Determinants of export performance of Pakistan: evidence from the firm-level data.
Din, Musleh ud ; Ghani, Ejaz ; Mahmood, Tariq 等
This paper explores the determinants of export performance at the
level of firms in respect of their characteristics and supply side
constraints. The analysis is based on a survey of export-oriented firms
in four major sectors. The results indicate a relationship between the
better performance of foreign-owned firms to their better know-how and
resources compared to the domestically owned firms. Export performance
is positively affected by the level of investment in market/client
oriented technologies. Lack of certification of product and process
standards is the main supply side constraint adversely affecting the
firms' export performance. Facilitation measures like export
processing zones, internationally recognised testing labs, and
industrial clusters would be helpful in improving the export performance
of firms.
JEL classification. F1, L1, L6
Keywords: Trade, Exports, Firms, Performance, Manufacturing
1. INTRODUCTION
Exports are widely believed to play a crucial role in the
development process. Access to the global market allows domestic firms
to achieve economies of scale and thus enhance their profitability.
Being a source of foreign exchange earnings, higher exports enable a
country to meet its growth and development needs through import of
capital goods and raw materials. Exports lead to an improvement in
economic efficiency by increasing the degree of competition; and
contribute to productivity gains through diffusion of technical
knowledge and learning by doing. (1) Export-led growth of East Asian
countries and the recent growth achievements of India and China through
their integration with global markets has brought export promotion to
the forefront in development policy agendas of most developing
countries.
Despite vigorous efforts to promote exports, Pakistan's
exports as a proportion of its GDP have made no significant gains over
the years with the country's share in global exports standing at a
meagre 0.13 percent. In order to understand why Pakistan's exports
have failed to pick up despite favourable export policies, this paper
analyses the determinants of export performance at the level of firms in
terms of their specific characteristics and supply side constraints. The
analysis is based on a survey of export oriented firms conducted by the
Pakistan Institute of Development Economics (PIDE) with the
collaboration of United Nations Industrial Development Organisation
(UNIDO). (2)
During the last couple of decades there has been a growing interest
among empirical researchers to investigate the determinants of export
performance at the firm and industry levels. (3) There are three main
reasons for this shift in focus from macro to micro level. First, there
are theoretical reasons to believe that firms' characteristics are
important in international trade. Traditional trade theories like the
Ricardian theory of comparative advantage and Heckscher-Ohlin model of
comparative advantage assume homogeneous firms within an industry.
However, new trade models following the seminal work of Krugman (1980)
assign explicit role to the characteristics of firms, mainly because it
is at the firm level that actual production and trade decisions are
made. Other developments such as out-sourcing and multinational
production practices have also brought the firm at the centre of
international trade theory. Second, globalisation and rapid increase in
the means of communication have enabled even relatively smaller firms to
target niche markets for higher profits, and this has led researchers to
study how firms' characteristics are related to export performance.
Third, availability of micro data sets and better computation techniques
has facilitated micro-level empirical research. All these factors have
raised the importance of firms' characteristics in international
trade literature.
The role of internal and external factors in export performance is
a relatively less explored area of empirical research in Pakistan. At
the macro level, Akbar and Naqvi (2001) find that Pakistan's export
performance is sensitive to both domestic and external market
conditions, particularly in the area of competivity. However the authors
find that it is relatively more sensitive to demand-side variables than
to other factors. At the micro level, Masakure, Henson, and Cranfield
(2009) assess the effects of quality certification on export sales and
share of exports for Pakistan's exporting firms using the Logit
model while treating certification as a binary dependent variable. The
results indicate a positive correlation between export performance and
ISO 9000 certification, implying that the latter plays a key role in
establishing exporters' credibility and bringing performance gains.
