nation should target to improve their overall
trade balance.
2.1. Theoretical Studies
Oskooee (1992) believed that different macroeconomic policies are prescribed by the different
school of thoughts to balance the external account of a country. For instance, Keynesians strongly
advocate fiscal policy use whereas monetarists support the monetary policy in establishing economic
equilibrium. This study examined the current account and balance of trade of the United States to
determine their long-run relationship with each policy tool using a co-integration technique. Fiscal
policy is reflected by the full employment budget and monetary policy is reflected by M1 (the most
liquid form of cash) and M2 (less liquid form of cash) figures. Along with these, three varying measures
of interest rate, real and nominal exchange rates and domestic income were also incorporated. The
main findings of the study state that budget is correlated to the current account and balance of trade,
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however, M2 monetary is only partially related to trade balance. Other than that, none of the other
variables (exchange rates, domestic real income, etc.) had a long-run relationship with either account.
Otto (2003) studied the Harberger-Laursen-Metzler (HLM) effect, which states that there is a
correlation between an increase in the terms of trade of a small country and its overall balance of trade.
Vector autoregression techniques are used to investigate if the responses to shocks in terms of trade
are arbitrary or systematic by using data obtained for many small countries. The findings were
bifurcated with evidence supporting the HLM effect and terms of trade shock are marginally more
important for impacting developing countries than developed.
Kutlo (2003) examined the theoretical framework based on the survey of approaches that
focuses on the relationship between trade balance and exchange rates. Elasticity approach is the base
for the development of the aforementioned approaches. It takes into account the changes in the
exchange and its resultant impact on the demand for exports and imports. It employs the principle of
price elasticity to analyse trade on a global scale. Although it presents some excellent theoretical
analysis and policy measures to help understand the trade practices and trends today, its oversimplified
hypothesis and insufficient theoretical framework presented the need for alternative approaches and
thus, ‘Harberger-Laursen-Metzler Effect’ and ‘Absorption Approach’ were developed over time.
Ali, Johari and Alias (2014) carried out secondary research to evaluate the impact of exchange
rate movements on the balance of trade. Their study briefly explained four major theories listed
chronologically in their methodology, starting with; (a) Standard Theory of International Trade; (b)
Elasticity Approach; (c) Keynesian Absorption Approach; and (d) Monetary Approach. The pros and
cons of all four were highlighted to retrieve the most plausible explanation and direction of movement
between the aforementioned variables. While (a) was deemed fairly simplistic and rudimentary, (c) and
(d) were merely theoretical successes with limited empirical evidence available to back them, the
elasticity approach was found the most revolutionary and fulfilling due to its empirical success.
2.2. Empirical Studies
2.2.1. International Empirical Studies
Sugema (2005) studied the impact of the Asian crisis of 1997 on Indonesia by making use of
time-series data from 1984-1997. The study's objectives were twofold. First, the impact of currency
devaluation was seen on imports and exports to determine whether the balance of trade will improve
as a result. Secondly, supply-side shocks on export performance were analyzed to study the impact of
socio-political turmoil and economic degradation on the exports of a country. Export and import
functions are initially estimated and the ECM procedure is used to find the short-run and long-run
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dynamics followed by the estimated vector error correction model (VECM). The findings indicated
that real exchange rate depreciation improves the balance of trade by stimulating export supply and
decreasing demand for imports. The export performance would have been appreciable in the case of
Indonesia had there not been supply-side shocks such as the collapse of the banking sector.
Ray (2012) examined the impact of various determinants on the balance of trade for India. He
used time-series data from 1972-2011 for various factors such as FDI, exchange rate, domestic
income, etc. He estimated an equation for the balance of trade and used Augmented Dicky Fuller test,
OLS, VECM and Johenson co-integration test to determine the correlation between different variables
and the trade balance. His findings pointed towards a causality existing between the independent and
dependent variables. Trade balance and foreign income were found to be positively related whereas a
negative relationship was observed between real effective exchange rate and domestic spending.
Nicita (2013) investigated the extent to which the exchange rate affects the trade and its
policies, internationally. The research relied on the use of bilateral data obtained for exchange rates,
trade policy and flows of trade for 100 countries over 10 years to empirically estimate the fixed-effects
model. The results indicate that the exchange rate instability affects the international trade flows in a
considerable amount. Currency devaluation encourages exports as they become cheaper and restricts
imports and vice versa. The policy implication suggests that it is essential to monitor the exchange rate
of both the trading partners as well as competitor countries.
Pandey (2013) attempted to empirically verify the Marshall-Lerner condition for India's trade
balance. He used time-series data from 1993 to 2011 and formulated log models for India's imports
and exports using variables such as world income, domestic income and real exchange rate. The results
show that while as expected, an increase in real exchange rate boosts India's exports, depreciation
causes an overall increase in imports. A positive correlation was exhibited between exports and world
gross income and imports and domestic income. Ultimately, the sum of import and export elasticity’s
for India exceeded unitary implying Marshall-Lerner condition to hold for India.
Cergibozan (2017) shed light on the trade balance dynamics in Turkey through the Johansen
co-integration test and vector error correction model (VECM). The time-series data were analyzed
from 1987 to 2015. The results indicated that in the long run, devaluation of domestic currency
positively affects the trade balance. Moving on, the VEC model results also showed that the real
exchange rate has no significant effect on the trade balance, whereas domestic and foreign income
affects the trade balance negatively. The policy implication reiterates on the need for policymakers to
understand whether the real exchange rate is the appropriate tool to manipulate the trading behaviour.
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2.2.2. National Empirical Studies
Atique, Ahmed and Zaman (2003) highlighted the significance of the short term and long term
elasticities of various determinants of supply and demand for exports, formed separate lag models and
examined them empirically. They used time-series data from 1972 to 2000 to calculate the lag via
Almon Polynomial Distributed Lag Model. Real effective exchange rates the only significant variable
in the long run however; it exhibited less elasticity whereas the world economic activity showcased
both short-run and long-run elasticity significance. Their policy implications for Pakistan included the
ineffectiveness of currency devaluation in improvements in the trade balance, studying trade partner
nation's business cycle to enhance exports and need for efficient utilization of domestic production
capacity to boost export supply.
Kemal (2005) examined that the exports and imports are affected positively and negatively due
to the exchange rate instability, which implies improvement in the trade balance. The impact was
found to be significant for imports but insignificant in case of exports. However, it cannot be
conclusively said whether it affects trade balance positively because their research did not include the
direct trade balance variable in their model. Exchange rate instability can cause short term imbalances
in the real exchange rate but it adjusts back to equilibrium in the long run. The study concluded that
imports and exports have a direct significant association with one another, which also shows that
Pakistan is implementing policies that are in agreement with the WTO regulations.
Bader (2006) has used annual data from 1973-2005 to evaluate and examine the long-run
dynamics of exports and imports using partially deduced export equation. The ordinary least squared
(OLS) method is used to determine the effect of imports on exports. The results of the study showed
that the import of capital goods and raw materials play a major role in improving the export
performance of the country. On the other hand, a country's exports are more responsive to the import
of raw materials as compared to capital imports. It also indicated that in the short as well as the long
run, the structure of imports, particularly raw materials and capital goods, should be closely observed.
