ISSN: 2277-9108 JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING · Journal of Regional Development and Planning, ... No. 2, 2014 ISSN: 2277-9108 JOURNAL OF REGIONAL DEVELOPMENT AND

Journal of Regional Development and Planning, Vol. 3, No. 2, 2014

ISSN: 2277-9108

JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING

Volume 3 Issue 2 December 2014

CONTENTS

Pages

Articles

Evolving a Composite Development Index of States: A

Critique

Ajit K Singh 1

Analytical Study of Urban Centres: A Case Study of

Nagpur District

Kirti D. Bhonsle , C

Deshmukh , N V. Nikam

13

Tribal Population in India: Regional Dimensions &

Imperatives

Tattwamasi Paltasingh

and Gayatri Paliwal

27

Input-Output Analysis for Rural Industrial

Development of Patna Region

Rashmi Kumari and

V. Devadas

37

Development and Disparity in Bihar Reena Kumari 51

Research Perspective

Working Conditions of Handloom Weavers in Madurai R Mayamurugan 67

Book Review

High Growth Trajectory and Structural Changes in

Gujarat Agriculture; (ed) Ravindra H. Dholakia and

Samar K Datta

Itishree Pattnaik 69

JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING

JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING Editorial Team Chief Editor

Kalyanbrata Bhattacharya formerly of Department of Economics, University of Burdwan Editor

Rajarshi Majumder Department of Economics, University of Burdwan Managing Editor

Jhilam Ray Department of Economics, University of Burdwan Editorial Advisory Board

Aditya Chattopadhyay, Calcutta University

Ajit K Singh, Giri Institute of Development Studies (formerly),

Amitabh Kundu, Jawaharlal Nehru University (formerly)

Alakh N Sharma, Director, Institute for Human Development

Biswajit Chatterjee, Jadavpur University

Dinesh C Sah, MPISSR (formerly)

Kausik Gupta, Rabindra Bharati University

Rabindranath Bhattacharya, Kalyani University (formerly)

Rajendra P Mamgain, Giri Institute of Development Studies

Shankar K Bhaumik, Calcutta University

Sibranjan Misra, Viswa Bharati

Tarun Kabiraj, Indian Statistical Institute, Kolkata

If you take care of the parts, the whole will take care of itself

Journal of Regional Development and Planning, Vol. 3, No.2, 2014 1

EVOLVING A COMPOSITE DEVELOPMENT INDEX OF STATES: A

CRITIQUE

Ajit Kumar Singh1

The Raghuram Rajan Committee was appointed by the Government of India to suggest methods

for identifying backward States and to recommend the criteria for allocation of funds from the

Central Government to the States. It is argued in this paper that the index of underdevelopment of

states prepared by the Committee suffers from serious conceptual and methodological

inadequacies. The choice of indicators and their specification used for preparing composite index

of development by the Committee are quite flawed both on account of exclusion of some critical

indicators and improper specification of individual sub-index. The methodology of combing the

indicators into a composite index by giving equal weights to the indicators is questionable.

Moreover, the allocation formula suggested by the Committee drastically upsets the present

scheme of things and will not be politically acceptable to most of the states. The report of the

Committee is, thus, likely to prove an exercise in futility.

INTRODUCTION

During the last five decades of Indian planning several committees have been appointed to identify

the backward states/areas and suggest strategy for their development like the Pande Committee

(1968), Wanchoo Committee (1968), National Committee on the Development of Backward Areas

(1978), Committee to Identify 100 Most Backward and Poorest Districts in the Country (1997)

and Inter-Ministry Task Group on Redressing Growing Regional Imbalances (2005) to name a few

well known committees. Several scholars have also prepared composite index of development of

states for different time periods (Sarker 1999, Singh 2009). The Raghuram Rajan Committee for

Evolving a Composite Development Index of States is which submitted its report in September

2013 is the latest committee to go into this question. Surprisingly, the report of the committee has

drawn little attention of the scholars and policy makers.

The Rajan Committee was appointed due to persistent and forceful demand of states like Bihar to

get “special category status” in the light of their backwardness. Taking cognizance of this demand

the Finance Minister Shri Chidambaram, while presenting the Union Budget on the 28th of

February 2013, said that: “The present criteria for determining backwardness are based on terrain,

density of population and length of international borders. It may be more relevant to use a measure

like the distance of the State from the national average under criteria such as per capita income,

literacy and other human development indicators. I propose to evolve new criteria and reflect them

in future planning and devolution of funds.” The statement implied that backwardness of states

should be identified in terms of multiple indicators of socio-economic development.

The Terms of Reference of the Committee were as under:

(a) To suggest methods for identifying backward States on the basis of measures such as the

distance of the State from the national average on a variety of criteria such as per capita

income and other indicators of human development;

(b) To suggest any other method or criteria to determine the backwardness of States;

1 ICSSR National Fellow, Giri institute of Development Studies, Aliganj, Lucknow, Uttar Pradesh, INDIA.

email: [email protected]

2 JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING

(c) To suggest the weightage to be given to each criterion;

(d) To recommend how the suggested criteria may be reflected in future planning and

devolution of funds from the Central Government to the States;

(e) To suggest ways in which the absorptive capacity of States for funds and their ability to use

the funds to improve well-being can be assessed and used to influence devolution to

incentivise performance.

The composition of the committee members was somewhat strange given its TOR. There was only

one economist member. There was no representation of any member of the Planning Commission,

development economists, statistical experts or scholars who have worked on the issues of regional

disparities in India. The committee did not include a single expert on Centre-state fiscal relations

that were at the heart of the committee’s mandate as Panagariya observes (Panagariya, 2013). Nor

did the Committee have the benefit of interaction with experts and policy makers. This explains

many shortcomings in the report related to its methodology and recommendations to which

attention in drawn in the latter part of this paper. One senior economist has called the approach of

the Committee as slipshod and whimsical, arbitrary and subjective (Debroy, 2013).

We may discuss the report under the following headings: the conceptualization of backwardness

of a state, the indicators used for identifying backward states, the method of preparing a composite

index and the recommendations regarding devolution of funds.

CONCEPTUALIZATION OF A BACKWARD STATE

The first two TORs required the committee to identify backward states in terms of multiple

indicators of socio-economic development. However, there is very little discussion about what is a

backward state. The issue is disposed of in just three pages. The Committee refers to three types of

constraints on growth of states. Firstly, it considers the lack of financial resources to be the major

impediment to growth. This reflects confusion between cause of backwardness and its effect.

Among other impediments to growth the report focuses on two: (i) endowments and environment

and (ii) institutions and absorptive capacity.

The report observes that a state may be underdeveloped because it has few natural resources or

because its environment is not conducive to economic activity. However, it goes on to add that

there are plenty of natural-resource-poor countries that have become developed and natural-

resource-rich countries that have not. Even in India, some resource rich states have not developed

as much as states with poor natural resources. The report concludes that endowments may not be a

pre-condition for development, and may sometimes hamper it.

The third factor that the report refers to as impediment to growth is the role of institutions and

absorptive capacity. The report observes that: “Some regions may be underdeveloped because they

have never been able to develop the administrative and taxation institutions to raise resources, or

when they do obtain resources, they do not have the governance capacity to use them well. The

institutional factors suggested as important in the literature include better law and order

conditions, business-friendly tax and labour laws, an effective legal and regulatory framework,

transparent and well-enforced property rights, sound monetary and fiscal frameworks, etc. In a

country characterised by a federal structure, the institutional arrangements outlining the relative

responsibility of the federal government, particularly those relating to taxation, public expenditure


and transfer of resources are also important.” It goes on to observe that: “Regardless of how a

region acquires strong administrative and governance capacity, clearly without sufficient

absorptive capacity in the receiving region, allocated resources may not be properly utilised, and

may create debt but not the income to service the debt with.”

The institutional issues listed refer to what is broadly called the quality of governance, which is

often mentioned in recent literature as a factor affecting the growth rate of states. However, it

amounts to putting the blame of backwardness on the backward states as being poorly governed

and not being able to absorb the resources transferred to them properly. Nothing is said about the

decline in the quality of governance of the central government. Also ignored is the fact that at one

time Bihar and UP, the two poorest states, were regarded as among the best governed states and

that some of the richest states at present are among the worst governed and known to be corrupt.

Inadequate central transfers to the poorer states is not mentioned at all. A passing reference is

made to factors such as availability of infrastructure as lower level drivers (!) of development.

Thus, the Rajan Committee does not spell out its vision of development or backwardness. It

proceeds to identify underdevelopment without first trying to define it, thus falling into a

methodological trap.

CRITERIA USED FOR PREPARING INDEX OF UNDERDEVELOPMENT

The underdevelopment index prepared by the Committee includes the following ten sub-

components: (i) monthly per capita consumption expenditure, (ii) education, (iii) health, (iv)

household amenities, (v) poverty rate, (vi) female literacy, (vii) percent of SC-ST population, (viii)

urbanization rate, (viii) financial inclusion, and (x) connectivity. Implicitly the Committee has

taken three dimensions of development into consideration, viz. standard of living (measured by

MPCE, poverty ratio and household amenities), human development (measured by education,

health and female literacy) and infrastructure (measured by financial inclusion and connectivity.

There is no discussion why urbanization has been taken into consideration. Inclusion of SC & ST

population as an indicator of backwardness is again problematic.

Some discussion of the indicators chosen and their specification is in order. The majority of the

Committee preferred to take consumption expenditure instead of per capita income as a measure

of well being of the people. A strong criticism of this has come from one of the members of the

Committee, Dr. Saibal Gupta, who has given a long dissenting note. Dr. Gupta has given forceful

arguments for using Per capita GSDP in place of PMCE. He points out that the first TOR of the

Committee lists per capita income as the first indicator for identifying backward States. He goes

on to argue that if both the PCI and the MPCE are measured accurately, the difference between the

two would be: (a) per capita savings and (b) remittance income. In his view a more developed area

would have a proportionately lower MPCE compared to its income (due to higher savings), in

relation to a less developed area (due to remittances). Thus, in his view the MPCE will always

under-measure the difference between the richer and poorer areas as compared to the PCI. He also

questions the assumption that estimates of MPCE are more accurate than that of NSDP. Dr. Gupta

also points out that MPCE comparisons are distorted by interstate price differentials which can be

as high as 30 to 40 per cent and corrections for such price differentials are very difficult.

The objections raised by Saibal Gupta against the use of MPCE in place of per capita income are

strong and valid. The basic issue here is what we are trying to measure. If the aim is to indicate the


actual living conditions or well-being of the people (which the Committee has tried to do) then use

of MPCE is clearly preferable over PCI. However, if the aim is to capture the relative

backwardness of an area (which the Committee was supposed to do) then choice would obviously

fall on PCI rather than MPCE. Moreover, as the Committee in its report has itself recognizes that

per capita income “could represent greater capacity of the state to raise and utilize resources from

its own people, for example through state taxes and household savings.” Fiscal capacity of the

state is an important determinant of the level of services it provides to people and is a major

consideration justifying larger resource transfers to the states with limited fiscal capacity. As

Panagariya (2013) observed “the committee fails to recognise that an important objective behind

intergovernmental transfers is to offset fiscal disabilities of the states. The index determining the

transfers must reflect these disabilities with appropriate weight assigned to them.” The Committee

dismisses this reason as in its view household savings may be invested outside the state rather than

internally, limiting the resources the state has for development. The Committee fails to recognize

that the outflow of savings from the backward states through banking and non-banking financial

channels is because of low investment opportunities within the backward states and resultant low

credit-deposit ratio.

The report tries to justify its choice of using MPCE by pointing out that the correlation between

index of development based on PCI and that based on MPCE is 0.997. However, the choice of an

indicator for preparing composite index has to be guided by theoretical justification rather than

statistical outcome.

The choice of proportion of SC/ST population in total population of a state as an indicator of

backwardness is also highly problematic and has little theoretical reason to support it. This is not

an outcome variable like the other indicators. Moreover, as Saibal Gupta in his dissenting note

points out, the disadvantage of a State, because of a higher percentage of SC/ST in its population,

is adequately captured in the remaining variables. In fact, SC/ST population shows a very weak

statistical correlation with the other indicators except amenities. The use of this indicator is hardly

justified in the light of the factor loading of only 0.02 in the Principal Component Analysis done

by the Committee. The special component plan and tribal area development plan take care of the

special needs of these groups. If this was used to measure social deprivation then the population of

other deprived groups like OBC and Muslims should also have been taken into account. The

Committee has itself excluded SC/ST population from the index of performance developed by it.

Furthermore, the Report does not provide any justification for the use of urbanization as an

indicator of backwardness. It is true that urban centres are focal points of growth, but pace of

urbanization depends on a number of factors. A higher proportion of urban population gets

reflected in the values of other indicators of quality of life, amenities, social development, etc.,

which indirectly capture the impact of urbanization. If urbanization is identified with industrial

development then indicators like proportion of non-agricultural workers, number of factories per

lakh of population could have been used as done by most of the earlier committees appointed to

look into the issue of regional backwardness.

The “education” sub-index is computed as a weighted average of (i) attendance ratio using NSSO

data, and (ii) number of institutions for primary and secondary education per 1000 of state


population in the age groups of 5-14 years. Gender dimension has been captured by using female

literacy as a separate indicator.

