The Influence of Competitiveness, Efficiency and Profitableness on Economic
Growth in Garments Manufacturing Sector
Authors: Daniela SCHOPPMEYER, PhD.Student, AES Bucharest
Abstract
In this paper we will study the influence of the competitiveness, the efficiency and the
profitableness on economic growth in garments manufacturing sector. This is a very important
chapter of the Romanian National Export Strategy which was first developed for 2004-2009 and
now is in process for 2010-2014. Out of the several sectors that the government picked to be a
part of this program, we have picked the garments sector. The reason we have picked this sector is
that Romania has tradition in garments; it is developed technologically, and was number one
producer in Europe from 1998 until 2004. Although some may view strategic plans useless, the
process is vital. It is only with this process businesses can examine their priorities, observe the
lacking production and marketing capabilities and set policies and practices. The garments sector in
Romania is no different than those of many developing countries. Enterprises are dependent on the
lohn system of production, which means that the foreign buyer delivers all raw materials to the
producer, who provides labour and workplace, after which the buyer re-imports the finished
merchandise. Consequently, the enterprises operating with this system do not build their strategic
and marketing competencies. This naturally creates a volatile situation sensitive to currency
fluctuations, and shifts in markets. There are however exceptions. The analysis of this competence
in Romania is therefore ananalysis of how many of the managers are willing to get away from the
lohnsystem.
A concise SWOT analyses in garment industry would underline the following points.
Strengths: it is a viable industry, its products are easy sold due to vital and fashion necessities of
people, it detains a stable and well trained labour force, it require slow costs for modernization, it is
very flexible and adaptable to changes. Weaknesses: no domestic raw materials available, lack of
investment funds, it doesn't have tradition in design and there are no internationally recognized
design schools in order to create successful brands, no managerial capabilities in order to move
away from the lohn system Opportunities: are tightly related to the positioning of our country and
the high adaptability of Romanian companies. Having a strategic position on the continent, the
Romanian companies can attract the European customers with very tight deadlines and the
possibility of manufacturing small orders inspire of the offers that other world garments
manufacturing companies have. Threats: lack of managerial competencies and professionalism in
doing international business can make the buyers pick a more competitive supplier.
It can be said that inspite of its apparent benefits, the lohn system negatively influences the
managerial competencies of Romanian businesses in the area of strategy design and its
implementation.
In conclusion, we will introduce several steps to be made by Romanian garments companies in
order to develop the sector but also the governmental support that these companies would need in
order to reach their strategic objectives.
Keywords: competitiveness, efficiency, profitableness, garments
JEL Classification: D24, D40
568
Influenţa competitivităţii, a eficienţei şi a rentabilităţii asupra creşterii
economice în sectorul de confecţii
Autor: Daniela SCHOPPMEYER, Doctorand ASEBucuresti
Rezumat
In cadrul aceastei lucrari vom studia influenta competitivitatii, eficientei si rentabilitatiia supra
cresterii economice. Acest subiect reprezinta un capitol foarte important al Strategiei Nationale de
Export a Romaniei care a fost intai elaborata pentru perioada 2004-2009 si este in curs de elaborare
pentru 2010-2014. Dintr-o serie de sectoare pe care guvernul le-a selectat pentru a fi parte
integranta in acest program, am selectat sectorul de confectii. Tara noastra are o traditie indelungata
in confectii, este foarte dezvoltata din punct de vedere tehnologic si a fost producatorul numarul unu
in Europa intre 1998 si 2004.Chiar daca unii considera inutila planificarea strategica, procesul este
vital. Doar prin intermediul acestui proces firmele isi pot examina prioritatile, pot observa lipsa
capabilitatii de productie si a marketing-ului pentru a-si stabili politici si proceduri.Sectorul de
confectii din Romania nu este diferit de al altor tari in curs de dezvoltare. Intreprinderile sunt
dependente de sistemul de productie in lohn: clientul strain livreaza toate materiile prime
producatorului care ii asigura forta de munca, spatiul de productie si tehnologia necesara, dupa care
cumparatorul importa produsele finite. In consecinta,companiile care lucreaza in acest sistem nu siau construit competente in marketing. Acest fapt creaza in mod natural o situatie volatila sensibila la
diferentele de curs valutar si schimbarea pietelor. Exista totusi si exceptii. In Romania analiza