This will assist the policymakers in formulating plans to target the imports of goods that are used
directly in export production to boost the export market and reduce pressure on trade imbalances. In
addition to this, imposing tariff barriers to reduce imports may not be the best way to tackle the trade
imperfections but instead, it could be attained through appropriate macroeconomic tools like
exchange rate and interest rate policies.
WaliUllah, Kakar and Khan (2010) assessed the existence of a long-run equilibrium
relationship linking trade balance, income, exchange rate and money supply. The bounds testing
8
approach to co-integration was used within the ARDL framework. The findings prove that Pakistan's
money supply and income determine the short-run and long-run behaviour of trade balance in
comparison to its exchange rate. This is because income and money supply directly impact the trade
balance. It is suggested that policymakers tackle trade balancing difficulties through the money supply
and not purely income and growth policies. Although the trade deficit can be reduced through altering
exchange rates, it is not as effective as the monetary policy.
Zada, Muhammad and Bahadar (2011) used time-series data from 1975- 2008 to examine the
determinants of exports of Pakistan. Export supply and demand-side equations were developed which
were inclusive of proper variables comprising of Generalized Methods of Moments (GMM)
accompanied by the Empirical Bayesian technique for Pakistan, as opposed to its trading partners. As
per their findings, it was suggested that exports are more sensitive to world demand and world prices.
The importance of demand-side variables such as world GDP, real effective exchange rates, and world
prices to determine the exports of Pakistan was established. Contrarily it was shown that the supply
revealed the smaller price and income elasticities. The results disclosed a higher demand for experts is
higher for countries in NAFTA, therefore, Pakistan should concentrate on improving their relations
with their trading partners in these specific regions to improve export performance and consequently,
the trade balance of Pakistan.
Gul, Siddiqui, Malik and Razzak (2013) worked towards investigating the different variables
affecting the demand of Pakistan's exports. Time Series data was collected over 20 years from 1990-
2010 from different sources. The determinants that influence the demand for imports in Pakistan were
mainly nominal and real effective exchange rate, production capacity of the world and world export
price variable. The Two-Stage Least Square method was also employed in their research. The multiple
results concluded a significant fall in the domestic demand with a rise in the exchange rate.
Furthermore, an insignificant relationship was seen between the demand for imports with a nominal
exchange rate and export price variable.
To sum up the discussion in this section, it may be noted that currency devaluation has a
positive and significant effect on the overall trade balance as backed by theory. The effect of the
aforementioned variable for developed and developing countries is surprisingly incongruent. While
export-based countries benefit from currency devaluation, import-based countries such as Pakistan
and Indonesia suffer from losses incurred from the subsequent increase in import prices. Other
determinants including, exportable surplus, domestic income and foreign income exhibit a significant
impact while the effect of the exchange rate is less pronounced. A positive correlation was observed
9
between domestic income and imports and similarly, foreign income and exports. Furthermore,
imported industrial raw materials were seen as significant determinants of export performance of
Pakistan and thus, policymakers should focus more on importing goods that are direct inputs in the
export industry to boost exports, alleviate pressure on exports industry and reduce trade imbalances.
Policy suggestions implied trade liberalization, increasing productivity, decreasing government
expenditure and monitoring of relative exchange rate with partner and competitor countries to
improve efficiency.
Internationally, a significant amount of work has been done analyzing the relationship and
impact of exports and imports determinants on a country's trade balance. However, in Pakistan, for
at least a decade there has been no relevant work that estimates both import and export equations to
examine the individual effect of variables on these models leaving a severe gap regarding the
determination of trade balance. Therefore, this study aims to reduce the deficit by calculating the
elasticities for all variables, analyzing their impact on each model and then the extrapolating the
observed changes in exports and imports to the real trade balance of Pakistan. While earlier studies
focused primarily on the direct impact of different determinants on the trade balance, this study
evaluates the channel with which this change is brought about to implicate specific and effective
policies targeting either export or import sides to attain an improvement in Pakistan’s trade balance.
Furthermore, this study incorporates the average tariff rate variable in its estimated import equation
which had been vastly ignored in the past by other researches. This is especially important for Pakistan
since it does not practice fully liberalized trade and thus, ATR's impact on imports and its demand is
of utmost significance as it causes changes in the country's balance of trade.
3. Overview of the Economy
Pakistan has been through many economic eras and due to certain decisions of the current
and past governments, it has been a hard time for Pakistan. From nationalization in the 1980s which
forced many businessmen to migrate to foreign lands, causing capital to flee from the market and
dropping shares in the stock market to the semi-Islamic financial system of Zia-ul-Haq which could
not deliver, Pakistan has faced poverty and unemployment. Tragically, no proper schemes have ever
been introduced to tackle these issues. Moving on, governments of Benazir Bhutto and Nawaz Sharif
constantly borrowed money from the IMF and the World Bank causing an overall increase in the
foreign debt. In 1998, Pakistan faced sanctions from the US which depreciated Pakistani exports and
the overall economic cycle. In the 2000s until the present day, governments have increased borrowing
10
which has brought Pakistan to a very difficult time due to its debt ever-increasing, highest ever
recorded at $111.047 billion3.
The trade sector is a key player in any country’s economy. It reflects how well a country is
manufacturing and to what extent it is dependent on foreign goods; imports. Pakistan’s imports have
always exceeded exports which have resulted in a negative trade balance. Cheap imports from China
hurt our import-substitution industries immensely. Along with the trade deficit, the balance of
payment crisis and current account deficit has deteriorated over the years. According to statistics,
Pakistan’s trade deficit has increased from $20 Billion in FY14 to $37.7 Billion in FY18, the highest
ever recorded debt in the history of Pakistan. Despite our currency being fixed from FY13 to FY18,
Pakistan’s exports did not increase as anticipated by the government4.
Structure of Exports
Pakistan’s exports mainly comprise of three products; cotton, leather and rice. Cotton makes
up almost 55% of Pakistan’s exports whereas rice and leather are approximately 9% and 5%,
respectively. These numbers slightly vary each year but there are no major fluctuations.
Table 3.1. Pakistan’s Major Exports Commodity 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 2017-18
Cotton
Manufactures
50.6 52.9 49.6 51.6 53.1 54.5 55.0 59.4 56.9
Leather** 4.5 4.4 4.4 4.7 5.1 4.8 4.9 4.5 4.6 Rice 11.3 8.7 8.7 7.8 7.6 8.5 8.8 7.9 8.8 Sub-Total of Three Items
66.4 66.0 62.7 64.1 65.8 67.8 68.7 71.8 70.3
Other Items 33.6 34.0 37.3 35.9 34.2 32.2 31.3 28.2 29.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Source: Pakistan Economic Survey (various issues).
Cotton textile exports in 2018 were valued at $59.2 billion and Asia supplies approximately
64.5% of the cotton. Pakistan’s share was $3.5 billion which is 5.9% of the total world supply of
cotton. This makes Pakistan the fourth largest exporter of cotton, worldwide5.