The health dimension is measured by infant mortality rate rather than life expectancy at birth used

in preparing HDI. The use of IMR seems to be justified as it is widely accepted in the literature as

a good indicator not only for health outcomes but as a proxy for a broad set of human

development outcomes.

For household amenities the Committee has taken a weighted average of the number of

households which have the following facilities: (i) electricity as primary source of lighting, (ii)

access to drinking water within premises, (iii) no sanitation facilities within premises, (iv)

mobile/phone facilities, and (v) no specified assets. One may agree with the choice of these

indicators reflecting quality of life, though these are likely to be highly correlated with poverty

ratio which is taken as one of the ten indicators of underdevelopment.

Two indicators of infrastructure have been used, namely, financial inclusion and connectivity.

Financial inclusion is measured as the proportion of households having a bank account. It would

have been better if credit per capita was also taken into account to reflect access to credit facilities.

Connectivity is taken as a weighted average of three indicators - length of surfaced national and

state highways, other surface road and rail route per 100 sq. km. Availability of these facilities in

relation to population has not been considered as it is felt that there is no capacity constraint. The

connectivity index also does not include proportion of villages connected with all weather roads,

which is an important dimension of development opportunities.

Thus, the choice of indicators and their specification used for preparing composite index of

development by the Rajan Committee are quite flawed both on account of exclusion of some

critical indicators and improper specification of individual sub-index.

DERIVING THE COMPOSITE INDEX

For calculating the overall index for the state the Committee decided to assign equal weights to

each of the sub-components on the ground that “not only is this simple, but it is also not far off

from the weights arrived at by using more sophisticated methods.” Simplicity in the age of

computers cannot be justified to prepare a composite index. The Committee has been heavily

criticized on this ground. The indicators used are clearly not of equal importance. Is having a bank

account as important as infant mortality rate, female literacy or poverty ratio? Using equal weights

for such diverse variable makes no sense at all. The commonly used principal components analysis

for preparing composite index from a large number of variables is widely recognized as a superior

and objective method as the weighting system is generated from the exercise itself. In fact, for

those sub-components that are an aggregate over various indicators (education, household

amenities, and connectivity), the Committee itself took into accounts the weights derived from the

Principal Component Analysis to the indicators that go into the sub-component.

The Committee has in fact also prepared the composite index using the Principal Component

method as a cross check and to justify its simple approach. It finds that the squared factor loadings

from principal component analysis turn out to be 0.16 for per capita consumption expenditure,

0.08 for education, 0.10 for health, 0.16 for household amenities, 0.12 for poverty ratio, 0.10 for

female literacy, 0.02 for percent of SC-ST population, 0.11 for urbanization rate, 0.07 for financial


inclusion, and 0.08 for connectivity. Differences in the weights in many cases are two times or

even more. However, in its wisdom the Committee felt that “the coefficients for most of the sub-

components did not differ significantly from the equal weights for indicators” and decided to give

weight of 0.1 for all indicators.

The Committee justifies its simple approach on the ground that correlation coefficient between the

index using the principal component weights and that based on equal weights is 0.99. The

statistical fact that the rankings derived from the simple method are close to those derived from

more sophisticated methods is clearly beside the point. One has to logically defend the

methodology used for preparing the composite index. It is difficult to avoid the conclusion that the

committee has been casual in its statistical approach for identifying the backward states.

Table 1

Ranks and Values of Underdevelopment Index for Different States

Rank State Underdevelop-

ment Index

Rank State Underdevelop-

ment Index

1 Odisha 0.80 15 Jammu & Kashmir 0.50

2 Bihar 0.76 16 Mizoram 0.49

3 Madhya Pradesh 0.76 17 Gujarat 0.49

4 Chhattisgarh 0.75 18 Tripura 0.47

5 Jharkhand 0.75 19 Karnataka 0.45

6 Arunachal Pradesh 0.73 20 Sikkim 0.43

7 Assam 0.71 21 Himachal Pradesh 0.40

8 Meghalaya 0.69 22 Haryana 0.40

9 Uttar Pradesh 0.64 23 Uttarakhand 0.38

10 Rajasthan 0.63 24 Maharashtra 0.35

11 Manipur 0.57 25 Punjab 0.35

12 West Bengal 0.55 26 Tamil Nadu 0.34

13 Nagaland 0.55 27 Kerala 0.09

14 Andhra Pradesh 0.52 28 Goa 0.05 Source: Report of the Committee for Evolving A Composite Development Index of States (GoI, 2013).

RANKING OF STATES BY UNDERDEVELOPMENT INDEX

We now take up the development index prepared by the Rajan Committee for discussion. The

values of composite index and ranking of states on underdevelopment index as prepared by the

Committee have been given in Table 1. The value of index ranges from 0.05 for Goa (the most

developed state) to 0.80 for Odisha (the most underdeveloped state). The Committee has classified

the states into three categories: the states that score 0.6 and above on underdevelopment index are

categorized as the “least developed” states; the states that score below 0.6 and above 0.4 are

categorized as “less developed” states; and states that score below 0.4 are categorized as

“relatively developed” states. The basis of selecting these cut off points has not been explained.

There are several states which have nearly similar value of the composite index but are placed in

different categories. Also within each category there are large gaps in the value of the composite

index. It would have been better if the states were classified according to clustering of the value of

composite index.

Out of the 28 states for which the index has been prepared 6 fall in category one, 12 in category

two and remaining 10 in category three. The five least developed states of the country according to


the index are in ascending Odisha, Bihar, Madhya Pradesh, Chhattisgarh and Jharkhand. On the

other hand, the top five ranks are occupied by the states of Goa, Kerala, Tamil Nadu, Punjab and

Maharashtra. While there may be a general agreement on classifying these states as least or most

developed, the relative ranking within each category is a matter of controversy. One may ask in

what sense Kerala is a more developed state than Punjab and Maharashtra or how Odisha is more

backward than Bihar. An interesting case is that of Gujarat which has been placed at 17th rank

from the top in terms of composite index of development with a score comparable to that of

Mizoram and Tripura.

Out of the 11 special category states only three fall in the least developed category (Arunachal

Pradesh, Assam and Meghalaya); six are among less developed category (Jammu & Kashmir,

Manipur, Mizoram, Nagaland, Sikkim and Tripura); and the remaining two (Himachal Pradesh

and Uttarakhand) fall in the developed category.

Table 2

Composite Development Ranks of Major States

Rank Sarker (1989-90) Singh (2000-01) Rajan Committee (2013)

Most Developed States

1 Punjab Punjab Kerala

2 Haryana Gujarat Tamil Nadu

3 Gujarat Maharashtra Punjab

4 Tamil Nadu Haryana Maharashtra

5 Maharashtra Karnataka Haryana

Middle Level Developed States

6 Karnataka Tamil Nadu Karnataka

7 Andhra Pradesh Kerala Gujarat

8 Kerala Madhya Pradesh Andhra Pradesh

9 Uttar Pradesh Rajasthan West Bengal

10 West Bengal Andhra Pradesh Rajasthan

Least Developed States

11 Rajasthan Odisha Uttar Pradesh

12 Madhya Pradesh Assam Assam

13 Bihar Uttar Pradesh Madhya Pradesh

14 Odisha West Bengal Bihar

15 Assam Bihar Odisha Source: Col. 2 Sarker (1999); Col. 3 Singh (2009); Col. 4 Rajan Committee Report (2013)

It would be interesting to compare the ranking of states as given by the Raghuram Rajan

Committee with those of some other scholars. Sarker prepared a composite index of development

for 15 major states using Principal component Analysis for different years over the planning

period (Sarker, 1999). The present author had prepared a composite index of development using

39 indicators related to agriculture, industry, economic infrastructure and social infrastructure with

the help of principal component analysis for the year 2000 (Singh, 2009). The index was prepared

for 17 states including undivided UP, Bihar and Madhya Pradesh. Table 2 shows the ranks

according to the composite index of development for 15 states common in the three studies.

Among the top five states Punjab, Maharashtra and Haryana are common in the three rankings.

Only Andhra Pradesh is ranked among middle category states in the three studies. Assam, Bihar


and Odisha are ranked among the bottom states in all the three studies. However, there is

significant divergence in the ranks of states on development index in the three studies. For

instance, Kerala, which enjoys the first rank according to Rajan Committee, is ranked 7th and 8th

in the other two studies. Similarly Tamil Nadu which is ranked second most developed state by

Rajan committee is ranked 4th by Sarker and 6th by Singh. On the other hand, Gujarat is placed at

7th rank by Rajan Committee, is placed at 2nd rank by Singh and at 3rd rank by Sarker. Odisha is

placed at 15th rank by Rajan Committee, at 14th place by Sarker and at 11th place by Singh. This

indicates that the task of preparing composite index of development is very complex and depends

upon the variables used and the technique applied for preparing the index.

ALLOCATION OF FUNDS

The formula used by the Rajan Committee to decide about the allocation of funds to the states

consisted of three parts: (a) a fixed share of 0.3 per cent of total allocation to be distributed to each

state; (b) 75 per cent of the balance to be distributed on the basis of the development index; and (c)

25 per cent of the balance to be distributed on the basis of performance in improvement in

development index over time.

The Committee recommends that each state should get a fixed basic allocation of 0.3 percent of

overall funds for meeting the minimum requirement of the fixed costs such as administrative

expenditure. It does not explain the rationale of 0.3 per cent fixed share for all states. It is neither

judicious nor equitable. It also does not take into account the variations in the population and size

of the state. The remaining 91.6 per cent of the amount was to be allocated on the basis of need

and performance of the state-75 per cent on the basis of the development index and 25 per cent on

the basis of performance index.

It decided to use the square of the underdevelopment index so that truly needy states get

disproportionately more, while more developed states get less. This is taken to represent the need

of an average individual in a state. The Committee decided to assign 80 percent of weight to a

state’s share in population and 20 percent to the state’s share in area for determining the factor by

which to multiply need.

In addition, the Committee also introduced an index of performance in the allocation formula in

the hope that a performance bonus can be thought of as removing the disincentive (or "tax") for a

state to improving its development index, which will result in a reduced share in allocations. The

committee settled on improvements to a state’s development index over time as the measure of

performance. The Committee decided to drop the change in the fraction of SC/ST population from

the performance index as it was not regarded as a meaningful measure of performance. The

Committee assigned a weight of 25 percent to performance out of the total allocation based on

need and performance.

Table 3 gives the state-wise share of funds as recommended by the Rajan Committee and

compares them with the share in Finance Commission and Planning Commission transfers.

Comparing the share of transfers based on Plan Grants and CSS, we find that a developed state

like Goa gets more than double of the present share, while the gain of Bihar is about 62 per cent

while Odisha, ranked lowest by the Committee, gains only 41 per cent over the current Plan

transfers. On the other hand, the transfers to Kerala will be reduced by 80 per cent. The special

category states of the North East, namely, Arunachal Pradesh, Assam, Manipur, Meghalaya and


Sikkim will get substantially lower plan transfers. So will be the case with the hill states of

Himachal Pradesh, Jammu and Kashmir and Uttarakhand.

Table 3

Comparison of Shares Recommended by Various Committees/Commissions

State

Present

Central

Assistance

Shares as recommended by Ratios

Rajan

Committee

Gadgil-

Mukherjee

Committee

Finance

Commission

Col. 2

over

Col. 3

Col. 2

over

Col. 4

Col. 2

over

Col. 5

1 3 2 4 5 6 7 8

Andhra Pr 7.3 6.9 2.7 6.6 93 252 104

Arunachal Pr 1.6 1.0 4.4 0.5 62 22 194

Assam 4.9 3.1 10.3 3.3 62 30 92

Bihar 7.4 12.0 5.0 10.1 162 243 120

Chattisgarh 3.1 3.7 1.2 2.4 118 306 152

Goa 0.2 0.3 0.2 0.2 200 136 130

Gujarat 3.1 3.7 1.7 3.1 121 215 118

Haryana 1.4 1.3 0.9 1.1 98 151 120

Himachal Pr 2.0 0.7 5.8 1.5 33 12 44

J & K 4.9 1.8 9.0 2.5 37 20 73

Jharkhand 3.0 3.9 1.5 2.8 131 264 140

Karnataka 4.1 3.7 2.0 4.4 90 184 85

Kerala 2.0 0.4 1.4 2.5 19 26 16

Madhya Pr 6.9 9.6 3.2 6.7 138 303 142

Maharashtra 6.6 3.9 3.0 5.3 59 131 75

Manipur 1.4 0.5 3.3 0.8 36 15 63

Meghalaya 1.1 0.7 2.7 0.5 59 24 127

Mizoram 1.1 0.4 3.3 0.5 37 12 80

Nagaland 1.4 0.5 3.5 0.8 32 13 54

Odisha 4.6 6.5 2.5 4.8 141 263 135

Punjab 1.3 1.1 1.1 1.5 85 102 74

Rajasthan 4.8 8.4 2.8 5.8 176 305 144

Sikkim 0.7 0.4 2.2 0.4 52 16 100

Tamil Nadu 4.5 2.5 2.7 5.0 56 94 50

Tripura 1.8 0.5 5.1 0.8 29 10 64

Uttar Pr 10.1 16.4 8.9 18.2 163 185 90

Uttarakhand 1.9 0.8 5.9 1.2 42 13 69

W Bengal 6.9 5.5 3.9 6.7 79 140 82 Source: Columns 1 to 5 Rajan Committee Report; Columns 6 to 8 calculated by author.