acestei competente este echivalenta cu analiza problemei: “cati manageri sunt dispusi sa iasa din
acest sistem”.O succinta analiza SWOT a sectorului romanesc de confectii o redam in punctele
urmatoare.Punctele forte ale industriei de confectii sunt: este o industrie viabila, produsele sale sunt
usor de comercializat datorita nevoilor vitale si de moda ale oamenilor, forta de munca este stabila
si calificata, necesita costuri relativ mici pentru modernizare, este foarte flexibila si se poate adapta
usor schimbarilor, etc.Punctele slabe ale industriei de confectii sunt: lipsa industriei primare si deci
a materiilor prime, lipsa investitiilor permanente, nu exista o traditie in design si nici nu exista scoli
de design recunoscute pe plan international, lipsa capacitatii manageriale de a se departa de sistemul
lohn, etc.Oportunitatile industriei sunt legate de pozitionarea teritoariala si adaptabilitatea firmelor
romanesti. Avand o pozitie strategica pe continent, firmele romanesti isi pot atrage clientii europeni
prin termene de livrare foarte scurte precum si prin posibilitatea de a elabora comenzi reduse
dimensional, spre deosebire de alte firme de profil de pe plan mondial.Amenintarile pe care le au
firmele romanesti sunt strict legate de competenta manageriala a producatorilor precum si de
capabilitatea acestora de a face afaceri in mediu international, fapte ce pot determina clientii sa-si
aleaga noi producatori mai competitivi.
Se poate spune ca in ciuda beneficiilor aparente, sistemul productiei in lohn influenteaza negativ
competenta manageriala a intreprinderilor romanesti in ceea ce priveste elaborarea si aplicarea unei
strategii.In concluzie vom prezenta cativa pasi ce trebuie facuti de catre intreprinderi pentru a
dezvolta sectorul de confectii, precum si sprijinul guvernamental de care acestea ar avea nevoie
pentru a-si atinge obiectivele strategice.
Cuvinte cheie: competitivitate, eficienta, rentabilitate, confectii
Clasificare JEL: D24, D40
After more than forty years of import quotas, the textile and clothing sector became subject
to the general rules of the General Agreement on Tariffs and Trade from 1 January, 2005.
Liberalization has been controversial because both textiles and clothing contribute to employment
in developed countries, particularly in regions where alternative jobs may be difficult to find. In the
European Union, for example, the sector is dominated by small and medium-sized enterprises
concentrated in a number of regions that are highly dependent on this sector (Commission of the
569
European Communities, 2003). The clothing industry is labour-intensive and it offers entry-level
jobs for unskilled labour in developed as well as developing countries. Job creation in the sector has
been particularly strong for women in poor countries, who previously had no income opportunities
other than the household. Moreover, it is a sector where relatively modern technology can be
adopted even in poor countries at relatively low investment costs. These technological features of
the industry have made it suitable as the first rung on the industrialization ladder in poor countries,
some of which have experienced a very high output growth rate in the sector (e.g. Bangladesh, Sri
Lanka, Vietnam and Mauritius).
At the same time, the textile and clothing industry has high-value added segments where
design, research and development are important competitive factors. The high end of the fashion
industry uses human capital intensively in design and marketing. The same applies to market
segments such as sportswear where both design and material technology are important. Finally,
research and development is important in industrial textiles where, again, material technology is an
important competitive factor.
The garments sector is both a labour-intensive, low wage industry and a dynamic, innovative
sector, depending on which market segments one focuses upon. In the high-quality fashion market,
the industry is characterized by modern technology, relatively well-paid workers and designers and
a high degree of flexibility. The competitive advantage of firms in this market segment is related to
the ability to produce designs that capture tastes and preferences, and even better – influence such
tastes and preferences – in addition to cost effectiveness. The core functions of firms servicing this
market segment are largely located in developed countries and often in limited geographical areas
or clusters within these countries.
The textiles and clothing sectors can be seen as a supply chain consisting of a number of
discrete activities. Increasingly the supply chain from sourcing of raw materials via design and
production to distribution and marketing is being organized as an integrated production network
where the production is sliced into specialized activities and each activity is located where it can
contribute the most to the value of the end product. When the location decision of each activity is
