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REGIONAL DISPARITIES IN INDUSTRIAL DEVELOPMENT IN INDIA
Rajiv Khosla*, Manoj Sharma
University School of Business,
Chandigarh University, Gharuan (Punjab) India.
Mob: +919814722870;
Email [email protected]
*Corresponding author
DR. MANOJ K. SHARMA is Senior Professor in the area of Business Economics at
University School of Business, Panjab University, Chandigarh. He has over 27 years of
experience in teaching and research to the Post Graduate classes. He has over 100 research
articles in various national and international journals. Dr. Sharma is a widely travelled person
and has attended 10 international conferences outside India. He has extensively undertaken the
consultancy work for both the corporate sector as well as government departments. He has
guided more than 10 doctoral theses. Currently, he is President, Chandigarh Management
Association and actively engaged in conducting Management Development Programs.
DR. RAJIV KHOSLA is Associate Professor and Head, University, School of Business,
Chandigarh University, Gharuan, Mohali. He has 12 years of experience in the area of Business
Economics in teaching and research. He has 17 publications to his name published in national
and international journals. He has attended 20 conferences. He is in the editorial board of many
journals of repute. He is supervising two doctoral students under his guidance.
Abstract
This article studies the level of industrial development across different states of India,
with the help of composite indices. The study has brought out that huge disparities exist among
the states which have accentuated over a period of time. In order to find out the magnitude of
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
92
inter-state disparities in industries, 21 major Indian states for the period 1980-81 to 2009-10 have
been examined.
JEL Classification: R15, L16
Keywords: Disparities, weighted indicators, composite index, convergence and divergence
INTRODUCTION
Economic development is a concern of all societies as well as the nations. During the
course of economic development, the determinants of developmental process shape up in the
form of agrarian transformation towards non-agricultural sectors. Also, at some stage of
economic development, increasing urbanization, improved quality of infrastructure, increased
standard of living of the human beings, and the improved quality of overall governance takes
place. However, in this process of development, some regions of the economy grow faster in
terms of these determinants whereas others tend to lag behind. Thus, with the economic
development of an economy, a variety of inter-regional and inter-state variations (related to all
macro indices) prop up. Of course, these differences have become inevitable all over the world,
but the developing countries bear more brunt of such disparities. It is attributable to the fact that
already meager resources in these economies are further invested in few economically efficient
areas in order to generate increased profits.
Myrdal (1957) argued that once growth starts in a locality, "the ever increasing internal
and external economies - tends to sustain the continuous growth at the expense of other localities
and regions where instead relative stagnation or regression became the pattern". This concerted
development fails to permeate even into the edging areas, thereby offering a lopsided
development. Thus, in the process of profit making, regional disparities broaden. Stern
disparities augment differences not only in the level of income, poverty, unemployment and
infrastructure, nevertheless, standard of living of the people also undergo substantial changes.
Segments of the populace in the neglected regions remain devoid of even fundamental services
such as health, education, clean drinking water and sanitation facilities etc. Such misbalanced,
dejected and disorganized development of few regions has its bearing on the overall economic
development as well. Not only this, these inequalities can create damaging effects on the national
unity and harmony also. Considerable differences in economic prosperity of some regions lay
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
93
foundation for discontent among the masses leading to protests and revolts, sooner or later. For a
national economy to prosper, all the regions have to be brought into some sort of harmony.
Hence, balanced regional development is taken as of paramount importance not only to achieve
self-sufficiency at national level, but also to ensure political stability. For balanced and sustained
growth, it is essential that various sectors of the economy namely agriculture, industry, trade etc.
grow harmoniously over the different regions of the country. But for the genuine progress of an
economy and in order to enlarge the gross domestic product (GDP), a shift in economic activity
away from agriculture is required i.e. towards services and manufacturing sectors, owing to
higher elasticity of the latter than that of former sector (Fisher, 1939 and Clark, 1940). On
account of high population growth and the limited capacity of the agriculture sector to absorb
additional labour, industrialization is seen as an effective remedy for uprooting major regional
imbalances also. Moreover, a country’s economic progress is judged and determined by the
progress and development of its industrial sector. Sutcliffe (1971) argues that for the vast
majority, if not for all countries, high levels of income cannot be reached without
industrialization. Industrialization is thus inseparable from substantial and sustained economic
development, because it is both a consequence of high income and a means of higher
productivity. The significance of industrialization for India was summed up by the first Prime
Minister of India late Pt. Jawaharlal Nehru when he said, “real progress must ultimately depend
upon industrialization” (Nehru, 1958). Industrialization is thus, a means for raising the national
income per capita. Henceforth, it may be concluded, that the impact of industrialization not only
remains limited to the economic aspects of the people’s life, but it also impinge upon their social
life.