Equally sharp changes will occur in the transfers recommended by the Finance Commission. Most

of the backward states get a higher share in the transfers but the gains vary from only 20 per cent

in case of Bihar and 35 per cent in case of Odisha to 52 per cent in case of Chattisgarh and over 90

per cent in case of Arunachal Pradesh. On the other hand, the share of Kerala will be reduced by

as much as 85 per cent and that of Tamil Nadu by 56 per cent. Himachal Pradesh, Jammu and

Kashmir, Manipur, Nagaland, Tripura and Uttarakhand will also be major losers.

The Committee feels that for most of the states, the loss in shares is small as it finds that relative to

the Finance Commission formula. This completely ignores the fact that a one per cent gain or loss


in total transfers makes a huge difference in absolute terms and is representative of the cavalier

approach of the Committee on the issues of methodology and results based on the same. Clearly,

such large variations in the level of transfers to different states will not be economically and

politically acceptable to most of the states and will drastically upset the balance in the pattern of

central transfers to the states evolved over last many decades.

Table 4

Allocation of Share in Relation to Population

State UIV

Fund

Share (

per cent)

Fund Share/

Population

Share Ratio

Per Capita

Allocation

in Rs. 1000 cr

Goa 0.05 0.30 2.5 20.6

Kerala 0.09 0.38 0.1 1.1

Tamil Nadu 0.34 2.51 0.4 3.5

Maharashtra 0.35 3.94 0.4 3.5

Punjab 0.35 1.07 0.5 3.9

Uttarakhand 0.38 0.79 0.9 7.8

Haryana 0.40 1.33 0.6 5.2

Himachal Pradesh 0.40 0.67 1.2 9.8

Sikkim 0.43 0.35 6.8 57.4

Karnataka 0.45 3.73 0.7 6.1

Tripura 0.47 0.52 1.7 14.1

Gujarat 0.49 3.69 0.7 6.1

Mizoram 0.49 0.40 4.3 36.5

Jammu & Kashmir 0.50 1.83 1.7 14.6

Andhra Pradesh 0.52 6.85 1.0 8.1

Nagaland 0.55 0.45 2.7 22.9

West Bengal 0.55 5.50 0.7 6.0

Manipur 0.57 0.50 2.3 19.6

Uttar Pradesh 0.64 16.41 1.0 8.2

Rajasthan 0.65 8.42 1.5 12.3

Meghalaya 0.69 0.65 2.6 21.8

Assam 0.71 3.05 1.2 9.8

Arunachal Pr 0.73 0.97 8.3 69.7

Chattisgarh 0.75 3.70 1.7 14.5

Jharkhand 0.75 3.88 1.4 11.8

Bihar 0.76 12.04 1.4 11.6

Madhya Pradesh 0.76 9.56 1.6 13.2

Odisha 0.80 6.53 1.9 15.6 Source: Rajan Committee Report (2013)

Note: UIV – Underdevelopment Index Value as per Rajan Committee Report

The recommended transfers fail the critical test of equity also. Table 4 shows the share in transfers

recommended in relation to population share and per capita transfers. The ratio of the

recommended share to population share of states varies from 0.7 in case of Kerala to 8.3 in case of

Arunachal Pradesh. Per capita transfers out of a Rs. 1000 crore devolution range from Rs. 1.13 in

case of Kerala to Rs. 69.74 in case of Arunachal Pradesh, clearly an unacceptable range. The per

capita share of Goa adjudged the most developed state comes to Rs. 20.63 and exceeds the per


capita transfer recommended for as many as 22 states including the five most underdeveloped

states.

FUNDS TO BE TRANSFERRED

The million dollar question is which funds are to be transferred to the states on the basis of the

recommendations of the Rajan Committee. At present the major transfers as those recommended

by the Finance Commission and the Central Plan Assistance to states governed by the Gadgil-

Mukherjee formula. Of the total resources transferred to states from the centre in 2011-12 about

54 per cent was on the basis of Finance Commission transfers and 46 per cent on the Plan side.

The Normal Central Assistance (NCA) grant, which is distributed to states based on categorization

of “Special Category” and “General Category” states, constituted only about 3.8 per cent of total

resources transferred to States and 8.2 per cent of plan transfers (Rajan Committee Report, 2013).

As Panagariya (2013) observes: “The new criteria proposed by the Rajan committee could not

possibly substitute for either those set by the Finance Commission or the Planning Commission.

Nor do they lend themselves to influencing the central schemes. So does the government want to

open yet another channel of central transfers? If yes, what is the rationale for it?”

The Committee recommends that the framework outlined in this report be used to allocate some of

the “development funds” that are allocated by the centre to the states. As far as transfer of non-

plan funds is concerned, these are to be determined on the basis of the Finance Commission which

is to be appointed every five year as per constitutional provisions. No other body can encroach on

the domain of the Finance Commission. That leaves the transfer of plan funds, major part of which

is through the centrally sponsored schemes each of which follows its own criteria. Thus, the

recommendations of the Rajan committee can be applied in deciding about the NCA grants

presently governed by Gadgil-Mukerjee formula. As we have pointed out above the formula of

transfers recommended by the Rajan Committee will disturb the present pattern of allocation of

plan funds.

Of more serious concern will be the drastic change in the list of the ‘special category’ states. The

National Development Council (NDC) has accorded the status of Special Category State to eleven

States which have been characterized by a number of features necessitating special consideration.

These features include: (i) hilly and difficult terrain, (ii) low population density and/or sizeable

share of tribal population, (iii) strategic location along borders with neighbouring countries, (iv)

economic and infrastructural backwardness, and (v) non-viable nature of state finances. At present

there are eleven Special Category States namely, Arunachal Pradesh, Assam, Himachal Pradesh,

Jammu & Kashmir, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, Tripura and Uttarakhand.

All of them are hilly states falling in the Himalayan region with long international border. The

need of special treatment to these states will remain there. However, out of the 11 special category

states only three falls in the least developed category of states identified by the Rajan Committee

(Arunachal Pradesh, Assam and Meghalaya). The other least developed states identified by the

Committee are Bihar, Chattisgarh, Jharkhand, Madhya Pradesh, Odisha, Rajasthan, and Uttar

Pradesh. These states belong to the states which have been referred to as the ‘Bimaru” states for a

long time (with the exclusion of Odisha). These are indeed among the most backward states of the

country deserving special treatment. However, exclusion of a large number of states presently


classified as special category states is not justified and politically sagacious (Mukhopadhyay

2013).

To conclude, the report of the Rajan Committee is methodologically unsound and practically non-

implementable. The index of underdeveloped states prepared by the Committee suffers from

serious conceptual and methodological inadequacies. Moreover, the allocation formula suggested

by it drastically upsets the present scheme of things and has little chance of finding acceptability in

the National Development Council which is the final arbiter in these matters. It is likely to prove

an exercise in futility.

__________________________________

Reference

Debroy, Bibek (2013), “Why the RBI Governor's Report on Growth of Indian States is Flawed,” Business

Today, October 27.

GoI (2013), Report of the Committee for Evolving a Composite Development Index of States, Government of

India, Ministry of Finance, New Delhi. [available from

htttp://finmin.nic.in/reports/Report_CompDevState.pdf, accessed on 12-08-2014

Mukhopadhyay, Sukumar (2013), “Rajan Committee on Underdevelopment Index,” November 11.

Available at http://tarafits.blogspot.com/2013/11/rajan-committee-on-underdevelopment.html,

accessed on 12-08-2014

Panagariya, Arvind (2013), “A Quickie And It Shows: Rajan Panel Report Leaves Many Questions On

Criteria For Central Funds Transfer Unanswered,” Times of India, October 19.

Sarker, P.C. (1999), Regional Disparities in India: Issues and Measurement, Himalaya Publishing House,

Mumbai.

Singh, Ajit Kumar (2009), “Inter-State Variations in Levels of Economic Development: A Sectoral and

Temporal Study,” in Yatindra Singh Sisodia (ed.), India’s Development Scenario: Challenges and

Prospects, Rawat Publications, Jaipur.


ANALYTICAL STUDY OF URBAN CENTRES: A CASE STUDY OF NAGPUR

DISTRICT

Kirti D. Bhonsle1, Charudatta Deshmukh

2, Nishant V. Nikam

3

Urbanization in India is not rapid but massive. In order to plan for balanced and integrated

development of the district and to control the growth of Nagpur, potential cities and towns should

be developed to their optimum capacity. These growth centres should be developed not only to

direct some of the population that would otherwise come to Nagpur and jeopardize its planned

growth. The paper discusses the various methods like the rank size rule, near neighbour analysis,

reed and mulch technique and functional classification of towns in the Nagpur district to study the

pattern of growth of urban centres in the Nagpur district.

INTRODUCTION

India ranks second among the countries of the world in terms of population, which as per the 2011

census has been recorded at 1.21 billion. Urbanization in India is not rapid but massive. It releases

constructive forces for development and the aim has to be planned urbanization to create a

settlement pattern of desirable hierarchy. Thus there is a need to develop potential urban centres

by aiming at a poly-nodal settlement structure by adopting strategies for their development at local

and regional scale. In order to plan for balanced and integrated development of the district and to

control the growth of Nagpur, potential cities and towns should be developed to their optimum

capacity. These growth centres should be developed not only to direct some of the population that

would otherwise come to Nagpur jeopardize its planned growth but also to help those towns to

grow in a planned way and to effect corresponding positive impact on the surrounding hinterland.

Hence an analytical study of urban centres has been done for the Nagpur district of Maharashtra

state in India.

SPATIAL PATTERN OF URBANISATION IN THE DISTRICT

In 2011 45.2 per cent of the total population of Maharashtra was living in urban areas while in

Nagpur district 64.2 per cent of the population is urban indicating higher urbanization in the

district. Urban population in the district was 0.24 million in 1901, about 30 per cent of total, and

has increased to 2.9 million in 2011. Urbanization has thus accelerated but the rate of increase is

modest. There has also occurred a significant increase in the number of urban centres in the

district from 29 to 41 during the last decade. The number of class II towns has increased to 3 with

Wadi and Umred added in the list. There is also an increase in number of class III, IV, V and VI

urban centres. The main reason behind this is the increasing industrial and allied activities which

have created job opportunities.

1 Associate Professor, Institute Of Design Education & Architectural Studies, Pipla, Nagpur - 440034. Email:

[email protected] 2 Director- Urban Planning, GVK, at Mumbai 3 Associate Professor, Rajiv Gandhi College Of Engineering & Research, Wanadongri, Nagpur-441110,

email: [email protected]


Figure 1

Locational Map of Study Region

SPATIAL ANALYSIS OF URBAN CENTRES IN NAGPUR DISTRICT

The system of towns with special reference to their size and spacing has been analyzed. The size

and spacing are the two intimately connected aspects in the location analysis for they exhibit a

certain order of relationship in the distributional pattern of urban centres over the space. The

centres of big size class for example are spaced widely while the small size class centres are closer

together. The idea of relationship with regard to size and spacing was introduced in urban

geography by Christaller’s k=3 hierarchy. Later Losch, brush and Bracey, Stewart, Browning and

Gibbs and Hagget explored the possibility of relationship between size and spacing on the national

and regional levels. They have formulated certain rules and principles according to which under

ideal conditions there is a constant ratio of relationship in the size and rank and size and spacing.

The Rank Size Rule and Near Neighbour Analysis are an outcome of such theorizations.

Rank Size Rule

The rank size rule states that the population of n-th town in a series of 1,2,3,4… n in which all

towns have been arranged in a descending order by population should be 1/n th size of the largest

town, the primate city. Although Auerbach discovered the regular relationship between rank and

size earlier in 1913 yet Zipf popularized the rank size rule in 1941. Mark Jefferson’s ‘law of

primate city’ was advanced roughly at the same time with similar connotations.

Table 1

Change in Class Wise Distribution of Urban Centres in Nagpur

Nagpur district 1951 1961 1971 1981 1991 2001 2011

Class I 1 1 1 1 1 1 1

Class II - - 1 1 1 1 3

Class III 2 3 1 2 4 8 10

Class IV 2 4 6 6 11 11 15

Class V 7 5 4 4 4 7 10

Class VI 1 - - - 2 1 2

Total 13 13 13 14 23 29 41

Source: Directorate of Economics & Statistics, Government of Maharashtra


Table 2

Distance between Urban Centres and Nearest Neighbour in the District

Urban centres

2011

Distance from

nearest

neighbour (d)

Deviation of d

from mean

Deviation of d

from HD

Rank

according to

size

Nagpur 12 3 8 1

Kamptee 2 7 18 2

Wadi 2 7 18 3

Umred 47 38 27 4

Katol 26 17 6 5

Digdoh 2 7 18 6

Wanadongri 3 6 17 7

Savner 8 1 12 8

Hudkeshwar 10 1 10 9

Kanhan[p] 5 4 15 10

Ramtek 7 2 13 11

Mahadula 3 6 17 12

Narkhed 12 3 8 13

Nildoh 2 7 18 14

Kalmeshwar 18 9 2 15

Chicholi 3 6 17 16

Narsala 8 1 12 17

Yerkheda 1 8 19 18

Khapa 10 1 10 19

Mouda 10 1 10 20

Devlameti 2 7 18 21

Tekadi 10 1 10 22

Borkhedi 12 3 8 23

Kamptee cantt. 2 7 18 24

Chandakpur 4 5 16 25

Bori 15 6 5 26

Tekalghat 16 7 4 27

Kandri 3 6 17 28

Bamhni 21 11 1 29

Walani 4 5 16 30

Sonegaon 8 1 12 31

Mowad 14 5 6 32

Bhokara 7 2 13 33

Waghoda 6 1 14 34

Sillewada 3 6 17 35

Mohpa 15 6 5 36

Koradi 3 6 17 37

Wadhammna 5 4 15 38

Kandri 4 5 16 39

Isasani 3 6 17 40

Nagalwadi 12 3 8 41

Source: Authors’ calculations.