The present study differs from Masakure, Henson, and Cranfield
(2009) in two important ways. First, it explicitly treats firms"
characteristics as explanatory variables while treating exports per
labour as an endogenous variable. Second, it regards certification as a
supply constraint from the exporters' perspective which is measured
on the Likert scale. By using exports as a dependent variable, the
present study promises to shed more light on the question of how export
performance of firms is influenced by their characteristics as well as
supply side constraints directly as against quality certification as in
Masakure, Henson, and Cranfield (2009).
The rest of the paper is organised as follows. Section 2 provides a
brief review of the literature. Section 3 describes the survey data and
provides a brief profile of exporting firms included in the survey.
Section 4 sets out the methodology, whereas Section 5 discusses the
empirical results. Section 6 spells out conclusions and policy
implications.
2. REVIEW OF LITERATURE
A growing body of literature has focused on analysing export
performance at the firm level using a variety of techniques and data
sets. Such works have been reviewed quite extensively in the literature;
see for example, Aaby and Slater (1989), Madsen (1987), Zou and Stan
(1998), and Sousa and Alserhan (2002). This section offers a brief
review of some recent studies on the subject.
Yoshino (2008) analyses how the different characteristics of
African manufacturing firms and the various domestic supply constraints
influence the pattern of geographical diversification of their exports.
The study uses firm-level data from World Bank Investment Climate Survey
(ICS) of the manufacturing sectors of seven Sub-Saharan African
countries. The bivariate analysis is performed to explain geographical
orientation and market diversification, and the results indicate a
positive correlation between export intensity and market diversification
measured as the number of export markets the firms serve. Tobit models
of firm-level export intensity and market diversification are also used
which indicate that the size, foreign ownership, and technology are the
dominant factors in explaining firm-level export performance. Laursen
(2008) explores the determinants of firm-level export behaviour for
Danish industries. The study uses a data set consisting of 1,873 Danish
firms in manufacturing and services using the share of their exports in
their total sales as a measure of their export performance. A Tobit
model has been used to estimate the regression equation with age, number
of employees, and fixed assets as independent variables. The model also
includes some variables relating to the source of innovation such as
suppliers, customers and universities. The findings support the idea
that innovative techniques are determinants of export behaviour
particularly in relation to customers. Process innovation and using
suppliers as a source of knowledge for innovation have a negative
relationship with export intensity. This has been taken to be the case
when Danish manufacturing and service firms have been at a disadvantage
in cost competition.
Wignaraja (2007) analyses firm-level export performance of clothing
enterprises in Sri Lanka. The data are taken from the Asian Development
Bank/World Bank investment climate survey of urban and rural enterprises
in Sri Lanka, conducted in 2004. Export-to-sales ratio has been used as
a measure of export performance which appears as the dependent variable
in a Tobit model. Explanatory variables include ownership, firm size,
human capital, technological capabilities, and geographical location.
The results indicate that size, foreign ownership, technology index and
the human capital variables have. positive and significant effect on
export performance. Similarly a dummy variable for geographical location
also turns out to be positive and significant, indicating that firms
located close to Colombo have an export advantage due to lower transport
costs and other locational externalities.
Duenas-Caparas (2006) analyses export performance of manufacturing
sectors in the Philippines. Firms are classified in three major sectors,
viz., Food, Clothing, and Electronics. The study uses data from the
firm-level survey conducted in 2002 by the Asian Development Bank (ADB)
in collaboration with the World Bank and the Philippines National
Statistics Office. The study uses a modified quasi-maximum likelihood
procedure to specifically address the issue of fractional responses.
Export performance is defined as export to sales ratio which is used as
a dependent variable in the model. Independent variables include age,
size (defined as the number of employees), share of skilled workers to
total workers, share of research and development expenditure to total
sales, and the ratio of capital stock to labour cost. Dummy variables
are used to estimate the effects of training and ownership (domestic vs.
foreign). It is found that foreign ownership, training, and research and
development positively affect export performance in all industries in
the sample. Capital per worker is found to positively influence the
export performance of electronic firms but not in the clothing and food
processing sectors. A nonlinear relation between size and export
performance is found in all firms, most significantly in the clothing
sector. This suggests that as firms expand, they gain in their export
performance. However, further expansion after a certain level results in
less than the desired outcome in export performance.
