1. 1
Iron & Steel Industry in Post-reform India: a SWOT Analysis
A Group Project Prepared by Group 12
as Paper XVI of Semester IV
in partial fulfillment of the requirements for the MA/M.Sc degree in Economics
Department of Economics
Calcutta University
2016

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3. 3
Executive Summary
Iron & Steel Industry in Post-reform India: a SWOT Analysis
Iron & Steel industry enjoyed a central position in India‟s endeavor towards planned
development of the economy, targeting self-reliance and economic prosperity as twin objectives
of planning. Here the industrialization process was mostly steered by the Public Sector
Undertakings and I&S as a core sector enjoyed all sorts of protections and priorities from the
Government. So, it was mostly state-run enterprise. In the post-reform era Indian I&S sector
continues to enjoy strong global presence and sustained global competition through successful
participation in a market-driven process. So, the industry has experienced a major change in
structure, which is expected to lead changes in conduct affecting performance at the observable
plain. Thus, the I&S industry seems to be an attractive case to study the relevance of structure-
conduct-performance paradigm in Indian context. The study that we are proposing here may
serve as an interesting case-study in the domain of empirical industrial economics. We intend to
identify the Strength (S), Weakness (W) Opportunity (O) and Threat (T) faced by this sector and
the role of government policy in creating proper incentives (threats) to reap benefits falling out
of the process of globalization through the process of local-global integration.
In this project we start with a description of the production process of the industry and its
structural features in Indian context and presented a brief historical account of its development
over the last two centuries. Then we carried out an analysis of production performance in terms
of trend, growth, productivity, technological progress and allocative (in)efficiency for both pre
and post reform periods. For the further analysis we concentrated on the post reform phase only
and here we have checked the nature of global presence enjoyed by India along with her relative
price competitiveness. The next question that came up naturally was related to the source of this
cost competitiveness and whether India is maintaining her competitive edge by overlooking
some unobserved components of social cost like environmental degradation. A crude estimate of
the total pollution content of steel production is obtained in terms of the share of abatement cost
in the total production through the input linkages suggested by appropriate input-output tables. It
was found that at unit level the pollution cost is marginally declining, but due to rapid increase in
the scale of production the aggregate pollution load is going up. The project is wrapped up by
providing a SWOT analysis of the sector and discussing the loopholes in the policy designing.

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TABLE OF CONTENTS
1. Motivation:
 Iron & Steel Industry as a Public Sector Enterprise
 Global Competition and the change in structure
 SWOT analysis
2. Structure of the Iron & Steel Industry in India:
 Types of steel plants
 Types of product
 Organizational priorities
 Extent of international presence
3. A Brief History:
 Scenario before first phase of development
 First Phase of Planned Development of the Industry
 Second Phase of Planned Development of the Industry
 Third Phase of Planned Development of the Industry
4. Performance of the Industry:
 Trend and growth of production at constant prices
 Average (labor) productivity of the sector over time
 Verification of the presence of unit root
 Endogenous structural Break and QLR-Test
 Technical Progress, Total Factor Productivity Growth and Solow Decomposition
5. Allocative Efficiency and Cost Structure:
 Formulation of a Cost Function
 Estimation of the Cost Function
 Empirical Estimation
 Interpretation and Analysis
6. Global Competition in the Post Reform Era:
 Revealed Comparative Advantage
 Revealed Systematic Comparative Advantage
 Constant Market Share (CMS) Analysis
 Nature of Price Competition between 1991-94 and 2008-11

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7. Environmental Implications:
 Total Pollution Content of Production & Input-Output Linkages
 Estimating the change in total pollution content from 1993-94 to 2007-08
 Analysis
8. Overall Assessment
 Summary Findings
 Strength-Weakness-Opportunity-Threat (SWOT) Analysis
 Policy Implications
REFERENCES & BIBLIOGRAPHY

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Iron & Steel Industry in Post-reform India: a SWOT Analysis
1. MOTIVATION
Steel is crucial for the development of any modern economy due to its important role in
accelerating industrialization and hence is considered to be the backbone of human civilization.
Iron and steel industry being one of the largest and technologically complex industry, has strong
forward and backward linkages in terms of material flows and income generation and
employment creation. Iron and steel industry has little or no competition because of its ideal
combination of strength, rigidity and workability and the relatively high cost of alternative
materials. The Indian iron and steel industry has traversed a long path since the first steel plant
went into operation in 1907. Starting at 1 million tonnes (m. t.) capacity at the time of
independence, Indian iron and steel industry has risen to be the third largest producer of crude
steel and largest producer of sponge iron in the world market of steel and iron (according to the
WSA Report 2015). A few interesting features of the industry may be noted as follows:
(i) Iron & Steel (I&S) industry enjoyed a central position in India‟s endeavor towards
planned development of the economy, targeting self-reliance and economic prosperity as twin
objectives of planning. Here the industrialization process was mostly steered by the Public Sector
Undertakings and I&S as a core sector enjoyed all sorts of protections and priorities from the
Government. So, it was mostly state-run enterprise.
(ii) In the post-reform era Indian I&S sector continues to enjoy strong global presence and
sustained global competition through successful participation in a market-driven process. So, the
industry has experienced a major change in structure, which is expected to lead changes in
conduct affecting performance at the observable plain.
(iii) Thus the I&S industry seems to be an attractive case to study the relevance of structure-
conduct-performance paradigm in Indian context. The study that we are proposing here may
serve as an interesting case-study in the domain of empirical industrial economics. We intend to
identify the Strength (S), Weakness (W) Opportunity (O) and Threat (T) faced by this sector and
the role of government policy in creating proper incentives (threats) to reap benefits falling out
of the process of globalization through the process of local-global integration.

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2. STRUCTURE OF THE IRON & STEEL INDUSTRY IN INDIA
Steel is a highly wanted alloy over the world. All the engineering machines, mechanical tools
and most importantly building and construction structures like bars, rods, channels, wires, angles
etc are made of steel for its feature being hard and adaptable. Earlier when the alloy of steel was
not discovered, iron was used for the said purposes but iron is usually prone to rust and is not so
strong.
Types of steel plants:
Based on size and nature of products used, steel plants are three types:
Alloy steel plants(ASP): These are unique special steel producers having both stainless steel as
well as non-stainless steel making facilities under one roof. These are situated in Durgapur,
Salem and Bhadravati.
Integrated Steel Plants: These plants are called integrated because in an integrated manner
factories produce coking coal and blast furnaces produce pig iron, steel ingot, finished steel etc at
the same time. At present, in India there are seven large or integrated iron factories and steel
plants and three alloy steel plants (producing stainless steel, nickel steel, chromium steel).
Small steel plants: These includes mini steel plants and sponge iron plants which are run by
electric arc furnace. They produce 15-20 metric tons of steel. At present 177 such steel plants
carry on production.
Mini mills can never completely replace integrated steel plants because they cannot maintain the
tight control over chemical composition and thus cannot consistently produce high quality steel.
Types of product :
Based on the nature, steel products are classified into two types viz., pig iron and sponge iron.
Pig Iron:
• Pig iron is the intermediate product of smelting iron ore. It is produced from large and
cylindrical shaped blast furnace charged with iron ore, coke and limestone.
• It has a very high carbon content around 3.5-4.5% along with silica. It has limited
applications.