In India, regional imbalance has been one of the major concerns of policy makers and
planners since independence. Throughout the planning era, colossal efforts have been undertaken
to reduce the inter-state disparities, but the menace has continued unabated. The advocates of
non-protectionist policies for industries, who succeeded in opening the Indian industries towards
competition also could not gain much out of their efforts. The disparities have continued to
broaden unabated. A World Bank report (2008) pointed out that disparity in income distribution
in India has increased (Gini-coefficient in this connection has risen from 0.3152 in 1993-94 to
0.3676 in 2004-05) during 1993-2005. A brief account of the analysis of the industrial policies is
presented in the following paragraphs.
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
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After independence, policy makers of the country consented on rapid industrialization of
the economy to gain economic sovereignty. Hence, specific priorities for industrial development
were laid down in the First Five Year Plan. However, the first comprehensive statement on the
strategy of industrial development took place in the Industrial Policy Resolution of 1956. It
reflected the desire of the Indian State to achieve self sufficiency in industrial production. This
policy was delineated by the Mahalnobis Model of growth focusing on the huge state
investments in heavy industries. Policy emphasized on the objectives of accelerating economic
growth and boost up the process of industrialization in order to achieve a socialistic pattern of the
society. With scarce capital and narrow entrepreneurial base, government was given the task to
encourage domestic production in order to achieve a socialistic pattern of the society. To remove
regional disparities emphasis was laid on the development of regions with low industrial base by
equipping them with adequate infrastructure. Further, all sorts of assistance to small and cottage
industries for more equitable distribution of income were given. However, in this process some
big industrial houses succeeded in obtaining disproportionately larger share of licenses. It led to
the concentration of economic power and wealth into fewer hands.
Accordingly, Dutt Committee was constituted by the government in the year 1967 which
advocated for an ungenerous approach in giving the licenses to big industrial houses. It
recommended that licenses to big houses should be given only for setting up industry in core and
heavy investment sectors. This context led to the Monopolies and Restrictive Trade Practices
(MRTP) Act, issued in 1969 to comprehensively control the concentration of economic power.
According to the Act, large industries were designated as MRTP companies and were eligible to
participate in industries that were not reserved for the government or the small scale sector.
Further, the industrial licensing policy of 1970 restricted large business houses to the core, heavy
and export oriented industries.
This strategy of giving philanthropic penchant to the large industrial houses ignored the
small and medium entrepreneurs. Thus, in the Industrial policy statement of 1973, preferential
treatment was accorded to the small and medium entrepreneurs over the large houses and foreign
companies in setting up new capacities particularly in the production of mass consumption
goods. Licensing requirements for setting up fixed assets for new undertakings were waived off
for an amount up to Rs.10 million. Another industrial policy statement was released in the year
1977 generously expanding the list of items reserved for production by the small sector from 180
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
95
to 500. To promote the Indian industries to respond to the emerging challenges effectively, a new
industrial policy statement was issued in the year 1980 that focused on giving autonomy to the
public sector units. A wave of deregulation gripped the industrial sector of India. In 1988, all
industries (except 26 industries on the negative list), were exempted from licensing though they
were subject to investment and locational limitations. Thus, before the onset of reform process in
1991, industrialization in India transpired in a protected environment. Deliberately, the tariffs
and quantitative controls were kept stringent to create a barrier for the foreign competition on the
domestic market.
The industrial policy announced in 1991 unleashed the Indian industry from bureaucratic
controls. Strict industrial licensing hitherto being followed was dispensed with giving way to
liberal foreign investment and technology transfers. Only six industries were such that required
compulsory licensing. Similarly, three industries were exclusively reserved for the public sector.
Successive policies primarily focused on industrial restructuring besides giving freedom and
flexibility to the Indian industries to respond to the market forces. Though, the liberalization
wave has been able to boost up the growth rate of GDP yet it has not been successful in reducing
regional disparities in industrial development. New industries are being located in developed
states like Maharashtra, Gujarat, West Bengal, Andhra Pradesh, Tamil Nadu and Karnataka.
Other states like Kerala, Uttar Pardesh, Bihar and Punjab failed to foster in terms of
industrialization. Hence, industrial policies since liberalization have perpetuated regional
inequalities in the industrial scenario of the country. The present study is an attempt to find out
regional inequalities in terms of industrialization in India before and after liberalization.
Specifically, our endeavor is to:
1. Find out if industrialization has transpired in all states or a few states of the union;
2. Identify the states which have exhibited dismal performance in terms of
industrialization in the time period taken for this study;
3. Assess if there is a potential for regional divergence of industries instead of regional
convergence.
SECTION II
DATABASE AND METHODOLOGY
In order to fulfill the above mentioned objectives secondary data related to the number of
factories, workers, employees, fixed capital, invested capital, wages, emoluments, total output,
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
96
profits, net value added and gross value added has been obtained from the Annual Survey of
Industries reports for the years 1980-81, 190-91, 2001-02 (data for the year 2000-01 could not be
obtained despite best efforts) and 2009-10. Fifteen structural and technical ratios have been
analyzed to facilitate comparison. Primarily, the ratios have been formed keeping in view the
physical, productivity, profitability and efficiency parameters.
