Working Paper 95
Working Paper 95
Working Paper 95
Rabia Latif
Attiya Yasmin Javid
Rabia Latif
Fatima Jinnah Woman University, Rawalpindi
and
E-mail: publications@pide.org.pk
Website: http://www.pide.org.pk
Fax: +92-51-9248065
List of Tables
List of Figures
(iv)
ABSTRACT
This study analyses the demand and supply side determinants of textile
and garments’ exports of Pakistan using time series data for the period 1972–
2010. Eight trading partners (US, UK, Canada, Italy, France, Japan, Spain and
UAE) contributing major share in this trade have been selected for analysis. The
demand and supply side factors have been examined using the simultaneous
equation approach and the Generalised Method of Moment to handle the
simultaneous equation bias. The results reveal that the income of the trading
partners has an important and significant role in determining performance of
textile and clothing exports of Pakistan. The relevance of devaluation policy in
accelerating demand for this export has been found to be comparatively small.
On the supply side, the relative prices and the capacity variable are important.
The results of the exports supply equation show that the removal of quantitative
restrictions does not provide any incentive to the suppliers. However, the real
wages in the textile sector have a significant but small effect on the supply. The
demand for textile and clothing products of Pakistan is relatively high in UK,
UAE, Italy and USA (as indicated by high income elasticities), therefore, factors
that help in the expansion of textile and clothing products in the local market
and the marked countries should receive special attention of the policy makers.
Keywords: Demand and Supply of Textiles and Clothing; Simultaneous
Equation; Real Effective Exchange Rate
1. INTRODUCTION
Over the years, exports have played an important role in the economic
growth of developing countries as aptly expressed in the well known words of
Roberston who has called trade as “an engine of growth”. Some newly
industrialised countries (NICs)—(Korea, Taiwan and Singapore)—which shifted
their import substitution policies to export promotion policies to promote the
exports of the manufacturing sector have done remarkably well. This success of
the NICs proved “elasticity pessimism” to be wrong and induced other
developing countries to replicate the same outward-oriented strategy of export-
led growth. The export performance of any country depends on many price and
non-price factors.
The debatable issue is whether other developing countries like Pakistan
could also make similar gains from an outward oriented growth strategy. It is
pointed out by Riedal (1984, 1988) that the massive growth of the NICs is due to
domestic incentives and supply side factors rather than external demand side
factors since countries compete in the international market on the basis of
prices. Muscatelli, et al. (1992, 1995) pointed out that growth of manufacturing
exports depends on the importing countries’ incomes i.e., the absorption
capacity of the international market. Malik (2000) supports Riedal and
concludes that the successful countries are able to differentiate their products in
the international market by focusing on modern techniques of production,
training and manpower.
There are several sectors on whose productivity and growth economic
prosperity and welfare depend. The most important is textile sector which has
always played an important role in the economic growth of developed and
developing countries. Trade in textile and clothing sector has increasingly been
subject to protection through bilateral trade agreements like the Multi Fibre
Agreement (MFA) which was effective from 1974-1994. It was replaced by the
Agreement on Textile and Clothing (ATC) which gave member countries a 10-
year time period (1995-2005) to eliminate the restrictions gradually in four
stages and to bring trade in textile and clothing under the general GATT rules.
The textile and clothing sector is the major industrial sector of Pakistan.
Its contribution to total exports, employment, foreign exchange earnings,
investment and value added makes it the country’s single largest manufacturing
sector. It contributes around 46 percent in manufacturing output, accounts about
60 percent in export earnings and absorbs approximately 39 percent of the
manufacturing labour force.
2
The textile and clothing industries have backward and forward linkages in
other sectors of the economy and in other production processes within the
industry. Many textile outputs such as cotton and cotton yarn are used as inputs
in the production of other final outputs (such as carpets, cloths and industrial
textile), and in other industries like furniture and automobiles. The climate of
Pakistan is suitable for the production of this industries’ important inputs—
cotton and wool. Pakistan has traditionally remained stuck in the early stages of
production and trade of these inputs and has not taken advantage of using these
inputs in the production of value added goods. Although this sector is very
important on the national level but its share in world exports continues to be
very small.
The structure of textile and clothing trade has undergone a number of
changes at the international and national levels during the past few years.
Among the major examples are changes in the pattern of consumer expenditure,
easing in protective curbs. Allowing greater access to the international market,
increased share of developing countries in the world textile and clothing exports
and incentives provided by the Government to encourage producers. These
changes have significantly influenced the magnitude and structure of textile and
clothing industry. According to studies [Goldstein and Khan (1978), Muscatelli,
et al. (1992), Hassan and Khan (1994) and Atique and Ahmed (2003)] it has
been found that the demand and supply sides are the major determinants of
exports but the factors affecting the exports of this sector have received scant
attention. Therefore, proper understanding of demand and supply side
determinants of this important sector is an urgent need. The export performance
of this sector has initially been analysed focusing on the demand side factors on
the assumption that the supply side was infinitely elastic. Later on both demand
and supply side elasticities were estimated. These studies generated biased
estimates because both demand and supply side equations were not correctly
specified. Keeping this in view, the simultaneous equations model has been
specified to incorporate the endogeniety problem in the demand and supply of
textile and clothing exports. Eight major trading partners (US, UK, Canada,
Italy, France, Japan, Spain and UAE) have been selected for the analysis of
disintegrated textile and clothing exports.
The study contributes to the existing empirical literature in several ways.