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Uses
i) Pig iron can also be used to produce gray iron.
ii) It is one of the basic raw materials required by the foundry and casting industry of
manufacturing of the engineering industries.
Sponge Iron:
• Sponge iron is also called direct reduced iron. It is produced from iron ore powder
through heating and chemical reduction by natural gas. The reduction gas is a mixture;
majority is hydrogen and carbon monoxide which act as reducing agent.
• This process of reducing the iron ore in solid form by reducing gases is called direct
reduction process. The production of directly reduced iron is much more expensive than
that of pig iron.
• India is the largest producer of sponge iron in the world since 2003 with coal based route
accounting for 90% of total sponge iron production in the country.
Uses:
i) Sponge iron used as an excellent feedstock for the electric furnaces used by mini mills.
ii) Sponge iron can be processed to create wrought iron.
Organizational profile:
The steel industry has a dichotomous structure in India. There is co-existence of both primary
(major or large-scale) producers and secondary (small-scale) producers. The main producers
SAIL (including IISCO), TISCO, RINL are the large scale producers. Steel has a variety of
grades i.e. above 2000 but is mainly categorized in divisions – steel flat and steel long,
depending on the shape of steel manufactured. Steel flat includes steel products in flat, plate,
sheet or strip shapes. The plate shaped steel products are usually 10 to 200 mm and thin rolled
strip products are of 1 to 10 mm in dimension. Steel flat is mostly used in construction,
shipbuilding, pipes and boiler applications. Steel long Category includes steel products in long,

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bar or rod shape like reinforced rods made of sponge iron. The steel long products are required to
produce concrete, blocks, bars, tools, gears and engineering products
Table 1: A Comparative Profile of the Two Sectors of Steel
Primary Sector Secondary Sector
They are mainly the integrated steel
plants capturing 50% of the market share.
They mainly form the mini and small steel plants.
Being the price maker they enjoy the
monopoly advantage – based on
oligopolistic principles.
Being the price taker they consider open market
prices and operate - based on competitive principles.
They tend to gravitate towards the
Eastern Region as integrated production
involves weight losing process.
They tend to locate away from the integrated steel
plants as they are involved mainly in rerolling
activities.
They process crude steel to finished steel
products.
Previously they used to produce non-flat products
but after reform they switched to flat products due to
rise in income and greater urbanization.
They ensure quality steel products. Involved in rerolling activities they produce low
quality steel.
Source: Sengupta (2004)
 Primary sectors are located mainly in the eastern Region which creates regional
imbalance. In order to correct this imbalance, Indian planners devised the Freight
Equalization Scheme (FES) so that steel produced by these main producers are available
at the same price throughout the country.
 There has been a downward trend in the recent past in the share of crude steel
productions by the main producers because of the capacity expansion in the secondary
sector by new producers with new technologies.
 Further, the development of the production of long products of high quality is receiving
little attention in the expansion of Indian steel industry as EAF units and integrated
rolling operations are not being modernized to improve the availability of long products
of high quality at a competitive cost.

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Table 2: Market Share of Leading Players in Iron and Steel Industry
Company Production of steel
(in million tonnes)
Market share
(in percentage terms)
SAIL 13.5 32%
TISCO 5.2 11%
RNIL 3.5 8%
ESSAR, ISPAT, JSWL 8.4 19%
OTHERS 14.5 30%
TOTAL 45.1 100%
Source: file:///C:/Documents%20and%20Settings/user/My%20Documents/Downloads/Iron-and-
Steel-Industry-in-India.pdf
Extent of international presence:
The countries like China, Japan, India and South Korea are in the top of the above in steel
production in Asian countries.
Table 3: Country Wise Crude Steel Production During the Year 2007-08
Country Crude Steel Production
(mtpa)
China 272.5
Japan 112.7
United States 98.9
Russia 65.6
South Korea 47.5
F.R. Germany 46.4
Ukraine 38.7
Brazil 32.9
India 32.6
Italy 28.4
Source: http://steel.gov.in/Performance%20Budget%20(2005-06)/English/chap2.pdf
China accounts for one third of total production i.e. 419m ton, Japan accounts for 9% i.e. 118 m
ton, India accounts for 53m ton and South Korea is accounted for 49m ton, which all totally
becomes more than 50% of global production. Apart from this USA, BRAZIL, UK accounts for
the major chunk of the whole growth. At present the steel and iron industry contributes near 2%
of total GDP in India.( Yadav, 2015).

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3. A BRIEF HISTORY
We will start by sketching the historical path followed by this industry in India to understand the
reasons behind its central position in the process of industrialization by the end of the colonial
regime and over different phases through which it had to pass in the post-Independence period.
The discussion here will throw light on (a) the structure of the industry in the early plan period
[mostly regulated and dominated by limited number of big players], (b) the typical process of
production [large-scale vis-à-vis small-scale], (c) types of products [pig iron, ingots, sponge iron,
etc.], (d) organizational priorities [nature of large-small, formal-informal linkages] and (e) the
extent of international presence [India as an international player and the quality of Indian steel in
the World market].
This discussion will be concluded by making a brief presentation of the existing structural
features of the industry, its share in the overall manufacturing sector, its pivotal importance in
the development of infrastructure and its contribution to pollution. The lead reference for this
sketch of the history would be Sengupta (2004 Gokern, Sen & Vaidya). The Genesis of I&S
sector and the present status would be assessed by collating information from different official
reports, official website of SAIL and other available reports on the assessment of untapped
market potentials generated by different consultants.
Background
The first iron and steel industry in India was constructed in Porto Novo in the year 1830. The
industry has its own importance and with time it has emerged as a global giant. The importance
of the industry has been traced during the pre and post independence period and the period after
globalization.
Table 4: Scenario before Independence
YEARS PLANTS AND POLICIES FACTS
1830 Porto Novo Production of pig iron at 40 tons per week
1874 Bengal Iron Works was setup at Kulti,
near Asansol in West Bengal.
It was taken over by the Bengal
Government and was rechristened as
Barakar Iron Works.

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Source: Sengupta (2004), Yadav, Burange (2008)
The Indian Plan Model and the Growth of the Steel Industry
 The first five year plan (1951-52 to 1955-56) had made no headway in iron and steel
production.
 The second five year plan (1956-57 to 1960-61) large iron and steel plants were set up at
Durgapur in west Bengal, Raurkela in Orissa and Bhilai at MP.
 The third five year plan (1961-62 to 1966-67) saw the increase in production in these
plants and attempted to set up another plant at Bokaro in Bihar.
 The fifth five year plan (1974-75 to 1978-79) and seventh five year plan (1985-86 to
1989-90) laid emphasis on expansion and increase in production of existing steel plants
and setting up of small steel plants in different parts of the country.
 The eighth (1991-92 to 1996-97) and ninth (1997-98 to 2002-03) five year plan emphasis
was on setting up mini steel plants ( MSP) and private entrepreneurship was welcomed
(Yadav, 2015).
First Phase of Planned Development (1950-51 to 1967-68):
The Industrial Policy resolution of 1956 reserved the expansion of the integrated steel plant
sector. The chronic balance of payments difficulty essentially reflected the shortage of domestic
1889 Bengal Iron and Steel Company acquired Kulti
1907 Tata Iron and Steel Company was setup
and they started their production in
1908.
Started producing pig iron and ingot steel
without any tariff protection
1918 Indian Iron and Steel Company (IISCO)
was formed.
Produces pig iron and steel
1921 Mysore Iron and Steel Works Produces pig iron and steel
1936 The Bengal Iron Works went into liquidation and merged with IISCO
1937 The Steel Corporation of Bengal
(SCOB) was formed.
Started making steel in its Asansol plant.
Later in 1953, SCOB merged with IISCO.