3 Haider, M. (2020, Feb 19). Pakistan external debt, liabilities increase by Rs 2,441bn in 18 months. The News. Retrieved from https://www.thenews.com.pk/ 4 Rana, S. (2018, July 12). Pakistan’s trade deficit skyrockets to historic high. The Express Tribune. Retrieved from https://tribune.com.pk/ 5 Workman, D. (2019, July 1). Cotton exports by country. World’s Top Exports. Retrieved from http://www.worldstopexports.com/
11
The global rice exports valued at a total of $24.5 billion in 2018 of which almost 78% exports
were from Asian countries. Pakistan’s exports were valued at $2 billion which makes up 8.2% of the
total world rice exports placing Pakistan as the fourth biggest rice exporter6.
According to a government official, the leather industry of Pakistan is 4.3% of its exports. Currently,
Pakistan exports $980 million annually and this value has room for major improvement if Pakistan's
leather quality and diversification are improved. Pakistan is a key player in the leather industry as it is
the second-largest exporting country, after Italy7.
The direction of Exports
Pakistan exports its goods to a small number of markets. It has ten major partner export
countries; USA, China, Afghanistan, UK, Germany, U.A.E., Bangladesh, Italy, Spain and France.
Between these countries, the United States owns the largest share of exports with 17%, followed by
China and the United Kingdom with 8% and 7%, respectively. The export shares to Afghanistan and
U.A.E experienced at 1% fall in FY19. Furthermore, robust efforts are being made to study and
explore new potential markets for the exports of Pakistan. The Formulation of Strategic Trade Policy
Framework is a step in the right direction in gaining access to more international markets8.
Table 3.2. Major Export Markets
COUNTRY 2015-16 2016-17 2017-18
Rs Billion % Share Rs Billion % Share Rs Billion % Share
USA 364.8 17 361.1 17 400.4 16 CHINA 174 8 153.8 7 185.7 7 AFGHANISTAN 149.9 7 133.1 6 165.2 6 UNITED KINGDOM 164.7 8 163.1 8 186.7 7 GERMANY 118 6 125.1 6 146.7 6 U.A.E 85.5 4 83 4 104 4 BANGLADESH 72.3 3 65.4 3 81 3 ITALY 67.7 3 68.6 3 84.5 3 SPAIN 84.3 4 85.5 4 104.5 4 FRANCE 36 2 38.8 2 45.5 2 ALL OTHER 849.6 45 860.7 40 1050.8 41 TOTAL 2166.8 100 2138.2 100 2555 100
Source: Pakistan Economic Survey (various issues).
6 Workman, D. (2020, April 24). Rice exports by country. World’s Top Exports. Retrieved from http://www.worldstopexports.com/ 7 Babar, W. (2019, June 27). Pakistan’s leather draws its last breath. Daily Times. Retrieved from https://dailytimes.com.pk/ 8 Pakistan Economic Survey (2019).
12
Real Effective Exchange Rate
The real effective exchange rate is the comparison of domestic prices relative to foreign
prices. The trend of the REER can be noted from Table 3.3., with the base year 2000-01.
In Pakistan’s case, the REER fluctuated around 100 and post-2014-15, it experienced a sharp
increase. Due to a high REER, Pakistan's export competitiveness increased as domestic prices were
below international prices. The REER has significant impacts on the imports and exports of a country.
On the other hand, the trends observed from 2015 to 2018 deviated from the expected pattern
of trade. The exports initially decreased but then exhibited a surge of 19.5% during 2017 whereas the
imports remained constant.
Table 3.3. Real Effective Exchange Rate of Pakistan YEAR REER
2007-08 100.0 2008-09 104.0 2009-10 99.8 2010-11 100.3 2011-12 104.5 2012-13 107.6 2013-14 108.7 2014-15 105.5 2015-16 112.3 2016-17 121.2 2017-18 124.3
Source: SBP (2020).
Table 3.4. Exports and Imports YEAR EXPORT (MILLION RS.) IMPORT (MILLION RS)
2015-16 2,166,846 4,658,749
2016-17 2,138,186 5,539,721
2017-18 2,555,042 6,694,897
Source: Pakistan Economic Survey (various issues).
Average Tariff Rate and Trade Balance
The average tariff rate is calculated as the ratio of trade tax revenue and nominal imports. In
this sub-section, the trends of Pakistan’s tariff rates are examined along with their effect on the
quantities of goods exported and imported. For real imports analysis, an additional variable of
imported industrial raw materials is also studied because of its indirect impact on the performance of
the export industry.
Pakistan’s imports have exhibited an increase over the years but the average tariff rate has
decreased over the years. As mentioned above, imported industrial raw materials are used as
13
intermediate goods in exports production; an increase in the imported raw materials has led to a boost
in the exports however, it has also worsened the trade balance situation of Pakistan.
Table 3.5. Different Trade Statistics Year Average Tariff Rate (%)
Exports
(Million Rs.) Imports
(Million Rs.) Industrial Raw Material
(Million Rs.)
1984-85 26.03 37,979 89,778 46,438 1985-86 32.26 49,592 90,946 41,319 1986-87 36.10 63,355 92,431 42,377 1994-95 24.20 251,173 320,892 165,173 1995-96 22.36 294,741 397,575 203,080 1996-97 18.51 325,313 465,001 224,638 2006-07 7.24 1,029,312 1,851,806 999,255 2007-08 5.99 1,196,638 2,512,072 1,524,867 2008-09 5.32 1,383,718 2,723,570 1,584,586 2013-14 5.20 2,583,463 4,630,521 2,768,999 2014-15 6.59 2,397,513 4,644,152 2,602,831 2015-16 8.72 2,166,846 4,658,749 2,305,094
Source: Pakistan Economic Survey (various issues).
Current Economic Situation
Currently, Pakistan is undergoing a huge trade crisis because of ever-increasing imports and
declining exports in recent years. This is because Pakistan lacks export competitiveness, faces low
productivity, rise in the cost of doing business, high-interest rates, high cost of trade and the slow
process of a tax reimbursement. Other major industries of Pakistan are also facing a downward slope.
The manufacturing industry has declined by -2.06% in FY19 while the agricultural sector fell by 0.85%
in the same period. Due to the slow or negative growth, the shares of manufacturing and agriculture
sectors in the overall GDP of Pakistan has dropped down to 13.0% and 18.5%, respectively. In
addition to this, the percentage of manufactured exports in the world exports has dropped down to
70% in FY19. As in recent times, global trade growth has experienced a downfall due to the
superpowers of the world, Pakistan, being the 10th largest workforce in the world should seize this
opportunity in terms of production for its domestic markets. Fortunately, Pakistan has a huge segment
of the population below the age of 30, which can enable Pakistan to accelerate economic growth.
Many successful overseas Pakistanis will surely return to their nation if they witness Pakistan's
economic development and growth through better policies and ground-level implementation. After
thoroughly examining of the state of Pakistan's trade and its behaviour patterns for the last few
decades, it is deemed necessary to empirically test the short-run and long-run determinants of exports
and imports and their impact on the trade balance of Pakistan. The analysis of this data would
implicate policy measures for the government of Pakistan to improve its trade performance.
14
4. Methodology
4.1. Theoretical Framework
There are numerous theoretical approaches to analyze the effect of different policy regimes
on the balance of payments (BOP). Elasticity approach and absorption approach to the balance of
payments draw out two distinct means of policy transmission and adjustment. The elasticity approach
hypothesis describes adjustment in the balance of payments through the exchange rate. It provides an
overview of the effect of devalued currency on the current account balance of an economy (Pilbeam,
1998). Elasticity approach is associated with the Marshall-Lerner condition, which was pioneered by
the two economist’s independently (Thirlwall and Gibson, 1992).