Concept of Near Neighbour Analysis

The idea of ‘Near Neighbour analysis’ is said to have been derived from the plant ecologists who

were concerned chiefly with the distributional pattern of various species of plants on earth. The

underlying principle of the near neighbour analysis is a straight measurement of the distance


separating any phenomenon from its nearest neighbour in space. It seeks to elucidate the random

occurrence of the location points while analyzing the pattern. Defining the ‘Nearest neighbour’,

Thomas pointed out that the population of the sample city and the nearest neighbour should be

approximately the same. But the size in near neighbour analysis should be considered only when

the distance-size relationship is to be analyzed. For the purpose of examining the general pattern

all the urban centres may be treated equally as has been done by king. Owing to the absence of a

well-graded hierarchy all the urban centres of the region have been equally treated for spatial

analysis in the first instance. For e.g. a small size town has been given the same locational weight

as a large one.

Spatial Pattern in Nagpur

Table 2 illustrates the distance between an urban centre and its nearest neighbour regardless of

size. It is evident that there is considerable variation in spacing of urban centres and they’re

nearest neighbour. Under ideal condition of spatial distribution the hypothetical distance can be

computed as:

HD = 1.07 X Sq rt (a/n)

where, a is the area of the district, n is the number of urban centres in the district and HD is the

hypothetical distance.

Thus for Nagpur, we find that the hypothetical distance of 16.6 km exceeds the average distance of

9 km by 84 per cent. Conversely, ratio of average to hypothetical distance is 54 per cent. This is an

indicator of the degree of dispersion. The higher is the percentage the greater will be the

dispersion and vice versa. It reveals that the spatial pattern of urban centres in the region is not

regular because the degree of dispersion is less than one half.

The above fact may be further attested using the King’s concept of distribution and clustering.

According to this method, the ratio Rn = 2 X d X Sq. rt (n/a) gives a measure of clustering where

d is the mean distance between the nearest neighbours, n is the number of urban centres and a is

the area of the district. If Rn is 0 then the centres are clustered together, whereas if Rn is 1 then the

centres are randomly distributed. If Rn is more than 2.15 then the centres are uniformly distributed.

In our case Rn comes out to be 1.15, suggesting that the urban centres in the region are not

uniformly spaced. The distribution is of the random kind. For the perfect uniform spacing

according to king the ratio should be 2.15. It is significant to point out that perfect uniform spacing

is only distant possibility because the pattern of distribution is influenced greatly by various

physical, cultural and economic activities. The transport network of rail, road and river also plays

the decisive role in location of urban centres.

Table 3

Distribution patterns of class wise urban centres in district

Class of town Number of towns Average distance Rn

Class I 1 12 0.24

Class II 3 2 0.04

Class III 10 13.62 0.77

Class IV 15 5.27 0.35

Class V 10 6.14 0.32

Class VI 2 45 0.90

Source: Authors’ calculations.


If we now consider the class wise distribution of urban centres we can conclude that the class I and

II towns in the district have a clustered distribution whereas the other class of towns have random

pattern of distribution (Table 3).

For the overall development of any region there should be specified number of service centres

properly linked with lower order settlements of specified number. According to Christaller

analysis number of higher order centres is less in number and the distance between them is more.

As we go down the hierarchy number of settlements increases but their size and distance between

them reduces. But distribution in the Nagpur district does not satisfy these conditions. The mean

distance between class III towns should be less than class IV towns which is not so. Even the

number of class I and class II town is the same. This means that there are insufficient numbers of

class II towns. The number of class V and VI towns is less than that of class IV towns, which

should have been comparatively more.

FUNCTIONAL CLASSIFICATION OF THE TOWNS OF THE REGION

Function is the essence of the towns without which they cannot survive. Dickinson observes,

“Functions are the driving force of city life and influence to a very large extent its growth and

morphology”. The urban centres as central places exist primarily to fulfil the multiple needs of the

people within its tributary area by discharging the various functional activities. In fact they have a

complex functional fabrication in their internal structure that they are multifunctional in character.

However some specialize in some one or other function. In each centre at least one activity

predominates the others. Thus they differ in functional specialization. In the present area of study

there are towns, which are unifunctional, bifunctional, trifunctional and diversified. In view of this

an attempt has been made to have the urban centres of uniform function in an array by

distinguishing their functional differentiation and to relate them to geographical factors. Such a

classification also aims at analyzing the spatial distribution of towns of various functional types

which can be meaningful in suggesting a balanced and ideal distribution of tons according to

functional needs of the people.

Declining proportion of non-workers is indicative of the increasing kinds of employment and

consequent declining inequalities, but the worrisome feature is the reduction in the percentage of

cultivators who are the backbone of the district. A further examination of the figures shows the

decline in cultivators from 14.6 per cent to 11.0 per cent in 2011. Considerable numbers of

cultivators are lured by the increasing land prices and sell off their cultivable lands to the investing

urban rich.

Nelson’s Method

According to Nelson “the proportion of the labour force actually employed in a service is of much

more direct significance to the economy of the city than the value or volume of sales of goods or

of services performed or similar measures for the manufactured products in a city”. The census of

population recognizes 9 categories of livelihood classes in the towns, which are –

1] Cultivators 2] agricultural labourers 3] livestock and fishing 4] mining and quarrying 5]

manufacturing 6] construction 7] trade and commerce 8] transport and communication 9] other

services.


These have been condensed to I] Primary activity [1, 2, 3, 4]: II] Manufacturing activity [5, 6]: III]

Commerce: IV] Transport: V] Other services

Table 4

Proportion of Labour Force in Selected Activities of the Urban Centres - 2011

Urban Centre Primary

Activity Manufacturing Commerce Transport Service

Nagpur 3.9 32.7 23.4 12.6 27.4

Kamptee 5.6 44.7 18.5 10.1 21.1

Umred 49.8 17.6 14.0 3.3 15.2

Wadi 2.0 56.4 8.9 14.7 18.0

Katol 48.9 9.2 15.2 5.1 21.7

Digdoh 0.7 59.2 7.4 1.9 30.8

Savner 49.3 12.3 15.2 6.0 17.2

Ramtek 38.0 16.0 17.4 4.9 23.6

Kanhan 29.5 32.4 12.0 6.9 18.5

Narkhed 67.2 6.0 10.1 2.8 14.0

Chicholi 28.0 22.2 9.6 5.3 34.9

Mahadula 5.5 34.3 6.8 6.9 46.5

Kalmeshwar 38.1 28.6 12.5 6.0 14.8

Tekadi 83.2 3.8 4.3 3.5 5.1

Wanadongri 16.7 62.2 7.5 1.5 12.1

Nildoh 1.0 66.4 4.7 1.4 26.4

Khapa 49.4 24.7 10.6 2.6 12.0

Kamptee cant 4.2 10.3 4.3 5.2 75.9

Sonegaon 0.9 29.9 1.8 0.6 66.9

Walani 82.3 3.8 5.7 4.4 3.8

Yerkheda 19.6 28.9 10.8 10.4 30.3

Devlameti 3.7 59.5 9.7 3.7 23.3

Mowad 71.0 11.2 8.5 0.7 8.6

Sillewada 84.0 3.1 5.2 2.4 5.4

Kandri 63.0 24.4 4.0 3.7 5.0

Mohpa 63.9 11.1 9.2 0.8 15.1

Mouda 46.9 16.4 11.5 6.4 18.9

Koradi 14.6 57.9 4.7 0.8 21.9

Nagalwadi 16.8 38.7 7.0 2.8 34.6

Bori 2.0 56.4 8.9 14.7 18.0

Takalghat 29.0 32.9 12.0 6.9 18.5

Kandri [p] 28.0 22.2 9.6 5.3 34.9

Bhokara 3.7 59.3 9.7 3.7 23.5

Borkhedi 19.6 28.9 10.8 10.4 30.3

Waghoda 29.5 32.4 12.0 6.9 18.5

Wadhammna 28.0 22.2 9.6 5.3 34.9

Isasani 16.7 62.2 7.5 1.5 12.1

Hudkeshwar 38.1 28.6 12.5 6.0 14.8

Narsala 38.0 28.7 12.5 5.9 14.8

Bamhni 19.6 28.9 10.4 10.8 30.3

Chandakpur 30.0 32.4 12.1 6.4 18.5

Source: District census 2011

Functional Specialization

To determine the degree of functional specialization the indices were calculated by using the

nelson’s method of standard deviation. The principle has been to conceive of a town and to


compare the occupational pattern of other towns with this average town. With this end in view

first of all the percentages of labour force in each of the five activity groups for the ten urban

centres were calculated

The arithmetic average for each activity group was calculated and with the help of this the

standard deviations for all activity groups were computed separately. By adding the standard

deviations to the mean three degrees of variation from the mean were distinguished.

In order to grade the intensity of specialization centres with +1S.D., +2S.D. and above

respectively were termed as specialized, very much specialized and highly specialized. Centres

near 1S.D. in one particular function [which are approaching 1S.D. limit] have also been

tentatively considered. Towns with over 1S.D. from the average for any of the activity [suppose

manufacturing] was given M1 rating and with over 2S.D. as M2 rating and so on. A similar

process was followed for all other functional groups as well; the distinction in unifunctional,

bifunctional, trifunctional and diversified centres has been made in the following manner –

1] If a town has positive deviation more than 1S.D. from the mean for only one functional class, it

has been designated as unifunctional town

2] If the towns have a positive deviation of more than 1S.D. in two functions then they have been

designated as bifunctional towns

3] If the towns have a positive deviation of more than 1S.D. in three functions then they have

been designated as trifunctional towns

4] If the positive deviation is less than 1S.D. for all functional groups the towns have been

classified as diversified towns.

In the above table – P= primary activity; M= manufacturing activity; C= commerce and trade; T=

transport activity; S= service activity

Functional Classification in Nagpur

Unifunctional Towns

There are 17 unifunctional towns in the region but the very much specialized towns are only three

of Nildoh, Kamptee cantt, Sonegaon and the remaining 14 are specialized with value between

1S.D. and 2S.D. of these 3 are class III size, 8 are of class IV size and 6 of class V.

Primary activity - The minimum labour force required for a town to be grouped in this is 61.7 per

cent. Narkhed, Tekadi, Walani, Mowad, Sillewada, Kandri, Mohpa are the towns which have

67.29 per cent, 83.20 per cent, 82.28 per cent, 70.99 per cent, 83.97 per cent, 62.93 per cent,

63.85 per cent respectively of the labour force in primary activity. This indicates that agriculture

and allied services are still dominating the economy of these towns. So far they have not been

provided complete urban amenities.

Manufacturing activity - Among the unifunctional town Nildoh is the town with very much

specialization in manufacturing as 66.35 per cent of labour force is employed in this activity

where the average of [1S.D. = 46.99 per cent; 2S.D. = 65.57 per cent].

Commercial towns - Ramtek specializes in commerce and trade employing 17.44 per cent of the

labour where the average of [1S.D. = 15.97 per cent]. It is basically due to the religious tourist

importance attached to the place. Also the agricultural production is of considerable importance.


Service - Services appear to be the chief function of Kamptee cantonment and Sonegaon as it has

high specialization with 75.94 per cent and 66.91 per cent of labour in service against average of

[1S.D. = 39.47 per cent; 2S.D. = 55.88 per cent] due to cantonment board. Mahadula is

specialized with 46.45 per cent of labour in service sector.

Bifunctional Centres

Although Nagpur is the largest central place of the region catering various functional needs of the

people yet it shows a high degree of specialization in commerce and transport activities. Hence it

is grouped as bifunctional centre. Due to its strategic location in central India, Nagpur specializes

in commercial and transport activities. These activities employ 23.36 per cent and 12.64 per cent

of labour against average of [1S.D. = 15.27 per cent; 2S.D. = 20.89 per cent] for commercial

activities and average of [1S.D. = 8.34 per cent; 2S.D. = 11.95 per cent] for transport activities.

Wadi in the urban agglomeration of Nagpur also specializes in manufacturing activity with 56.39

per cent of labour force against average of [1S.D. = 48.99 per cent; 2s.d. = 65.57 per cent]. Wadi

shows high specialization in transport with 14.70 per cent of labour in this field due to its being

the octroi toll depot.

Kamptee is bifunctional class II town specialized in commercial and transport activities with 18.46

per cent labour in commercial and 10.10 per cent in transport activity.

Diversified Towns

Umred, Katol, Savner, Kanhan, Chicholi, Kalmeshwar, Khapa, Mansar, Totladoh do not have

specialization in any function hence are diversified. The geographical surroundings do not favour

the location of these towns. The main problem, which these towns come across for their

development, is of easy accessibility by transport and communication. Mostly these towns have

more labour in primary activity.