1. Factories per unit of population (X1)
2. Factories per unit of area (X2)
3. Invested capital per unit of population (X3)
4. Invested capital per unit of area (X4)
5. Wages per unit of population (X5)
6. Total emoluments per unit of population (X6)
7. Employment per unit of population (X7)
8. Gross value added per unit of population (X8)
9. Net value added per unit of population (X9)
10. Gross value added per unit of invested capital (X10)
11. Net value added per unit of invested capital (X11)
12. Profits per unit of invested capital (X12)
13. Profits per unit of net value added (X13)
14. Output per unit of invested capital (X14)
15. Invested capital to factories (X15)
For studying the industrial development among different states, use of composite index
has been made. It is because 15 indicators selected for this study do not give a true picture of the
overall development of industrialization individually. In case of one indicator a state may be at
the top and in another at the bottom. Henceforth, a comprehensive index pertaining to different
aspects of industrialization has been sketched. The composite index is defined as,
Ci = W1x11 + W2x12 + W3x13 +…………. + Wnx1n
or Ci = ΣWj xij
where, Ci is the composite index for the ith
observation, Wj is the weight assigned to the jth
indicator and xij is the observation value after elimination of the scale bias.
From the above formula, it is evident that to compute the composite index, weights
assigned to the indicators need to be known. Variables chosen for analysis are converted into
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
97
standard comparable units in order to minimize the chances of biasness. The method adopted to
standardize the variables is:
xij = (Xij/σ) x 100
where, xij is the scale free observation, Xij is the original observation and σ is the standard
deviation. The transformed series will have a standard deviation of unity. Though the bias gets
removed still the crucial problem remains of assigning appropriate weights to the selected
indicators. To derive the weights, we have made use of the principal component technique given
by Hagood (1943) to reduce the dimension of analysis.
SECTION III
ANALYSIS AND INTERPRETATION
Table 1 shows the standardized indicators of industrial development for the selected
states in the year 1980-81. It is clear from the table that in seven indicators i.e. X3, X5, X6, X8,
X9, X10 and X11 Maharashtra ranked first followed by Delhi and Himachal Pardesh, which
secured first rank in five (X1, X2, X4, X7 and X14) and three indicators (X12, X13 and X15)
respectively. Other states that excelled in the time period taken for this study included Gujarat,
Punjab and West Bengal. However, states like Jammu and Kashmir, Bihar, Uttar Pardesh,
Orissa, Rajasthan, Andhra Pardesh and Madhya Pardesh showed a dismal performance either in
all or the majority of the indicators. Over a period of time i.e. until 2009-10 (table 4) the same
phenomena existed wherein some states headed in terms of few indicators whereas others
remained at an equally low level. It is understandable also as various indicators pertaining to
efficiency, productivity and profitability reflected huge variations. From tables 1 to 4, it clearly
emerges that the Indian states have shown huge disparities in terms of selected indicators of
industrial development. But the study of overall level of development calls for the building up of
a composite index that incorporates all the dimensions of industrial development. The creation of
composite index brings into picture the technique of factor analysis to arrive at the weights. The
task has been achieved in tables 5 to 8.
Table 5 shows the results of factor analysis. It follows from the table that during 1980-81,
1990-91, 2001-02 and 2009-10, the first principal component could explain 64 percent, 70
percent, 78 percent and 85 percent of variations among the variables set pertaining to industrial
development. Some variables having exhibited negative results made them redundant for
analysis. To avoid this problem, squaring of the results is carried out and shown in parentheses.
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
98
Further, on the basis of first factor the relative weights of 15 indicators have been calculated and
shown in table 6. It clearly follows from the table that X6, X5, X3, X9 and X8 are the most
important variables for explaining the variation in industrial development across Indian states.
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
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Table 1
Standardized indicators of industrial development for the selected states: 1980-81
Andhra Pradesh Assam Bihar Gujarat Haryana
Himachal Pradesh
Jammu & Kashmir Karnataka Kerala
Madhya Pradesh
X1 67.32 28.34 19.65 106.27 62.18 13.06 17.65 46.83 38.71 21.60
X2 19.14 9.52 11.54 26.99 26.54 1.47 0.69 13.24 37.03 3.71
X3 122.64 63.74 153.11 309.47 258.28 127.65 52.34 132.93 128.23 138.66
X4 33.30 20.45 85.87 75.05 105.29 13.69 1.97 35.90 117.14 22.76
X5 87.62 36.13 80.50 236.12 139.64 43.86 37.48 109.30 104.13 69.26
X6 93.18 37.82 78.66 231.76 172.40 53.64 35.43 124.14 98.85 70.79
X7 153.09 77.20 64.98 244.10 170.53 61.83 55.35 126.93 130.70 74.03
X8 77.47 46.95 73.45 253 227.60 103.88 25.64 114.23 104.00 80.33
X9 72.69 42.80 61.17 222.79 222.33 96.61 19.97 108.29 102.35 76.96
X10 115.62 134.85 87.81 139.91 161.30 148.96 89.67 157.30 148.46 106.05
X11 115.36 130.72 77.76 140.13 167.56 147.31 74.27 158.57 155.37 108.03
X12 0.14 1.19 0.19 0.67 1.68 2.05 0.03 0.67 0.58 0.62
X13 0.02 0.14 0.04 0.08 0.16 0.22 0.01 0.07 0.06 0.09
X14 117.97 136.84 73.75 165.15 142.61 63.66 84.28 127.75 155.91 82.40
X15 0.53 0.65 2.26 0.84 1.20 2.83 0.86 0.82 0.96 1.86
Contd……….
