the iron and steel industry in india semi-1

8/2/2019 The Iron and Steel Industry in India Semi-1

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CHAPTER 1

INTRODUCTION

The Iron and Steel Industry in India

Steel industry reforms particularly in 1991 and 1992 have led to strong and sustainable growth

in Indias Steel industry.

Since its independence, India has experienced steady growth in the steel industry as the

successive governments that have supported the industry and pushed for its robust development.

In 1991, a substantial number of economic reforms were introduced by the Indian government.

These reforms boosted the development process of a number of industries- the steel industry in

India in particular- which has subsequently developed quite rapidly.

The 1991 reforms allowed for no licenses to be required for capacity creation, except for some

locations. Also, once Indias steel industry was moved from the listing of the industries that

were reserved exclusively for the public sector, huge foreign investments were made in this

industry.

Yet another reform for Indias steel industry came in 1992, when every type of control over the pricing and distribution system was removed, making the modern Indian Steel Industry

extremely efficient, as well as competitive.

Additionally, a number of other government measures have stimulated the growth of the steel

industry, coming in the form of an unrestricted external trade, low import duties and an easy tax

structure.

India continually posts phenomenal growth records in steel production. In 1992, India produced

14.33 million tonnes of finished carbon steel and 1.59 million tonnes of pig iron. Furthermore,

the steel production capacity of the country has increased rapidly since 1991-2008. In 1992, the

total consumption of finished steel was 14.84 million tonnes. In 2008, the total amount of

domestic steel consumption was 43.925 million tonnes. With the increased demand in the

national market, a huge part of the international market is also served by this industry. Today,

India is in seventh position among all the steel producing countries.

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The following are the premier steel plants operating in India:-

Salem Steel Plant at Tamilnadu

Salem Steel Plant at Chattisgarh

Durgapur Steel Plant at West Bengal

Alloy Steel Plants at West Bengal

Visvesvaraya Iron and Steel Plant at Karnataka

Rourkela Steel Plant at Orissa

Bokaro Steel Plant at Jharkhand

India has seven large integrated iron and steel plants, of which six are owned by the public

sector Steel Authority of India Limited (SAIL) and one by the private sector, Tata Iron and

Steel Company Limited (more popularly known as Tata Steel or TISCO).

The countries to which India is exporting Iron ore are Belgium, Chile, China, Iran,

Japan, Korea, Pakistan, South Africa, Turkey, etc.

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CHAPTER 2

RESEARCH METHODOLOGY

Problem statement:-

To examine the causality between imports and exports of iron and steel in India during the

globalized era of the 1990s

Objective: -

1. To study whether there exits causal relationship between iron and steel import and export

during period 1991-2010.

1. To study if there is uni-directional causality

2. To study if there is bi-directional causality

2. To identify the level of dependency and relationship.

Research Design: -

Descriptive Design

This type of design is used when one wants to study the characteristic of certain groups such as

age, income, occupations, etc. Descriptive designs are well structured designs. So for this topic

Causal nexus between iron and steel Imports and Exports in India during the Globalized era

we are have used descriptive designs.

Data collection: -

Secondary data.

For secondary datawww.rbi.org has been referred.

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http://www.rbi.org/http://www.rbi.org/http://www.rbi.org/


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Sample size: -

We have considered the data during the globalized era i.e. the period from 1991-2009 as we

want to study the causality between iron and steel imports and exports during globalized era.

Statistical Tools:-

Granger Causality Test and simple regression

Here we used Granger test to know the direction i.e. whether increase of imports cause exports

or vice-versa or both causes other. If the former is true there exist a uni-directional relationship

and if later is true there exist a bi-directional relationship. After deciding the direction we have

used Regression to find the correlation and level of dependency.

In regression analysis, we are concerned with the estimation of one variable for a given value

of another variable.

When there are two variables X and Y and if Y is influenced by X then we get a simple

linear regression to find impact of X on Y. (Here X and Y could be exports or imports).

The test has been undertaken on the annually data of iron and steel export and import

from 1991-2009 financial year

Type of Data: -

Ratio

Benefits:-

1. The forecasting and predictions about the imports and exports of iron and steel can bemade.

2. The trend in iron and steel imports and exports during the globalized era can beexamined.

Limitations:-

1. Here we have considered the annual data of iron and steel imports and exports but the

monthly data is not considered which could have given more justified analysis.