Smith, et al. (2002) analyse the role of research and development
in the export behaviour of Danish firms. The study uses a data set for
3,500 Danish firms for the year 1997, obtained from the official Danish
Research and Development (R&D) Statistics. The study is concerned
with the interaction between the firms' R&D decisions and the
export performance as well as other influencing factors. Specifically,
the firm's age and size, labour cost, human capital and the
firm's financial solvency are taken as key determinants of export
behaviour. The study uses a bivariate Probit specification and through
the maximum likelihood technique estimates a simultaneous model for
export orientation and investments in R&D. The results show that the
likelihood of being an exporter and investment in R&D positively
depends on firm size and age. The export orientation is also found to
depend positively on the firm's financial solvency. The effect of
wage share on exports turns out to be negative. The decision to invest
in R&D is found to be high in concentrated industries and low among
industries with high entry barriers.
Bhavani and Tendulkar (2001) investigate export performance of
Garment and Apparel firms located in Delhi (India). The study estimates
the export performance and export decision functions using the census of
small-scale industrial units. For export decision function, a Probit
model is estimated using the scale of operation, sales expenses and the
form of business organisation as independent variables. The export
performance function is estimated by Tobit model. The ratio of exports
to production is taken to represent the export performance which is used
as a dependent variable. Independent variables include the value of
production, technical efficiency index, ratio of wage bill to
production, and the share of sales and other expenses in production. The
results of the export performance equation indicate that the value of
production, technical efficiency index, and the share of sales and other
expenses in production have a positive effect on export performance,
whereas the ratio of the wage bill to production and types of ownership
viz., single proprietorship or partnership, show a negative impact. The
study provides two important policy implications. First, in view of the
importance of scale, it wants the existing policy of reserving garments
and apparel for exclusive production in small-scale units scrapped and
second, recommends amendment in the labour legislation applicable to
large-scale factory units as it makes labour markets inflexible and
becomes an impediment to the expansion of existing units and the entry
of new ones.
In their study of Pakistan's economy, Masakure, Henson, and
Cranfield (2009) use a Logit model to explore the effects of quality
certification on export sales and the share in exports of firms using
certification as a binary dependent variable. The results indicate a
positive correlation between export performance and ISO 9000
certification, implying that the certification plays a significant role
in export performance of the firms through enhancement of their
credibility in international markets. It is important to note here that
the study does not provide a direct evidence of the role of
characteristics and supply side constraints in the export performance of
the firms, a question that is being explored in the present study.
3. SURVEY DATA AND PROFILE OF EXPORTERS
The study is based on a survey of exporters in the provinces of
Punjab and Sindh. The survey was conducted by the Pakistan Institute of
Development Economics (PIDE) with the collaboration of United Nations
Industrial Development Organisation (UNIDO). The survey focused on four
major exports of Pakistan, viz., textiles/apparel, leather, agro-food
processing and fisheries. (4) Each of these sectors comprises various
sub-sectors (Table 1) Textiles comprise yarn, fabrics, knitwear,
garments, bed sheets and towels; leather comprises tanning, footwear and
leather products; agro-food group includes processing, horticulture
products, and rice; and the fisheries comprise various types of fish
processing enterprises and fish exporters.
As a first step, a list of all exporters in the four sectors was
compiled. (5) In line with the survey objectives it was decided
initially that the universe would consist of exporters with 50 or more
employees. However, except for the textiles mills identified by the All
Pakistan Textiles Mills Association (APTMA), which are generally
large-scale enterprises, the information on the number of employees was
not available. Hence an alternative criterion of determining the size of
an enterprise was adopted for firms other than textiles enterprises
listed with APTMA, and that was to focus on enterprises having exports
of Rs 1 million or more. The presumption here is that the higher the
export value, the larger would be the scale of the enterprise. (6)
Using the stratified random sampling approach, a total of 180 firms
were chosen covering the four major export categories (Table 2). The
enterprises in the four sectors were stratified according to the
sub-processes listed in Table 1.