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savings to meet the domestic investment requirement. This explains why the import of steel
during the first four decades has been mostly canalized, SAIL being the canalizing agent.
In the second five year Plan of the first sub period, Hindustan steel limited in Rourkela, Bhilai
and Durgapur was set up under the public sector steel company, where the Rourkela plant was
designed to produce flat products (sheets and plates) the other two were intended to make long
products (rails, rods, bars). By 1968-69 all these expansion projects which had been initiated
during the Third Five Year Plan was completed. Due to lack of adequate financial resources, the
plants at Bhilai, Rourkela and Durgapur were set up and expanded with foreign aid from the
Soviet Union, Germany and the UK respectively.
Second Phase of Planned Development of the Industry: Change in Government Policy and
Deceleration of Growth (1967-68 to 1991-92)
After the third plan expansion programme, the growth of the steel industry decelerated because –
i) Financial resource constraint.
ii) Long gestation lag due to indigenization of the plant and capital equipment of the
projects.
iii) Some changes in government policy regarding both the rate of public investment as well
as priority of the steel sector in the central sectors plan investment allocation.
The constraint in the availability of such finance in the form of aid is evident from the fact that
India could depend only on the Soviet Union for the Bokaro Steel Plant project, the Bhilai Steel
Plant‟s 4-million –tonne expansion project, and the Vishakhapatnam Steel Plant Project which
were the major Greenfield projects of expansion during the second sub period (1967-68 to 1991-
92).
The low rate of generation of surplus within the steel industry caused delay in releasing finances
for the public sector projects due to–
i) Increase in inefficiency in public sector output.
ii) Low administered steel prices.
iii) Limited availability of state to mobilize resources.

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Table 5: Scenario during First and Second Phase of Planned Development
1950-
1970
During the first two decades of planned economic development, i.e. 1950-60 and 1960-
70, the average annual growth rate of steel production exceeded 8 per cent.
1972 The management of IISCO was taken over by the Government of India
1973 New plant at Bokaro With a capacity of 2.5 million tonnes per annum
went into production in 1973-74.
1976 The management of the Indian Iron and Steel was taken over by the Government on
14th July, 1976.
1978 The year 1978 witnessed a major
restructuring of these steel-
making public sector units giving
birth to the public sector giant,
SAIL.
With an aggregate capacity of over 10 million
tonnes
1970-
1980
Institution for Steel Development
& Growth (INSDAG) was set up
involving leading steel producers
in the country.
The Development Commissioner
for Iron & Steel had launched a
National Campaign to boost the
domestic demand and
consumption of steel
Growth rate in steel production came down to 5.7
per cent per annum.
To boost the domestic demand and consumption of
steel.
1986 SAIL took over Maharashtra Elektrosmelt Limited, a mini steel plant
1989 Visweswaraya Iron and Steel Limited were taken over by SAIL.
1990 Until the 1990s the iron and steel
sector was by and large the
exclusive preserve of only the
public sector, the sole exception
being TISCO.
Advent of NEP. One of the foremost sectors to be opened under the
NEP. Substantial private investments, interplay of
free market enterprise, liberalisation of the
policies and institutions governing trade, industry
and finance.

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Source: Sengupta (2004), Yadav, Burange (2008)
The Third Phase of Development:
Economic Reforms, Market Orientation, and Technical Change
There has been a significant structural break in the development of the Indian steel industry since
the announcement of a series of economic reforms by GOI in 1991-1992. The new steel policy
has dereserved the integrated steel-making sector from the public domain and decided that no
new steel plant will be built in the Greenfield site in the public sector. The government has also
started privatizing the public sector steel companies by partly divesting their shares in the
market. (Sengupta).
Table 6: Scenario During the Third Phase of Planned Development
1991 New Economic Policies of govt.  Withdrawal of state control
 De-reservation
 De-licensing of private investment.
 Abolishing administered steel price
 Imports of foreign technology as well as
foreign direct investment up to 51%.
1992 The first shore-based public
sector integrated steel plant is
Rashtriya Ispat Nigam Limited
 3 million tonnes per annum capacity went
into production
 Steel industry was included in the list of
„high priority‟ industry
1994  The SDF levy was abolished
 Cabinet decided recycled corpus for loans to Main Producers
 Interest on loans to Main Producers for promotion of R&D on steel.
 Set up of an Empowered Committee to guide the R&D effort.
 Fixed floor price to check unbridled cheap imports of steel for seven items of finished
steel viz. HR coils, HR sheets, CR coils, Tinplates, CRNO and ASBR.
1996 EGEAF – Was a levy started for
reimbursing the price differential cost
of inputs used for engineering exporters
 Fund was discontinued.

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Source: Sengupta (2004), Yadav, Burange (2008)
It is apparent from the foregoing discussion that the Iron & Steel industry has a long standing
importance in the economy of India because of the presence of strong domestic demand and easy
availability of basic raw materials like iron ore in the rich mineral resource base of the country.
Whether this potential is properly utilized is the next important issue to settle. In the following
section we are going to explore the production, productivity and technical development of the
sector over time.
2005 National Steel Policy: Long term goals-
 A modern and efficient steel industry of world standards, catering to diversified
steel demand.
 Achieve global competitiveness not only in terms of cost, quality and product-mix
but also in terms of global benchmarks of efficiency and productivity.
2007 Eleventh Five Year Plan A new scheme, for the promotion of R&D in
the iron and steel sector, has been approved.
The development of technology for Cold-
Rolled Grain Oriented (CRGO) steel sheets
and other value-added products is also included
under the policy.
2007-
08
In the Union Budget, the import duty on seconds and defective has been further reduced
from 20% to 10%.
2012 The National Steel Policy 2012 aimed
at
 Becoming global leader in
terms of production,
consumption, quality and
techno‐economic efficiency
while achieving economic,
environmental and social
sustainability.
 ensure availability of quality
steel to accelerate growth of
the domestic economy and
provide amenities of life to the
people of India at par with the
developed world.
Since NSP 2005 the Indian economy
experienced a paradigm shift with the actual
performance of the economy as well as that of
Indian steel industry surpassing the projected
levels of performance. Steel consumption grew
by 10% per annum from 2005‐06 to 2011‐12
and production at an annual rate of 7.8%
during the same period thereby surpassing the
NSP 2005 projections by a significant margin.

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4. PERFORMANCE OF THE INDUSTRY
We plan to collate information on the input-output structure of the industry from the
industrial statistics reported in successive rounds of the Annual Survey of Industries
conducted by the Central Statistical Information, Government of India. The following
exercises would be undertaken over the period (1973-74 to 2011-12):
(i) Estimation of the trend and growth in production (measured by the Gross Value
Added) at constant prices.
(ii) Estimation of average (labor) productivity of the sector over time.
(iii) Since the time-series would be sufficiently long, we intend to verify the presence
of unit-root and if present, want to eliminate it.
(iv) Next, we want to check the presence of structural break endogenously, by
applying Quandt Likelihood Ratio (QLR) test. We expect to observe some break
around the structural adjustment program initiated in July 1991.
(v) The nature of technical progress in pre and post reform periods can be estimated
in terms of estimation of total factor productivity growth by applying the Solow
decomposition technique. We intend to take up that exercise also.
The lead articles that we have consulted so far in search of appropriate methodology
include Sanyal (2010 NSHM), Majumder, Banerjee & Bandyopadhyay (2012 JIS), Bit &
Banerjee (2014 FTR), etc.
Data Description and Time Interval
We have collated information on the input-output structure of the industry from the
industrial statistics reported in successive rounds of the Annual Survey of Industries
conducted by the Central Statistical Information, Government of India. The following
exercises have been undertaken over the period (1973-74 to 2011-12). The time horizon
has been taken from 1973 since the NIC 1987 for that period was readily available.
After collecting the data of Gross Value Added, Total Emoluments, Depreciation and
Fixed Capital in current prices we converted it to constant prices by using the GDP
Deflator[Constant=(Current value/Price Index)*100]. The base year taken for the
reference period is 1980.