Besides providing a detailed overview of the textile and clothing sector at the
disaggregated level, it also adds policy variables like real devaluation/
depreciation of domestic currency vis-à-vis the trading partner’s currency and
removal of trade restriction regime in the demand and supply framework. The
Real Effective Exchange Rate is calculated which captures the effect of
devaluation from outside the model and GMM is used to address simultaneity. It
also highlights several factors which affect this sector’s demand and supply.
These factors are important for investors and policy makers to bring positive
changes in the production and exports of this sector.
3
The main objective of the study is to analyse the impact of demand and
supply side determinants on the textile and clothing exports of Pakistan and
evaluate their relative importance in export performance. It is generally believed
that real devaluation of domestic currency as against the currency of the
competitor helps to accelerate export performance. A few evidences contrary to
this view are also present in the literature [Vermani (1991), Malik (2000),
Akhtar and Malik (2000) and Atique and Ahmed (2003)]. Therefore, the
objective in this case is to see the impact of real devaluation on the textile and
clothing exports of Pakistan.
Recently, the non-tariff restrictions on textile and clothing exports have
been removed in four phases under the ATC. It is expected that the removal of
these restrictions would provide exporters with greater access to the
international markets and enable them to expand the quantum of their supplies
[Malik (2000)]. Therefore, the final objective is to examine whether the removal
of MFA restrictions encourages domestic suppliers to increase the quantum of
their exports or not.
The study is organised as follows. After the introduction, the structure of
the textile and clothing sector’s exports is discussed in Section 2. The relevant
literature on the exports’ determinants is presented in Section 3. The model,
methodology and data sources are discussed in Section 4. The discussion and
analysis of the results are given in Section 5. The final section of the study
includes the conclusion and policy implications.
clothing in world exports. The growth in Pakistan’s textile and clothing exports
is mainly driven by low value textile items. The reasons for this trend are
discussed below.
Table 1
Textile and Clothing Exports (2010)
(US$ billion)
World % Share Pakistan % Share
Textile 250.7 41.63 7.8 66.10
Clothing 351.5 58.36 3.9 33.05
Total 602.2 11.8
Source: Pakistan Economic Survey 2011-12.
Textile
Processing
Source: PBS (2008-09)
17.08%
Table 2
Number of Spindles in Spinning Sector
No. of Spindles No. of Spindles No. of Spindles
Years (x1000) Years (x1000) Year (x1000)
1972-73 3226 1985-86 4422 1997-98 8368
1973-74 3308 1986-87 4293 1998-99 8392
1974-75 3392 1987-88 4330 1999-00 8477
1975-76 3478 1988-89 4790 2000-01 8601
1976-77 3544 1989-90 5195 2001-02 9060
1977-78 3560 1990-91 5493 2002-03 9260
1978-79 3704 1991-92 6141 2003-04 9499
1979-80 3731 1992-93 6768 2004-05 10941
1980-81 3983 1993-94 8182 2005-06 11292
1981-82 4180 1994-95 8307 2006-07 11266
1982-83 4265 1995-96 8493 2007-08 11834
1983-84 4224 1996-97 8137 2008-09 11366
1984-85 4396
Source: APTMA.
1
Textile and clothing trade 2007-08, Ministry of Textile Industry.
6
600000
600000
500000
500000
Blended
400000
400000 Grey
300000
300000 Bleached
Dyed & Printed
200000
200000
100000
100000
00
1971-72
1973-74
1975-76
1977-78
1979-80
1981-82
1983-84
1985-86
1987-88
1989-90
1991-92
1993-94
1995-96
1997-98
1999-00
2001-02
2003-04
2005-06
2007-08
2009-10
Source: APTMA.
2
Data used in figure is given in Appendix 1A.
3
Data used in figure is given in Appendix 1B.
7
fibre was zero in production of textile products in Pakistan before 1980-81. But
subsequently it started increasing and highest at 45 percent and 43 percent
during 1993-94 and 2009-10 respectively, whereas the share of cotton
consumption has remained at more than 70 percent over the review period.
3000000
2500000
2000000
Cotton
1500000
Fibre
1000000
500000
0
19 73
1 9 -7 5
19 77
19 79
19 1
19 83
19 85
19 87
19 89
19 1
19 93
19 95
19 97
20 99
2 0 -0 1
20 03
20 05
20 07
9
-8
-9
-0
-
-
-
-
-
-
-
-
-
-
-
-
-
-
72
74
76
78
80
82
84
86
88
90
92
94
96
98
00
02
04
06
08
19
Source: APTMA.
Table 3
Pakistan’s Textile Exports
(US$ million)
2006-07 2007-08 2008-09 2009-10
Cotton & Cotton Textile (%ge) 94.00 93.45 95.25 94.36
Synthetic Textile (%ge) 3.89 4.55 3.26 4.31
Wool & Woollen Textile (%ge) 2.11 2.00 1.48 1.33
Total Textile 100 100 100 100
Source: Economic Survey of Pakistan 2011-12.
4
Data used in figure is given in Appendix 1C.
8
Table 4
Comparison of Pakistan’s Textile and Clothing Exports with Asia
(US$ million)
Growth
Countries / Rate per
Years 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Annum (%)
World 341166 356870 405301 453786 478405 525465 583302 612028 525336 602116 70.95
Bangladesh 5238 5314 6067 6893 7595 9812 9739 12010 13411 16923 209.95
Share in World
Exports (%) 1.54 1.49 1.50 1.52 1.59 1.87 1.67 1.96 2.55 2.81
China 53475 61864 78961 95284 115213 144057 171552 185772 167088 206738 296.00
Share in World
Exports (%) 15.67 17.34 19.48 21.00 24.08 27.42 29.41 30.35 31.81 34.34
India 11011 11645 12750 14332 17070 18444 19547 21340 21116 24118 108.67
Share in World
Exports (%) 3.23 3.26 3.15 3.16 3.57 3.51 3.35 3.49 4.02 4.01
Pakistan 6661 7018 8521 9151 10691 11376 11177 11092 9867 11778 76.42
Share in World
Exports (%) 1.95 1.97 2.10 2.02 2.23 2.16 1.92 1.81 1.88 1.96
Source: World Trade Organisation (WTO).