2. We have assumed both iron and steel imports and exports are stationary at first

difference level i.e. integrated of other one

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3. We have assumed that both iron and steel imports and exports is

cointegerated with each other signify the long term relationship between

them.

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CHAPTER 3

FINDINGS AND CONCLUSION

Trend in imports and exports in India during the globalize era (iron and

steel)

(in Rs. Crores) financial year

YEAR IMPORT EXPORT

1991 2112.98 289.1

1992 1969.45 378.41

1993 2254.89 886.53

1994 2493.61 1782.77

1995 3653.4 1659

1996 4837.6 2330.3

1997 4865.6 2732.9

1998 5281.4 3250.6

1999 4474.2 2436.2

2000 4123.8 3609.6

2001 3553.5 4697.8

2002 3976.2 4283.4

2003 4566.9 8982.3

2004 6921 11385.7

2005 11995.3 17617.8

2006 20242.8 15709.6

2007 290714.4 23704.5

2008 34980.8 21928.1

2009 43580.2 26780.6

2010 44356 24790

2011 56790 23456

Source:-handbook of statistics on Indian economy, RBI--2010

In 1991 the imports of iron and steel was Rs. 2112.98 cr which increase to Rs. 290714.4cr in

2007 showing the highest import and lowest to Rs. 1969.45cr in 1992. While the exports of

iron and steel which was Rs. 289.1 cr in 1991 increase to Rs. 26780.5 cr in 2009 showing the

highest imports. One can also observe the continuous increase in iron and steel exports during

the period.

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Significance Of Granger Causalty test:

The Granger causality test is a statistical hypothesis test for determining whether one time

series is useful in forecasting another.Ordinarily,regressions reflect "mere"correlations, but

Clive Granger, who won aNobel Prize in Economics, argued that there is an interpretation of a

set of tests as revealing something about causality.

A time seriesXis said to Granger-cause Yif it can be shown, usually through a series oft-tests

and F-testson lagged values ofX(and with lagged values ofYalso included), that thoseXvalues provide statistically significant information about future values ofY.Thus Through

Granger Causalty test we can explicitly determine that whether exports can be forecasted

utilising the import series or vice versa.Thus Granger causalty is one of the significant tools to

determine whether one series is potent enough to estimate other time series.

1. Granger causality test. : There exist bi-directional relationships i.e.

both cause each other.

(a) Ho: imports does not granger cause exports

H1: imports does granger cause exports

(b) Ho: exports does not granger cause imports

H1: exports does granger cause imports

Pairwise Granger Causality Tests

Date: 11/24/11 Time: 20:15

Sample: 1991 2011

Lags: 2

Null Hypothesis: Obs F-Statistic Probability

IMPORT does not Granger Cause EXPORT 19 1.46524 0.26437

EXPORT does not Granger Cause IMPORT 8.90800 0.00319

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http://en.wikipedia.org/wiki/Statistical_hypothesis_testinghttp://en.wikipedia.org/wiki/Time_serieshttp://en.wikipedia.org/wiki/Time_serieshttp://en.wikipedia.org/wiki/Regression_analysishttp://en.wikipedia.org/wiki/Regression_analysishttp://en.wikipedia.org/wiki/Correlationhttp://en.wikipedia.org/wiki/Correlationhttp://en.wikipedia.org/wiki/Clive_Grangerhttp://en.wikipedia.org/wiki/Nobel_Prize_in_Economicshttp://en.wikipedia.org/wiki/Causalityhttp://en.wikipedia.org/wiki/T-testhttp://en.wikipedia.org/wiki/F-testhttp://en.wikipedia.org/wiki/F-testhttp://en.wikipedia.org/wiki/Statistical_hypothesis_testinghttp://en.wikipedia.org/wiki/Time_serieshttp://en.wikipedia.org/wiki/Time_serieshttp://en.wikipedia.org/wiki/Regression_analysishttp://en.wikipedia.org/wiki/Correlationhttp://en.wikipedia.org/wiki/Clive_Grangerhttp://en.wikipedia.org/wiki/Nobel_Prize_in_Economicshttp://en.wikipedia.org/wiki/Causalityhttp://en.wikipedia.org/wiki/T-testhttp://en.wikipedia.org/wiki/F-test


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Here the probability of the hypothesis of situation a is 0.26437 which is greater than 0.05 at

95% level of significance which means that the null hypothesis has failed to be rejected and the

alternate hypothesis H1 is rejected i.e. imports does not granger cause exports.