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
100
Maharashtra Orissa Punjab Rajasthan Tamil Nadu Uttar Pradesh
West Bengal Delhi Mean
X1 80.18 19.16 109.49 25.43 68.71 20.85 37.65 166.95 52.78
X2 23.89 4.74 53.31 3.72 37.35 11.47 33.82 134.25 25.14
X3 316.86 110.43 254.56 120.89 188.56 93.02 183.05 269.13 167.98
X4 90.17 26.09 118.36 16.88 97.89 48.85 157.01 206.67 70.74
X5 302.03 72.99 111.35 63.56 180.74 64.19 269.44 278.26 127.03
X6 326.32 68.51 134.04 68.05 177.53 60.83 254.52 281.72 131.57
X7 253.47 60.08 166.61 66.36 195.36 82.69 207.13 267.68 136.56
X8 315.11 59.79 166.57 69.06 172.68 45.39 164.07 203.86 127.03
X9 317.18 50.12 153.35 65.02 169.37 45.07 168.00 203.56 122.09
X10 182.04 99.11 119.78 104.57 167.64 89.31 164.06 138.66 130.84
X11 194.84 88.34 117.26 104.69 174.84 94.32 178.64 147.22 131.96
X12 1.10 0.32 0.59 0.38 0.89 -0.70 0.19 0.34 0.61
X13 0.09 0.06 0.08 0.06 0.08 -0.12 0.02 0.04 0.07
X14 176.20 85.58 141.82 94.70 176.86 89.11 145.94 195.84 125.35
X15 1.14 1.67 0.67 1.38 0.79 1.29 1.41 0.47 1.20
Source: Calculated from suppliment to Annual Survey of Industries 1980-81
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
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Table 2
Standardized indicators of industrial development for the selected states: 1990-91
Andhra Pradesh Assam Bihar Gujarat Haryana
Himachal Pradesh
Jammu & Kashmir Karnataka Kerala
Madhya Pradesh
X1 107.45 32.46 24.83 124.50 87.64 25.63 14.09 61.77 56.27 28.14
X2 12.94 4.62 8.47 13.06 16.25 1.19 0.25 7.21 20.98 2.09
X3 190.41 42.26 98.57 281.47 230.66 157.28 11.56 108.72 81.41 128.30
X4 53.82 14.12 78.96 69.34 100.40 17.08 0.48 29.80 71.25 22.38
X5 117.83 34.60 126.78 221.93 225.72 114.71 17.41 143.97 118.44 86.49
X6 115.99 33.52 123.57 237.27 242.61 160.44 16.73 160.94 113.75 101.25
X7 179.46 69.72 80.10 234.53 220.40 148.63 24.85 133.61 134.06 90.40
X8 129.73 86.46 111.44 299.04 261.65 188.53 24.98 165.37 107.91 128.87
X9 116.74 85.24 104.86 281.68 258.80 190.13 25.34 160.33 109.37 118.31
X10 0.05 0.16 0.09 0.08 0.09 0.09 0.17 0.12 0.10 0.08
X11 0.00 0.01 0.00 0.00 0.00 0.01 0.01 0.01 0.01 0.00
X12 -0.04 24.78 4.29 4.36 4.62 8.64 21.80 6.54 5.92 0.43
X13 -0.10 20.31 6.67 7.20 6.81 11.82 16.43 7.33 7.28 0.77
X14 0.24 0.55 0.37 0.43 0.47 0.25 0.89 0.46 0.46 0.30
X15 0.01 0.01 0.03 0.01 0.02 0.04 0.01 0.01 0.01 0.03
Contd……….