The number of firms in each stratum (sub-process) was chosen
roughly on the basis of the share of exports of each sub-sector in the
corresponding sector. For instance, the number of firms in yarn was
chosen on the basis of the share of yarn in total export-s in the
textiles group. The universe column indicates the total number of firms
in each sector and sub-sector meeting the size criteria from which the
sample was drawn. The details are as follows (Table 3).
The age distribution of firms (Table 4) reveals that the majority
of firms (62 percent) were less than 25 years old in 2005. For domestic
firms the percentage is 64 and for foreign firms it is 52. The number of
entrants (domestic as well as foreign) has been highest in the period
1990-1999. Incidentally, there has been no entry of foreign firms in the
period 2000-2005. (7)
The size distribution of firms shows that a majority of firms
employ more than 99 employees and hence fall in the category of large
firms (8) (Table 5). At the sectoral level, the textile sector mostly
consists of large firms, whereas in agro-food and fishery smaller firms
dominate.
Location is an important determinant of firms' export
performance. Karachi, being the largest industrial city and a hub of
exporting activities, accounts for the highest proportion of firms in
the sample, followed by Lahore and Sialkot (Table 6). Together, these
three cities account for more than 80 percent of firms under study.
Trends in Sales
In the textiles sector, the average sales of firms increased over
time (2000-2004) for firms of all sizes except for smaller firms with up
to 50 employees. Firms with 50-99 employees witnessed a six-fold
increase in their sales during the period 2000-2004, increasing from US$
1141.2 thousand in 2000 to US$ 6852.9 thousand in 2004. It is
interesting to note that firms with 100-249 employees had lower sales
than smaller size firms (50-99 employees). This is essentially due to
aggregation of sales because the problem does not exist at the
sub-sector level. The sales of larger size firms also witnessed robust
growth during 2000-2004.
The sales of leather firms of all sizes generally exhibited a
declining trend during the period. The only exception was very high
sales in the years 2001 and 2002 due to strong growth, in one company
particularly. In the agro-food sector, while the sales of firms with
less than 1000 employees showed a fluctuating trend, the sales of firms
with 250-999 employees registered manifold increase during the period,
from US$ 6276 thousand in 2000 to US$ 39170 thousand in 2004. Except for
fish exporters with 250-999 employees who witnessed an increase in their
exports during the period, other exporters in this sector reported
either declining or sluggish sales over time.
Distribution of Sales by Domestic and Foreign Markets
A majority of firms in all sectors were largely export-oriented:
total exports as percentage of total sales ranged from 80 percent to 100
percent in all sectors. This is hardly surprising in view of the fact
that our sample is focused on firms that are export firms. However,
there are a large number of firms that may be selling their products
exclusively in domestic markets. That the export firms also sell in the
domestic market is a positive trend that may result in the local
consumer getting better quality products.
Export Diversification by Markets
The European Union is a major market for textiles and leather
exporters, followed by North America and Asia. (9) For agro-food
exporters, North Africa and Middle East are
the major markets, followed by Asia, EU and North America. Most of
the fisheries exports are marketed in Asia, followed by EU, North Africa
and Middle East, and North America. It is clear that Pakistan's
exports are concentrated in a few markets, and, therefore, there is an
urgent need for exploring new markets for Pakistani products.
The exporters indicated the desire to diversify the export markets
towards Africa, Middle East and Latin America. Nevertheless, the
traditional markets would continue to play a major role. For example,
the majority of textiles exporters accorded high priority to EU as a
future market followed by North America. Only a few textiles exporters
indicated a high priority for Asia as a future market. However, it was
suggested that Pakistan would focus on the Chinese market in Asia to
exploit its potential. North America emerged as a high priority future
market for leather exporters, followed by EU, Latin America, the
Caribbean, and Asia. About half of agro-food exporters attached high
priority to EU as a future market, followed by Asia. A majority of
fisheries exporters indicated high priority for EU, North America and
Asia as future markets.