IDENTIFICATION OF DIFFERENT ORDER OF URBAN FUNCTIONS

Nature and Spatial Pattern of Urban Functions

Towns and cities show functional specialization to certain extent. The number and complexity of

the functions vary with the size of the urban structure and with other variables including the nature

of the areas, which are served. Some of the functions occur almost universally in urban settlements

of a given size. These are known as the ‘Central place functions’ and the settlements called

‘Central Places’. Following can be regarded as characteristically urban functions –

1] Central place functions or general services, which are carried out for a more or less extensive

but contiguous area

2] Transport functions, which are carried out at, break of bulk points along the major lines of

communications.

3] Specialized functions, which are carried out for non-local, non-contiguous areas. These urban

functions need not occur in isolation. The relative importance of each function does vary from one

town to another. Based on the dominance of one particular type of function distinct type of towns

can be marked out.

Identification of Urban Hierarchy in Nagpur

Urban hierarchy is defined as the ranking of cities into successive groups on the basis of the

number of functions or the size of the population served by the function or by the area of the


population served. There exist discrete classes of central cities, towns with associated groups of

functions organized together in a nesting pattern. The concept developed by Walter Christaller

suggests that the urban centres are the central places providing a wide variety of functions to the

surrounding areas [complementary regions].

Table 9

Different Orders of Urban Functions for identifying Urban Hierarchy

Orders Urban functions Threshold Values

First order 1 Publication of daily newspaper 150000

Second order

2 Engineering colleges 75000

3 Working women’s hostel 55000

4 Stadium 22000

5 Arts / science college 17000

6 Auditorium 14000

Third order

7 Adult literacy 12500

8 Railway station 11500

9 Hospitals 11000

10 Dispensary 10000

11 Vocational training 8500

12 Cinema theatres 8000

Fourth order 13 Public library 7500

Fifth order 14 Primary school 3000

15 Banks 2500

Source: Authors’ calculations

Grouping of Urban Functions

Urban functions have been grouped into different classes as per population threshold i.e. minimum

population required for the existence of the function. Keeping I view the degree of reliability of

the collected information and the details Reed and Munch method of calculating population

thresholds has been chosen to compute the threshold values

In this technique all the towns in the district have been grouped as per their classes. Under these

classes places with function Fi and without Fi are noted. Cumulative summing of the two columns

gives us the index [indicating the absence of function at this and greater level] and the other index

[indicating the presence of this function at this and smaller level].

The threshold values that are calculated through the graphs give the order of urban functions

(Table 5). Detailed examination of these variables indicates that wide variety of variables do have

a role to play in the attainment of the present status of the towns.

Distribution of Urban Functions in Urban Centres of Nagpur

After grouping the urban functions according to their population thresholds the weightage to all

the 15 urban functions have been calculated based on the following formula:

Wi = n / [Fi X t]

Where, N = number of settlements in the district, Fi = total number of settlements having the ith

facility, T = frequency of occurrence of ith

facility, Wi = weightage to ith

facility.

The analysis of functional structure reveals that the urban centres in the district are characterized

as central places rendering central place functions to their population and to surrounding areas.

Within the centres the variation is noted both in the nature and intensity of the function. Spatially


first order functions are confined to the class I centre Nagpur. Compared to it the functions of

other order are more widespread but the fifth order functions are noticed in all the towns. The

spatial distribution of different order urban functions confirms the relationship as discussed by

Christaller i.e. the relationship existing between size of the centre and the nature of the function.

Higher order functions are confined to big towns while lower order functions are observed in all

towns of all sizes. Other relationship highlighted by the study is that the large towns render

functions of higher order in addition to all those lower order functions, which exists in the smaller

centres. Their existence has made them distinct from the other centres. Another point to be noted

is that the largest concentration of lower order functions is also noticed in cities. The small and

medium towns have neither that many functions nor have that much variety of functions. The

phenomenon of urbanization in a way is also associated with the geographic setting and resource

base of the district. It is seen that the pattern of urbanization cannot be even or uniform

throughout. It is related to the economic base of the particular area and the degree of

industrialization. In Nagpur district the degree of urbanization is the highest and the urban centres

are clustered together in the proximity of the regional centre i.e. Nagpur. Urban centres are

clustered along the transport lines.

Table 6

Urban Concentration Index of Various Tehsils in Nagpur

Name of Tehsil Concentration

index

Level of

concentration

Nagpur [ u ] 156.3 Very high

Savner 54.7 Medium

Parshivni 51.6 Medium

Ramtek 37.5 Low

Mouda 0.0 No urbanization

Kamptee 93.8 High

Kuhi 0.0 No urbanization

Bhiwapur 0.0 No urbanization

Umred 51.6 Medium

Nagpur [r] 39.1 Low

Hingna 60.9 Medium

Katol 37.5 Low

Narkhed 35.9 Low

Kalmeshwar 32.8 Low


Pattern of Urban Concentration

For demarcating the spatial urban concentration on the map, the concentration index has been

calculated by the formula: CI = (L/R) X 100, where L = Local coefficient = [urban population of

tehsil / total population of tehsil], R = regional coefficient = [urban population of region / total

population of region]. The values are provided in Table 6.

Extent of Urban Influence

The degree of urbanism in the district has also been determined by demarcating the hypothetical

extent of influence exercised by each town. Assuming that the extent of urban influence of each

town will be circular in shape the radii of influence have been computed by the formula:


R = Sq. rt [(T X A) / U ]

where, T = population of town, A = total area of region, U = total urban population of region.

Based on the above formula the extent of influence of each town has been computed (Table 7).

Table 7

Extent of Urban Influence of Urban Centres in Nagpur

Urban Centres Size Rank Extent of Influence

Nagpur 1 90

Kamptee 2 17

Wadi 3 13

Umred 4 13

Katol 5 12

Digdoh 6 11

Wanadongri 7 11

Savner 8 10

Hudkeshwar 9 9

Kanhan[p] 10 9

Ramtek 11 9

Mahadula 12 8

Narkhed 13 8

Nildoh 14 8

Kalmeshwar 15 8

Chicholi 16 8

Narsala 17 8

Yerkheda 18 7

Khapa 19 7

Mouda 20 7

Devlameti 21 7

Tekadi 22 6

Borkhedi 23 6

Kamptee cantt. 24 6

Chandakpur 25 6

Bori 26 6

Tekalghat 27 6

Kandri 28 6

Bamhni 29 6

Walani 30 6

Sonegaon 31 6

Mowad 32 5

Bhokara 33 5

Waghoda 34 5

Sillewada 35 5

Mohpa 36 5

Koradi 37 5

Wadhammna 38 5

Kandri[R] 39 4

Isasani 40 4

Nagalwadi 41 3



Figure 2

Extent of Urban Influence


Table 12

Functional Centrality Index of Urban Centres

Ist Order

Nagpur 81

IInd Order

Kamptee M 3.27 Bhokara 0.41

Wadi 1.61 Hudkeshwar 0.38

Umred 1.37 Yerkheda 0.37

Digdoh 1.29 Khapa 0.37

Katol 1.07 Borkhedi 0.37

Kamptee cant 0.85 Narkhed 0.36

Savner 0.82 Isasani 0.35

Ramtek 0.76 Bori 0.35

Nildoh 0.75 Takalghat 0.32

Kanhan 0.70 Devlameti 0.32

Mahadula 0.69 Narsala 0.30

Wanadongri 0.66 Walani 0.27

Chicholi 0.66 Waghoda 0.25

Kalmeshwar 0.53 Kandri (P) 0.25

Sonegaon 0.47 Chandakpur 0.25

Tekadi 0.46 Sillewada 0.24

Nagalwadi 0.46 Mohpa 0.15

Bamhni 0.45 Kandri (R) 0.15

Wadhammna 0.43 Mowad 0.13



Functional Centrality Index

The basic problem in the context of hierarchy is that of determining the centrality. Different

authors have used different variables to express the centrality. But the suitability of variables is

equally an important factor for its selection must take an account of the prevailing conditions in

the respective regions of study.

The district for example has 7 class V towns but to think that all of them have the same regional

importance is absolutely wrong. A little refinement that could be made in this was calculating the

functional centrality index based on Sven Godiund’s formula of retail trade. As retail trade

activities are only little pronounced, the proportion of non-primary workers of a place to that of

total non primary workers in a region served as the basis of functional centrality index for central

place studies in India. But to examine the relative importance of towns only the total urban non-

primary workers in a region should be considered.

F.C.I. = [NPW X 100] / UNP

Where NPW = non-primary workers of a central place

UNP = total urban non-primary workers

The mean of centrality index was calculated for grouping the towns in the hierarchical orders. The

mean was estimated to be 3.4, based on which the tiers of centres may be delineated.

1] Low order centres – they are the centres of the third order as the F.C.I. is below 3.4 [1 mean]

and almost all the urban centres except Nagpur fall in this category.

2] Intermediate centres – there are no intermediate centres with the F.C.I. value between 3.4 and

6.8.

3] Regional centre – only Nagpur has the F.C.I. value much above the minimum required value of

6.8 and above to be the regional centre in the district.

CONCLUSION

The distribution of urban settlements based on hierarchy is neither ideal nor balanced. The

concentration of one order in one sector and the absence of the same in the other part of the region

are not desirable and there is therefore a need of redistribution of centres based on a model.

Raising the status of lower order centres and having relationship in distribution of growth nodes

and service centres within the district may help achieve this.

________________________________________

References

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_________ (1984), Trends in Regional Disparities,” Productivity, Vol.35, No.2, July-September.


TRIBAL POPULATION IN INDIA: REGIONAL DIMENSIONS &

IMPERATIVES

Tattwamasi Paltasingh1 and Gayatri Paliwal

2

Scheduled Tribe (ST) population represents a heterogeneous group scattered in different regions

of India. The differences are noticed in language, cultural practices, socio-economic status and

pattern of livelihood. The STs are confronted with problems like forced migration, exploitation,

displacement due to industrialization, debt traps and poverty. Based on the regional classification

with diverse socio-cultural issues, the present paper focuses on the profile of tribal population

through an analysis of the socio-economic indicators like literacy, work participation, livelihood,

occupational pattern, health, poverty and migration. The impact of industrialization and

urbanization on ST population residing in different regions has been highlighted. The paper has

been concluded with relevant suggestions with implications for policies with a focus on region

specific issues.

INTRODUCTION

The scheduled tribe (ST) population is 104.2 million, which is 8.6 percent of the total population

of India (Census 2011). Madhya Pradesh, Maharashtra, Orissa, Gujarat, Rajasthan, Jharkhand,

Chhattisgarh, Andhra Pradesh, West Bengal, and Karnataka are the states having a large number

of ST populations. The overall areas inhabited by the tribal population constitute a significant part

of the underdeveloped areas of the country. About 93 per cent of them live in rural areas and are

engaged in agriculture and allied activities. The socio-demographic figures clearly reveal the

disadvantaged position of the STs compared to other category of population. The literacy rate

among the STs in India is 63.1 per cent (NSSO, 2010), which is lower than the national literacy

rate i.e. 72.8 per cent (Census, 2011). The dropout rate among the STs is 70.5 which is much

higher than the dropout rate of all categories i.e. 49.15 percent. The sex ratio among the STs is 990

which is relatively better than the general population i.e. 940 (Census, 2011). The infant mortality

rate among the ST children is 62.1 which is 57 for the other social groups. The child mortality rate

among the tribes is 35.8 which is much higher than the other social groups i.e. 18.4 percent. The

work force participation rate (WFPR) is 60 among the ST population and that is higher than the

total population i.e. 53percent (NSSO, 2010). The WFPR indicates that majority of the ST

population are engaged in unorganized sector without any job security.

The demographic figures reveal that the tribal population is the most disadvantaged, exploited and

the neglected lot in India. Despite certain constitutional provisions, they are backward compared

to the general population, even their situation is worse than the Schedule Caste (SC) and Other

Backward Class (OBC) population (Xaxa, 2012). Majority of the tribes used to reside in the

remote forest areas, remain isolated, untouched by civilization and unaffected by the development

processes. This situation has changed to a great extent over the years. As long as the tribes have

1 Associate Professor, Sardar Patel Institute of Economic and Social Research (SPIESR), Ahmedabad,

Gujarat; email: [email protected] 2 Research Associate, Sardar Patel Institute of Economic and Social Research (SPIESR), Ahmedabad,

Gujarat


access to resources generated from the forest, they have no difficulties in satisfying their basic

needs. In turn they have an interest in preserving the forest as it is their life support system. But

large scale industrialization, urbanization and exploitation of natural resources due to deforestation

to meet the urban and industrial demands has greatly affected the livelihood pattern. This trend has

been responsible for displacing large number of tribes from their habitations (Nathan & Xaxa,

2012; Singh, 2012).

The initiation of developmental projects and rapid industrialization has not made much difference

in the socio-economic status; rather in some instances the situation of STs has become worse. The

widespread poverty, illiteracy, malnutrition, absence of safe drinking water, inadequate sanitation

facility, poor living conditions, ineffective coverage of maternal, child health and nutritional

services has made their condition more vulnerable. The subsequent section has focused on the

regional variation of tribes residing in different parts of India. The paper has also analysed the

issues related to literacy, work participation, livelihood, occupational pattern, health, poverty and

migration; impact of industrialization and related consequences among STs in specific regions.

Relevant suggestions and recommendations are included in the concluding section of the paper.