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Table 7: Data Sources
Year Source Data Collected
1973-74 to 1997-98 Hard Copy- Annual Survey Of
Industies. (1973-74 to 1997-98):
A Database on the Industrial
Sector in India.
Gross Value Added,
Depreciation, Total
Emoluments, No. of
Workers, Fixed Capital.
1998-99 to 2011-12 Soft Copy- www.mospi.nic.in Net Value Added,
Depreciation, Total
Emoluments, No. of
Workers, Fixed Capital.
1973-74 to 1997-98
1998-99 to 2011-12
HardCopy-Database Of Indian
Economy: Volume I-Chandok
Group. Pranay Ray
Soft Copy-www.rbi.org.in
Wholesale Price Index
1973-74 to 2011-12 Soft Copy-www.rbi.org.in Interest rate on Term
Deposit.
i) Estimation of the trend and growth in production (measured by the Gross Value Added)
at constant prices:
To compare the post-reform scenario with that of the pre-reform situation analysis have
been carried out for the iron and steel industry, over the period 1973-74 and 2011-12. For
the industry level study of specific factor productivity, total factor productivity and
average labour productivity on the sector at the 3-digit level of aggregation is used. The
trend of iron and steel production is estimated by running a regression of the annual gross
value added
 tY
figure against time:
tYt  
and growth rate is obtained by
regressing the natural logarithm of net value added against time:
tYt  ln
. The
results are reported in the Table 8.

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Fig 1:Trend Line GVA Seies(Yt)
Fig 2:Growth of GVA series (ln Yt)
Both trend and growth rate are significantly positive over our reference period. We
observed the industry grew annually by 4.5%.
ii) Estimation of average (labor) productivity of the sector over time.
Labour productivity measures the amount of goods and services produced by one hour of
labor.
0
5000001.0e+061.5e+06
GVA_cons
1970 1980 1990 2000 2010
time
1011121314
ln_gva
1970 1980 1990 2000 2010
time

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Average Labor Productivity = Gross Value Added/Number of Workers
The trend of Average labor productivity (ALP) is estimated by running a regression of
the ALP against time: talpt   and growth rate is obtained by regressing the
natural logarithm of net value added against time: talpt  ln . The results are
reported in Table 8.
Fig 3: Trend line of ALP series and Growth of ALP Series (alpt) & (ln alpt)
Both trend and growth rate are significantly positive over our reference period. We observe that
average labor productivity grew by 3%.
iii) Since the time-series is sufficiently long, we intend to verify the presence of unit-root and
if present, want to eliminate it.
It is important to explore the presence of stochasticity in this apparent upward trend. To do that,
we need to examine the stationarity properties of the concerned series. The methodology adopted
is as follows : to allow for the possibility of stochastic trend a 39-year horizon is chosen (1973-
2012).Dickey-fuller test with the intercept is applied on the whole series to check the presence of
unit root. The Yt, (lnYt), alpt and (ln alpt) series turned out to be non-stationary at the level. The
series turned out to be stationary at first difference.. This presence of stochastic trend basically
indicates time dependence of the parameters of the error distribution. (confer table 9)
-2-1
0123
1970 1980 1990 2000 2010
time
A.L.P ln_alp

21. 21
iv) We check the presence of structural break endogenously, by applying Quandt Likelihood
Ratio (QLR) test.
It is highly probable that the time dependence be an offshoot of omission of some important
explanatory factor(s) which may have significant influence on the study variable in question. It
indicates a possible presence of omitted variable bias ,where the policy regime is considered to
be most likely contender of omitted influence. If the series responds to policy changes, then it
should have corresponding structural breaks before and after introduction of the intervention.
The breaks in each of the two variables, viz, gross value added and average labor productivity
have being identified in terms of Quandt Likelihood Ratio(QLR) Statistics and Table 10 reports
the year corresponding to the highest QLR value for each variable. For both the variables the
highest break point is noted around 1980‟s when Iron and Steel Industry went through a huge
technological transformation due to the restructuring of SAIL.
Fig 4: QLR for GVA Series(Yt)
0
1020304050
1970 1980 1990 2000 2010
Year

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Fig 5:QLR for ALP series (alpt)
v.) The nature of technical progress in pre and post reform periods can be estimated in terms of
estimation of total factor productivity growth by applying the Solow decomposition technique
To examine the change in total factor productivity Solow Index has been calculated. Out of total
change in productivity when the part explained by individual specific factors like capital,
labour,etc. are taken away the residual portion is ascribed to general increase. This general
increase is known as the total factor productivity and is claimed to be associated with business
environment, technological optimism, and so on. If the neo-classical production function is
represented by:  LKFY , where the symbols have their usual meaning then change in Y
 Y is due to change in K  K , change in L  L and change in A  A . The change due to K
and L are ascribed to specific factor productivity whereas the change due to A is termed as total
factor productivity. So,
t
t
t
t
t
t
t
t
t
t
K
K
r
L
L
w
A
A
Y
Y 






, where
0
102030
QLRstatistic
1970 1980 1990 2000 2010
time

23. 23


t
t
Y
Y
rate of change of gross value added;


t
t
L
L
rate of change of labour force;


t
t
K
K
rate of change of fixed capital;
tw total emoluments in gross value added;
tr share of capital (depreciation) in gross value added;
Therefore, by Solow Index 




 






t
t
t
t
t
t
t
t
t
t
K
K
r
L
L
w
Y
Y
A
A
and 




 

t
t
tt
A
A
AA 11 . If tA in t =
0 is taken as unity then the series of tA can be generated.
Fig 6:Trend Line of A series(At)
The above figure indicates the trend of the solow residual.It has been observed that over the
phase 1973-74 to 2011-12, the trend in total factor productivity was decreasing marginally by
0.072 annually as reported in Table 8.
The At series turned out to be stationary at the level. (confer Table 9)
-20-15-10
-5
0
1970 1980 1990 2000 2010
Year

24. 24
The break of the Solow Residual (At) has being identified in terms of Quandt Likelihood
Ratio(QLR) Statistics. We observe the highest QLR value (1929.516) in the year 1982 due to
the restructuring of SAIL.(confer Table 10)
Fig 7: QLR for A series(At)
Summary Results
Table 8: Trend and Growth Rate of Iron & Steel Production (Yt), Average Labor
Productivity (alpt) and Solow Residual (At): 1973-74 to 2011-12
Variable Unit Root Trend Growth R2
df t-value p-value
Yt I(1) 30495.48 - 0.82 38 13.18 0.000
d Yt I(0) 14967.03 - 0.87 38 3.28 0.002
ln Yt I(1) - 0.094 0.94 38 25.19 0.000
d ln Yt I(0) - 0.045 0.95 37 3.06 0.004
alpt I(1) 0.0713295 - 0.78 38 11.68 0.000
d alpt I(0) 0.0095791 - 0.95 38 1.66 0.106
ln alpt I(1) - 0.096 0.93 38 21.52 0.000
d ln alpt I(0) - 0.0305 0.96 37 2.55 0.015
At I(0) -0.071779 - 0.063 37 -1.55 0.129
Source: Calculated on the basis of ASI Data
0
500
100015002000
QLRstatistic
1970 1980 1990 2000 2010
Year

25. 25
Table 9: Trends and Random Walk- Iron and Steel Products
[H0:ρ=1]: 1973-74 to 2011-12
Dependent Variable ADF** Test Statistics Degrees of Freedom
Yt -3.662 -0.898 38
d.Yt -3.668 -9.470 37
ln Yt -3.662 -1.426 38
d.ln Yt -3.668 -8.472 37
alpt -3.662 1.461 38
d.alpt -3.668 -6.486 37
ln alpt -3.662 -0.321 38
d.ln alpt -3.668 -7.062 37
A -3.668 -6.148 37
**significant at less than 1% level
Source: Calculated on the basis of ASI Data
Table 10: Status of Series Stationarity (1973-74 to 2011-12): Base Year (1980 = 100)
Variable Stationary at
(Level of
Difference)
Structural Break
(Most Significant
Break Year)
Maximum QLR
Statistic
(Chi square value)
Gross value added (Yt) 1 1980 47.91947
Average labor
productivity(alpt)
1 1981 32.47164
Solow residual (At) 0 1982 1929.516
Source: Calculated on the basis of ASI Data
The foregoing analysis shows that the GVA of the sector is growing at an annual rate of 4.5%
and the labor productivity is growing at an annual average rate of 3% over the selected time
horizon. However, in terms of total factor productivity there is no sign of improvement. So, the
industry did not experience any serious level of technological innovation at an aggregate level.
Another interesting feature is the presence of endogenous break in the performance of the
industry, identified in terms of the Quandt Likelihood Ratio (QLR) test is not the year of
structural reform, i.e., 1991, but around the year 1980-81. This is mostly because of the
integration, modernization and restricting drive taken up by setting up SAIL in 1978.