5
During this time, textile and clothing trade was under General Agreement on Tariffs and
Trade (GATT) and quantitative restriction had been removed.
9
Table 5
Concentration of Exports6
1972-1980 1981-1990 1991-2000 2001-08
%Share Growth % Share Growth % Share Growth % Share Growth
Raw Cotton 8.76 23.03 12.80 8.35 3.00 –6.06 0.51 –11.81
Cotton Waste 0.19 –4.83 0.26 304.21 0.67 5.03 0.31 as 1.08
Cotton Yarn 12.53 0.62 10.71 77.40 16.60 10.80 8.79 3.65
Cotton Thread 0.42 14.01 0.20 –3.56 0.04 –1.31 0.01 74.79
Cotton Cloth 12.99 11.72 10.67 40.20 13.50 27.34 12.22 13.57
Synthetic 0.49 –0.65 3.60 25.81 6.57 20.35 3.41 –2.51
Readymade
Garments 2.27 81.70 7.99 182.49 16.66 36.00 19.04 13.11
Source: Statistical Supplement and Economic Survey of Pakistan.
6
Due to the problem of data availability in similar pattern for 1972-2010, this table consists
of few components not all textile exports categories.
10
Source: APTMA.
Table 6 presents the percentage share and growth rate of major textile and
clothing export categories, over four decades. The category wise, in-depth
analysis of exports and percentage change for fiscal years 2007-10 is presented
below. It explains the export growth of different categories in competitive
environment after the removal of quantitative restrictions. There is more than 50
percent increase in exports of three categories, raw cotton, yarn other than cotton
yarn and art silk and synthetic textiles.
11
Table 6
Category Wise Exports of Pakistan
Value in US$ Million % Change % Change
2007-08 2008-09 2009-10 (2007-08 to (2008-09 to
Unit 2008-09 ) 2009-10)
Raw Cotton MT 38,509 72,636 157,962 88.62 117.47
Cotton Yarn MT 419,528 379,597 500,130 –9.52 31.75
Cotton Cloths TH.SQM 1,437,467 1,496,972 1,256,944 4.14 –16.03
Cotton Carded or
Combed MT 12,207 14,374 8,628 17.75 –39.97
Yarn Other Than
Cotton Yarn MT 15,366 7,140 13,203 –53.53 84.92
Knitwear TH.DOZ 73,913 81,224 74,711 9.89 –8.02
Bed Wear MT 247,898 238,526 243,099 –3.78 1.92
Towels MT 106,680 124,539 155,663 16.74 24.99
Tents, Canvas and
Tarulin MT 17,714 16,984 17,088 –4.12 0.61
Readymade Garments TH.DOZ 28,250 22,129 20,336 –21.67 –8.10
Art, Silk and Synth.
Textile TH.SQM 362,351 222,546 336,337 –38.58 51.13
Made up Articles – 0 0 0 0 0
Other Textile
Materials – 0 0 0 0 0
Source: Economic Survey of Pakistan.
The articles in category Art, Silk and Synthetic Textile rank 3rd in textile
exports, cotton yarn also shows significant growth rate of 31.75 percent.
Readymade garments, cotton cloth and knitwear are important value added
categories but their exports have declined by 8.10 percent, 8.02 percent and
16.03 percent respectively. Textile and clothing exports mainly consist of cotton
yarn, cotton cloth, knitwear, bed wear and readymade garments. Analysis in
Table 6 reveals that Pakistan is unable to clearly diversify in textile and clothing
export, and unable to take much advantage of cotton base and more focus is
given to exporting raw material products (cotton and cotton yarn etc.). Whereas,
value added products contribute small part in total textile exports. Therefore,
positive trend in the total textile and clothing exports is due to growth in low
value products at the cost of finished products.
Unit values are calculated by using export quantities and export values of
the respective categories, reflected in Table 6. While unit value of major textile
and clothing exports for three fiscal years (2007-08, 2008-09 and 2009-10) are
shown in Figure 6. Readymade garments and knitwear has high unit value for
exports despite of their decreasing share in total exports. The share of bed wear
exports has also decreased over the period but unit value has increasing trend. At
the same time, the prices of other raw material categories (cotton, cotton yarn
and yarn other than cotton yarn) have decreased in international market. These
categories have a major share in total exports and exhibit more than 50 percent
growth over the period concerned.