The absorption approach (Alexander 1952 and Alexander, 1959) to the balance of payments
is seen as an alternate to the elasticity approach and is based on the National income relationship. It
is a macroeconomic approach which examines the production and expenditure of an economy. It
further asserts that employing the tool of devaluation would only be effective if it widens the gap
between the output and expenditure of a country. The theory states that if a country faces a BOP
deficit, it simply means people are absorbing more than they are producing. Consumption and
investment expenditure exceed national income. The approach uses national identity model and takes
Y as national income on the left side of the equation and absorption (A) taken as a sum of
consumption, investment and government expenditure (C, I, G) on the right side alongside the
difference between exports and imports is taken as trade balance, B.
Y = C + I + G + X – M … (1)
Y = A + B … (2)
B = Y – A … (3)
It is evident from equation (3) that to improve BOP, a country should reduce absorption/expenditure
or increase its national income.
4.2. Variables Description
Previous literature based on its theoretical and empirical frameworks highlights that a country's
trade balance is determined and affected by a set of variables. This study hypothesizes the relationship
between the possible factors and Trade Balance, which will be evaluated and explored as follows;
Real Effective Exchange Rate (REER)
Real Effective Exchange Rate is the weighted sum of the home currency value relative to a
specific index or basket of foreign currencies. Sugema (2005) states that a fall in REER is the real
depreciation of domestic currency interpreted as an improvement in international competitiveness.
15
Several International and National studies have analyzed the relationship between REER and balance
of trade. The international studies state that a desirable impact of devaluation is observed on the trade
balance in the long run (see, Bahmani-Oskooee. 1992; Pandey, 2013). However, in the case of
Pakistan, the findings are inconclusive. Waliullah, Kakkar and Khan (2010), and Shahbaz, Awan and
Ahmed (2010) do not find a significant impact of real effective exchange rate on the balance of trade
in the long run. Contrarily, Kemal (2005) stated that the deterioration of REER improves the trade
balance in the case of Pakistan.
Real Domestic (Y) and Foreign Income (Y*)
Domestic income is positively correlated with imports and adversely affects the trade balance
as when there is an increase in disposable income, the demand for imports also increases which
worsens the trade balance. There is a positive correlation between foreign income and trade balance
as an increase in foreign income yields improvement in exports as studied by Panday (2013).
Export Surplus (ES)
The maximum possible surplus an economy can produce given the available resources is its
export surplus. Exportable surplus refers to the leftover products a country exports after meeting its
domestic demand. Under this situation, when GDP increases then its additional growth generates a
higher exportable surplus which is eventually utilized to increase exports (Leff, 1969).
Imported Industrial Raw Material (IRM)
Imported industrial raw material comprises of the real capital and consumer goods. Import
restrictions tend to improve the export performance for a country and hence, the trade balance. It
also shows that relative to capital imports, imported industrial raw materials have a more significant
impact on exports (Bader, 2006).
Average Tariff Rate (ATR)
The average tariff rate is a strategy employed by countries to promote their domestic industrial
production against imports by giving them a competitive price advantage. It is an especially popular
policy amongst the developing nations as it protects the domestic industry that improves its
competitiveness, and suppresses imports which improve the balance of trade (Kreinin, 1961).
4.3. Empirical Model
This section discusses the framework used to estimate specific, linear econometric models for
Pakistan's imports and exports, which are further incorporated to produce an overall trade balance
equation. The OLS regression is used to determine the significant variables that are then integrated
into the general trade model. The empirical analysis makes use of the elasticity approach by applying
16
natural log to the trade equation to generate elasticity's and assess their impact individually in the
specific import and export functions and the balance of trade model.
The difference between the exports and imports of an economy is its trade balance. For
simplicity, an economy is assumed which consists of only two types of goods; home goods and foreign
goods. The former is produced domestically, excess of which are sold in the international market as
exports. Similarly, foreign goods are produced by foreign countries that are demanded domestically
by the home country are known as imports.
4.3.1. Export Function
Based on economic theory, real export (X) is determined by the real effective exchange rate
(REER), real foreign income (Y*), exportable surplus (ES) and imported industrial raw material (IRM).
Y* influences the demand side of the real export variable while ES is a supply-side shifter (Rose, 1990).
The REER comprises of three components;
REER= n. P / P*
where, P is the price of home goods, P* is the prices of foreign goods and n is the nominal exchange
rate. The Export function is thus, described as;
X= x(REER, Y*, ES, IRM) … (4)
After empirically testing the general real export function above, we can establish whether, in
the case of Pakistan, exports are supply or demand determined. The export demand function is defined
according to the Traditional Marshallian Approach (Rose, 1990, 271-3) as follows;
Xd = f(REER, Y*)
On the other hand, small country case assumption states that a country is unable to influence
the prices in the international market and therefore, can only produce tangible results in trade account
by focusing on improving the supply of exports. The international market can absorb all goods
produced by the small country such as Pakistan for exporting purposes and therefore, it is essential
for it to focus on determinants that directly or indirectly affect its export supply to improve its exports.
The present study aims to explore and determine if the small country case can be assumed for Pakistan
and if so, then Y* should be insignificant. And thus, the real export function should be supply-driven;
Xs= f(REER, ES, IRM)
4.3.2. Import Demand Function
Real Imports are a function by the real effective exchange rate (REER), domestic income (Y)
and average tariff rate (ATR). The small country case assumes that import is demand determined
implying that the supply of imports from the international market is perfectly elastic. The theory states
17
that when the real exchange rate decreases, the price of imports rises diminishing demand for imports.
The consequence of a rise in domestic income, ceteris paribas, increases the purchasing power.
Average tariff rate (ATR) causes import demand to decrease in the domestic country which is desirable
as it improves the trade balance.
Md = m(REER, Y, ATR) … (5)
4.4.4. Trade Balance Function
T = X - M
T= t(REER, Y*, Y, IRM, ES, ATR)
Rose (1990), amongst others, estimated the aforementioned general trade balance equation in
their studies for primarily two reasons. The first advantage of the reduced form equation is that it is a
more straightforward method and its results are corresponding to the estimated equations (4) and (5).
Secondly, it is easier to determine and interpret the estimated coefficients which explain changes in an
economy's trade balance caused by currency depreciation. If the coefficients estimated are positive
and significant for the real exchange rate, it implies that trade balance will improve as a result of
currency depreciation.
One of the shortcomings of the above approach, however, is that it is unable to highlight the
impact of real exchange rate depreciation on the exports and imports, individually. This is crucial to
the present study as it aims to implicate policy measures for Pakistan's trade balance improvement in
the future. If exports are inelastic to depreciation, then an adjustment can be brought about only via
import compression policies. Additionally, higher prices of imported industrial raw materials used as
an input in export industries may depress investment and the aggregate output (Bruno, 1979). Thus,
the overall trade balance will depreciate if the expected increase in exports does not counterbalance
the negative influences of devaluation. Alternatively, when the quantity of exports increases but
imports remains unaffected then the aggregate effect on trade balance will be expansionary. Therefore,
while it is important to test the trade balance improvement, the way this improvement is achieved is
even more important.