being made, costs, quality, reliability of delivery, access to quality inputs and transport and
transaction costs are important variables.
The basic production technology of the apparel industry has not changed much over the past
century, and is characterized by the progressive bundle system. Work is organized such that each
worker is specialized in one or a few operations. The fabric is first cut and then grouped by parts of
the garment, tied into bundles (pre-assembly) and then sewed together. The individual sewing tasks
are organized in a systematic fashion and specialized sewing machines have been developed for the
individual tasks. A worker receives a bundle of unfinished garments, performs her single task and
places the bundle in a buffer. A buffer of about one day's work has been common at each operation.
It takes about 40 operations to complete a pair of trousers, which implies that there is about 40 days
of in-process inventory. For men's jackets, however, it takes as much as 100 operations. Although a
number of improvements in terms of systematizing the operations and reducing the time at each
individual operation has taken place over time, the basic system has remained the same. One
explanation for this is that technology changes cannot be implemented in a partial fashion involving
only a few operations. This would unbalance the system and any major technological change
therefore needs to involve the entire system.
In this paper we will study the influence of the competitiveness, the efficiency and the
profitableness on economic growth in garments manufacturing sector. This is a very important
chapter of the Romanian National Export Strategy which was first developed for 2004-2009 and
now is in process for 2010-2014. Out of the several sectors that the government picked to be a part
of this program, we have picked the garments sector. The reason we have picked this sector is that
Romania has tradition in garments, it is developed technologically, and was number one producer in
570
Europe from 1998 until 2004.
Before the revolution Romanian garment industry was set up with the aim of achieving
national industrialization. Evidently, before 1990, the textile and garment industries were the
country's second largest employer. The garment industry was characterized by large vertically
integrated production facilities which today we can still see the remains and affects of them
especially in Bucharest.
Before the revolution all the exports were controlled by a department called CONFEX. By
controlling we mean to handle all contacts with buyers from overseas and when and where to
produce. In other words, total control of the total buying and production process.
However with the end of Communist regime CONFEX had no longer existed thus smaller
units were created by means of privatization.
However the transformation from being a large vertical garment factory to smaller units was
not easy. Today we can still see remnants of the large factories which are large, unproductive, with
surplus capacity old machinery and usually not fully functioning do still exist.
Most of the orders placed utilize what is called a "Lohn system" (CM- cut and make or
CMT- cut, make and trims) where the buyer delivers all materials to the producer and the
manufacturer provides the labour.
Unfortunately this system has delivered the biggest damage to the Romanian garment
industry and to this day it still continues. Maybe at that time, this could have been seen by a factory
as a system that they can afford to open to the export markets where the risks were low, foreign
currency was flowing and capital investments could be afforded.
The “Lohn” (meaning employee salary in German language) production had an extremely
negative effect on the Romanian garment industry and still continues to dominate a lot of
manufacturers. It appears that not a single fabric mill survived the privatization period. Most of
Romanian garments factories do not know how to source fabrics or trims, and are extremely limited
in their design abilities. A big part of them have not been attending trade shows and are not seeking
any additional customers.
The garments sector in Romania is no different than those of many developing countries.
Enterprises are dependent on the “lohn system” of production, which means that the foreign buyer
delivers all raw materials to the producer, who provides labour and workplace, after which the
buyer re-imports the finished merchandise. Consequently, the enterprises operating with this system
do not build their strategic and marketing competencies. This naturally creates a volatile situation
sensitive to currency fluctuations and shifts in markets. There are however exceptions.
Romania, is one of the largest supplier of clothing to EU, has direct competition at the
moment from Bulgaria, Moldavia, and Ukraine.
We have established a list of threats to Romanian garment industry. Main problems of the
producers are:





China’s entrance into the EU markets
Competition from other Eastern European countries
Currency fluctuations
Labour migration – Labour Shortage
Financing – Lack of SME support by the Banks
In order to understand whether this is a valid argument we decided to look at different
factors determining the costs.
Romania’s entry to the European Union brought a big increase to the labour costs due to
compliance with the EU mandates.
A recent statistics shows that in August 2007, average salary in the garment industry is
EUR190. This is a high cost considering all other competitors in the region.
571
However based on the same statistics Romania’s drop in garment exports to the EU
countries by 9.4% (from 2005 to 2006) can not be attributed to other East European countries but to
the sourcing from Asia.
Romanian garment manufacturers second most complaint was growing shortage of labour.
This also can be validated since the rate of unemployment fell from 8.3% in 2002 to 5.1% in July
2006 and 2.4% in the beginning of 2008. This number is also highly influenced by the fact that
around 2 million Romanians already work in Italy and Spain.
It is said that by 2013 the Romanian currency will be switched to Euro. This could be
construed as the element to eliminate currency fluctuation. As with any exporting countries
Romania has been going on through the gyrations of currency fluctuations.
A concise SWOT analyses in garment industry would underline the following points.
Strengths: it is a viable industry, its products are easy sold due to vital and fashion
necessities of people, it detains a stable and well trained labour force, it requires low costs for
modernization, it is very flexible and adaptable to changes.
Weaknesses: no domestic raw materials available, lack of investment funds, it doesn't have
tradition in design and there are no internationally recognized design schools in order to create
successful brands, no managerial capabilities in order to move away from the “lohn system”.
Opportunities: are tightly related to the positioning of our country and the high adaptability
of Romanian companies. Having a strategic position on the continent, the Romanian companies can
attract the European customers with very tight deadlines and the possibility of manufacturing small
orders in spite of the offers that other world garments manufacturing companies have.
Threats: lack of managerial competencies and professionalism in doing international
business can make the buyers pick a more competitive supplier.
In order to evaluate correctly Romania's potential in garments industry we will introduce the
term of Trade Performance Index.
Trade Performance Index (TPI) has the aim of assessing and monitoring the multi-faceted
dimensions of export performance and competitiveness by sector and by county. At present, the TPI
covers 184 countries and 14 different export sectors. The index calculates the level of
competitiveness and diversification of a particular export sector using comparisons with other
countries. In particular, it brings out gains and losses in world market shares and sheds light on the
factors causing these changes. Moreover, it monitors the evolution of export diversification for
products and markets. The TPI is limited by its purely quantitative approach, although it does
provide a systematic overview of sectoral export performance and comparative and competitive
advantages. For each country and each sector, the TPI provides three types of indicators: a general
profile, a country position for the latest available year and changes in export performance in recent
years. Altogether, the TPI makes use of around two dozen of quantitative performance indicators.
For ease of reference, these indicators are presented in absolute terms and, in addition, ranked
among the 184 countries covered by the TPI. Moreover, one composite ranking referring to the
overall position of a country and sector was calculated by International Trade Centre (ITC) experts.
This composite ranking is based on five criteria, namely the value of net exports, per capita exports,
the world market share, the diversification of products, and the diversification of markets.
The trade performance of individual countries tends to be a good indicator of economic
performance since well performing countries tend to record higher rates of GDP growth. The
majority of developing countries have joined the World Trade Organization (WTO) and have taken
initiatives aimed at opening their economies. Nevertheless, the outcome has not always been
572
systematically positive with export performance sometimes remaining disappointing. It is difficult
to establish an all embracing definition of successful trade performance. Trade champions contrast
with certain specialised exporters that suffer from a deterioration in their terms of trade. For
example, some developing countries record high growth rates by specialising in niche markets and