4. METHODOLOGY
In a pioneering study on export performance of firms, Aaby and
Slater (1989) define two broad categories of variables that can
influence their export performance: (a) external factors which mainly
determine the environment under which firms are operating, and (b) firm
characteristics and strategy which are internal to the firm. In this
study we focus on the latter. Firms' performance is measured by the
value of exports in US dollars. To control for the firm size, the
dependent variable is defined as the value of exports per unit of labour
employed (Exp). The independent variables include age, type of
ownership, investment in product and process technologies, managerial
competence, certification of product and process standards, and
location. The complete regression equation is specified below. (10)
[Exp.sub.i] = [[beta].sub.o] + [[beta].sub.1][Age.sub.i] +
[[beta].sub.2][Ownership.sub.i] + [[beta].sub.3][DInvest.sub.i] +
[[beta].sub.4][DFinv.sub.i] + [[beta].sub.5][Cer.sub.i] +
[[beta].sub.6]DLoc + [u.sub.i]
The variable 'Age' represents the number of years of
establishment of the firm. This variable may affect export performance
of the firm in different ways and its sign is theoretically ambiguous.
For example, this variable could have a positive sign if older firms
being more experienced are able to demonstrate better export
performance. On the other hand, one could argue that new firms, having a
modern outlook with better management and production techniques, may be
more efficient and thus may show better export performance. The evidence
in the empirical literature is mixed. Smith, et al. (2002) and Barrios,
et al. (2003) find a positive sign for the age coefficient, but
Ramstetter (1999) and Sjoholm (2003) report a negative coefficient for
the age variable.
'Ownership' is a dummy variable to control for the type
of ownership. The dummy variable takes a value of 1 for firms with
domestic ownership and a value of zero for foreign ownership. Firms with
foreign ownership are expected to perform better than domestic firms due
to better technical and managerial expertise, greater access to and
networking with foreign markets. In the literature, the evidence is in
favour of foreign owned firms: for example, Ramstetter (1999) and
Wignaraja (2007) find that foreign-owned firms outperform domestic-owned
firms in export markets. The ownership variable, therefore, is expected
to have a negative sign.
Investments by firms to improve their product and market strategies
and to strengthen networking with clients are expected to play an
important role in determining their export performance. The surveyed
firms were asked about their level of investment during the last three
years, and the average of these yearly investments is used as an
explanatory variable (DInvest). Firms with investment in client/market
oriented technologies are expected to outperform those who made no such
investment. Therefore, this variable is expected to have a positive
sign.
Managerial competence strongly affects a firm's performance. A
competent management has a long term horizon, is well aware of markets
and new challenges, and is better able to cope with present and future
challenges. Unfortunately, data on managerial competence are not
available. We have thus tried to proxy this variable by a binary
variable (DFinv) that captures the firms' responses to their future
investment plans. It is plausible to assume that a competent management
will be aware of the available investment opportunities and will have
prepared future investment plans in line with the market outlook. The
variable assumes a value of 1 if a firm has prepared such a plan, and
zero otherwise. On a priori grounds, we expect this variable to have a
positive coefficient.
The capacity challenges on the supply side faced by the firms can
significantly influence their export performance. In the survey, the
firms were asked to use Likert scale responses (ranging from 0 =
'not applicable' to 5 'major problem') to indicate
how a particular supply constraint applied to their firms. A major
constraint identified by the firms was the lack of certification of
products and process standards and consequently this variable was
included in the model. Certification of conformity with standards and
technical regulations is intended to ensure uniformity of products and
processes and to ensure minimum safeguards on quality and safety. More
and more international buyers ask for the proof that internationally
recognised (certified) operational systems and procedures were in place
for quality process and product management. The performance of exporters
not having international certifications is likely to be hampered owing
to their inability to demonstrate compliance with international product
and process standards and technical regulations. We, therefore, expect a
negative sign for this constraint.