Additionally, estimating equations (4) and (5) using error Autoregressive distributed lag
(ARDL) approach, which specifically identifies the short-run and long-run integrating relationships,
will enable us to examine the various aspects of the adjustment process of real exports and real
imports. Hence, within a single framework, short-term and final effects on different factors
constituting trade balance can be observed and analyzed. Therefore, instead of using a reduced form
trade balance equation, our study estimates equations (4) and (5), separately.
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4.4 Data and Econometric Procedure
The models used in the study comprises of eight variables with real exports (X) and real
imports (M) as the dependent variables; and real effective exchange rate (REER), exportable surplus
(ES), the real imported industrial raw material (IRM), real domestic income (Y), Average Tariff Rate
(ATR) and real foreign income (Y*) as the independent variables. The data series incorporated in the
empirical model are taken from Pakistan Economic Survey (PES), Handbook of Statistics by the State
Bank of Pakistan (SBP) and the World Development Indicators by the World Bank (WB). The data
are annual and observations involved are from 1980-2018. All variables are transformed into their log
natural forms.
Real exports (X) are defined as the goods produced domestically and sold to a foreign country.
Similarly, real imports (M) are defined as the goods produced by foreign countries that are sold in
Pakistan. They were calculated using the total value of exports and imports at current prices in rupees
adjusted by their respective unit value indices. The world income (Y*) was calculated by taking the
average of the sum of adjusted net national per capita income of the top eight export partner countries
of Pakistan divided by the US GDP deflator. The gross national income at constant market price in
rupees was used to reflect the domestic income (Y). The real effective exchange rate (REER) is the
dollar value of goods multiplied by the nominal exchange rate divided by the Rupee value of the good.
REER shows the international competitiveness of Pakistan’s trade. The next variable used in the data
were exportable surplus (ES) which was represented using GDP (factor cost) at constant prices in
rupees as a proxy. This study also incorporates imported industrial raw material (IRM) in the estimated
export equation. IRM was calculated by multiplying total real imports with the sum of percentage
share of imported industrial raw materials used in consumer and capital goods industries. Lastly, we
calculated average tariff rates (ATR) in the import function using trade tax revenue divided by import
values nominal. The elasticity of each variable is estimated by taking their log forms.
The analysis begins with specifying and employing suitable processes to generate data. A unit
root test, Augmented Dickey-Fuller (ADF) approach is used for the selection of the econometric
model on the base of data stationarity. The stationarity of data is initially tested using the unit root test
implying that over time the shape of the distribution remains relatively unchanged or exhibits
stochastic trends. Hence, to avoid random and misleading regression, the use of unit root test is
necessary.
19
Table 4.1. List of Variables Variable Abbreviated As Proxied As Data Source
Export X Actual variable. Pakistan Economic Survey, PES
Import M Actual variable. Pakistan Economic Survey, PES
Real Effective Exchange Rate
REER The relative price of foreign goods to domestic prices.
Handbook of Statistics, SBP
Domestic Income Y GNI per capita. Pakistan Economic Survey Foreign Income Y* Average of the sum of adjusted net
national income per capita (USD) for Pakistan’s top eight export partner countries.
WDI, World Bank
Exportable Surplus ES Gross Domestic Product (GDP). Pakistan Economic Survey
Imported Industrial Raw Material
IRM Actual variable Pakistan Economic Survey
Average Tariff Rate ATR The ratio of Trade tax revenue to nominal imports (%).
Pakistan Economic Survey
Traditionally, the long run and short-run relationships of variables are determined using the
standard Johansen Co-integration and VECM framework; however, this approach has some serious
shortcomings according to Pesaran et al. (2001). To analyze and examine the correlation between the
variables, this study uses the autoregressive distributed lag (ARDL) framework (Pesaran et al., 1996
and Pesaran, 1997). The results obtained via the ARDL framework are in correspondence to theory
and robust both for the short-run and long-run relationships between dependent and independent
variables. It is effective in describing the existence and relationship in terms of short-run and long-run
dynamics without compromising the information of long run. Considering the aforementioned
advantages, the present study employs the ARDL approach to estimate the following equation (6) for
exports (X) and (7) for imports (M):
∆𝑙𝑛(𝑋)𝑡 = 𝛼0 + ∑ 𝛽𝑖∆ 𝑙𝑛(𝑋)𝑡−1𝑛𝑖=0 + ∑ 𝛿𝑖∆𝑙𝑛(𝑅𝐸𝐸𝑅)𝑡−1 + ∑ 𝛾𝑖∆𝑙𝑛(𝑌
∗)𝑡−1𝑛𝑖=0
𝑛𝑖=0 +
∑ 𝜗𝑖∆𝑙𝑛(𝐼𝑅𝑀)𝑡−1𝑛𝑖=0 +∑ 𝜌𝑖∆𝑙𝑛(𝐸𝑆)𝑡−1
𝑛𝑡=0 + 𝜏1 𝑙𝑛(𝑋)𝑡−1 + 𝜏2𝑙𝑛(𝑅𝐸𝐸𝑅)𝑡−1 + 𝜏3𝑙𝑛(𝑌
∗)𝑡−1 +𝜏4 𝑙𝑛(𝐼𝑅𝑀)𝑡−1 + 𝜏5 𝑙𝑛(𝐸𝑆)𝑡−1 + 휀𝑖 … (6) ∆𝑙𝑛(𝑀)𝑡 = 𝛼0 + ∑ 𝛽𝑖∆ln(𝑀)𝑡−1 +∑ 𝛿𝑖∆ln(𝑅𝐸𝐸𝑅)𝑡−1 +∑ 𝛾𝑖∆ln(𝑌)𝑡−1
𝑛𝑖=0
𝑛𝑖=0
𝑛𝑖=0 +
∑ 𝜗𝑖∆ln(𝐴𝑇𝑅)𝑡−1 + 𝜏1ln(𝑀)𝑡−1 + 𝜏2ln(𝑅𝐸𝐸𝑅)𝑡−1 + 𝜏3ln(𝑌)𝑡−1𝑛𝑖=1 + 𝜏4 ln(𝐴𝑇𝑅)𝑡−1 + 휀𝑡 … (7)
The former section of the equation where 𝛽𝑖, 𝛿𝑖, 𝛾𝑖, 𝜗𝑖 , 𝜌𝑖 parameters represent the
dynamics of the model in the short run whereas the coefficients 𝜏1, 𝜏2, 𝜏3, 𝜏4, 𝜏5 represent the long-
run relationship. The model’s null hypothesis is:
20
Ho: there is no long-run relationship
H1: there is a long-run relationship
This study used the bounds test to check for the existence of a long-run relationship exists
between the variables. The estimated F value is checked against the critical value tabulated by Pesaran
(1997) and Pesaran et al. (2001). According to the null hypothesis, there is no long-run relationship
and if the F statistic is greater than the upper critical value at 5%, we reject H0, regardless of the
variable’s integration order. Alternatively, if the F statistic is less than the critical value at 5%, H0 is not
rejected. If the order of integration is known, the decision is based on the value of f statistic compared
to the critical value at lower bound for I(0). Similarly, for I(1), the F value is compared to the critical
value at the upper bound.