12
Table 7
Principal Buyers of Textile and Clothing Exports from Pakistan
(US$ Million)
2007-08 (Textile and Clothing 2008-09 (Textile and Clothing
Exports) Exports)
Countries Value Percentage in Total Value Percentage in Total
USA 3,303,455 31.2 2,925,545 30.6
UK 783,749 7.4 678,592 7.1
Germany 598,549 5.7 547,440 5.7
China 368,437 3.5 457,414 4.8
Italy 471,616 4.5 385,168 4
Bangladesh 255,319 2.4 334,342 3.5
Spain 422,085 4 327,980 3.4
UAE 379,852 3.6 324,872 3.4
Belgium 319,601 3 321,600 3.4
Turkey 331,915 3.1 304,380 3.2
Netherlands 352,777 3.3 293,778 3.41
Hong Kong 397,900 3.8 282,674 3
France 260,659 2.5 228,946 2.4
Saudi Arabia 135,919 1.3 169,618 1.8
South Africa 200,604 1.9 136,218 1.4
Canada 149,197 1.4 132,530 1.4
Portugal 150,139 1.4 113,480 1.2
Sri Lanka 127,023 1.2 105,405 1.1
South Korea 91,041 0.9 91,182 1
Australia 95,123 0.9 84,768 0.9
Rest World 1,376,857 13 1,318,458 13.8
Total 10,571,817 100 9,564,390 100
Source: APTMA.
13
two fiscal years. Their share in Pakistan’s total textile exports is 30.6 percent
and 7.1 percent respectively during fiscal year 2008-09. Germany and China are
the 3rd and 4th largest buyers of Pakistani textile and clothing exports having
5.7 percent and 4.8 percent share in total exports respectively. Then follow
Bangladesh, Spain, UAE, Belgium, Turkey, Netherlands, Hong Kong and
France. The remaining world has less than 2 percent contribution in Pakistan’s
total textile exports. The share of China, Bangladesh, Belgium, Turkey,
Netherlands and Saudi Arabia has slightly increased over the recent period. The
share of the remaining countries has either decreased or has been constant which
clearly shows Pakistan’s inability to expand its textile exports more than 50
percent of which remains tied to five countries only.
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Source: WTO.
14
3. LITERATURE REVIEW
A large body of empirical literature has examined the factors which
determine the supply and demand of manufactures in general and textiles in
particular. After the inception of WTO and reduction of quota’s and application
of Most Favoured Nation (MFN) status it has become an important area of
research. This section briefly reviews some relevant studies in this area:
Riedal (1988) examined simultaneously the demand and supply sides’
equations for quarterly data from 1972–84. The demand side parameters for
Hong Kong resemble that of other countries but the supply side determinants
vary from country to country according to domestic conditions such as industrial
policy and wage rate. Findings of new models strongly contradict the previous
consensus views and indicate that the volume of exports is determined by its
ability to compete in the world market on the basis of prices; the factor of world
income has but a minor effect on the export volume.
Amazonas and Barros (1996) test the demand and supply function for
Brazil’s manufacturing exports using the instrumental variable method of
Philips and Hansen (1990). The results show that income elasticity of demand is
low and insignificant which indicates that Brazil has to build its competitiveness
in the international market. The combined effect of subsidies and exchange rate
has been observed to be negative on exports. Industrial productivity is an
important determinant; it affects the competitiveness of manufacturing exports.
Muscatelli, et al. (1992) estimate price and income elasticity for Hong
Kong exports using ECM and modified OLS estimates. The results show that
both long-run price and income have significant effect on export demand. The
adoption of new production and marketing techniques can be beneficial for the
export growth of a country. The increase in the productive capacity of the
15
7
Ahmad (2000) and Atique and Ahmad (2003) also calculated REER in the similar way.
8
Atique and Ahmed (2003), See Appendix-3 for more details.
18
9
Dummy is introduced in supply side equation instead of demand side equation because only
USA and EU impose restrictions and manufacturers were producing under the pressure of trade
restrictions.
10
According to Muscateli (1992), normalisation problem can be resolved by incorporating
endogenity and serial correlation.
19
Kingdom, Canada, Italy, France, Japan, Spain and United Arab Emirates. The
country selection criteria is more than 1 percent share in Pakistan’s exports. The
data for GDP has been taken from the World Development Indicators (WDI).
The data for export prices, CPI and exchange rate has been taken from
International Financial Statistics (IFS). The data for textile wage rate has been
taken from the International Labour Organisation (ILO). The data for textile and
clothing exports have been taken from United Nations Commodity Trade
Statistics Database (UN COMTRADE). The data from the UN COMTRADE is
extracted according to SITC Rev. 1.
5. EMPIRICAL RESULTS
GMM estimates using lag explanatory variables as instruments for the
demand of textile and clothing exports are given in Table 8. The results for
Gross Domestic Product show that growth in the trading partners’ income has
the expected positive and significant impact on Pakistan’s exports’ demand
which is elastic with respect to the trading partners’ GDP in all cases except for
Japan, UK, and USA. The lowest value of income elasticity is for UK i.e. 0.84
while the highest is for Spain i.e. 1.91. Therefore, the result indicates that
improvement in world economic conditions will help to boost textile and
Table 8
GMM Estimates for the Demand Equation
Ln Xdt = α0 + α1 lnREERt + α2 lnWYt + ε
Trading Partners α0 α1 α2 R2
USA –4.67 1.11 0.93 0.95
(3.05)* (2.48)** (3.39)*
UK –3.55 1.18 0.84 0.86
(6.83)* (2.49)** (6.44)**
Canada –4.35 0.96 1.09 0.93
(6.50)* (6.63)* (9.58)*
Italy –2.73 0.88 1.23 0.93
(1.53) (2.27)** (9.48)*
France –4.13 0.86 1.08 0.94
(3.87)* (3.79)* (7.15)*
Japan –2.63 0.71 0.93 0.96
(6.83)* (3.83)* (9.44)*
Spain –5.24 1.37 1.91 0.96
(1.01) (2.78)* (2.51)**
Note: The t-ratios are given in parenthesis, (*), (**) and (***) represents 1 percent, 5 percent and 10
percent significance respectively.