REGIONAL VARIATIONS OF TRIBES IN INDIA:

The ST population of India are scattered all over the country depicting heterogeneous culture and

socio-economic status. It is interesting to know the different types of tribes residing in different

geographical location and confronting different situation. There are about 700 tribes (with

overlapping categories in some States/UTs) as per notified Schedule under Article 342 of the

Constitution of India (Annual Report, Ministry of Tribal Affairs, 2012-13). Classifications of the

tribes in different regions depict a diverse picture in India.

The total number of tribes, Primitive Tribal Groups (PTGs) and list of major tribes in different

states and union territories (UTs) in India reflect the heterogeneity among them (Table-1). There

are about 75 such groups identified as PTGs located in 17 States and in 1 UT. There are many

tribal communities having stagnant or declining population with low level of literacy and poor

socio-economic condition. Most of these groups are small in number and generally inhabit remote

localities having poor infrastructure and administrative support. Many of them are socio-

economically under-privileged and not benefited much from developmental projects and other

initiatives. The ST population and PTGs has been divided broadly into seven regions residing in

different states and islands (Table 1).

North Eastern Region

North East India comprises the states like Arunachal Pradesh, Assam, Manipur, Meghalaya,

Mizoram, Nagaland, Tripura and Sikkim. The region is surrounded by foreign territories like

Bhutan, Tibet-China, Burma, and Bangladesh on the north-south and the east. The long narrow

passage in the west connects the region with West Bengal and the rest of India (Deb, 2010). It

represents a kind of ethnological transition zone between India and the neighbouring countries.

This region is the homeland of about 145 tribal communities of which 78 are larger groups; each

with a population of more than 5000 persons. They constitute around 12 per cent of the total tribal

population of India (Ali & Das, 2003). In Mizoram, the tribes constitute 94.75 per cent of the total

population of the state. The percentages of STs to the total population in the states like Assam,

Manipur and Tripura, is 12.4, 35.1 and 31.8 respectively (Census, 2011). The PTGs in Tripura


include Riang and Maram Naga in Manipur. This region depicts extreme heterogeneity in terms of

distribution of tribal populations in different areas including their social structures and culture.

Table 1

Tribes in India: Regional Classification

States Major Tribes No. of

Tribes PTGs

North East Mizoram Lusai, Kuki, Garo, Khasi, Jayantia, Mikir etc. 15 NA

Nagaland Naga, Kuki, Mikir, Garo, etc. 05 NA

Meghalaya Garo, Khasi, Jayantia, etc. 17 NA

Sikkim Lepcha, Bhutia, Limbu, and Tamang

4 NA

Tripura Chakma, Garo, Khasi, Kuki, Lusai, Liang, Santhal etc 19 01

Arunachal Pr Dafla, Khampti, Singpho etc. 16 NA

Assam Boro, Kachari, Mikir (Karbi), Lalung, Hajong etc 15 NA

Manipur Meities, Pangals, Naga tribes, Kuki etc. 33 01

East Orissa Birhor, Gond, Juang, Khond, Korua, Oraon, Tharua,

etc. 62 13

West Bengal Asur, Birhor, Korwa, Lepcha, Munda, Santhal, etc. 40 03

Bihar Asur, Banjara, Birhor, Korwa, Oraon, Santhal, etc. 33

09 Jharkhand

Biga, Banjara, Bathudi, Bedia, Bhumij, Chik, Baraik,

etc 30

Central Madhya Pradesh Bhil, Birhor, Damar, Gond, Kharia, Oraon, Parahi, etc. 21 03

Chhattisgarh Gond, Baiga, Korba, Bison Horn Maria, Halba etc. 31 04

West

Gujarat Bhil, Dhodia, Gond, Siddi, Bordia, etc. 31 05

Rajasthan Bhil, Damor, Garasia, Meena, Sahariya etc. 12 01

Maharashtra Bhil, Bhunjia, Chodhara, Dhodia, Nayaka, Rathwa etc. 48 03

Goa Dhodi, and Siddi (Nayaka). 08 NA

Daman & Diu

Dubla, Dhodia, Varli, Naikda & Siddi 5 NA

Dadra&Nagar Dhodia, Dubla, Kathodi, Kokna, Koli, Dhor, and Varli 7 NA

North UP & Uttaranchal Bhoti, Buxa, Jaunsari, Tharu, and Raji 15 2

Himachal Pradesh Gaddi, Gujjar, Lahuala, Swangla, etc. 10 NA

J&K Chdddangpa, Garra, Gujjar, Gaddi, etc. 12 NA

South Andhra Pradesh Bhil,Chenchu, Gond, Kondas, Lambadis, Sugalis etc. 35 12

Kerala Adiyam, Kammrar, Kondkappus, Malais, Palliyar, etc. 43 05

Tamilnadu Irular, Kammara, Kondakapus, Kota, Toda etc. 36 06

Karnataka Bhil, Chenchu, Goud, Kuruba, Koya, Mayaka, Toda,

etc.

50 02

Islands

Andaman&

Nicobar Islands

Jarawa, Nicobarese, Onges, Sentinelese, Shompens

and Great Andamanese 06 05

Lakshadweep Amindivi, Koyas, Malmis and Malacheries 0 NA

Source: Classified based on Annual Report, 2012-13. Ministry of Tribal Affairs.

Note: NA (Not Available): No PTGs are available in these states.


Literacy among the tribes of the north eastern region is relatively higher compared to other

regions. In the ranking of the ST literacy rate (per 1000 persons among 5 years and above) states

like Mizoram, Meghalaya, Nagaland, Sikkim and Manipur occupy 1st, 2

nd, 4

th, 6

th and 8

th position

respectively. It is interesting to note that the literacy rate of these states is higher than the national

literacy rate. ST population of Assam, Tripura and Arunachal Pradesh ranks 9th

, 11th

, and 13th

position respectively with regard to the literacy rate (NSSO, 2010). The sex ratio in the states like

Meghalaya, Mizoram, and Nagaland and Manipur is much higher compared to other regions

(Census, 2011).Literacy among the tribes of the north-eastern and island regions is relatively

higher than tribes in other regions (Sharma, 2009). STs residing in north eastern states are more

urbanized as compared to other region.ST children in the north eastern states didn’t come under

malnourished category as compared to all India level (Pala and Khongjoh, 2012). These findings

supports that the STs in north eastern states are in better position than the tribes residing in the

other parts of India.

Exposure to urbanization and educational expansion has changed the economic and socio-cultural

systems in the North eastern states. It is reported that the benefits of state-sponsored development

have been concentrated particularly among the educated and urban tribal elites. Under

demographic compulsion, rural natives and particularly women confront with challenges like

hardship, poverty and unemployment (Ghosh & Choudhuri, 2011). Despite the high literacy rate

in this region; dropout rate is much higher compared to other regions. States like Meghalaya,

Arunachal Pradesh, Tripura, Manipur and Assam exhibit high infant mortality rate among ST

population. The rate of landless households is higher in the state like Mizoram (19.5), Arunachal

Pradesh (11.2) and 8.3 percent in Manipur (NSSO, 2010). Availability of power supply and

transport linkages within the region and with the rest of India is still primitive.

Eastern Region

Eastern India comprises of West Bengal, Orissa, Bihar and Jharkhand. The diversity of East India

is evident from its population, nature and the types of tribes residing in this region (Sinha &

Behera, 2009, Basu et al, 2004). Multinational corporations are attracted to exploit the natural

resources and reserves at the cost of tribal livelihood. This is leading to involuntary displacement

of people from their homeland. Development projects in the eastern India particularly in the state

of Orissa are initiated in the areas with tribal dominated populations due to rich natural resources.

Due to these projects the tribal lands continue to be passed on to the hands of non-tribals in Orissa

and some of the investors in the area of Niyamgiri hills in Rayagada district (Jena, 2013). The

same trend is witnessed in other districts like Kalahandi, Koraput, Malkangiri, Kandhamal and

Balasore district. Tribals are alienated from their land and land alienation is one of the important

reasons of poverty and dispossession of tribals in Orissa (Ambagudia,2010).Consequently some

other problems exist like deforestation, loss of agricultural land, environmental degradation, and

marginalization of the STs (Mohanty, 2012). There is low pace of development in Jharkhand, at

the same time the state has one of the richest mineral reserves in India (Roy, 2012).

The literacy rate among the STs in this region is found to be lower compared to other regions of

the country. In the ranking of the literacy rate of ST population (per 1000 persons among 5 years

and above); West Bengal, Bihar, Jharkhand, and Orissa occupy 19th

, 24th

, 25th

and 27th

position


respectively (NSSO, 2010). The major tribes in Orissa are Birhor, Gond, Juang, Khond, Korua,

Oraon, Santhal, Tharua, etc. and the tribes like Asur, Birhor, Korwa, Lepcha, Munda, Santhal, are

found in West Bengal. The major tribes in Bihar are Banjara, Birhor, Korwa, Munda, Oraon,

Santhal, etc. and the tribes like Biga, Banjara, Chero, Chik Baraik, Gond, Ho, Kisan, Kora, Lohra,

and Santhal etc. are found in Jharkhand. Santhal is the common and most populated tribe in the

eastern region.

It is important to note that the maximum number of tribes i.e. 62 in Orissa and large number of

PTGs reside in eastern India; with 13 PTGs in Orissa, 9 in Bihar and Jharkhand and 3 in West

Bengal (Table-1) The PTGs in Orissa are Chuktia, Bhunjia, Birhor, Bondo, Didayi, Dongria

Khond, Juang, Kharia, Kutia Khond, Lanjia Saura, Lodha, Mankirdia, Paudi Bhuyan and Saura.

Many PTGs live entirely on forest resources, but have adopted settled agriculture since more than

a decade. Shifting cultivation used to be their main economic pursuit but now their livelihood

source has been transferred to stable farming and noticed among Chuktia Bhunjia (Sabar, 2010).

Some of these PTGs are losing their identity and even some of them are getting extinguished due

to the rapid urbanization. Due to industrialization and development projects more land is being

acquired to encourage investment by the Indian and foreign investors. They are targeting mining

land and land with rich natural resources in Jharkhand and Orissa (Ekka, 2012). The tribal

displacement is the major issue in this region. Low productivity in agriculture and poor

infrastructure are the major reasons for high rates of poverty in Bihar, Orissa and Jharkhand.

Central Region

The central India tribal belt is rich in natural resources. Stretching from Madhya Pradesh (MP),

and Chhattisgarh, it is one of the poorest regions of the country. More than 90 per cent of the STs

belong to rural area and they are directly or indirectly dependent upon agriculture. Though some

of them have small land holdings, agricultural practices are quite primitive and productivity is low

(Sah et. al. 2008). In the ranking of the literacy rate of ST population (per 1000 persons among 5

years and above) Chhattisgarh and Madhya Pradesh occupies 16th and 23rd position respectively

(NSSO, 2010). The major tribes in Chhattisgarh are Gond, Baiga, Korba, Abhuj Maria, Muria,

Halba, Bhatra and Dhurvaa and the tribes like Bhil, Birhor, Damar, Gond, Kharia, Oraon, Parahi,

etc. are found in MP (See Table-1). The PTGs in Chhattisgarh are Abujhmaria, Birhor, Hill

Korwa, and Kamar; while Bharia and Sahariya are the PTGs reside in MP. PTGs like Baigas

reside in both the states.

STs in this region are facing multiple problems due to natural calamity, crop failure, poverty,

illness, reduced access to land and lack of employment opportunities leading to debt and migration

(Planning Commission Report, 2010). Poverty rate is extremely high among the STs residing in

MP and Chhattisgarh (NSSO, 2010). Central region also depicts high rate of infant mortality

among ST population and situation is worse among the PTGs like Birhor, Korwa, Abhujmaria,

Kamar and Baiga in Chhattisgarh (Dhar, 2012).

Western Region

The states like Gujarat, Rajasthan, Maharashtra, and UTs like Daman & Diu, Dadra & Nagar

Haveli represent the Western part of the country. Bhil is a common tribe found in all three major

states of Western India. The other tribes found in Gujarat are Dhodia, Gond, Siddi, Bordia, etc.

The major tribes in Rajasthan are Damor, Garasia, Meena, Sahariya etc. The common tribes


residing in Maharashtra are Bhunjia, Chodhara, Dhodia, Gond, Kharia, Nayaka, Oraon, Pardhi and

Rathwa (Table-1). The PTGs in Gujarat are Kolgha, Kathodi, Kotwalia, Padhar and Siddi. PTGs

residing in Maharashtra are Katkari/Kathodi, Kolam and Maria Gond. On the ranking of tribal

literacy (per 1000 persons among 5 years and above) Maharashtra is placed in 18th

position.

Gujarat and Rajasthan occupy 20th

and 26th

position respectively. Daman & Diu indicates better

literacy rate and ranked at 3rd

position; Dadra & Nagar Haveli occupies the 17th

position (NSSO,

2010).

The tribal handicrafts are specialised skills which are passed on from one generation to another

and these handicrafts are the means of livelihood among the artisans in Rajasthan. In some

instances the STs with such skills migrate for alternative livelihood. This age-old activity may

disappear if they are not facilitated to retain their traditional skills (SEEDS, 2006). The livelihood

of STs in Maharashtra and Gujarat includes agricultural activities, wage labor, collection of forest

products, animal husbandry (Chattopadhyay & Durdhawale, 2009). There are very few job

opportunities for the STs in organized sector (Kokate, & Solunke, 2011). Maharashtra from the

western region depicts high poverty rate among the STs (NSSO, 2010). The main problem faced

by STs in Gujarat is migration due to lack of sustained employment and scarcity of water in some

tribal regions that affect the agricultural and allied activities.