In the second step, contingent upon the co-integration results of whether or not long run
relationship exists between variables, the following equation (8) is estimated for the long run,
𝑙𝑛(𝑋)𝑡 = 𝛼𝑖 + ∑ 𝛽𝑖∆𝑙𝑛(𝑋)𝑡−1 + ∑ 𝛿𝑖∆𝑙𝑛(𝑅𝐸𝐸𝑅)𝑡−1 + ∑ 𝛾𝑖∆𝑙𝑛(𝑌∗)𝑡−1 +
𝑛𝑖=1
𝑛𝑖=1
𝑛𝑖=1
∑ 𝜗𝑖∆𝑙𝑛(𝐼𝑅𝑀)𝑡−1 +∑ 𝜌𝑖∆𝑙𝑛(𝐸𝑆)𝑡−1 + 휀𝑖𝑛𝑖=1
𝑛𝑖=1 …(8a1)
𝑙𝑛(𝑀)𝑡 =𝛼𝑖 + ∑ 𝛽𝑖
𝑛𝑖=1 ∆𝑙𝑛(𝑀)𝑡−1 +∑ 𝛿𝑖∆𝑙𝑛(𝑅𝐸𝐸𝑅)𝑡−1 +∑ 𝛾𝑖∆𝑙𝑛(𝑌)𝑡−1 +
𝑛𝑖=1
𝑛𝑖=1
∑ 𝜗𝑖∆𝑙𝑛(𝐴𝑇𝑅)𝑡−1 + 휀𝑡𝑛𝑖=1 …(8a2)
If a long run relationship exists, we estimate the Error Correction Model (ECM) which shows
the speed with which adjustment takes place after a short run disruption to establish the long run
equilibrium. The following equation is estimated by ECM model,
∆𝑙𝑛(𝑋)𝑡 = 𝜔1 + 𝛿1(𝐸𝐶𝑀)𝑡−1 + ∑ 𝛼𝑖∆ 𝑙𝑛(𝑋)𝑡−1 + ∑ 𝛽𝑖∆𝑙𝑛(𝑅𝐸𝐸𝑅)𝑡−1 + ∑ 𝛾𝑖∆𝑙𝑛(𝑌∗)𝑡−1 +
𝑛𝑖=1
𝑛𝑖=1
𝑛𝑖=1
∑ 𝜗𝑖∆𝑙𝑛(𝐼𝑅𝑀)𝑡−1 +∑ 𝜌𝑖∆𝑙𝑛(𝐸𝑆)𝑡−1 + 휀𝑖𝑛𝑖=1
𝑛𝑖=1 …(8b1)
∆ 𝑙𝑛(𝑀)𝑡 = 𝜔1 + 𝛿1(𝐸𝐶𝑀)𝑡−1 + ∑ 𝛼𝑖∆𝑙𝑛(𝑀)𝑡−1 + ∑ 𝛽𝑖∆𝑙𝑛(𝑅𝐸𝐸𝑅)𝑡−1 + ∑ 𝛾𝑖∆𝑙𝑛(𝑌)𝑡−1 +
𝑛𝑖=1
𝑛𝑖=1
𝑛𝑖=1
∑ 𝜗𝑖∆𝑙𝑛(𝐴𝑇𝑅)𝑡−1 + 휀𝑡𝑛𝑖=1 …(8b2)
To confirm the suitability of the ARDL model and how well it fits, diagnostic and stability
tests are carried out. The purpose of a diagnostic test is to examine the problem of serial correlation
and heteroskedasticity within the model. In time-series data like the one used in this study, the problem
of serial correlation and heteroskedasticity may exist. Serial correlation is the existence of a relationship
between a variable and its lagged version over various time intervals. A patterned behaviour of
correlation over time is problematic and thus ideally, no relationship should exist over time between
21
the error terms of each period. Heteroskedasticity is the difference between the variance of error terms
across different variables and it includes the precision of estimated p values.
The cumulative residual (CUSUM) and the cumulative sum of squares of recursive residuals
(CUSUMSQ) are used to conduct a structural stability test. Both these tests are important to test how
constant the estimated coefficients of the model are9.
5. Results and Discussion
The Augmented Dickey-Fuller (ADF) test is conducted on the variables to determine their
order of integration before testing their co-integrating relationships. The ARDL framework is not
contingent upon the testing of variables before the test however, the results of the unit root test could
help determine if the application ARDL approach is suitable for the current estimated model. Table
5.1 presents unit root tests on all the variables constituting the empirical model. The table exhibits the
t and p values taken for each variable at the level and 1st difference. Except for Y* and REER, all the
remaining variables are significant at 1st difference. The null hypothesis states that there is a unit root.
H0 is rejected for the case of REER and Y* because there is no pattern observed in the data and thus,
the alternate hypothesis is accepted for the existence of data stationarity.
Table 5.1. Unit root test
At level At 1st difference Conclusion
Variable T-value Probability Variable T-value Probability
X -1.8085 0.3706 X -5.9643 0.0000 I(1) M -0.5534 0.8686 M -4.5065 0.0010 I(1) REER 3.4456 0.0157 REER -5.8095 0.0000 I(0) Y* -4.1944 0.0025 Y* -2.7142 0.0824 I(0) RM -0.4663 0.8864 RM -5.8596 0.0000 I(1) Y -0.3971 0.7646 Y -4.0742 0.0032 I(1) ATR -0.7831 0.8119 ATR -4.5826 0.0008 I(1) ES (GDP) -1.3504 0.5949 ES (GDP) -4.0683 0.0032 I(1)
H0: there is a unit root
H1: there is no unit root
The following tests aim to evaluate and analyze the impacts of the independent variables on
exports and imports separately. First, all the test results based on exports variables will be discussed
followed by the interpretation of tests used on import variables.
9 See Appendix 1.
22
Real Export Model
We then move on to determine long-run relationships of exports employing the ARDL
approach as shown in Table 5.2.
Table 5.2. Lag Length Criteria for Real Exports Lag Order LR AIC SC HQ
0 NA -5.296036 -5.071571 -5.219487 1 345.8537 -16.17737 -14.83058* -15.71807 2 51.33989* -16.93895* -14.46984 -16.09691* 3 20.65458 -16.61584 -13.02440 -15.39105
The main assumption underlining the ARDL model is that all the variables used are either co-
integrated to order I(0), I(1) or both. This supports the use of bounds testing procedure. Firstly, lag
order is selected based on the Akaike Information Criterion (AIC) as the calculated F-statistics is
sensitive to lag length. From the output, the selected lag order is indicated by an asterisk sign (*). The
lag order that minimizes AIC is 2.
The F-statistics computation (value=4.3018) exceed the upper bound critical value at 5%
significance level (value=4.01) using a restrictive intercept. This signifies that at 5%, the null hypothesis
of no co-integration is rejected and thus, there is a co-integration relation between the variables.