X is Textile and Clothing Exports, REER represents Real Effective Exchange Rate and WY is
the Trading Partners Income.
20
clothing exports of Pakistan. Goldstein and Khan (1978) find positive and
significant income elasticity of exports demand for the eight trading partners; it
lies between 0.39 for Germany and 1.40 for France. Similarly, Virmani (1991)
has reported more elastic and significantly positive income elasticity of
manufacturing exports demand for India. Muscatelli, et al. (1992) have also
found world income to be an important determinant of exports demand for Hong
Kong. Rijesh (2007) shows significant and positive relationship between world
demand and India’s machine tools exports demand; here the reported coefficient
is less than unity. Income elasticity estimates obtained by Zada (2012) are very
close to our estimates, the coefficient ranges from 0.73–0.90.
The Real Effective Exchange Rate depicts variation in real exchange
rate. Textile and clothing exports’ demand is quite responsive to REER. The
estimated coefficients for Spain, UK and US are greater than unity, while the
rest are less than unity. Coefficients across the countries appear to have their
expected positive signs ranging from 0.71 to 1.37. The impact of REER is
larger for Spain i.e. 1.37 percent followed by UK 1.18 percent; the lowest is
0.71 percent for Japan. The REER elasticity of textile and clothing exports’
demand is 1.11 percent for USA, 0.96 percent for Canada and 0.88 percent for
Italy and 0.86 percent for France. The positive sign of devaluation coefficient
reflects improvement in the competitiveness of our textile and clothing
exports. The positive and significant coefficient indicates that real devaluation
of Pakistan rupee against all trading partner’s currencies leads to increase in
textile and clothing demand from Pakistan. The results indicate that the real
devaluation of rupee is very helpful in increasing the textile and clothing
exports. The significant and large coefficient of REER is also reported by
Goldar (1989) for India. The study finds devaluation an effective measure to
boost engineering exports demand from India. Virmani (1991) also finds
manufacturing exports demand for India relatively more responsive to
devaluation. Ahmad (2000) has observed the exports’ performance of
Bangladesh and has reported that real devaluation of domestic currency leads
to increase in the competitiveness of exports. It can be noted that their
estimates are very close to our estimates i.e. 0.96. Contrary to the findings of
the present study, Atique and Ahmad (2003) find significant and small
elasticity of devaluation for Pakistan’s exports demand, the size of the
coefficient is 0.39. In a similar way, Malik (2000) finds devaluation
insignificant and less effective to increase textile exports demand from
Pakistan. The textile and clothing exports’ demand from Pakistan is elastic to
change in prices; therefore, price effects have strong and important role in
boosting the exports’ demand.
The GMM estimates for the supply side equation are given in Table 9.
Relative prices have the expected positive and significant influence on the
textile and clothing exports to all trading partners, except Spain where they are
21
Table 9
GMM Estimates for the Supply Equation
S
lnX t = β0 + β1 ln RPTt + β2 ln Wt + β3 ln Yt + β4D + εt
Trading Partners β0 β1 β2 β3 β4 R2
USA –2.41 4.41 –0.60 1.07 –0.21 0.69
(1.24) (2.06)** (1.82)*** (2.59)** (0.82)
more responsive to change in real devaluation on demand side than the relative
prices on the supply side. The result shows that the textile and clothing exports
of Pakistan are more elastic to change in relative prices across countries. The
coefficient of the relative price variable is found to be greater than unity.
The highest relative price elasticity is 7.43 for Italy and the lowest is 2.19
for Spain. This shows that export prices have substantial role in determining the
exports supply as compared to the domestic prices of the exportable goods.
Therefore, increase in export prices11 compared to domestic prices will
encourage manufacturers to increase textile and clothing exports of Pakistan.
Zada (2012) also found similar results. Goldstein and Khan (1987) have
examined exports supply elasticities with respect to relative price for seven
European countries. Havrila and Gunawardana (2006) have estimated the
relative price elasticity for textile exports supply of Australia and report long run
elasticity of 1.83.
11
Exports price is used as a proxy for textile and clothing exports, see relative prices in
explanation of variables for more details.
22
The real wages of the textile sector12 seem to have negative impact on
supply of textiles and clothing exports to five out of seven trading partners;
however, coefficients for US, Canada and Spain are found significant at 10
percent and Atique and Ahmad (2003) have come up with the same results. The
size of the estimated coefficient is also small and this result implies that though
the supply of Pakistan’s textile and clothing exports increases with decrease in
real wages but it is not very responsive. It shows that decrease in real wages in
the textile sector without corresponding increase in productive capacity cannot
improve the performance of the same sector. It means cuts in real wage are not
effective in boosting textile and clothing exports.
Few estimates of exports supply elasticity with respect to real wages are
available in literature to compare the results of this study with. Muscatelli, et al.
(1992) have used the index of nominal wage of manufacturing sector and
estimated relatively large response of –1.48 for Hong Kong. Atique and Ahmad
(2003) have used wage rate per worker as a proxy for the cost of production.
They have obtained significant and negative exports supply (for Pakistan)
response with respect to wages of –0.70. This is very close to our results.
Amazonas and Barros (1993) report negative and significant response of
Brazilian manufacturing exports to change in real wage of –0.83.