concentrating their export markets, while other developing countries record more moderate rates of
growth with a well diversified array of products and partner countries. In other cases, successful
performance is the result of a favourable product or market penetration since the beginning.
Successful performance can also be gauged in terms of a country’s ability to adapt its export profile
to changing patterns of world demand. The last approach is the most dynamic and demand-driven
trade policy stance.
The Trade Performance Index (TPI thereafter) designed by ITC aims to tackle the complex
and multidimensional nature of trade patterns. This index is computed using the world’s largest
trade database, COMTRADE (of the United Nations Statistics Division), covering 184 countries,
where more than 95% of world trade in 5,000 products is reported at the 6-digit level of the
Harmonized System (HS). Since COMTRADE captures around 95 % of world trade, the TPI is
calculated not only for countries that report their own trade data, but also for over one hundred
primarily low-income countries that do not report national trade statistics. Given that such an
amount of information would be overwhelming to the final user, products are grouped into 14
sectors. Calculations are made at the product level and results are presented at the sectoral level and
for the economy as a whole. For each country and each sector, the TPI provides a general profile,
indicators on a country’s position and indicators on changes in export performance in recent years.
The rest of the paper covers the objectives, methodology and results of the TPI framework.
The motivation for developing the Trade Performance Index was because generally, trade
performance is characterised by rough indicators, such as the level of openness (total trade in goods
and services divided by GDP) or growth of exports over a given period (such as the World Bank’s
World Development Indicators). Recent research on the relationship between trade and growth
suggests that openness alone is not a sufficient criteria for determining high levels of growth. Other
factors, such as the type of product available, the level of market and economic diversification, the
positioning on quality ladders, are also significant in explaining growth. In addition, it is important
to determine the reasons for country differences in export growth and to determine the redistributive
process of market shares among competitors. Departing from the rough indicators referred to above,
microeconomic and generally qualitative indicators are used to characterise the competitiveness of
nations. In this light, the “Microeconomic index of competitiveness” (Porter and Christensen,
1999), is based on the micro-foundations of a country’s competitiveness. Launched in 1998 as part
of the Global Competitiveness Report, this index is based on a survey of some 4,000 businessmen
and government officials in 58 countries, including OECD countries. Regressing income per capita
on this index explains more than 80% of the variance of income in the sample. A quantitative
method was developed in order to complement the qualitative approach, which may be criticised on
the ground of being limited to a small number of developing countries. It appears that the relative
position of a country or product on the international market, and its development over time, is a
good indicator of competitiveness. Trade statistics capture these changes. Trade statistics have the
advantage of being available for a substantial number of countries. For those countries which do not
report trade statistics, their trade profile can be (partially) completed by using mirror statistics.
Lastly, trade data is broken down at the industry and product levels, which provides a disaggregated
insight into trade performances. On this basis, developing countries can be ranked according to their
trade performance, based on various criteria. A ranking can be provided by country, sector, or a
combination of different criteria. It must be stressed that the performance of individual countries
cannot be determined on the basis of a restricted sample of countries or products. The derivation of
the relative export performance is achieved by including a significant number of countries, together
with a detailed product breakdown.
573
For each country and each sector, the TPI provides indicators on a country’s general profile,
on a country’s position and on the decomposition of the country’s change in world market share.
Altogether, the TPI consists of 22 quantitative indicators of trade performance. For ease of
reference, these indicators are presented in absolute terms and, in addition, combined to form a
ranking among the countries. All this information is grouped under three categories referring to
“general profile”, “current performance” and “decomposition of changes in trade performance”, as
illustrated in Table 1.
Table 1: Groups of indicators used
Current performance
General profile
(Indicators used for the