H0: there is no co-integration
H1: there is co-integration
Table 5.3. ARDL bounds test for Real Exports F STATISTICS 4.301846
K 4 CRITICAL VALUE BOUNDS SIGNIFICANCE Lower Bound, I(0) Upper Bound, I(1) 10% 2.45 3.52 5% 2.86 4.01 2.5% 3.25 4.49 1% 3.74 5.06
Table 5.4 shows that in the short run, aside from imported industrial raw materials, all other
variables are insignificant. However, all the variables are significant in the long run. The results indicate
that REER is the most significant with the smallest p-value and largest t value implying that an increase
in REER means real depreciation of the domestic currency. It further implies improvement in the
competitiveness of the export products in the export market because relative to foreign prices,
domestic prices are low and thus, exports of the country increase. An increase of 1% in REER yields
23
on average 0.52% improvement in the real exports, so for Pakistan exports are responsive to currency
depreciation.
Table 5.4. ARDL Co-integrating and Long-run form for Real Exports ARDL (1,0,0,0,2) Based On Akaike Information Criterion (AIC) Dependent Variable: Ln(X) Included Observation: 35
SHORT-RUN COEFFICIENTS
VARIABLES Coefficients Std. error T-statistic Prob.
D(LNREER) -0.201811 0.232358 -0.868537 0.3928 D(LNREER(-1)) -0.391425 0.237593 -1.647463 0.1111 D(LNFI) 0.341869 0.204075 1.675211 0.1054 D(LNES) 0.254496 0.144529 1.760863 0.0896 D(LNIRM) 0.340545 0.158766 2.144955 0.0411 COINTEQ(-1) -0.759315 0.183188 -4.144995 0.0003
LONG RUN COEFFICIENTS
LNREER 0.526930 0.184782 2.851629 0.0082 LNFI 0.450234 0.212590 2.117855 0.0435 LNIRM 0.448490 0.174532 2.569676 0.0160 LNES 0.335165 0.160027 2.094426 0.0457 C -5.664023 1.429495 -3.962255 0.0005
With an increase in foreign income, Pakistan's demand for exports increases in the global
market to the extent of the elasticity. As the estimated coefficient indicates, a 1% rise in foreign income
leads to an increase of 0.45% in Pakistani exports. This result is not consistent with the available
literature (Athukorala and Riedel, 1996), which states that exports for the small country are supply
determined. The significance of REER and Y* implies that the present estimated export model agrees
with the Marshallian demand approach. Similarly, ES and IRM, both supply-side variables, are also
found to be significant meaning export supply-side argument is also supported. Thus, the test results
can be used to indicate that for the case of Pakistan the exports are both demand and supply
determined.
Pakistan's main export goods i.e. textile, leather and rice provide strong evidence for this
finding as they own a significant share in the international market and thus, can influence international
prices. Hence, for the case of Pakistan, exports are rather an amalgam of demand and supply-side
factors.
Results obtained for imported industrial raw material are significant in the short run as well as
the long run. Pakistan's export production relies on imported raw materials. The coefficients show
that a 1% increase in imported industrial raw material increases by 0.45% in real exports. It may be
24
noted that although overall industries in Pakistan uses about 15% of the imported industrial raw
material besides locally produced raw material yet they proportionately use more of imported industrial
raw material when goods are intended for exports market.
We have used GDP data as the proxy for the availability of exportable surplus or export
production capacity. This variable can be interpreted as a hurdle impeding production and thus
significantly obstruct the export performance. The sign of the estimated coefficient shows that
increase in exportable surplus does increase real exports. The long-run estimated coefficient is
statistically significant but has a relatively small coefficient implying that exportable surplus is less
robust in boosting real exports as compared to the other variables.
The error correction term represented as Co-inteq(-1) is negative with a co-efficient estimate
of -0.759. This means that 75 per cent of any instability or deviation from equilibrium is corrected
within one period. Moreover, the t-value (-4.145) obtained is large thus, we can conclude that the
coefficient is highly significant.
H0: There is no serial correlation
H1: There is a serial correlation
Table 5.5. Breusch-Godfrey Serial Correlation LM Test F-statistic 0.797251 PROB. F(2,25) 0.4617
Obs*r-squared 0.38462 Prob. Chi-Square(2) 0.3502
The P-value (0.4617) of Obs*R-squared is greater the 5% and based on the observed p-value
of Obs*R-squared, we will accept H0 (Table 5.5).
Table 5.6. Heteroskedasticity Test: Breusch-Pagan-Godfrey F-statistic 5.067339 PROB. F(7,27) 0.9081
Obs*r-squared 19.87307 Prob. Chi-Square(7) 0.5910
H0: There is no heteroskedasticity
H1: There is heteroskedasticity
Table 5.6 displays output of heteroskedasticity. As the P-value (0.9081) of Obs*R-squared is
greater than 5%, hence on the base of the observed p-value of Obs*R-squared, we will accept H0.
25
Real Imports Model
The other important component affecting the trade balance is the demand for imports in the
home country and it is determined real income, average tariff rate and REER. The study tests and
interprets the results carried out for the case of real imports in Pakistan.
Table 5.7. Lag Length Criteria for Real Imports
Lag Order LR AIC SC HQ
0 NA -1.079252 -0.903306 -1.017842 1 349.7872* -11.47382* -10.59409* -11.16677* 2 16.74887 -11.20526 -9.621742 -10.65257 3 22.05025 -11.27508 -8.987773 -10.47675
Table 5.7 shows that the AIC is minimized at a value of -11.47382 for real imports. We can
conclude that the optimal lag length for the import model is 1 and the best criterion to adopt for the
model is AIC.
Table 5.8 demonstrates the results of the bounds test for real imports. The value of F-statistics
(4.77055) is more than the upper bound of bounds value at 5%, suggesting the existence of a long-
run relationship between the variables. The proposed variables for import model exhibit co-
integration, implying they will move together in the long-run.
Table 5.8. ARDL Bounds Test for Real Imports F-STATISTICS 4.877055
K 4
CRITICAL VALUE BOUNDS
SIGNIFICANCE LOWER BOUND, I(0) UPPER BOUND, I(1)
10% 2.72 3.77
5% 3.23 4.35
2.5% 3.69 4.89
1% 4.29 5.61
The estimated results in Table 5.9 show that domestic income is statistically significant in the
short run as well as the long run, average tariff rate is only significant in the short run and real effective
exchange rate which is insignificant in the long run.
The results further indicate that domestic income is highly significant with a high t value
(6.305) and small p-value (0.000) meaning that changes in domestic income would lead to tangible
impact on the real imports. Every 1% increase in domestic income boosts the real imports by 0.835%,
26
implying that real imports are very sensitive to changes in national income. It is mainly because the
share of capital goods and luxury goods is not very high in the total volume of imports. This finding
supports the theory as an increase in domestic income implies an increase in individuals' purchasing
power. Consequently, individuals tend to spend more on nonessential and luxury goods when their
disposable income increases and therefore, their demand and spending on imports also increases. As
the theory states, when demand for imports increases, ceteris paribus, trade balance deteriorates.
Table 5.9. ARDL Co-integrating and Long-run form for Real Imports ARDL (1,1,1,1) Based of Akaike Information Criterion (AIC)
Dependent Variable: (M)
Included Observations: 37
SHORT-RUN COEFFICIENTS
VARIABLES Coefficients Std. error T-statistic Prob.