The GDP figures of Pakistan are employed to explain the production
capacity of the domestic economy. This variable has the expected positive and
significant impact on exports to all trading partners. The range of elasticity is
0.72 (lowest) for France and 1.07 (highest) for USA. The results show that GDP
is an important determinant of this sector’s exports supply for Pakistan. Growth
in domestic economy will encourage manufacturers to produce and export
textiles and clothing products. Virmani (1991) reports significant and positive
relationship between GDP (manufacturing) and export supply of manufacturing
product for India, where the magnitude of coefficient is 0.75. In the same way,
Atique and Ahmad (2003) have computed income elasticity of exports supply
for Pakistan and have found significant and positive coefficient of 3.67. Zada
(2012) finds significant and positive income elasticity of exports supply for 11
trading partners, where the range of the coefficient is from 0.02 to 0.36.
The estimated coefficient of the dummy variable has an unexpected
negative sign for six out of eight trading partners. All coefficients are
insignificant except for Canada and Japan and these estimates are small except
for Japan. The response of Pakistan’s textile and clothing exports supply to the
liberalisation agreement (ATC) is not according to expectation. The trade in
textile and clothing sector was supposed to operate freely after 2005, but results
reveal a different story and indicate that trade liberalisation is unable to boost
the exports supply and may even worsen the performance. There are other
12
It is used to represent cost of textile and clothing production. See wage rate in explanation
of variables.
23
hurdles which lead to low textile and clothing exports performance; (i) After
removal of quantitative restriction, Pakistan has to face strict competition from
countries like China, South Korea and India in the form of quality and price; (ii)
supply side deficiencies i.e. technological backwardness and lack of skilled
labour force are responsible for less productive capacity. From policy point of
view appropriate steps were not taken to benefit from the abolition of the quota
restrictions regime.
The results for the textile and clothing exports demand and supply
equations are obtained by applying GMM and Empirical Bayesian techniques.
The results support that all techniques lead to almost the same findings. The real
effective exchange rate and GDP of trading partners have a positive effect on the
demand of Pakistan’s textiles and clothing exports. In respect of the demand for
textile and clothing exports, the REER and GDP of the trading partners have
long-run equilibrium relationship among them. On the supply side, the relative
prices and domestic production capacity have the positive and wage rate the
negative impact on textile and clothing exports’ supply. The results suggest that
the Empirical Bayesian is a better technique to estimate the demand and supply
of textiles and clothing exports of Pakistan. These results are in conformity with
most of the earlier findings for other developing countries in general and for
Pakistan in particular, as mentioned in the above discussion.
more than the domestic prices provides incentives to domestic producers. The
significant and negative magnitude of real wages represents that increase in cost
leads to decrease in exports supply. The significant and large income elasticity
on the supply side indicates that the domestic capacity of the economy plays an
important role in the supply of textile and clothing exports. The result reveals
that both demand and supply side factors play important role in the
determination of textile and clothing exports.
Textile and clothing exports from Pakistan remained stagnant during the
first five years of the Agreement of Textile and Clothing (ATC) 1994–2005,
after that there was a positive turn in exports growth. The change in composition
of textile and clothing exports from primary to manufactured products is
supported by several demand and supply side factors. Relative prices and
domestic capacity plays a significant role in explaining textile and clothing
behaviour on the supply side. On the other hand, world demand and real
devaluation are important determinants on the demand side. Textile and clothing
exports growth was not in line with world demand because of many restrictions
from developed countries.
The results of descriptive statistics given in the overview section suggest
that in addition to diversification of textile and clothing exports market, Pakistan
needs to improve its competitiveness in the international market which has
grown more competitive since the trade liberalisation regime of WTO. To
survive in this competitive environment producers need to adopt new techniques
for the production of high value added products i.e. readymade garments and
cloths. The result also supports that devaluation is helpful in the improvement of
long-run textile and clothing exports. Devaluation can be more effective when
combined with exports of high quality products and diversification of exports
markets.
On the supply side, significant and large magnitude of relative prices has
important implications. Price incentives encourage domestic producers to
increase exports supply. The composition of investment in textiles and clothing
indicates that the spinning sector holds major share in total investment and as a
result, the share of cotton yarn is equally high in production and exports. There
is need to focus on converting good quality yarn in the value added categories
i.e. cloth and readymade garments. The major share of fabrics is produced with
cotton in Pakistan but demand for man-made fibre is increasing at the
international level. Textiles and clothing producers should increase synthetic
fibre content in textiles and clothing production. The newly industrialised
countries (China, Hong Kong and South Korea) achieved high growth targets in
international market through relying more on domestic supply side factors. The
reduction in wage rate cannot entirely improve the production of textile and
clothing; producers should be provided incentives such as easy capital
availability.
25
It is clear from the analysis that the textile and clothing exports of
Pakistan have slightly increased over the study period but remain concentrated
in a few markets. The implication that comes out of the findings is that GDP has
great effect on the demand side and relative prices and domestic production
capacity on the supply side. Therefore, authorities should take account of these
factors while making decisions in this sector.
This study examines the determinants of overall textile and clothing
exports. Components of textile and clothing (raw cotton, cotton yarn, cotton
cloth, readymade garments, synthetic textile etc) exports are not considered
because of non-availability of data on each variable. For future research, this
study can be extended by taking account of all components of textile and
clothing.
26
Appendices
APPENDIX-1
APPENDIX 1A
Production and Exports of Cloth
Qty. in ‘x1000’ Sq. Mtrs
Non-mill Total Mill Sec. Non-Mill Sec. EXPORTS
Year Mill Sector Sector Production (% of Prod.) (% of prod.) Quantity % of Prod.