computation of the composite
index)
Decomposition of changes in
world
market share since 2001
P1. Value of net exports
P2. Per capita exports
P3. Share in world market
P4. Product diversification
and concentration
P5. Market diversification
and concentration
C1. Relative change of world
market share
Decomposed into:
(C1a) Competitiveness effect
(C1b) Initial geographic
specialisation
(C1c) Initial product
specialisation
(C1d) Adaptation effect
G1. Value of exports
G2. Trend growth of exports,
since 2001
G3. Share in national exports
G4. Share in national imports
G5. Growth in per capita
exports since 2001
G6. Level in relative unit values
G7. Matching of dynamics of
world demand since 2001
G8. Change of world market
share in % points, since 2001
The raw trade data using for calculating the indicators are defined at the 6-digit level of the
Harmonized System, 1996 edition, which includes more than 5000 product items. The data are
extracted from COMTRADE (http://comtrade.un.org), the United Nations Commodity Trade
Statistics Database, maintained by the Statistics Division of the UN.
Around 100 countries have reported their trade data systematically over the 2001-2005
period in the 1996 edition of the HS. For the other countries, we are using mirror estimates, which
are derived from partner countries statistics. Since COMTRADE captures around 95 % of world
trade, mirror estimates give usually gives fairly reliable results.
This section examines the rationale and the calculation of each indicator entering in the TPI.
General profile indicators, position-related indicators and change-related indicators are surveyed
respectively. All indicators are calculated for each of the 14 sectors at the product level. Original
data used in the computation is at the 6-digit level of the HS nomenclature, corresponding to more
than 5,000 products as a whole.
P1- Value of net exports: Net exports are defined as exports less imports. A country's net
exports are a reliable indicator of its position on the world market for two reasons. Firstly, net
exports eliminate re-exports, which would otherwise introduce a bias into the raw data. Secondly,
the indicator takes into account the international division of production processes, since a large part
of imported intermediate products found within exports usually belong to the same sector. Hence,
net exports provide a very simple but reliable correction for dealing with the globalisation of
production processes and the induced vertical specialisation of countries at various stages of
production.
P2- Per capita exports: The value of per capita exports indicates the level of outward looking
of a country and the extent to which a country’s population produces for the world market.
P3- Share in world market (percentage share of world exports): the world market share for a
specific country is the ratio of total country exports to total world exports.
574
P4- Product diversification: diversification, measured through exports, is a good indicator of
production structures and industry’s development level. Diversification limits the dependence on a
small number of products and hence reduces a country’s vulnerability to industry-specific external
shocks.
In order to capture the degree of product diversification, two separate indicators are
calculated: the equivalent number of products and the spread. The spread is the inverse of the
corresponding concentration. The equivalent number (EN=1/Herfindal), is a theoretical value which
represents the number of markets of identical size that would lead to the degree of export
concentration exactly equal to the observed one. Because this indicator is not highly sensitive to
activities of relatively weak importance, it is a measurement that is suited to sectoral studies. We
start by presenting these indicators and then turn to an example illustrating the value added of
combining the two indicators.
Calculating product differentiation by means of the equivalent number distinguishes for each
country the equivalent number of exported goods of equal importance (either within each sector or
in the whole national economy) leading to the same concentration of exports. The increase in rank
is a function of the increase in the level of diversification (both for products and markets). The
larger the index value, the greater the diversification of exports, and consequently the better the
ranking.
The spread index complements the equivalent number. Spread indices measure the
dispersion between the highest and lowest value in a given statistical series. They are calculated
using a weighted standard error. The spread index for products calculates for each country the
distribution of export products and compares it to the average export value. The greater the
distribution (i.e. spread) of exports from a country as compared to the average, the higher the value
of the index.
In technical terms, the equivalent number (for products) is calculated as in equation (2).
1
t
NE