Location of firms is also an important determinant of firm
performance. Firms that are located at a geographically advantageous
position in terms of both logistics and industrial clusters are expected
to perform better than firms that do not possess these locational
advantages. For example, proximity to a port can help the firm improve
its performance through rapid delivery of imported inputs, timely export
shipments, and lower transportation costs. On the other hand, firms
located in industrial clusters enjoy various positive externalities
including availability of business-related amenities and infrastructure.
To capture these advantages, a dummy variable is used that assumes a
value of 1 if a firm is located in Karachi, and zero otherwise. Because
of the locational advantages, it is expected that firms that are located
in Karachi would exhibit a better export performance than firms located
elsewhere.
5. EMPIRICAL RESULTS
The estimation has been performed by Ordinary Least Squares
technique. In order to avoid the problem of heteroskedasticity,
White's Consistent Standard Errors and Covariance Procedure has
been used. This technique is preferred in cross-section data that
include variables relating to the 'size' aspects of firms. In
such cases, the error term may also pick up variations due to size,
possibly because of some omitted variables in the model. (11) In the
context of the present study, variables such as exports and investment
are related to the size of the firm and hence the data are susceptible
to the problem of heteroskedasticity.
The results of estimation of coefficients of variables along with
their standard errors, t-values and probability of rejection (i.e.,
probability of rejection of null hypothesis that the coefficient of a
specific variable is zero) are given in Table 7. The F-statistics are
significant implying that selected variables significantly explain
export performance of firms. (12)
The results show that the age of the firm has a negative but
insignificant effect on firms' performance. (13) The dummy variable
for ownership is negative and significant, implying that foreign-owned
firms exhibit superior export performance than the domestically owned
firms. (14) It is generally accepted that foreign-owned firms possess
better managerial and technical expertise and are better able to meet
the global market requirements through their international linkages.
(15) This result underscores the fact that the domestic firms can also
compete effectively in international markets provided they upgrade their
managerial and technical competencies and build international networks
as demonstrated by foreign-owned firms.
There is a positive and highly significant relationship between the
level of investment in product and process technologies and export
performance. Higher investment in product quality as well as in
production processes allows the firms to capture export markets and
improve their profit margins. (16) Similarly, managerial competence has
a positive and significant impact on export performance. Firms that
possess better managerial expertise are more attuned to market dynamics
and hence are able to perform better in export markets. The lack of
certification turns out to be an important supply side constraint that
adversely affects the firms' export performance. (17) The dummy
variable for firms located in Karachi is positive and significant and
this shows that such firms enjoy the benefits of proximity to port and
industrial clusters.
6. CONCLUSIONS AND POLICY IMPLICATIONS
This paper has investigated the determinants of export performance
at the firm level, based on a survey of export-oriented firms in four
major export segments including textiles and apparel, leather products,
agro-food, and fisheries. The results of the regression analysis
indicate that foreign-owned firms outperform the domestic firms in
export markets, not least because of the formers' advantages in
terms of better managerial and technical expertise and networking with
international clients. The export performance of firms is positively
influenced by the level of investment in market/client oriented
technologies. This underlines the importance of strengthening marketing
networks and upgrading products and process technologies in line with
the latest market requirements. Managerial competence also turns out to
be an important determinant of export performance highlighting the
importance of this factor in gaining access to highly competitive export
markets. Lack of certification of compliance to international product
and process standards is a major supply capacity constraint hindering
export performance of the firms. Firms located in geographically
advantageous areas with strong industrial clusters and easy access to
international transportation exhibit better export performance as
compared with firms that do not enjoy these advantages.