Northern Region

North India includes states like Himachal Pradesh (HP), Jammu & Kashmir, UP and Uttarakhand

(previously known as Uttaranchal). The tribes found in UP and Uttaranchal are Bhoti, Buxa,

Jaunsari, Tharu, Raji, etc. The major tribes found in Himachal Pradesh are Gaddi, Gujjar, Lahuala,

Swangla, etc. and tribes in Jammu & Kashmir (J& K) are Chdddangpa, Garra, Gujjar and Gaddi

(Table-1). The PTGs in U.P. and Uttarakhand are common and they are Buksa and Raji. On the

ranking of literacy of ST population (per 1000 persons among 5 years and above) Himachal

Pradesh occupies 23rd

position; Uttaranchal and Jammu & Kashmir occupy 15th

and 30th

position

respectively. UP occupies 28th

position in the ranking of the ST literacy rate (NSSO, 2010). Gross

enrolment ratio of scheduled tribe (ST) students is quite low in J & K (MHRD, 2011).

UP & Uttaranchal from the northern region indicate high poverty rate among STs. Large number

landless households i.e 9.1 percent are found in Himachal Pradesh (NSSO, 2010). Livelihood in

north India is based on agriculture. Wood carvings are important handicraft of Uttarakhand due to

the availability of wood as raw material from nearby forest areas (SEEDS, 2006). At present, the

high costs of raw materials due to deforestation compel the STs to migrate for livelihood.

Southern Region

States like Andhra Pradesh, Kerala, Tamilnadu and Karnataka are included in the Southern region.

The main occupations of the tribes in the Southern region are settled agriculture, podu (shifting)

cultivation and collection of Non-Timber Forest Produce. The tribes in Andhra Pradesh are Bhil,

Chenchu, Gond, Kondas, Lambadis, Sugalis etc. The major tribes in Kerala are Adiyam,

Kammrar, Kondkappus, Malais, Palliyar, etc. The common tribes residing in Tamilnadu are Irular,

Kammara, Kondakapus, Kota, Mahamalasar, Palleyan and Toda. The tribes residing in Karnataka

are Bhil, Chenchu, Goud, Kuruba, Kammara, Kolis, Koya, Mayaka, Toda, etc. (Table-1). Higher

number of PTGs resides in southern India; with 12 PTGs (Chenchu, Bodo Gadaba, Gutob Gadaba,

Dongria Khond, Kutia Khond, Kolam, Konda Reddi, Kondasavara, Bondo Porja, Khond Porja,


Parengi Porja, and Thoti) in Andhra Pradesh, 5 in Kerala, 6 in Tamilnadu and 2 in Karnataka.

Literacy among the tribal population of this region is lower than the national level literacy rate of

general and tribal population in India except Kerala which ranks 7th

position in literacy rate of ST

population (per 1000 persons among 5 years and above). Tamilnadu, Karnataka and Andhra

Pradesh occupy 21st, 22

nd and 28

th position respectively with regard to literacy rate among the STs

(NSSO, 2010). In Andhra Pradesh, the livelihood of STs is based on the occupations like making

of toys, baskets, mates, local cosmetics and collection of leaves, honey, medicinal plants etc.

Tribes were displaced at the cost of private gain for mining in the Narayangiri Hills near

Lanjigarh; Araku Valley and Jerrela Hills of Visakhapatnam district in Andhra Pradesh

(Oskarsson, 2012; Prasad et al, 2012). Various factors are responsible for the slow development

among the STs in this region like poor irrigation facility for agricultural land, displacement and

migration and slow pace of resettlement and rehabilitation (Reddy & Kumar 2010). The

percentage of landless households is higher in Andhra Pradesh (7.9) compared to southern region.

Poverty percentage is moderate in the states like Andhra Pradesh and Karnataka (NSSO, 2010).

Island Area

The Andaman and Nicobar Islands is the largest archipelago in the Bay of Bengal, consisting of

306 islands and 206 rocky outcrops; covering area about 8200 sq. kms. Hunting is the main source

of food and livelihood of the ST population in Andaman and Nicobar Islands. They also grow

vegetables and run poultry farm for their livelihood. The excellent craftsmanship of the STs in

Lakshadweep has made them popular across the globe. Some of them own land in these islands

while others work as labourers. The majority of the STs in Lakshadweep follow Islam as religion.

Lakshadweep ranks 5th

position, followed by Andaman & Nicobar which occupies 10th

position in

the literacy rate (per 1000 persons among 5 years and above) among STs (NSSO, 2010). The ST

literacy rate in island region is comparatively higher compared to other regions. Despite that the

gross enrolment ratio among scheduled tribe (ST) students in class I-VIII is quite low in the island

region. The common tribes residing in Andaman & Nicobar Islands are Jarawa, Nicobarese,

Onges, Sentinelese, Shompens and Great Andamanese etc. The tribes residing in Lakshadweep are

Amindivi, Koyas, Malmis and Malacheries (Table-1). The PTGs in Andaman and Nicobar Islands

are Great Andamanese, Jarawa, Onge, Sentinelese and Shom Pen. PTGs like Andamanese follow

a peculiar cultural practice that can prove the capacity of the young boys to hunt and gather in

accordance with a prescribed norm that can help in negotiating marriage with the father of the

selected partner (Pandya & Mazumdar, 2012). There are no PTGs in Lakshadweep islands.

Unemployment is high among the STs in this region. Poor infrastructure and inadequate water

supply is the main problem and this is due to topography of the islands.

Challenges Ahead

The level of socio-economic development varies considerably between tribal and non-tribal

population, between one region to another region; between one tribe to another tribe; and even

among different tribal sub-groups. These disparities and diversities make tribal development more

challenging and demanding. In India 52 per cent of the STs belong to the category of Below

Poverty Line (BPL) and 54 per cent of them have no access to economic assets such as

communication and transport (World Bank, 2011). Issues like literacy, work participation and


livelihood, changes in occupation pattern, poverty, displacement, migration and health issues are

the major areas of concern among the STs.

Literacy among the tribes of the north-eastern and island regions is relatively higher but despite

that high dropout rate and infant mortality rate is also observed in the north eastern region. In the

western region; Gujarat and Maharashtra are high on infant mortality among ST population. Child

and infant mortality rates are higher among the STs in Orissa as compared to other states. Large

scale displacements and unsatisfactory compensation and rehabilitation are confronted by the STs

in India. The eastern region is facing large displacement due to industrialization and development

projects. North eastern region still faces the problems like poor infrastructure, inadequate transport

connectivity and less power supply.

Dependency on agriculture, natural calamity, crop-failure, reduced access to land and lack of

employment are the contributing factor for poverty in the states like MP and Chhattisgarh. Poverty

rate is extremely high in states like MP and Chhattisgarh of central region and a large part of ST

dominated eastern region consisting of states like Bihar, Orissa and Jharkhand. Rates of

unemployment are high in the tribals of the island region. Presently the tribes are caught in a

situation where they are losing command over the natural resources, and are unable to cope with

the new pattern of work and resources for living. Majority of them are dependent on daily wages

or labour work because of landlessness. Percentage of landless households is high in some north

eastern states and Himachal Pradesh from the northern region. There are efforts from different

organizations and government for the development of STs. However the initiatives are not enough

and tribal issues as discussed require intensified efforts from all segments and stake-holders.

RECOMMENDATIONS AND CONCLUSION

ST Population depicts heterogeneity at national, state and even in district level having differences

in language, cultural practices and pattern of livelihood which influence their socio-economic

status. Their problems differ from area to area even within their own groups (Dubey, 2009). There

are different types of tribes residing in different parts of the country. The tribes in different regions

of India are different in terms of their rituals and customs and literacy level; economic conditions

and diverse occupational patterns.

Many organizations and government have made substantial efforts to bring positive changes and

resolve the problems faced by the STs. Because of such initiatives progress has been made but still

a lot needs to be done. Region specific approach is required to bring positive change among the

tribes. For example the unemployment problems of the island region can be resolved by

developing fisheries and tourism industry at large scale. There are multiple reasons for the

vulnerable status of STs. In some regions (States like Bihar, Jharkhand, Orissa, Rajasthan, UP and

Andhra Pradesh) where the literacy level of STs is low; are not fully aware of the schemes

available for them. Such information is not clearly disseminated to them. Their access to benefits

is less. The main reason for lesser beneficiaries is the complicated procedure of the sanctioning of

the schemes and poor implementation. Awareness generation to avail the existing schemes and

programs targeted for tribal community is very much required. In the states with low rate of

literacy; special camps can be organized to make them aware of the schemes meant for

educational development. The strategic planning with a special focus to the problems and issues of

the tribes residing in different regions should be implemented; where a particular segment of the


population remains to be under privileged for many decades. To cope with the requirement of the

existing labour market one has to be well equipped with basic skills imparted through education

and training from the very beginning (Chakraborty et al, 2012). Starvation deaths had been

reported among tribes and PTGs in several states including Jharkhand, Madhya Pradesh and

Rajasthan (Khera, 2008). The implementation of the NREGA has changed the situation of tribes in

Rajasthan to certain extent but the situation is not changed in other states. According to the needs

of labour market, training programmes may be implemented targeting the migrated, displaced and

unemployed STs especially in the central and eastern region.

Among the STs the practice of traditional agriculture needs to be encouraged. The farmers and

artisans should be given financial assistance and capacity building training to sustain their skill

and expertise. Access to credit and banking facilities should be made simpler that can benefit the

tribes. Access to the forest products among the forest dwellers should be facilitated in a positive

direction. Only improvement of literacy status may not be sufficient. Vocational and professional

education using the locally available resources needs to be encouraged. Support mechanism and

collaboration between government, NGOs, CBOs, corporate sectors and SHGs need to be

strengthened.

_______________________________

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INPUT-OUTPUT ANALYSIS FOR RURAL INDUSTRIAL DEVELOPMENT OF

PATNA REGION

Rashmi Kumari1 and V. Devadas

2

Rural industries have a major aspect in Indian economy due to scarcity of capital; increasing

unemployment; regional imbalances and disparities; inequalities in the distribution of income and

wealth; and un-utilization and/or under-utilization of rural resources. This study analyses the

potential of rural industrialization and their impact using the system approach, based on resource

availability, in the untapped areas of Patna region. This study aims at analyzing the present

scenario and forecasting the production and demand in the future using input-output model.

Based on these analyses, the location and type of rural industries have been identified on the map

of the Patna region. This study proposes planning model to ensure sustainable development in the

system by imparting rural industrialization in the study area.

INTRODUCTION

Introduction

Patna region, blessed with rich soil, adequate rainfall, propitious hydrological profile, water

resources, and composite climatic conditions, has the high agricultural production potential.

However, its agricultural productivity and processing is very low, resulting in higher degrees of

poverty, unemployment, and absolute deprivation in the region. In fact, the Patna region, India,

can be called as the spirit of the great Indo-Gangetic Plains, one of the most fertile plains of the

world. It is inexplicable that the Patna region has been a wealthy region inhabited by the deprived

people. Hence, the untapped resource reservoir of the region needed to be harnessed judiciously to

liberate the region from its socioeconomic and ecological caliginosity, and trigger the process of

strengthening of the human resource further. It has been widely acknowledged that agriculture

sector is the precursor of the economic growth process. Hence, It is needed to bring another farm

revolution and agro-industrial development for the overall development of the Patna region.

Rural industrialization is an effective mean to achieve balanced development between the rural

and the urban system of any country. Industrialization is the means to advance the sustainable

economic development by creating productive employment and generating value added income,

and hence contributes to the poverty reduction more significantly. Channel of development in the

rural system takes place due to rural industrialization. An increase in the agricultural productivity

releases raw material for manufacturing sector and thus contributes towards growth of the

manufacturing sector. A higher income raises the demand for manufacturing products.

Furthermore, it accelerates the savings increase which is used in financing the industries.

Sustained industrial growth has been extensively known as an engine of economic and social

development. The development of the rural industry can help stabilize and make agriculture more

profitable and create employment opportunities in different stages of production and marketing.

Rural Industries can be categorized as resource based industries, demand based industries & need

based industries. Further rural Industries are can also be categorized on the basis of investment

1 PhD Scholar, Department of Architecture and Planning, IIT Roorkee, Roorkee, Uttarakhand 247667, India.

Email: [email protected] 2 Professor, Department of Architecture and Planning, IIT Roorkee, Uttarakhand 247667, India. Email:

[email protected]


scale in the following types: (a) Run by rural households characterized by very little capital

investment, less mechanisation and high manual labour; products include Ghee, Papad, Pickles,

Bangles etc. (b) Small scale industry which make use of medium investment and semi-automation;

products include flour mills, rice mills, edible oil etc. (c) Large scale industry which requires large

investment and a high level of automation; products include jute, sugar, cotton mills etc.