icl
2
n
t
X
 (2)
i.k

t 

X
i.cl
k
1
with:
X it.k the export of product k by country i at year t .
X it.cl country i exports of all products belonging to the cluster cl at year t .
Xit.k
t
i
k
Xit.cl the export of product by country at year .
Turning to the index of weighted spread, equation (3) indicates that the standard deviation
divided by he number of products times the average value of exports for individual products has
been used.



t
Scl 



with:

X X  

NX 

2
cl
k1
t
i.k
t
i.cl
t
i.cl

 (3)
X it.k country i exports of product k to market i in year t .
X it.cl the average value of country i exports in year t for the cluster cl .
Xit.k Xit.cl the deviation to the average of product k in cluster cl for country i .


575
2
t
i.cl
X X  the standard deviation.

cl
k
1
t
i.k
t
cl
S the weighted spread.
P5- Diversification of markets: diversifying partner countries reduces a country’s
dependence on a small number of export markets and hence the vulnerability to shocks within
destination countries. In order to capture the degree of market diversification, the same two
complementary indicators referred to above are used: the equivalent number of markets and the
spread.
The equivalent number used for calculating market diversification (equation 4) distinguishes
for each country, the number of partner countries weighed according to their importance. The
increase in rank is a function of the increase in the level of diversification of markets. The bigger
the index value, the greater the diversification of markets and consequently the better the ranking.
t
NE
i 
1
2
X
 (4)

t 



X
i.cl
k
1
with:
p
t
ijcl
t
X ijcl
country i exports of all products belonging to the cluster cl to country t in year t .
X it.cl country i total exports of all products belonging to the cluster cl .
t
Xijcl
j
i
Xit.cl the share of market in country total exports of products belonging to the
cluster cl .
Spread indices measure the existing dispersion between the highest and lowest value of a
given statistical series.
They are calculated using the weighted standard error (equation 5). The spread index for
markets compares for each country, the share of its exports directed to different partner countries
with the average export value. The greater the dispersion of exports from this country (i.e. the
greater the spread) as compared to the average, the higher the value of the index.
Concerning positions, the ranking of the 184 countries is a function of the degree of diffusion of
exported products (of a country’s exports to partner countries). The smaller the index, the more
exported products are evenly distributed (amongst partner countries) and the better the ranking.
2
 p
t
t
 Xijcl

Xipcl


j

1
Stpcl
 (5)
t
N Xipcl









with:

t
X ijcl
country i total exports to market j in cluster cl in year t .
t
X ipcl
country i average export to the p markets of products belonging to the cluster cl in
year t
2
t
ipcl
X X  the standard deviation.