26. 26
5. ALLOCATICE EFFICIENCY AND COST STRUCTURE
The analysis carried out in the preceding section will equip us to explore the cost-structure of
Indian I&S industry in terms of allocative efficiency in the pre and post reform period. Here the
analysis will mostly follow the methodology developed in Toda (1976) and Jha, Murty, Paul &
Sahni (1991).
In the production process allocative efficiency is achieved by a production unit by equating the
relative marginal factor productivities with the relative factor prices. This equality also
guarantees the correspondence between the market price and the shadow price (socially optimal
price) of the factors of production. If the actual price relatives are different from this shadow
prices then the disparity indicates the presence of allocative inefficiency.
Figure-8: Isoquant and Isocost in the Presence of Factor Price Disparity
(Toda, 1976)
Figure 8 illustrates the relation of the observed cost to the minimum cost. The two axes of the
figure measure the factor-product ratios. We draw an iso-quant that corresponds with the
observed output q. From the point of view of technical efficiency, the observed factor mix V is
on this iso-quant. The observed cost is depicted by the iso-cost line Ca passing V with the slope
w1/w2. The minimum cost at V is shown by the broken line C whose slope is equal to p1/p2, the

27. 27
shadow price ratio. At the price ratio w1/w2, cost minimizing production was possible at V*. So,
operating at V instead of V* shows the extent of allocative inefficiency.
Formulation of a Cost Function:
The method can be illustrated with a simple example of 2-factor Leontief-type cost function,
without loss of generality (Toda 1976, Jha, Murty, Paul & Sahni 1991). Our model, which
consists of one output and two inputs (called capital and labour), has the following variables:
C = the unit cost which is minimum with the output level as given;
Ca = the unit cost as actually observed;
q = the level of output;
t = time;
k = the capital-output ratio;
l = the labour-output ratio;
p1 = the shadow price of capital, i.e., the socially optimal rental rate;
p2 = the shadow price of labour, i.e., the socially optimal wage rate;
w1 = the market rental rate;
w2 = the market wage rate;
We first assume that a producing unit is technologically efficient when the factors actually in use
are on the isoquant that corresponds to the observed output level. From this assumption it follows
that the unit cost is minimum if the observed k & l are evaluated at shadow prices.
(1) ;21 lpkpC 
We take a cost function of Generalized Leontief type where it is a quadratic function of shadow
(input) prices.
(2) 222
2/1
2
2/1
112111 2 pAppApAC  ;
The convexity condition of (2) is that the off-diagonal coefficient be non-negative,
(3) ;012 A

28. 28
An important property of Cost function is stated by Shepherd‟s lemma that shows that the partial
derivative of the cost function with respect to the shadow price of a factor is equal to the quantity
of that factor. Taking partial derivatives of (2) we may express the capital-output ratio (k) and
the labor-output ratio (l) as follows:
(4) ;
2/1
2
1
1211







p
p
AAk
(5) ;
2/1
2
1
1222 





p
p
AAl
The observed unit cost can be defined as:
(6) ;21 lwkwCa 
This cost may be different from cost (1), because the observed prices may be different from the
shadow prices. Let us assume that the observed price ratio differs from the shadow price ratio by
a fixed proportional factor α. So,
(7) ;
2
1
2
1
w
w
p
p
 with α > 0;
Using (7) equations (4) & (5) can be written as:
(8) ;
2/1
2
1
1211








w
w
AAk 
(9) ;
2/1
2
1
1222 






w
w
AAl 
Substitution of (8) & (9) into (6) leads to the actual cost function whose variables are all
observed ones.
(10) ;)( 222
2/1
2
2/1
112
2/12/1
111 wAwwAwACa  


29. 29
If α is equal to 1, then there will be no deviation between the shadow price and the observed
price and the efficient cost function (1) would become:
(11) ;2* 222
2/1
2
2/1
112111 wAwwAwAC 
Comparing (10) with (11) one may decide about the efficiency status of resource allocation; in
fact, testing for efficiency (or the absence of price disparity) boils down to testing the hypothesis
α = 1.
Estimation of the Cost Function:
The estimable system of equations will comprise equations (8), (9) & (10) with stochastic error
terms added to each one.
(8)‟ ;1
2/1
2
12/1
1211 u
w
w
AAk 









(9)‟ ;2
2/1
2
12/1
1222 u
w
w
AAl 





 
(10)‟ ;)( 3222
2/1
2
2/1
112
2/12/1
111 uwAwwAwACa  

Since by equation (6) k, l and Ca are linearly connected, hence equations (8)‟ – (10)‟ are not
linearly independent. To estimate the system one needs to drop one equation. The estimation
result of the system should be robust with respect to this dropping decision. It has been discussed
in the literature that the most robust estimation is possible by using Full Information Maximum
Likelihood (FIML) technique where equation (10)‟ will be dropped.
Equation (8)‟ & (9)‟ can jointly be written as:
  




































































2
1
22112/1
2
1
2/1
2
1
2/1
12
2/1
2
1
2/12/1
12
1
0
0
1
0
u
u
AA
w
w
w
w
A
w
wA
l
k

Or,   ;222111
2/1
12
2`/12/1
12 ucAcAwAdAy  
 …… (12)

30. 30
Our procedure would be to estimate equation (11) twice, once with d included and once with d
excluded. The significance of the price disparity will be tested by the extent to which the RSS
will reduce due to inclusion of d. The values of the likelihood functions can be compared in a F
test to ascertain the presence of allocative (in)efficiency.
Empirical Estimation:
Data is needed on
 k: value of fixed capital by the value of output,
 l: Number of employees by the value of output,
 (w1/w2): [share of capital in GVA/ share of labour in GVA]*[l/k];
Method is OLS.
 Since in equation (12), u1 & u2 are both homoscadastic, serially uncorrelated and their
contemporaneous covariance is likely to be zero, hence, we can stack the variables in
appropriate vector form and can apply Ordinary Leasts Squares (OLS) to estimate the
unknown parameters. We will divide the entire period under consideration into two sub-
periods: Phase I, the pre-reform period (1973- 1991) with 19 years and Phase II, the post
reform period (1992- 2011) with 20 years. For each phase we will have equal number of
observations on k & l variables and, hence 38 observations for Phase I and 40
observations for Phase II.
 For each phase we will estimate the equation once with the variable d and once by
dropping the variable d. While the former equation will give the unrestricted residual sum
of square (URSS) the latter one will give the restricted residual sum of squares (RRSS).
Then by applying the following F test we may decide on the statistical influence of „d‟,
which, if significant would indicate the presence of allocative inefficiency.
 
dfrF
dfURSS
rURSSRRSS
F ,~
/
/

Results are reported in table 11 below.