1972-73 588.61 649.5 1238.11 47.54 52.46 517.98 41.84
1973-74 592.17 1236.55 1828.72 32.38 67.62 353.02 19.3
1974-75 555.86 1271.22 1827.08 30.42 69.58 440.81 24.13
1975-76 520.44 982.92 1503.36 34.62 65.38 463.84 30.85
1976-77 408.29 1037.01 1445.3 28.25 71.75 416.84 28.84
1977-78 391.35 1181.72 1573.07 24.88 75.12 453.47 28.83
1978-79 339.35 1147.75 1487.1 22.82 77.18 531.53 35.74
1979-80 342.33 1377.69 1720.02 19.90 80.10 545.77 31.73
1980-81 307.89 1526.11 1834 16.79 83.21 500.9 27.31
1981-82 325.02 1875.42 2200.44 14.77 85.23 584.35 26.56
1982-83 335.54 1713.23 2048.77 16.38 83.62 605.33 29.55
1983-84 296.6 1869.38 2165.98 13.69 86.31 664.38 30.67
1984-85 271.83 1728.17 2000 13.59 86.41 687.62 34.38
1985-86 253.48 1731.92 1985.4 12.77 87.23 727.35 36.63
1986-87 238.17 1771.68 2009.85 11.85 88.15 693.42 34.5
1987-88 281.62 1949.2 2230.82 12.62 87.38 848.61 38.04
1988-89 269.86 1980.14 2250 11.99 88.01 845.33 37.57
1989-90 294.84 2439.93 2734.77 10.78 89.22 1017.87 37.22
1990-91 292.91 2561.09 2854 10.26 89.74 1056.53 37.02
1991-92 307.93 2931.06 3238.99 9.51 90.49 1196.12 36.93
1992-93 325.4 3034.6 3360 9.68 90.32 1127.58 33.56
1993-94 314.91 3063.09 3378 9.32 90.68 1046.79 30.99
1994-95 321.84 2778.91 3100.75 10.38 89.62 1160.66 37.43
1995-96 326.98 3379.02 3706 8.82 91.18 1323.09 35.7
1996-97 333.5 3447.7 3781.2 8.82 91.18 1257.43 33.25
1997-98 340.28 3573.42 3913.7 8.69 91.31 1271.27 32.48
1998-99 384.56 4002.23 4386.79 8.77 91.23 1355.17 30.89
1999-00 437.19 4549.97 4987.16 8.77 91.23 1574.88 31.58
2000-01 490.16 5101.24 5591.4 8.77 91.23 1736 31.05
2001-02 568.43 5084.66 5653.09 10.06 89.94 1957.35 34.62
2002-03 582.14 5068.38 5650.52 10.30 89.70 2005.38 35.49
2003-04 683.39 5051.9 6833.12 10.00 73.93 2412.87 35.31
2004-05 924.67 5556 6480.67 14.27 85.73 2751.56 42.46
2005-06 915.26 7609 8524.26 10.74 89.26 2633.98 30.9
2006-07 1012.92 7682 8694.92 11.65 88.35 2211.84 25.44
2007-08 1016.39 7889.05 9005.44 11.29 87.60 2035.14 22.6
2008-09 1019.68 7995.57 9015.26 11.31 88.69 1898.54 21.06
2009-10 1009.59 7940.18 8949.77 11.28 88.72 1787.66 19.97
Source: APTMA.
27
APPENDIX 1B
Category Wise Share in Total Cloth Production
Qty. in ‘000’ Sq. Mtrs
Dyed &
Blended, Grey Bleached Printed (%
Dyed & (%Share in (%Share (% Share Share in
Period Blended Grey Bleached Printed Total Prod.) in Prod.) in Prod.) Prod.)
1971-72 0 403,961 105,627 118,601 628,189 0 64.31 16.81 18.88
1972-73 0 383,318 115,110 90,178 588,606 0 65.12 19.56 15.32
1973-74 0 353,209 134,635 104,328 592,172 0 59.65 22.74 17.62
1974-75 0 342,992 107,806 105,057 555,855 0 61.71 19.39 18.90
1975-76 0 360,948 76,069 83,421 520,438 0 69.35 14.62 16.03
1976-77 3,428 279,961 57,004 67,894 408,287 0.84 68.57 13.96 16.63
1977-78 4,469 252,278 60,476 74,124 391,347 1.14 64.46 15.45 18.94
1978-79 10,229 246,682 38,719 43,722 339,352 3.01 72.69 11.41 12.88
1979-80 18,149 231,054 44,128 49,004 342,335 5.30 67.49 12.89 14.31
1980-81 28,279 191,263 39,527 48,813 307,882 9.19 62.12 12.84 15.85
1981-82 40,912 197,433 33,485 53,191 325,021 12.59 60.74 10.30 16.37
1982-83 38,397 175,801 53,622 67,717 335,537 11.44 52.39 15.98 20.18
1983-84 36,632 152,465 47,766 59,733 296,596 12.35 51.40 16.10 20.14
1984-85 28,855 148,672 39,424 54,876 271,827 10.62 54.69 14.50 20.19
1985-86 31,870 142,883 29,576 49,151 253,480 12.57 56.37 11.67 19.39
1986-87 54,028 115,967 23,384 44,789 238,168 22.68 48.69 9.82 18.81
1987-88 61,136 142,444 20,891 57,150 281,621 21.71 50.58 7.42 20.29
1988-89 49,185 147,666 19,061 53,950 269,862 18.23 54.72 7.06 19.99
1989-90 47,223 174,565 19,442 53,609 294,839 16.02 59.21 6.59 18.18
1990-91 57,534 160,935 16,613 57,829 292,911 19.64 54.94 5.67 19.74
1991-92 66,256 158,790 18,345 64,542 307,933 21.52 51.57 5.96 20.96
1992-93 67,344 163,213 20,363 74,476 325,396 20.70 50.16 6.26 22.89