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
102
Maharashtra Orissa Punjab Rajasthan Tamil Nadu Uttar Pradesh West Bengal Delhi Mean
X1 92.86 21.75 144.95 35.87 122.99 35.19 38.70 172.27 68.19
X2 11.86 2.20 29.07 2.30 26.30 8.28 14.78 71.53 14.08
X3 278.90 121.98 249.38 97.48 197.08 93.67 114.36 116.02 144.42
X4 83.63 28.99 117.40 14.65 98.94 51.74 102.54 113.09 59.37
X5 344.84 76.19 261.20 82.53 236.50 85.28 188.10 205.21 149.32
X6 369.10 79.89 261.83 87.25 238.63 84.58 189.17 236.12 158.48
X7 225.17 69.42 283.57 78.66 247.18 81.35 156.12 220.09 148.74
X8 402.38 105.87 252.36 98.60 275.82 92.95 120.96 270.92 173.55
X9 396.01 94.82 238.47 92.06 270.07 86.58 122.35 280.96 168.45
X10 0.11 0.07 0.08 0.08 0.11 0.08 0.08 0.18 0.10
X11 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.01 0.01
X12 0.69 3.56 0.02 2.58 8.30 2.06 -0.77 14.42 6.23
X13 0.80 7.58 0.04 4.51 10.01 3.68 -1.18 9.84 6.66
X14 0.50 0.23 0.44 0.36 0.45 0.36 0.38 0.93 0.45
X15 0.02 0.04 0.01 0.02 0.01 0.02 0.02 0.00 0.02
Source: Calculated from suppliment to Annual Survey of Industries 1990-91
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
103
Table 3
Standardized indicators of industrial development for the selected states: 2001-02
Andhra Pradesh Assam Bihar Chhattisgarh Gujarat Haryana
Himachal Pradesh
Jammu & Kashmir Jharkhand Karnataka Kerala
X1 121.72 34.76 11.60 39.93 179.37 136.71 53.60 22.35 34.58 86.13 98.46
X2 5.64 1.97 1.71 1.03 7.75 10.93 0.98 0.17 1.95 3.97 13.49
X3 85.23 28.93 6.61 120.86 335.19 155.93 129.99 9.36 112.35 121.95 52.39
X4 25.02 10.42 6.17 19.73 91.79 79.00 15.03 0.45 40.23 35.60 45.47
X5 158.90 54.16 11.54 120.26 259.58 261.60 96.34 38.68 263.47 178.61 162.95
X6 144.07 46.03 10.12 151.40 288.06 307.92 110.04 33.44 214.41 193.56 139.13
X7 198.19 70.03 12.69 75.73 236.69 228.57 100.38 40.59 97.66 155.27 161.26
X8 114.72 31.13 6.33 96.67 329.38 263.65 178.89 14.34 115.30 157.84 86.01
X9 118.40 31.83 6.63 99.40 290.95 268.91 184.65 13.97 105.90 161.41 93.15
X10 4.59 3.67 3.26 2.73 3.35 5.76 4.69 5.22 3.50 4.41 5.59
X11 2.43 1.92 1.75 1.44 1.52 3.01 2.48 2.61 1.65 2.31 3.11
X12 2.85 2.35 -2.20 0.73 1.56 4.93 6.27 -0.97 -1.59 2.06 3.23
X13 4.93 5.13 -5.27 2.15 4.33 6.87 10.60 -1.56 -4.06 3.74 4.37
X14 0.09 0.10 0.11 0.05 0.08 0.13 0.07 0.15 0.06 0.08 0.13
X15 1.63 1.94 1.32 7.04 4.34 2.65 5.64 0.97 7.55 3.29 1.24
Contd……….
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
104
Madhya Pradesh Maharashtra Orissa Punjab Rajasthan
Tamil Nadu
Uttar Pradesh Uttaranchal
West Bengal Delhi mean
X1 32.59 120.06 30.25 193.88 60.87 197.44 35.90 53.57 50.34 160.68 83.56
X2 1.07 6.32 1.20 15.68 1.68 15.84 18.65 0.32 7.60 32.94 7.18
X3 47.67 165.88 60.53 94.05 51.26 127.72 40.71 66.55 62.47 48.89 91.64
X4 9.89 55.32 15.16 48.19 8.97 64.92 134.00 2.48 59.79 63.50 39.58
X5 67.02 299.41 85.96 231.53 70.96 289.40 53.40 134.99 167.39 149.47 150.27
X6 68.90 325.60 78.27 206.97 69.68 261.14 55.47 150.81 140.72 174.97 150.99
X7 58.28 201.90 52.87 240.83 69.04 295.48 51.95 81.02 114.46 143.77 127.94
X8 82.84 252.99 51.49 178.85 73.80 198.01 51.85 81.38 68.05 119.48 121.57
X9 86.18 264.87 46.17 194.59 74.52 204.56 52.57 84.81 68.16 134.28 123.14