p
j
1
t
ijcl
576
In addition to these indicators, the TPI includes a composite index CI  , which is based on
a simple average of the five rankings of indicators P1 to P5, described previously.
The composite index reflects the position of a country in a given sector for a given year, in
terms of trade performance. Changes over time of this position reflect improvements or
deterioration in trade performance of the country under analysis.
A second set of indicators aims at giving the general profile for the country considered.
However, these indicators are not used in the calculation of the final ranking provided by the TPI, as
already mentioned.
G1- Value of exports: Value of total country exports by sector is given in million of US$ for
the current year.
G2- Trend of exports: Average per annum growth of export values since the year 2001.
G3 (G4)- Share in national exports (imports): This refers to the share of exports (imports) by
sector in relation to total country exports (imports).
G5- Change in per capita exports: The level of exports is determined by the demand for a
country’s products on world markets and a country’s ability to satisfy that demand, which can be
related to its size. Hence, the value of per capita exports shows how outward looking is a country,
and the extent to which the population produces for the world market. The change in per capita
exports reflects changes in a country’s outward looking stance and performance for the group of
products considered.
G6- Relative unit value: The RUV of each sector is calculated as the ratio of the average unit
value of exports for a country to the world average unit value. The reference point or average
relative unit value is 1 (the unit value in the targeted country equals the unit value in the world
market). If the RUV is below (above) 1, then the country exports its product at a lower (higher)
price than the world average unit price.
Traditionally, the comparison of unit values for homogeneous products gives an indication
of exporters’ relative prices. However, according to the new theories of international trade, products
are differentiated by quality, which is often reflected by differences in price. Accordingly, prices are
considered as an indirect indicator of the quality of differentiated products: assuming that a
consumer has access to product information, two products of different quality cannot be sold at the
same price. However, since prices are not available for individual products, or even for industries,
unit values (values divided by quantities) are taken as proxies for prices. Higher unit values are
considered as reflecting a higher quality, other things being equal, and not as an indication of poor
price competitiveness.
G7- Adaptation to world demand: this index is calculated with a view to ranking countries
according to their ability to adapt to the dynamics of world demand. It is based on Spearman’s rank
correlation between the ranking share of the exporting countries’ export products in its total exports,
and the rank of growth trends in worldwide exports of those products.
Each country is given a correlation index that takes a value between 1 and –1. A value of 1 (1) indicates that the relative importance of a country’s exported goods is in full accordance
(discordance) with the ranking of world export growth rates for the same goods. The country
ranking is dependent on the rank correlation index. The closer the index is to 1, the better the
country ranking under analysis.
G8- Change of world market share (in % points) since 2001: The change (variation over
time) in a country’s world market share is the difference in the world market share between time 0
and time t. If it is positive, country i has increased its world market share.
In addition to the general profile indicators, we also provide detailed figures on the decomposition
of the relative change in world market share in different effects. The decomposition of the change in
the world market share provides information on the competitiveness of the country considered. The
market share variation can be tabulated as the simple average of the rankings according to four
criteria: competitiveness, initial geographic specialisation, initial product specialisation and
responsiveness to changes in world demand. These indicators are calculated by decomposing
changes in a country’s market share in elementary markets.
3
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In the following table, we will calculate the TPI for the year 2006 in the Romanian garments
manufacturing industry.
Indicator's Description
Clothing (Value) Clothing (Rank)
Number of exporting countries for
N
the ranking in the sector
124
Value of exports (in thousand
G1
US$)
4420599
G2
Export growth in value, p.a. (%)
8%
56
G3
Share in national exports (%)
13%
G4
Share in national imports (%)
1%
G5
Relative trade balance (%)
72%
Relative unit value (world
General profile
G6
average=1)
1.2%
P1
Net exports (in thousand US$)
3687332
11
Per capita exports
P2
US$/inhabitant
205.2
22
P3
Share in world market (%)
1.51%
16
Product diversification (Number
P4a of equivalent products)
40
12
P4b Product concentration (Spread)
11
Market diversification (Number of
P5a equivalent products)
4
48
P5b Market concentration (Spread)
49
Position in 2006 for
Relative change of world market
Current Index
C1
share, p.a. (%)
-0.0237%
C1a Competitiveness effect, p.a. (%)
-0.0185%
51
Initial geographic specialisation,
C1b p.a. (%)
0.0098%
40
Initial product specialisation, p.a.
C1c (%)
-0.0103%
87
C1d Adaptation effect, p.a. (%)
-0.0046%
57
Matching with dynamics of world
Change 2002-2006 for
demand
Change Index
C2
4
Absolute change of market share
A
(% points p.a.)
-0.0407%
104
Average Index: Current Index
3
Indicators included in P
the chart
C
Average Index: Change Index
5
In conclusion, there are several steps to be taken by Romanian garments companies in order
to develop the sector but also the governmental support that these companies would need in order to
reach their strategic objectives and to increase competitiveness.
Companies should develop their sourcing capabilities, so they can go away from the “lohn
system” and start selling full package and not only manufacturing services. This would bring them a
much higher added value. In Romania, there is a lack of capable managers (both on production and
marketing, but also general managers), which makes the bargaining power of garments companies
limited. A very important issue is also the lack of designers and recognized designs schools, so that
both the sector associations and the state partners should get involved in solving this matter. The
unstable market conditions should be better managed by the authorities. There is a big need of
financial stability (starting with currency fluctuations and ending with the tax quantum and the
credit possibilities). The state should also better manage the work law, so the employees are stable
and satisfied with the working environment.
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References:
1. Abernathy, F.H., Dunlop, J.T., Hammond, J.H. and Weil, D, 1999, Lean Retailing and the Transformation of
Manufacturing – Lessons from the Textile and Apparel Industries, Oxford: Oxford University Press.
2. Evans, C.L. and Harrigan, J., 2003, "Distance, time and specialization", NBER Working Paper, 9729, May,
3. Hummels, D., J. Ishii and K.M. Yi, 2001, "The nature and growth of vertical specialization in world trade",
Journal of International Economics vol. 54, no 1. pp. 75-96.
4. Elbehri, A., Hertel, T. and Martin, W., 2003, "Estimating the impact of WTO and domestic reforms on the
Indian cotton and textiles sectors: a general equilibrium approach", Review of Development Economics,
5. Francois. J.F., Glisman, H.H. and Spinanger, D., 2000, "The cost of EU protection in textiles and clothing", Kiel
Institute of World Economics, Working Paper no 997.
6. Commission of the European Communities, 2003, "The future of the textiles and clothing sector in the enlarged
European Union", Communication from the Commission to the Council, the European Parliament, the European
Economic and Social Committee and the Committee of the Regions. COM (2003) final, 29.10. Commission of the
European Communities, 2004,
7. Institut Français de la Mode, 2004, "Study on the implications of the 2005 trade liberalization in the textile and
clothing sector", study commissioned by the Commission of the European Communities, tender No
ENTR/02/04, Consolidated Report.
8. http://comtrade.un.org
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