1993-94 59,835 170,032 15,482 69,565 314,914 19.00 53.99 4.92 22.09
1994-95 51,907 180,810 12,008 77,116 321,841 16.13 56.18 3.73 23.96
1995-96 61,293 191,492 13,110 61,086 326,981 18.75 58.56 4.01 18.68
1996-97 57,198 194,420 11,935 69,942 333,495 17.15 58.30 3.58 20.97
1997-98 56,478 206,254 13,032 64,516 340,280 16.60 60.61 3.83 18.96
1998-99 64,799 195,687 25,722 98,353 384,561 16.85 50.89 6.69 25.58
1999-00 60,607 263,593 11,064 101,926 437,190 13.86 60.29 2.53 23.31
2000-01 67,474 277,931 19,939 124,820 490,164 13.77 56.70 4.07 25.46
2001-02 77,039 317,247 18,281 155,869 568,436 13.55 55.81 3.22 27.42
2002-03 92,612 295,791 32,227 161,515 582,145 15.91 50.81 5.54 27.74
2003-04 101,687 332,361 43,841 205,503 683,392 14.88 48.63 6.42 30.07
2004-05 51,453 498,095 82,381 292,743 924,672 5.56 53.87 8.91 31.66
2005-06 52,273 504,899 78,354 279,730 915,256 5.71 55.16 8.56 30.56
2006-07 61,100 582,819 71,681 297,318 1,012,918 6.03 57.54 7.08 29.35
2007-08 54,737 561,695 73,311 326,647 1,016,390 5.39 55.26 7.21 32.14
2008-09 56,093 553,551 78,201 331,838 1,019,683 5.50 54.29 7.67 32.54
2009-10 59,441 566,020 86,127 297,999 1,009,587 5.89 56.06 8.53 29.52
Source: APTMA.
28
APPENDIX 1C
Consumption of Cotton and MMF in Textile Production
(Fig. in ‘000’ Kgs)
Raw Material Growth % % age of Total
Period Cotton Fibre Total Cotton Fibre Cotton Fibre
1972-73 463118 N.A 463118 14 N/A 100 N/A
1973-74 475348 N.A 475348 3 N/A 100 N/A
1974-75 420608 N.A 420608 -12 N/A 100 N/A
1975-76 419735 N.A 419735 0 N/A 100 N/A
1976-77 343194 N.A 343194 -18 N/A 100 N/A
1977-78 355986 N.A 355986 4 N/A 100 N/A
1978-79 387581 N.A 387581 9 N/A 100 N/A
1979-80 428554 NA 428554 11 N/A 100 N/A
1980-81 407523 37088 444611 -5 N/A 92 8
1981-82 459,459 41,550 501,009 13 12 92 8
1982-83 478,716 37,983 516,699 4 -9 93 7
1983-84 457,629 48,829 506,458 -4 29 90 10
1984-85 459,394 52,237 511,631 0 7 90 10
1985-86 500,065 58,534 558,599 9 12 90 10
1986-87 634,886 62,833 697,719 27 7 90 10
1987-88 712,456 67,282 779,738 12 7 91 9
1988-89 809,978 69,256 879,234 14 3 92 8
1989-90 998,447 71,904 1,070,351 23 4 93 7
1990-91 1,128,978 85,560 1,214,538 13 19 93 7
1991-92 1,257,399 105,775 1,363,174 11 24 92 8
1992-93 1,318,892 125,525 1,444,417 5 19 91 9
1993-94 1,511,610 182,077 1,693,687 15 45 89 11
1994-95 1,412,732 192,152 1,604,884 -7 6 88 12
1995-96 1,509,955 192,691 1,702,646 7 0 89 11
1996-97 1,444,368 236,692 1,681,060 -4 23 86 14
1997-98 1,471,169 318,923 1,790,092 2 35 82 18
1998-99 1,441,923 407,686 1,849,609 -2 28 78 22
1999-00 1,566,348 404,008 1,970,356 9 -1 79 21
2000-01 1,673,280 405,038 2,078,318 7 0 81 19
2001-02 1,755,669 409,557 2,165,226 5 1 81 19
2002-03 1,943,197 449,424 2,392,621 11 10 81 19
2003-04 1,938,678 468,984 2,407,662 0 4 81 19
2004-05 2,099,380 488,804 2,588,184 8 4 81 19
2005-06 2,407,560 525,000 2,932,560 15 7 82 18
2006-07 2,563,510 580,000 3,143,510 6 10 82 18
2007-08 2,521,170 638,000 3,159,170 -2 10 80 20
2008-09 2,519,184 676,464 3,195,648 -0.1 6 79 21
2009-10 2,401,840 970,524 3,372,364 -4.7 43 71 29
Source: APTMA.
APPENDIX-2
Calculation of Real Effective Exchange Rate
α i Eit Pit*
REERit =
Pj
Here, REER shows the bilateral real exchange rate. Eit is the nominal
exchange rate between country i and Pakistan currency which has been taken
29
from various issues of Economic Survey. αi stands for trade weights and
represents the share of trading partner exports in total textile and clothing
exports of Pakistan. Pit* is the Whole Sale Price Index of partner I; it is used here
to represent the price of tradable commodities. Pj is Consumer Price Index of
home country (Pakistan), it represents the price of non-tradable goods.
APPENDIX-3
Share of Textile
Exports in Total
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