X10 5.92 5.20 2.90 6.48 4.90 5.28 4.34 4.17 3.71 8.33 4.67
X11 3.16 2.79 1.33 3.62 2.54 2.80 2.26 2.23 1.91 4.80 2.46
X12 6.71 2.84 -1.01 6.82 3.36 3.09 3.48 0.31 -1.38 7.84 2.44
X13 8.92 4.27 -3.19 7.92 5.56 4.64 6.48 0.59 -3.04 6.86 3.34
X14 0.12 0.10 0.06 0.15 0.10 0.11 0.09 0.08 0.08 0.21 0.10
X15 3.40 3.21 4.65 1.13 1.96 1.50 2.64 2.89 2.88 0.71 2.98
Source: Calculated from suppliment to Annual Survey of Industries 2001-02
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
105
Table 4
Standardized indicators of industrial development for the selected states: 2009-10
Andhra Pradesh Assam Bihar Chhattisgarh Gujarat Haryana
Himachal Pradesh
Jammu & Kashmir Jharkhand Karnataka Kerala
X1 138.60 50.44 13.48 55.94 181.21 125.50 155.76 36.67 44.35 98.50 116.86
X2 8.30 3.81 2.71 1.94 10.57 13.96 3.69 0.37 3.39 5.92 20.22
X3 88.98 20.82 3.36 78.97 251.62 110.69 214.13 17.26 61.75 92.42 28.04
X4 36.28 10.71 4.60 18.70 99.98 83.87 34.57 1.20 32.16 37.86 33.05
X5 126.37 37.92 6.11 74.38 215.17 308.39 178.02 40.62 93.44 152.63 93.42
X6 113.15 33.48 4.90 86.39 236.04 307.07 211.57 33.07 89.16 157.75 78.26
X7 151.10 55.19 10.12 72.31 222.83 261.44 214.41 51.33 51.00 169.05 119.61
X8 60.16 19.33 2.81 65.42 165.39 130.71 266.15 25.22 56.36 76.46 24.47
X9 51.16 18.30 2.63 60.53 144.11 121.82 258.18 24.81 53.14 69.79 22.93
X10 2.74 3.76 3.38 3.35 2.66 4.78 5.03 5.91 3.69 3.35 3.53
X11 1.18 1.81 1.61 1.58 1.18 2.26 2.48 2.96 1.77 1.55 1.68
X12 0.87 1.60 1.45 1.51 1.09 1.66 2.97 3.05 1.48 1.25 0.70
X13 1.76 2.11 2.16 2.28 2.21 1.74 2.85 2.46 1.99 1.92 1.00
X14 2.54 4.71 7.04 2.89 3.47 5.15 2.93 5.34 2.83 3.48 13.06
X15 1.85 1.19 0.72 4.07 4.01 2.54 3.97 1.36 4.02 2.71 0.69
Contd……….
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
106
Madhya Pradesh Maharashtra Orissa Punjab Rajasthan
Tamil Nadu
Uttar Pradesh Uttaranchal
West Bengal Delhi Mean
X1 33.56 118.61 34.47 254.20 69.06 271.48 37.78 161.98 52.17 108.19 102.80
X2 1.52 8.41 1.75 27.11 2.65 27.40 27.40 1.29 10.22 33.89 10.31
X3 27.30 112.97 112.19 75.85 35.18 126.55 23.46 198.46 41.11 20.48 82.93
X4 8.42 54.57 38.86 55.09 9.19 87.01 115.91 10.80 54.85 43.70 41.49
X5 44.92 182.36 78.93 181.95 56.13 291.05 37.53 278.43 69.56 60.31 124.17
X6 45.68 222.98 69.46 157.56 56.71 276.70 39.18 260.29 59.26 82.07 124.80
X7 44.08 152.61 63.18 232.66 65.79 316.64 43.23 272.76 72.34 75.29 129.38
X8 25.19 122.75 45.00 63.65 35.81 108.76 19.01 203.29 26.09 23.46 74.55
X9 23.56 115.62 40.03 58.77 33.10 96.51 17.10 197.13 23.80 22.81 69.32
X10 3.73 4.40 1.62 3.40 4.12 3.48 3.28 4.14 2.57 4.63 3.69
X11 1.77 2.11 0.73 1.59 1.94 1.57 1.50 2.04 1.19 2.29 1.75
X12 1.48 1.79 0.60 0.95 1.72 0.89 1.11 2.17 0.73 0.92 1.43
X13 1.98 2.03 1.95 1.42 2.11 1.35 1.76 2.53 1.46 0.95 1.91
X14 3.61 4.01 1.17 4.57 3.73 3.58 3.93 3.29 3.48 7.13 4.38
X15 2.35 2.75 9.39 0.86 1.47 1.34 1.79 3.54 2.27 0.55 2.54
Source: Calculated from suppliment to Annual Survey of Industries 2009-10
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
107
during 1980-81. Careful categorizations of these factors highlight that more or less physical and
somewhat productivity indicators explain the variations in industrialization significantly.