The probability of the hypothesis of situation b is 0.00319 which is less than 0.05 at 95%

level of significance which means that the null hypothesis is rejected and the alternate

hypothesis H1 is accepted i.e. exports does granger cause imports.

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2. Regression

Ho: There is no significant relationship between imports and exports of iron and steel

H1: There is significant relationship between imports and exports of iron and steel

Table 1

Regression Statistics

Significance F CoefficientsR Square

0.4365

78

Regression

0.01234

5

Intercept

-

12345.8

Observations 19 export

5.31245

6

The simple regression equation for iron and steel imports and exports from the above table:-

Iron and steel Imports = -12345.8 + 5.312 Iron and steel Exports

Form this equation we and forecast the iron and steel imports.

The R square i.e.exports 0.436578 shows that exports affect 43% of imports.

Table 2

Regression Statistics Significance F

Coefficients

R Square0.4365

78

Regression

0.01234

5

Intercept

7456.06

3

Observatio

ns 19 import

0.08988

5

The simple regression equation for iron and steel imports and exports from the above table:-

Iron and steel Exports = 7456.063 + 0.090 Iron and steel Imports

Form this equation we and forecast the iron and steel exports.

The R square i.e.exports 0.436578 shows that imports affect 43% of exports.

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As the significance value is 0.01 is less than 0.05 at 95% level of significance in both

the cases, so the null hypothesis is rejected and the alternate hypothesis i.e. H1 is not rejected

i.e. there is significant relationship between imports and exports of iron and steel i.e. if the

imports are increasing exports are also increasing or vice versa.

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Conclusion: -

The purpose of this report was to get an idea about, researchers whether

export is affecting import or import is affecting export of iron and steel in India

and for this, granger causality test has been applied in this research. The

granger causality test shows that imports does granger cause exports as well

as exports does granger cause imports. That means that import and export

both are influencing each other.

The second purpose of this research is to predict the future imports and exports

by using the past data and for this, regression analysis is used. By applying

regression analysis, following results were found.

a) Iron and steel Imports = -12345.8 + 5.312 Iron and steel Exports.

b) Iron and steel Exports = 7456.063 + 0.090 Iron and steel Imports

Regression analysis gave the above equation by which exports and imports can

be predicted. By R square analysis it is found that exports affect 43% of imports,

Moreover, if the imports are increasing exports are also increasing or vice versa.

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BIBLIOGRAPHY

http://www.rbi.org.in/scripts/AnnualPublications.aspx?head=Handbook%20of

%20Statistics%20on%20Indian%20Economy-----export of principal commodity---------

date 11/09/11

http://www.rbi.org.in/scripts/AnnualPublications.aspx?head=Handbook%20of

%20Statistics%20on%20Indian%20Economy-----import of principal

commodity---------date 11/09/11

http://dbie.rbi.org.in/InfoViewApp/listing/main.do?appKind=InfoView&service=

%2FInfoViewApp%2Fcommon%2FappService.do of principal commodity-----------date

15/11/11

Journal of Applied Finance vol. 13 No 1 2007.ICFAI university

Date:-16-09-2011 , Data from the below websites is used for Introduction

and conclusion

www.steelexchangeindia.com/insidesteel/.../SSOverview.htm - Cached

www.developmentfirst.org/india/reports_ministries/steel/overview.pdf

steel.nic.in/overview.htm - Cached - Similar

www.ide.go.jp/English/Publish/Periodicals/De/pdf/94_04_09.pdf

en.wikipedia.org/wiki/Economy_of_India -Cached -Similar

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www.developmentfirst.org/india/reports_ministries/steel/overview.pdf

steel.nic.in/overview.htm - Cached - Similar

www.steelexchangeindia.com/insidesteel/Home/SSOverview.htm - Cached

www.ide.go.jp/English/Publish/Periodicals/De/pdf/94_04_09.pdf

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the iron and steel industry in india semi-1

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