31. 31
Table 11
Change in Allocative Efficiency of Iron & Steel Sector in India:
Pre and Post reform Comparison
Time Period d t-value p-value # obs RRSS URSS F p-value df
Phase I
(1973 – 91)
2.34 5.80 0.00 38 3.587 1.803 33.65 0.00 (1, 34)
Phase II
(1992 – 2011)
-0.5 -6.35 0.00 40 0.62 0.29 40.38 0.00 (1, 36)
Source: Calculated from ASI data
 It is interesting to note that over both the phases the coefficient of d is statistically
significant. However, in the first phase it has a positive sign whereas in the second phase
its sign is negative. Since, the coefficient of d is
 2/12/1
12

A
and given A12 > 0
by the assumption of convexity [confer equation (3)], the positive sign of d implies α > 1
and the negative sign implies 0 < α < 1.
Figure 9: Allocative Inefficiency in Input-use in Pre & Post Reform Period

32. 32
 If α > 1, then
2
1
2
1
w
w
p
p
 ; that means labor is enjoying greater market return compared to
its marginal productivity, or socially optimal (shadow) price and/ or capital is getting
relatively under paid. The opposite would be the case for 0 < α < 1.
 During the pre-reform days provision of social security through employment protection
was one of the major targets of the organized industrial sector. Here labor used to enjoy
greater market return that its shadow value. So, in this phase labor is over used to lead to
allocative inefficiency. However, in the post reform days the picture reversed. Now,
following financial reforms capital is enjoying more lenient backing from the
policymakers and the industrial labor is increasingly getting converted into underpaid
informal workers. So, here the source of inefficiency has been shifted from over-paid
labor to over-paid capital.
In spite of these shortcomings in the domestic market, in the global market the Indian Steel is
increasingly gaining prominence. So, the following section will try to explore the nature and
causes of this enhance market presence in the international arena.
6. GLOBAL COMPETITION IN POST-REFORM ERA
We intend to establish the extent of enhanced competitiveness of the Indian I&S industry in the
global market during the post-reform period. For that we want to carry out the following
exercises:
(i) Calculation of both Revealed Comparative Advantage (RCA) Index and the Revealed
Systematic Comparative Advantage (RSCA) Index following Balassa and its subsequent
improvement recently proposed by Laursen (2015).
(ii) Using COMTRADE data available from the WITS site we want to carry out a Constant
Market Share (CMS) analysis for the period 1990-94 and 2008-12. The first period will
represent the situation before the reform measures started affecting the performance of the
industry and the WTO has been emerged. The second phase will represent the state attained

33. 33
when the structural adjustment process influenced the economy in a significant way and
Indian Steel is becoming a global player in the international market.
(iii) The CMS analysis will help us to decompose the total change in the export of I&S sector
into four components, viz., (a) the change due to World growth of the industry, (b) the change
due to direction of trade, (c) the change due to the commodity composition and (d) the change
due to market competitiveness.
Here the major references would be Sanyal, Banerjee & Majumder (2009).
Analysis of Revealed Comparative Advantage
To explore the exact nature of this enhanced competitiveness here we have turned to the analysis
of change in revealed comparative advantage (RCA) of Indian iron and steel sector of India for
the years 1990, 1994, 2008 and 2012. RCA index is important measure of international
specialization. In the era of global connectivity trade is inherent part of the economy of all
nations. According to the international trade theory, a nation produces goods in which it has
comparative advantage i.e., in which it entails minimum opportunity cost and exchange that for
other goods through trade with other nations. The nation specializes along the line of production
in which it has lower comparative advantage. In the context of international export
specialization, Revealed Comparative Advantage is a relative measure indicating a strong focus
on some sectors but less on others. RCA indicates the relative trade performance of a nation in
the world market on a particular good.
Relative trade performance is captured by technological specialization, trade specialization and
product specialization. The concept of specialization implies a strong focus on one narrow area
of activity and a less intense focus on others.
RCA index (Balassa) is defined as-



i
iw
i
ij
ij
xiw
x
x
x
RCA
Where,

34. 34
:ijx India‟s (j) I&S (i) Export; :
i
ijx India‟s Total Export;
:iwx World‟s I&S Export; 
i
iwx : World‟s Total Export;
The numerator represents percentage share of given sector in national export.The denominator
represents percentage share of given sector in world export. RCA index provides comparison of
the national export structure with world export structure. We interpret the values of RCA index
in following way-
RCA=1 : country j and the world have same percentage share of export in commodity i
RCA>1 : country j has revealed comparative advantage hence specialized in commodity i
RCA<1 : country j has revealed comparative disadvantage in commodity i.
Drawback of RCA Index
The result of RCA index is the amount of output which cannot be compared on both sides of
1(its neutral value) hence asymmetric around its neutral value. The index ranges from zero to
unity if the country is categorized as non-specialized but ranges from unity to infinity if it is
specialized. In regression analysis asymmetry problem leads to skewed distribution invalidating
normality assumption of error term and hence producing unreliable t-statistic. Using non-
adjusted RCA in regression analysis would give more weight to values above 1 compared to
observations below 1.
To make the index symmetric, we propose RSCA (Revealed Systematic Comparative
Advantage) index which is defined as-
RSCA = (RCA-1) / (RCA+1), RSCA is symmetric and [-1 ≤ RSCA ≤ +1].
Calculation
Based on the COMTRADE data collected from WITS site, a dataset has been arranged where
values of Indian export of iron and steel, India‟s total export, World export of iron and steel and
World‟s total export for the years 1990, 1994, 2008, 2012 are recorded. The reason for taking
these years is to trace the impact of two important events incorporating structural change in the

35. 35
Indian iron and steel sector; one being economic reforms of 1991 and another is the global
financial crisis of 2008.
Relative share of Indian and world iron and steel export are calculated from the dataset and then
applying the formula for RCA and RSCA index we get the corresponding values (table 12).
Table 12: RCA and RSCA values of iron & Steel for Selected Years
Year 1990 1994 2008 2012
RCA 0.49 1.04 1.73 1.51
RSCA -0.34 0.02 0.27 0.20
Source: calculated from COMTRADE data
Interpretation
In 1990 India revealed an index value less than unity indicating that India‟s relative share in the
World market was below less than all-country average export. So, India was not an important
player in the international market. However, after that it started increasing steadily and in 1994
the value marginally crossed 1, became 1.04. This may capture the initial impetus caused by the
structural adjustment measures initiated within the country. By 2008 the RCA value went up to
1.73 where in the global market India turned out to be a very large player, next to China. After
2008 the global financial crisis affected the global economy and a period of recession started.
There was a drastic fall in the global demand for steel. India also loses her market share to some
extent, though the value of RCA still remained high (1.51). The values of RSCA index
concentrates around zero (making it symmetric) and also depicts a rise in value since 1994 and
fall in value after 2008.
.
.