D(LNREER) -0.623218 0.272744 -1.986840 0.0680
D(LNY) 0.504540 0.213427 2.814140 0.0275
D(LNATR) -0.202988 0.205043 -1.939507 0.0782
COINTEQ(-1) -0.623218 0.198600 -3.138058 0.0048
LONG RUN COEFFICIENTS
LNREER -0.256270 0.286073 -0.895819 0.3800
LNY 0.834698 0.132370 6.305817 0.0000
LNATR -0.084054 0.095358 -1.881458 0.0876
C 0.240767 2.731129 0.088157 0.9305
When tariffs rates are high they restrict imports by acting as a hurdle to import demand. The
average tariff rate is used in the regression and it turned out statistically significant at 10% level in the
short-run. The estimated coefficient indicates that a 1% increase in the tariff rate would reduce real
imports by 0.084%. This estimate turns out to be quite small in magnitude with a low margin of
significance. Therefore, the government aiming at influencing imports via raising tariff rate will not
give a desirable outcome. Non-tariff barriers (NTBs) are too often used to restrict imports but time
series data for NTBs are not available to examine this relationship.
REER is considered as an important variable that affects imports, but it turned out statistically
insignificant, though the direction of the coefficient is according to the predictions of the theory.
Thus, in the case of Pakistan, the real depreciation of currency does not help in import contraction.
The co-inteq(-1) is negative bearing a co-efficient value of -0.621 implying that 62 per cent of
any movement into disturbances are fixed and stabilized within a single period. Additionally, the large
t-statistic (-3.138) indicates that the coefficient is highly significant.
27
Table 5.10. Breusch-Godfrey Serial Correlation LM Test F-statistic 0.212599 PROB. F(1,26) 0.6486
Obs*R-squared 0.300091 Prob. Chi-Square(1) 0.5838
H0: there is no serial correlation
H1: there is serial correlation
Table 5.10 demonstrates the serial correlation results. It can be observed that the p-value
(0.6486) of Obs*R-squared is larger than 5%, we accept the null hypothesis that no serial correlation
exists in the case of real imports.
Table 5.11. Heteroskedasticity Test: Breusch-Pagan-Godfrey
-statistic F 1.088980 PROB. F(12,22) 0.4144
Obs*R-square 13.04251 Prob. Chi-Square (12) 0.3660
H0: There is no heteroskedasticity H1: There is heteroskedasticity
Table 5.11 displays the results obtained for the presence of heteroskedasticity in the real
imports data. The p-value (0.3660) for Obs*R-squared is greater than 5% thus; based on the observed
p-value we accept the null hypothesis.
6. Conclusion and Policy Implications
6.1. Conclusion
The present study made use of time series data from 1980-2018 to examine the effect of export
and import determinants on the overall trade balance of Pakistan. The export function includes real
effective exchange rate, foreign income, imported industrial raw material and exportable surplus to
witness the importance of each variable on the export performance and test for the small country case
assumption. Similarly, the estimated function for import demand has been augmented by introducing
real effective exchange rate, domestic income and average tariff rate to identify their impact on the
aggregate demand for imports in Pakistan. Initially, the unit root test, Augmented Dickey-Fuller
(ADF) was carried out using co-integration using bounds testing approach incorporated within an
ARDL framework.
The results provide strong evidence that REER plays the most significant part in improving
export performance as compared to all other variables. The robust findings obtained for imported
industrial raw material confirm the hypothesis that imported industrial raw materials are prime inputs
in export production. This disproves the inward-looking policy of the government, which may hinder
28
the production of exports and import substitute goods. The empirical analysis performed earlier
suggested that foreign income can improve Pakistan's trade balance by generating increased demand
for exports. Furthermore, the results indicate that exportable surplus is statistically significant and
positively related to export performance thus, assist in decreasing the trade deficit. The test results
obtained suggest that for the case of Pakistan, exports are determined by both demand and supply
side.
Similarly, the estimated results for real imports indicates that domestic income has a significant
impact on import demand, worsening Pakistan’s trade deficit. Real currency depreciation does not
help in import contraction and therefore, plays no significant role in improving the trade deficit. The
average tariff rate results were only significant in the short run with a low margin of significance
implying that the government aiming at influencing imports by raising tariff rate will not a produce
desired outcome.
6.2. Policy Implications
The estimated export function can be analyzed from two aspects; demand and supply. The
income elasticity carried a greater magnitude and high significance. This implies that the demand-side
factor plays an important role in determining export behaviour. Therefore, it is essential to give
significant importance to the demand side variables and to not focus solely on overcoming supply-
side limitations. This would allow the government to work on feasible strategies supporting export
growth and hence improving trade balance. Policymakers should monitor the international market,
relative exchange rate and income behaviour of the world to design and implement effective policies
focusing on the demand side of exports.
In explaining the export trends, the supply-side determinants proved to be relatively less
important. This leaves enough room to increase the share of value-added in exports which would
cause the export technology to get upgraded. Export production is driven by imported industrial raw
material indicated by its positive and significant coefficient. This rejects the policy of compressing
imports to manage and fix trade imbalances.
Pakistan should adopt strategies to expand and diversify its export base to more
unconventional, non-agricultural and technologically advanced finished goods to improve its
competitiveness in the world and regional markets. This would improve Pakistan’s trade balance and
enhance the growth in its GDP. As previously discussed, real currency devaluation can boost the
competitiveness of Pakistan’s exports thus, improving trade balance. However, the government
29
should prevent exchange rate policy from being overused especially without considering Pakistan’s
macroeconomic context.
Pakistan relies heavily on imported industrial raw material in the production of exports and
since real depreciation also increases import prices, the overall impact of devaluation might cause the
gain in the competitiveness of domestic producers to be undermined. Therefore, it is essential to
analyze whether products with low imported inputs and vice versa dominate the commodity structures
of exports.
The analysis suggests that real currency depreciation can improve the real balance of trade
through expansion in real export and not through import contraction. A policy of reversing tariff
liberalization to contract imports to attain trade balance would not be successful. The imposition of
regulatory duties could lead to under-invoicing of imports in the case of Pakistan due to its systematic
and institutional shortcomings (see also Mahmood, 2013). Furthermore, instead of import tariffs,
Pakistan should impose non-tariff barriers that are permitted e.g., strictly adopting technical barriers
to trade to suppress import demand without compromising its open trade policy measures. However,
the use of non-tariff barriers should be for adopted in the short term to improve the trade balance.
Pakistan must secure its balance of trade through strategic, vigorous and effective trade policies.
Appendix 1 CUSUM and CUSUM Square Test for Exports CUSUM and CUSUM Square Test for Imports
-15
-10
-5
0
5
10
15
1998 2000 2002 2004 2006 2008 2010 2012 2014 2016
CUSUM 5% Significance
-16
-12
-8
-4
0
4
8
12
16
12 14 16 18 20 22 24 26 28 30 32 34 36 38 40
CUSUM 5% Significance
-0.4
0.0
0.4
0.8
1.2
1.6
1998 2000 2002 2004 2006 2008 2010 2012 2014 2016
CUSUM of Squares 5% Significance
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
12 14 16 18 20 22 24 26 28 30 32 34 36 38 40
CUSUM of Squares 5% Significance
30
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