Abysmally weak X13, X15 and X12 indicators bring to light the feeble magnitude of
profitability indicators in explaining the variations in industrialization in the Indian economy. In
the year 1990-91, once again the physical factors dominated in explaining the variation in
Table 5
Rotated component matrix
1980-81 1990-91 2001-02 2009-10
X1 0.644
(0.415) 0.698
(0.487) 0.777
(0.604) 0.850
(0.722)
X2 0.557
(0.310) 0.408
(0.167) 0.288
(0.083) 0.324
(0.105)
X3 0.900
(0.811) 0.882
(0.779) 0.849
(0.721) 0.833
(0.693)
X4 0.750
(0.562) 0.620
(0.385) 0.587
(0.344) 0.570
(0.325)
X5 0.937
(0.878) 0.928
(0.862) 0.943
(0.890) 0.952
(0.907)
X6 0.945
(0.893) 0.957
(0.915) 0.960
(0.922) 0.960
(0.922)
X7 0.857
(0.735) 0.872
(0.760) 0.891
(0.794) 0.956
(0.913)
X8 0.894
(0.798) 0.990
(0.981) 0.926
(0.858) 0.830
(0.689)
X9 0.898
(0.807) 0.987
(0.974) 0.917
(0.841) 0.811
(0.657)
X10 0.549
(0.301) -0.019
(0.00001) 0.116
(0.013) 0.097
(0.009)
X11 0.603
(0.363) -0.005
(0.00001) 0.090
(0.008) 0.071
(0.005)
X12 0.079
(0.006) -0.270 (0.073)
0.172 (0.030)
0.082 (0.007)
X13 -0.027 (0.001)
-0.240 (0.058)
0.211 (0.045)
0.069 (0.005)
X14 0.636
(0.404) 0.044
(0.002) -0.020
(0.00001) -0.156 (0.024)
X15 -0.079 (0.006)
0.010 (0.00001)
0.139 (0.019)
0.140 (0.020)
Note: Figures in parentheses indicate the squaring of the result to make the results positive and
meaningful
Source: Computed from tables 1 to 4
industrial development across Indian states. In the post liberalization period also, weights of X1
and X7 factors assumed increased importance. On the whole, only five variables i.e. X1, X5, X6,
X7 and X15 have shown a consistently increasing trend. Thus, it becomes clear from the table
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
108
that only physical indicators like number of factories, wages, total emoluments and invested
capital have gone up. Efficiency (output), profitability and productivity (gross and net value
added) indicators have shown a declining trend.
In order to find out the trend in disparities among the Indian states, a coefficient of
variation for all the four time periods has been calculated (table 7). The results show an
increasing trend over disparities. Especially, after liberalization the coefficient of variation has
increased at a greater pace. Coefficient of variation that increased by 4.25 percentage points from
48.35 percent in 1980-81 to 52.60 percent in 1990-91, increased by 7.2 percentage points each in
time periods 1990-91 to 2001-02 and 2001-02 to 2009-10. Further, in as many as 10 variables the
Table 6
Standardized Weights of industrial development
1980-81 1990-91 2001-02 2009-10
X1 0.41 0.49 0.60 0.72
X2 0.31 0.17 0.08 0.11
X3 0.81 0.78 0.72 0.69
X4 0.56 0.38 0.34 0.33
X5 0.88 0.86 0.89 0.91
X6 0.89 0.92 0.92 0.92
X7 0.73 0.76 0.79 0.91
X8 0.80 0.98 0.86 0.69
X9 0.81 0.97 0.84 0.66
X10 0.30 0.0004 0.01 0.01
X11 0.36 0.00002 0.01 0.01
X12 0.01 0.07 0.03 0.01
X13 0.001 0.06 0.04 0.005
X14 0.40 0.002 0.0004 0.02
X15 0.01 0.0001 0.02 0.02
Source: Computed from tables 1 to 4
coefficient of variation has experienced an increase. Only in case of five indicators i.e. X1, X2,
X4, X12 and X13 there has been a decrease in coefficient of variation over time (from 1980-81
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
109
to 2009-10). This has resulted into wide variations in industrial development of Indian states.
This may be due to the existence of more efficient industries which are localized into fewer
hands and benefited from the advantages of privatization and liberalization. Similarly, national
industrial policies of different states might have promoted few industries and their growth which
has resulted into fewer higher performances in few states in India. To portray differences among
states in terms of industrial disparities, weighted composite index have been developed.
Table 7
Trends in regional disparities in industrial development
1980-81 1990-91 2001-02 2009-10
X1 78.60 71.38 72.22 70.22
X2 123.41 118.34 115.21 101.98
X3 48.25 53.91 78.64 83.61
X4 79.45 64.77 86.96 78.37
X5 69.09 57.70 59.23 73.05
X6 67.89 57.76 61.06 73.86
X7 53.79 51.10 62.05 70.61
X8 62.85 56.51 70.60 92.41
X9 66.10 57.84 68.27 94.83
X10 23.04 35.16 28.61 25.59
X11 27.52 38.77 33.22 28.55
X12 103.48 116.89 121.12 46.71
X13 107.06 86.64 133.73 24.98
X14 32.23 42.99 37.38 55.42
X15 52.20 58.52 64.64 77.19
Coefficient of Variation 48.35 52.60 59.82 67.02
Source: Computed from tables 1 to 4
In the year 1980-81 five states that dominated the other states in terms of composite index
comprised of Maharashtra, Delhi, Gujarat, West Bengal and Haryana. Similarly, low performing
five states comprised of Jammu and Kashmir, Uttar Pardesh, Orissa, Assam and Rajasthan. In the
year 1990-91 among the top five ranked states, three states i.e. Maharashtra, Delhi and Gujarat
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
110
continued to rule the roost. But Haryana and West Bengal were replaced by Punjab and Tamil
Nadu among the top five slots in the year 1990-91. So far the low performing states are
concerned there was no change experienced overtime. In the year 2001-02 top performing states
comprised of Gujarat, Haryana, Maharashtra, Tamil Nadu and Punjab. By comparison to the year
1990-91, there was only one change experienced that was the inclusion of Haryana in the top
five states instead of Delhi which went to the seventh slot.