The above findings have important policy implications. First,
foreign direct investment in export-oriented industries can play an
important role in boosting Pakistan's exports. Pakistan offers
attractive incentives to foreign investors but so far it has not been
able to attract significant investments, especially in export-oriented
industries. A step in the right direction has been the establishment of
export processing zones in major cities that are designed to cater to
the specific needs of export-oriented firms (18). However, there is a
need to make these zones more attractive to foreign investors by
providing them with better physical infrastructure and utilities.
Second, it is important to facilitate the certification of
compliance to international product and process standards. There is a
dearth of internationally recognised testing laboratories in Pakistan
that can cater to certification needs and consequently exporters have to
rely on testing laboratories in Singapore, Hong Kong, UK, Germany and
other countries making the whole process costly. There is, therefore, a
need to help develop internationally recognised and accredited local
testing laboratories to cater to the testing needs of textile, leather,
agro-food and fisheries sectors. Also, there is a need to raise the
level of awareness among exporters about the importance of
certification.
Finally, the results underscore the importance of advantages of
location and clustering in export performance of the firms. Businesses
thrive and grow in clusters which help the firms in lowering their costs
through easy access to amenities and other business-related facilities
that are typically available in such clusters. In this respect, an
important initiative is the concept of Textiles City being developed in
the industrial area of Karachi's port Qasim which can be an
important inducement for export-oriented firms. There is a need for more
such initiatives to help cluster export-oriented manufacturing, allowing
the firms to benefit from agglomeration economies.
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(1) Krugman (1984).
(2) See PIDE (2007)
(3) See Madsen (1987) and Aaby and Slater (1989) for a survey of
this literature.
(4) Textiles, agro-food and leather were chosen because there are
the major exporting sectors. Fishery was chosen because its potential to
become a major exporting sector.
(5) There were some 1357 exporting enterprises in this list with
607 in textiles and apparel, 363 in leather sector, 308 in agro-food
processing and 16 in fisheries.
(6) As the final criterion for selection was export value rather
than the number of employees, the sample also includes enterprises with
less than 50 employees.
(7) In fact, net inflow of foreign direct investment gained
momentum in the year 2005-06 and peaked in 2007-08 at about US$5.2
billion. This phenomenon is very prominent in "Food, Beverages and
Tobacco" sector where net foreign direct investment registered
manifold increase (Pakistan Economic Survey 2007-08). The FDI started
declining in later years: FDI was US$3.2 billion in 2008-09 (Pakistan
Economic Survey 2008-09) and further fell to US$1.8 billion during the
period July to April 2009-10. Pakistan Economic Survey (2009-10).
(8) This line of division has been used in literature; see for
example Wignaraja (2007).
(9) Within the textiles sector, Asia is a major market for yam and
fabrics, besides EU and North America. Asia is also a major market for
exports of tanneries.
(10) As pointed out by a referee, the model specification may be
subject to endogeneity bias. The problem of endogeneity is pervasive in
economic research, and it is difficult to handle, especially in survey
data that are inherently limited in scope, making it hard to use
appropriate instruments.
(11) See Cooper and Weekes (1983), p. 217.
(12) As suggested by a referee, we have tried sectoral dummies but
the results are amenable to any useful interpretation.
(13) This is similar to the finding by Masakure, et al. (2009).
(14) Other empirical studies have found similar results for
developing countries; see, for example, Bhavani and Tendulkar (2001),
Duenas-Caparas (2006), and Wignaraja (2007).
(15) See Baldwin and Gu (2003).
(16) Alvarez and Lopez (2005) find such investments to be highly
significant in influencing performance of exporters.
(17) Various other supply side constraints--including lack of
skilled labour, inability to meet market requirements, problem on
on-time deliveries--were tried but these turned out to be insignificant.
(18) A variety of incentives are offered to investors in the export
processing zones including duty and tax free import of machinery,
equipment and materials.