36. 36
CMS-Analysis of the Change in India’s Iron &Steel Export
The Basic Measure: A country‟s export may grow due to four factors: (a) growth of world
export; (b) growth of export to relatively faster growing regions; (c) concentration of export in
commodities for which demand is growing relatively fast; and (d) more effective competition
with other sources of supply. For the first three factors the export-growth will be experienced
even by maintaining a constant market share. However, the fourth factor, if effective, will lead to
an increase in the relative market share. CMS analysis can isolate the contribution of first three
factors in the observed change in export between two points in time and the residual effect is
designated as the change due to competitiveness.
The formulae for CMS decomposition may be developed with the help of the following
notations:
..V : Value of Total Iron &Steel Export of India in the base year;
ijV : Value of export of the ith component of Iron &Steel to the jth country by India in the base
year;
(The notations with prime [„] represent corresponding final year figures).
r : Percentage increase of total World Export of Iron &Steel from the base year to the final year;
jr : Percentage increase of total World Export of Iron &Steel to country j from the base year to
the final year;
ir : Percentage increase of World Export of ith c Iron &Steel omponent from the base year to the
final year;
ijr : Percentage increase of World Export of the ith Iron &Steel component to country j from the
base year to the final year;
Therefore,  
i j
ij
i
i
j
j VVVV .... ; ……. (A)
The change in export over two different points in time is given by: ..
'
.. VV  ;
At the first level this can be expressed as:
..
'
.. VV  =  ....
'
.... rVVVrV  , where the first term in the RHS isolates the effect of change in
World export and the second term is the residual effect of competitiveness. At the second level
the effect of change in the direction of trade can be isolated by using relation (A) as follows:

37. 37
    
j
jjjjj
j
j
j
j
j
j VrVVVrrrVVV ..
'
.....
'
. ,where the second term in the RHS
represents the effect of change in the value of export due to change in the direction of trade, and
the first and third terms carry their usual meaning. Finally, at the third level, by using relation
(A), the effect of change in the commodity composition can be isolated as follows:
     ;'
...
'
 
i j
ijijijijij
i j
jijj
j
j
i j
ij
i j
ij VrVVVrrVrrrVVV
………. (B)
Here the third term on the RHS is representing the contribution of change in the commodity
composition to the change in Iron &Steel export, and the other terms carry their usual meaning.
CMS Analysis in Pre and Post WTO era
The data considered here corresponds to the SITC (Revision II) code obtained from World
Integrated Trade Solution (WITS) site. One has to first register on the site after which a
password is obtained and using that one can access the site. The data is downloaded by
generating an appropriate query. Here all the eight categories of Iron and Steel are taken into
account in order to show the export performance of India in all the categories. The data is
collected for two time periods: 1990-94 and 2008-12. The reason behind choosing such time
period is that the first period represents the situation with immediate reforms and gradual
changes. The second phase represents the state attained when the structural adjustment process
influenced the economy in a significant way and Indian Steel is becoming a global player in the
international market with WTO having to play a significant role in influencing trade at the
international level. This period is also of great significance because the global financial crisis
(subprime lending crisis in the US) occurred in the year 2008.As the work is mainly focused on
the period of WTO so the data is also collected on the basis of the WTO country groups. Another
country group named “Rest of the World” is created to take into account those countries which
are neither a member of the WTO nor outside WTO i.e. they are in the negotiating process.
Market Distribution
This represents the change in the direction of exports or the destination. Here the market
distribution is done for the period 1990-94 taking 1990 as the base year and 1994 as the final
year and for 2008-12 taking 2008 as the base year and 2012 as the final year.

38. 38
Figure 10: Screenshot showing how to generate a query on WITS site
Figure-11: Screenshot representing the calculations for market distribution

39. 39
Commodity Composition:
This analysis represents the change in the composition of the export basket. Its basis lies in the
fact that how each of the product categories being exported to each destination has changed over
time. For this purpose the countries are divided in six categories according to the WTO
classification and the product classification is taken from 671 to 679(for Iron &Steel exports).
The data which is obtained from the WITS site is arranged accordingly and it is done for the
years 1990-1994 and 2008-2012.
Figure-12: Screenshot representing the calculations involved in commodity composition
The CMS Results
Table 13 presents the final CMS results. It is important to note that the total change in Iron &
Steel export of India between 2008 and 2012 is much lower than the change between 1990 and
1994. This may be attributed to the global financial crisis of 2008 and the consequent changes in
the world economy. To compare these changes in terms of the relative influence of component

40. 40
factors we have normalized each one to 100 percent and report the relative contributions in
columns (3) and (5) of table 13.
Table 13: CMS Analysis of India’s Iron & Steel export Growth
Change in
Iron and Steel
Export
Change in
Absolute value
(1000 USD):
1990-1994
% change Change in
Absolute value
(1000 USD):
2008-2012
% Change
(1) (2) (3) (4) (5)
Change in Total
Export:
V’.. – V..
490418.76 100% 351235.43 100%
Increase in
World Trade:
rV..
25973.111 5.296% -2084795.7 -593.56%
Change in
Market
Distribution:
∑j(rj-r)V.j
14012.60899 2.857% -2366342.773 -673.71%
Change in
Commodity
Composition:
∑i∑j(rij-r.j)Vij
-46136.892 -9.408% -2817703.1 -802.22%
Change in
Competitiveness:
∑i∑j(V’ij-Vij-
rijVij
496569.932 101.254% 7620077.003 2169.506%
Source: Calculated on the basis of COMTRADE data (WITS/ SITC)
The increase in total World trade between 2008 and 2012 was negative whereas India‟s export
increased over that period. Though between 1990 and 1994 market distribution contributed
favorably to the increase in the change in export, in the later phase that also became negative.
Commodity composition never had any positive contribution indicating concentration of India‟s
steel in the lower part of the value-chain. The increased value of the percentage change in
residual (representing price competitiveness in the World market) from 101.254 to 2169.506 is
the most significant result of this analysis, the only change which is positive and substantial
enough to counteract the other factors.

41. 41
7. ENVIRONMENTAL IMPLICATIONS
Competitive Edge vis-à-vis Long-run Sustainability is the central query for this section. When
India is gaining prominence by enhancing her share in the global export of crude steel is she
following a clean path or is it another instance of the race to the bottom case where the cost
competitiveness is an off-shoot of the violation of pollution norms in the face of weak
enforcement? Here by utilizing the backward linkage pattern of an industry presented in an
Input-output table, we will try to estimate the total pollution content of I&S export from India for
1993 and 2007 for which appropriate statements and tables are available from the CSO. The
information on marginal abatement cost of pollution provided by the CSO (1998-99) would be
extremely useful in this context. The methodology followed will be that of Chattopadhyay
(2005).
Methodology:
Suppose for product Xj the direct pollution content is measured by the per unit abatement cost,
say cj. However to produce Xj a number of other goods have been used as inputs, each one of
them has generated certain degree of pollution. So, we need to consider the entire input vector
[Xij], j= 1,2, ….,n; which is the jth column of the input-output transaction matrix (absorption
matrix) containing elements [ X1j, X2j, …., Xnj]‟. The total pollution content (TPC) of Xj would be:
ij
n
i
iX XcTPC j

1
;
Data Extraction:
Here by utilizing the backward linkage pattern of an industry presented in an Input-output table,
we tried to estimate the total pollution content of Iron & Steel export from India for 1993 and
2007 for which appropriate statements and tables are available from the CSO. The information
on marginal abatement cost of pollution provided by the CSO would be extremely useful in this
context. All of this has been collected from the website of Ministry of Statistics and Programme
Implementation (MOSPI). Since we have carried out our entire analysis at 2-digit level of NIC
code and the abatement cost schedule is available at 3-digit NIIC87 code-wise, so we have to

42. 42
club different components of the I&S products by taking their weighted averages from both the
absorption matrix and the abatement cost schedule.
Figure 13: Snapshot of Transaction Matrix
Data Analysis:
The effect of trade liberalization on the environment has been analyzed in terms of the scale
effect (trade liberalization raises the level of economic activity in the economy which further
enhances the level of pollution) and the technique effect (due to trade liberalization there is an
increase in income levels which leads to the adoption of cleaner technologies). A small reduction
in the value of per unit abatement costs is noticed from 1993-94 to 2007-08, from 0.049 rupees
per unit of steel production to 0.046 rupees per unit, indicating a shift towards cleaner
technology (Table 14). However, an overall increase in the level of output from Rs. 4163912.00
lakh to Rs. 36171939.00 lakh somehow counterbalances it. The marginal improvement due to
technique effect is completely outweighed by the aggressive scale effect. In terms of