Table 8
COMPOSITE INDEX
1980-81 Rank 1990-91 Rank 2001-02 Rank 2009-10 Rank
Andhra Pradesh 1076.09 10 1024.53 8 988.40 9 785.03 9
Assam 767.36 15 448.81 17 324.35 19 265.18 19
Bihar 870.74 12 769.04 12 72.39 21 67.07 21
Chhattisgarh DNE DNE 739.13 13 530.27 11
Delhi 2494.65 2 1711.59 5 1056.73 7 486.68 14
Gujarat 2135.86 3 1774.91 3 2033.93 1 1541.54 4
Haryana 1859.30 5 1656.13 6 1736.58 2 1481.59 5
Himachal Pradesh 880.70 11 1024.46 9 899.65 10 1556.70 3
Jammu & Kashmir 495.63 18 174.99 18 179.80 20 251.63 20
Jharkhand DNE DNE 992.95 8 500.52 12
Karnataka 1256.97 9 986.19 10 1110.24 6 874.65 8
Kerala 1322.47 8 827.23 11 869.98 11 557.51 10
Madhya Pradesh 857.14 13 707.84 13 482.67 17 269.16 18
Maharashtra 2580.62 1 2206.86 1 1710.77 3 1107.96 7
Orissa 746.99 16 612.58 15 426.63 18 499.36 13
Punjab 1647.86 7 1838.80 2 1430.70 5 1119.65 6
Rajasthan 804.75 14 596.93 16 499.20 16 378.71 16
Tamil Nadu 1809.30 6 1732.38 4 1671.92 4 1614.33 1
Uttar Pradesh 745.56 17 625.82 14 513.78 15 373.96 17
Uttrakhand DNE DNE 666.20 14 1602.14 2
West Bengal 1964.94 4 1045.60 7 743.15 12 421.09 15 Note: DNE stands for ‘Did Not Exist’
Source: Computed from tables 1 to 4
Table 8 gives the weighted composite index of various states. Similarly, among the lowest
performing states Madhya Pardesh and Bihar led to the ouster of Uttar Pardesh and Rajasthan.
Perhaps the birth of Chhattisgarh and Jharkhand respectively, from the states of Madhya Pardesh
and Bihar led to their downfall. In 2009-10 top five states were Tamil Nadu, Uttrakhand,
Himachal Pardesh, Gujarat and Haryana. Punjab and Maharashtra that went down to sixth and
seventh slot respectively gave way to two hill states i.e. Uttrakhand and Himachal Pardesh.
Rajiv Khosla, Manoj Sharma - Regional Disparities in Industrial Development in India
111
Bihar, Jammu and Kashmir, Assam, Madhya Pardesh and Uttar Pardesh continued to be the low
performing states.
CONCLUSIONS
Broad conclusions emerging from the study are presented in the following points:
1. With reference to overall industrialization it emerges that industrialization in India has
hovered around a few states i.e. Gujarat, Maharashtra, Tamil Nadu, Haryana, Punjab and
Delhi. The neo-liberal regime has seen an increase in private investment in those areas
which yielded more profits than the regions desperately crying for investments.
2. Bihar, Jammu and Kashmir, Rajasthan, Orissa, Assam, Madhya Pardesh and Uttar
Pardesh have shown a dismal performance in terms of the majority of indicators.
3. State of Delhi has borne the brunt of liberalization the most in terms of industrialization.
4. It becomes imperative to note that only physical indicators like number of factories,
wages, total emoluments and invested capital have gone up. Efficiency, profitability and
productivity indicators have shown a declining trend in the time period covered by this
study.
5. The entrance of states like Himachal Pardesh and Uttrakhand in the top states in the
recent past has shown that there is a potential for balanced regional development in India.
To wind up the discussion, it is pertinent on the part of various states to identify
the key core competence industries and promote them while inefficient industries needs
to be restructured so that they can withstand the pressure of liberalization and
privatization. States which have very low productivity and efficiency indicators need to
diversify those economic activities that have potential for growth, while traditional
industries should be regenerated.
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