MUSLEH UD DIN, EJAZ GHANI, and TARIQ MAHMOOD
Musleh-ud Din <
[email protected]> is Joint Director at
the Pakistan Institute of Development Economics, Islamabad. Ejaz Ghani
<
[email protected]> is Chief of Research at the Pakistan Institute
of Development Economics, Islamabad. Tariq Mahmood
<
[email protected]> is Senior Research Economist at the Pakistan
Institute of Development Economics, Islamabad.
Table 1
Sectoral Coverage
Textile/Apparel Leather
* Yarn * Tanning
* Fabric * Footwear
* Garments * Leather products/
* Knit wear garments
* Bed sheets and
Towels
Agro-food Processing Fisheries
* Horticulture products * Fish processing
(fruits and vegetables) enterprises
* Rice (grading and * Fish exporters
polishing)
Table 2 Sectoral Distribution of Firms
Number of Percentage in
Sectors Enterprises Total Sample
Textiles/Apparel 90 50
Leather 45 25
Fisheries 16 10
Agro-food 29 15
Total 180 100
Table 3
Sector-wise Sample and Universe
Enterprises in
the Sample Universe
Textiles/Apparel
Yarn 14 64
Fabrics 24 54
Garments 16 48
Knit Wear 16 27
Bed Sheets and Towels 20 33
Total 90 226
Leather
Tanning 19 19
Footwear 7 7 *
Leather Products/Garments 19 62
Total 45 88
Agro-food Processing
Horticulture Products (Fruits and 7 22
Vegetables)
Rice (Grading and Polishing) 22 43
Total 29 65
Fisheries 16 16
* There were only seven firms having exports of Rs one million or
more. Therefore, all the seven firms were included.
Table 4 Percentage Distribution of Firms by Age and Ownership
Year of
Establishment Total Domestic Foreign
Up to 1947 4.1 2.4 13.0
1947-1959 7.5 8.1 4.4
1960-1969 11.6 10.5 17.4
1970-1979 15.0 15.3 13.0
1980-1989 21.1 21.8 17.4
1990-1999 29.9 29.0 34.8
2000-2005 10.9 12.9 0
Source: Survey data.
Table 5 Percentage Distribution of Firms by Employment
Textiles Leather Agro-food
Less than or Equal to 49 3.3 4.1 5.7
From 50 to 99 3.3 9.8 5.7
From 100 to 249 9.8 4.9 4.1
From 250 to 999 16.4 3.3 2.5
Greater than or Equal to 1000 13.9 1.7 0
Fishery Total
Less than or Equal to 49 1.6 14.8
From 50 to 99 4.1 23.0
From 100 to 249 4.9 23.8
From 250 to 999 0.8 23.0
Greater than or Equal to 1000 0 15.6
Source: Survey Data.
Table 6
Percentage Distribution of Firms by Location
City of Location Percentage of Firms
Karachi 54.1
Lahore 20.4
Multan 3.2
Sialkot 12.1
Wazirabad 1.3
Faisalabad 5.1
Kasur 1.3
Others 2.4
Source: Survey Data.
Table 7
Regression Results
Dependent Variable: Exports per Unit of Labour (Exp) *
Method: Least Squares
White Heteroskedasticity-Consistent Standard Errors and Covariance
Variable Coefficient Std. Error
C 2.2211 0.5220
Age -0.0005 0.0057
Ownership -0.7436 0.4170
DInvest 0.0510 0.0049
DFinv 0.9628 0.2853
Cert -0.5759 0.2198
DLoc 0.6191 0.3576
R-squared 0.5593 F-statistic
Adjusted R-squared 0.4334 Prob. (F-statistic)
Variable t-Statistic Prob.
C 4.2549 0.0004
Age -0.0904 0.9288
Ownership -1.7829 0.0891
DInvest 10.3078 0.0000
DFinv 3.3747 0.0029
Cert -2.6204 0.0160
DLoc 1.7312 0.0981
R-squared 4.4421
Adjusted R-squared 0.0047
* Dependent variable in natural log.