43. 43
environmental awareness we are moving in the sustainable direction, though the speed of
adjustment is too low to be complacent about future security. Here an integrated approach is
needed at the level of policy designing.
Table-14: Estimation of Total Pollution Content of Iron and Steel Production
Year Marginal Abatement Cost
(MAC) [%]
Total Output
(in lakhs)
Pollution Load
(in lakhs)
1993-94 0.049 4163912 203220
2007-08 0.046 36171939 1681880
Source: Calculated on the basis of data extracted from www.mospi.gov.in
Figure 14: Snapshot of calculations of abatement cost 1993-94

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8. OVERALL ASSESSMENT: SWOT ANALYSIS
Summary Findings:
The present study analyses the Iron & Steel Industry with respect to the performance, trade and
environmental aspect comparing the pre and post reform scenario in the Indian Economy. The
evolution of the Industry can be traced back to the 19th
Century but a processed planning has
been undertaken in post-independent India. In the Second Five Year Plan the main emphasis was
on heavy industrialization. The Iron & Steel Industry been strongly backed by government
received many subsidies. Initially the focus was on import substitution strategy. Following the
planned development policy the Steel Authority of India (SAIL) was established in 1978.
Following the establishment of SAIL a dichotomous structure of the Industry evolved. The
primary producers were mainly composed of public sector units with TISCO being the only
private player. On the other hand the secondary producers focused on the production of steel
from steel scrap. The paper has been divided into following subsections: Performance of the
Industry, Allocative Efficiency and Cost Structure, Global Competition in the post-reform era
and Environmental implications. The production and average labor productivity of the industry
has grown overtime while the total factor productivity showed a downward trend. The structural
break for the production, average labor productivity and total factor productivity has being
around 1980s since the industry went through a technological transformation due to the
restructuring of SAIL. It has been observed that the allocative inefficiency persisted throughout,
although the pattern of inefficiency changed from pre reform to post reform.
To analyze the global competitiveness of the iron and steel sector RCA analysis has been carried
out. RCA (Revealed Comparative Advantage) is an important measure of international
specialization and captures the relative trade performance of a nation. The RCA index shows the
relative measure of percentage share of national export and percentage share of world export of
Iron and Steel sector. In the analysis it has been found that though Indian Iron and Steel sector
had no revealed comparative advantages in pre-reform period but for post reform period revealed
comparative advantage exists. The global financial crisis of 2008 reduced the world steel
demand which impacted India‟s national export that was evidently shown by slight decline in the
values of RCA index. Constant Market Share analysis is defined as a fact that the country‟s share
in the world market remains constant over time. Any change is attributed to a change in relative

45. 45
prices. The massive changes in the values in the pre and post reform period can be attributed to
the US Subprime crisis and the situations of the world economy thereafter. During the period of
global financial crisis the world market for steel collapsed but India‟s market survived due to its
price competitiveness. Whether this competitiveness has been achieved as a case for race to the
bottom or whether it‟s a situation of true improvement has been analyzed in terms of the
Marginal Abatement Cost, Total Output and Pollution Load. An improvement in terms of the
technique effect is observed but it is overshadowed by the scale effect. The final results about the
overall situation of the industry have been represented by a SWOT analysis.
SWOT Analysis: In SWOT analysis favorable and unfavorable factors are identified by applying
two different yardsticks. Some factors are structural in nature and reflect internal strength as well
as weakness of a sector, whereas some other factors are mostly external in nature representing
the opportunities and/or threats created by the immediate situations. So, the Strength-Weakness
part is constitutional in nature and the Opportunity-Threat part is contextual in nature. Table 14
presents a comprehensive assessment of the Iron & Steel Sector of India in terms of a SWOT
analysis.
Strength: Obviously the strength of the industry primarily lies in its long history in this sub-
continent. Steel making is not a new product to the Indian entrepreneurs. Another favorable
factor is the availability of raw material due to abundance of mineral resources. In her thrive for
self-reliance in the immediate post-independence days and during the early plan periods,
emphasis was laid on rapid industrialization in India. In that pursuit Iron & Steel industry played
a pivotal role and was identified as a core sector with extensive government protections. Internal
demand for steel products was very high and the Industry mostly grew for the domestic market.
However, this comfortable environment did not take away the capability of the sector to achieve
global competitiveness in the post reform period. India could establish herself as a major player
in the international circuit.
Weakness: In spite of so many structural advantages the performance of the sector is not always
up to the mark. Our analysis revealed lack of technological upgradation and allocative
inefficiency dominating the sector. This may be due to lack of challenge from the external
environment in the early phase of development and the concentration in low quality steel in the
later stage with some competitive price edge.

46. 46
Table 15: SWOT Analysis of Indian Iron & Steel Sector
Source: Our Understanding
Favorable Unfavorable
Internal
STRENGTH WEAKNESS
The major strengths of the industry are:
 Strong historical standing.
 Easy access to raw materials due to abundance of mineral
stock.
 Sufficient internal demand due to planning initiatives.
 Identified as a priority sector by the Government of India.
 Flexibility in the production structure to adapt to the
global competitive environment
Some of the weaknesses are:
 Low quality of steel.
 Lack of technological advancement in the
production mechanism-Dominance of primitive
methods.
 Production concentration is mainly on crude steel as
no high valued products are attempted.
 Allocative inefficiency persists.
 Power shortage hampering production.
 Lack of matching infrastructural support needed for
market expansion.
External
OPPORTUNITY THREAT
Opportunities of the industry:
(i) Globalization: The industry is flexible enough to adapt to
changing market conditions. The market shares have
increased in the post reform period.
(ii) Price competitiveness has increased in the post reform
period. During world recession world competition fell but
India survived the situation.
(iii) Unit cost of pollution abatement from the production
process has reduced. Social cost of production has not
increased.
The major threats are:
i)The emergence of China as a global competitor.
ii) Market production is shifting from pig iron to sponge
iron which is more polluting, hence creating a private and
social cost discrepancy (environmental threat).
iii) Excessive foreign dependence both for supply of steel
and for fulfilling internal demand due to which India‟s
position becomes vulnerable in case of any disturbance in
world economy.
iv) Mismatch between market pulse and government thrust
thereby creating allocative inefficiency.

47. 47
Opportunity: The changed policy environment created some opportunities for the sector. The
production is gradually getting decentralized and the dominance of public sector is also on the
wane. The emergence of smaller units in steel production is making the sector more
technologically flexible and cost competitive. In fact, the benefit of this is clearly noted through
the performance of the sector in the global sphere. Another important observation relates to the
performance of Indian export during the recent global economic crisis, financial meltdown and
world recession. Though the overall growth of the sector is negative during this period, India is
standing out with a very favorable output growth. Another important point to remember is that
the cost competitiveness of India is earned not by overlooking some hidden social cost of
pollution inflicted on the system and here the pollution content per unit of steel production has
marginally reduced over time.
Threat: Three important sources of threat can be identified as: (a) aggressive invasion of China
in the World market, (b) high dependence of India for both the supply of quality steel for her
internal infrastructure development and selling of lower quality steel products in the international
market and (c) inadequacy of the reduction in pollution content due to dominance of the
technique effect by the scale effect. While the first two factors will create vulnerability for India
in terms of unanticipated external disturbances the third factor will cause long run sustainability
problem for the domestic economy itself.
Policy Implications:
Two important findings are bothering us a lot: (i) on the first count in spite of having so many
favorable and strong factors we are yet to overcome our weakness in terms of appropriate work
culture, policy coordination and judgment related to the intensity of intervention required to
achieve the socially desirable scale of operation, and (ii) even when India is coming up as a
promising player in the global market she is not producing quality steel to meet her own demand
and there is definite aversion noted against technological improvement. These are the two major
areas where the future policy should focus and coordination among different Ministry be worked
out with utmost seriousness.

48. 48
REFERENCES AND BIBLIOGRAPHY
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and-Steel-Industry-in-India.pdf

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Iron & Steel Manufacturing, Pollution Prevention & Abatement Handbook,
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