One of the major issues of the agricultural economy is the huge wastage of fruits and vegetables

due to lack of processing and inadequate storage capacity. Food processing industry requires

addressing the key issues of wastage and value addition for attracting new investment in the

sector. Global experiences indicate that agricultural development in the region can be given a big

boost by developing agro-based and food processing industries in the rural system itself. The role

of agriculture in economic development is a widely discussed issue since long time (Sharma,

2007). The need of positive linkages between agriculture and industrialization has been

emphasised in the literatures (Runge, 2006). The agro-industry has a direct link to both agriculture

and industry, thereby plays major role in connecting the two sectors. The agro-industry can be

referred as the part of manufacturing sector that processes raw materials and intermediate products

derived from the agricultural and allied sectors. Along with the agriculture, the allied industry

includes horticulture and its allied sectors (fruits, vegetables, flowers, plantation crops, spices,

aromatic and medicinal plants); fishery; animal husbandry and livestock; and sericulture. The

agro-industries procure products generated from agriculture and allied sectors, and process them

into packed food, beverages, fruit juice, dairy products, meat, textile and clothing, leather, wood

and rubber products etc.

Agriculture and allied sectors is the mainstay of the Indian economy as they contribute nearly 22

per cent of Gross Domestic Product (GDP) of India. About 65-70 per cent of the population is

dependent on agriculture for their livelihood. They are the important source of raw material; as

well as generate demand for many industrial products, such as fertilizers, pesticides, agricultural

implements etc. Thus, the policy initiatives aiming at maximization of agricultural output in the

region need to be emphasized on checking decline in net and gross sown area on one hand and

enhanced use of yield augmenting inputs like irrigation, fertilizer and HYV seeds with more

pronounced support from institutional finance on the other. Efficient and balanced use of modern

technologies becomes all the more imperative to sustain the development process. Consolidation

of land holdings, providing legal status to tenancy cultivation, opening up institutional finance to

lease cultivators and promotion/propagation of technologies suitable in local conditions with

adequate R&D support would further accelerate the growth process.

The Patna region, possessed with a long hiatus in socioeconomic history till the independence,

today displays all degree of unevenness in inter-regional and intra-regional economic development

pattern. The Patna region with a geographical area of 16.96 thousand square km is divided by river

‘Sone’ into two unequal parts and lies in the south Bihar alluvial plains of India, Agro-Climatic

Zone III (based on soil characteristics, rainfall, temperature and terrain) of Bihar. River Ganges

creates a boundary on the North side of the region, which flows from the West to the East. The

total population of the study area is 14,448,392 (Census of India, 2001) with a sex ratio of 900

females per 1000 males. The total literacy rate varies from 53.2 per cent to 62.9 per cent in

different districts of Patna region. The percentage of the working population employed in


agricultural operations in the region is estimated to be 85 per cent, which is much higher than the

national average.

About 42 per cent of GDP of the state (2004-05) has been from the accrued agriculture sector

(including forestry and fishing). The growth rate of Bihar’s GSDP was 11.03 per cent during

2004-09, which made it the second fastest growing state in India, just behind Gujarat state (growth

rate-11.05 per cent). This growth rate is needed to be maintained or increased for achieving the

development goals of the region. Two-third of the total land area of Patna region is used for

agricultural purpose, and is one of the leading producers of agro-products, and still, the region is

struggling with the problems of underdevelopment, unemployment, lack of infrastructure in terms

of quality and quantity and absence of plausible government policies. The major crops produced in

the region are paddy, wheat, pulses, potato, sugarcane and oil seeds. The Fruits like, Mango,

Guava, & Lichi, and vegetable production are good in terms of quantity and quality. Sudha, a

dairy cooperative, lies in the region, and one of the most successful enterprises of its kind in India.

The region has abundance of water-bodies, thus, it has very high potential for fisheries and

aquaculture which has not been realized completely. The livestock is also a major resource in this

region. The lack of processing and inadequate storage of perishable agricultural resources results

into huge wastages. The high concentration of population, largely dependent on agriculture along

with low agro-industrial development, is the main reason for the high poverty ratio in the region.

There is a great pressure on other urban centres of the nation due to migration of human resource

from this region for better employment opportunities as there is a negligible industrial

development within the region. The available resources in the region can be judiciously utilized

for production purposes within the region, which will not only save transportation cost,

preservation cost and time, but also generate employment opportunities and income earning

opportunities in the system (Please see Figure 1, Figure 2 and Figure 3).

There is need of agro-industrial development of the region to minimizing the huge wastage of

agricultural products and employment generation within the region which will not only ensure

proper utilization of the region’s resources but also help in minimizing the pressure on other urban

centres, which lie outside the region, have their own acute problems of traffic congestion, in

migration, housing shortage, slum formation, water scarcity etc. The agricultural productivity in

Bihar was much better among all the states in India, in the fifties, which is now much below the

national average. In the last two years, there has been an appreciable growth due to improved

seeds, technologies and other inputs, but the state has to go miles to achieve regional balance in

terms of agriculture and agro-based industrial development. This would require infrastructure,

technology and other inputs. R&D has a vital role to play.

METHODOLOGY

The study area of Patna region has been selected for the present research. This region is the

administrative geographic unit of Bihar, India. Few homogeneous characteristics were taken into

consideration, while delineation of the study area. The region is least prone to flood hazard, has

same soil type: Gangetic alluvial plane, agro-climatic conditions are same, comes in same agro-

climatic zone (zone-iii). Similar kind of agricultural production, similar language, socioeconomic

condition and demographic condition persist in the region.


Data have been collected from literatures, case studies, observations and by conducting a primary

survey at the grassroots level. Both secondary and primary data have been analyzed to obtain the

inferences and do the forecast. Pre-testing the Schedule on site after Preparing the Schedule was

done. Consequently, revision of the schedule, then identification of areas and samples of survey

has been identified. After conducting the survey, data vetting and data feeding in the Ms excel

sheet has been done for tabulation and generating diagrams. Statistical techniques have been

employed to analyze the data and draw the findings. Input-output analysis, population projection

techniques, and system approach have been applied. Finally, recommendations have been made

based on these findings.

DATA, TOOLS & TECHNIQUES

Data required for the research are collected from secondary and primary sources. The random

sample technique was employed for conducting the primary surveys and opinion polls at the

grassroots level. Secondary sources of data including government documents are also considered.

The survey schedule, questionnaire, and the random sampling technique were employed for

conducting the survey at grassroots level. Data vetting, data feeding, graph generation for

analyzing the data has been done by using MS Excel software; map digitization was done by using

AutoCAD and the proposed rural industrial locations were identified using the same software.

FORECASTING

Projections have been done in order to arrive at the real situation in the future, i.e., optimal and

feasible solution for 2031 AD. Forecasting the demand & supply of resources & products

respectively and finding the gaps for future have been done for industrial development in the study

area.

Population Projection has been done to decide the demand for future. According to the future

demand, planning for the rural industrial location has been done. The methods employed for

population projection are: Arithmetic method, Geometric Method, Exponential method,

Population Projection by Curve fitting method.

The average of the three populations projected using arithmetic method; geometric method; and

exponential method has been calculated, which is 27 million, has been considered for the present

study.

APPLICATION OF THEORIES/ MODELS/ TECHNIQUES

To understand the real life situation different theories were employed and a model is also

generated. They are, trend analysis, growth pole theory, location theory and Input-Output model.

System approach has been considered while analyzing the rural system, and thus, the region is

considered as a system. The subsystems of the system which include physical subsystem; social

subsystem; economic subsystem; ecological subsystem; environmental subsystem; Infrastructure

subsystem and institutional subsystem, are considered. These subsystems are interconnected and

interdependent to each other and they function as a whole.


Table 1

Input-Output table: Wheat & Paddy (In x 1000,000 Rs.) (Base year: 2001)

Inputs to

Economic Activity

Agriculture Manufacturing

Tra

nspo

rt

Ser

vice

s

Ene

rgy

Lab

our

Tax

es

Exp

ort

Fin

al D

eman

d

Tot

al O

utpu

t

Whe

at

Ric

e/ p

addy

Straw

/Hus

k/

Bra

n

Flo

ur

Bea

ten

Ric

e

Pac

ked

food

Sna

cks

Fod

der

xi1 xi2 xi3 xi4 xi5 xi6 xi7 xi8 xi9 xi10 xi11 xi12 xi13 xi14 Yi Xi

Agr

icul

ture

Whe

at

x1j

683.

2

0.0

100.

5

1057

1.9

0.0

0.0

1.1

0.1

106.

8

0.1

0.6

0.6

0.1

11.9

0.0

1147

6.9

Ric

e/pa

ddy

x2j 0.0

1310

.3

161.

4

14.5

115.

6

115.

6

1.0

0.2

84.9

0.1

0.8

0.8

0.1

30.0

1008

0.0

1191

5.2

Straw

/Hu

sk/B

ran

x3j 0.2

0.2

0.0

0.0

0.0

0.0

0.0

246.

5

0.9

0.0

1.3

0.1

0.0

20.2

2.5

271.

9

Man

ufac

turing

Flo

ur

x4j 0.0

0.0

0.0

0.0

0.0

132.

9

575.

0

0.0

50.7

1.2

0.0

11.5

1.2

187.

0

1932

0.0

2027

9.4

Bea

ten

Ric

e

x5j 0.0

0.0

0.0

0.0

0.0

75.4

75.4

0.6

0.7

0.3

0.0

3.6

0.6

3.5

186.

6

346.

8

Pac

ked

food

x6j 0.0

0.0

0.0

0.0

0.0

0.0

0.0

1.5

1.5

1.5

0.0

1.5

1.5

423.

7

1501

.7

1932

.9

Sna

cks

x7j 0.0

0.0

0.0

0.0

0.0

0.0

0.0

1.0

5.3

4.0

0.0

2.0

10.0

1020

.2

4241

.1

5283

.6

Fod

der

x8j 0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

7.3

0.0

0.0

0.0

0.0

4.7

1960

.0

1972

.0

Tra

nspo

rt

x9j 0.5

0.5

0.0

0.5

0.1

0.1

0.1

0.1

5.0

0.5

0.1

0.0

5.0

5.0

261.

9

279.

2

serv

ices

x10j 0.5

0.5

0.0

0.5

0.1

0.1

0.1

0.1

0.5

0.1

0.1

0.0

0.5

0.1

9.9

12.8

Ene

rgy

x11j 0.5

0.5

0.0

0.5

0.1

0.1

0.1

0.1

0.1

0.0

0.1

0.0

0.1

0.1

5.9

7.9

Lab

our

x12j 5.0

5.0

0.0

0.5

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.5

0.0

0.1

14.3

25.7

Tax

es

x13j 0.5

0.5

0.0

0.5

0.1

0.1

0.1

0.1

0.5

0.0

0.1

0.0

0.0

0.1

21.7

24.0

Impo

rt

x14j 0.5

0.5

0.0

0.5

0.1

0.1

0.1

0.1

15.0

5.0

5.0

5.0

5.0

0.0

663.

4

700.

1

Tot

al

690.

9

1318

.0

262.

1

1058

9.3

115.

9

324.

3

652.

8

250.

2

279.

2

12.8

7.9

25.7

24.0

1706

.4

3826

8.9

5452

8.3

Source: Planning for Rural Industrial Development of Patna Region, 2011, A Dissertation Report,

Rashmi Kumari, IIT Roorkee.


Table 2

Matrix of Input-Output coefficients: Wheat & Paddy (Base year: 2001)

Inputs to

Economic

Activity

Agriculture Manufacturing

Tra

nsp

ort

Ser

vic

es

En

ergy

Lab

ou

r

Tax

es

Ex

po

rt

Wh

eat

Ric

e/

pad

dy

Str

aw/H

us

k/

Bra

n

Flo

ur

Bea

ten

Ric

e

Pac

ked

food

Sn

ack

s

Fo

dd

er

αi1 αi2 αi3 αi4 αi5 αi6 αi7 αi8 αi9 αi10 αi11 αi12 αi13 αi14

Ag

ricu

ltu

re W

hea

t α1j 5

95.3

0.0

36

95

.9

52

13

.1

0.0

0.0

2.1

0.5

38

24

.9

84

.4

75

8.9

23

3.2

25

.0

17

0.2

Ric

e/p

ad

dy α2j

0.0

10

99

.7

59

36

.3

7.1

33

33

.3

59

8.0

1.9

0.9

30

40

.1

78

.2

10

11

.9

31

1.0

33

.3

42

8.0

Str

aw/

Hu

sk/

Bra

n α3j

0.2

0.2

0.0

0.0

0.0

0.1

0.0

12

50

.0

32

.5

2.0

15

81

.1

48

.6

5.2

28

8.2

Man

ufa

ctu

rin

g

Flo

ur

α4j

0.0

0.0

0.0

0.0

0.0

68

7.7

10

88

.3

0.1

18

15

.6

89

9.0

0.0

44

70

.0

47

9.4

26

70

.6

Bea

ten

Ric

e α5j

0.0

0.0

0.0

0.0

0.0

39

0.2

14

2.7

3.0

24

.7

23

4.5

0.0

13

99

.3

25

0.1

50

.4

Pac

ked

food α6j

0.0

0.0

0.0

0.0

0.0

0.0

0.0

7.6

55

.1

11

72

.6

0.0

58

3.0

62

5.3

60

51

.7

Sn

ack

s α7j

0.0

0.0

0.0

0.0

0.0

0.0

0.0

5.1

18

9.2

31

27

.0

0.0

77

7.4

41

68

.5

14

57

3.0

Fo

dd

er

α8j

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

25

9.6

15

.6

0.0

7.8

0.8

67

.8

Tra

nsp

ort

α9j

0.4

0.4

0.9

0.2

1.4

0.3

0.1

0.3

17

9.1

39

0.9

63

.2

1.9

20

84

.2

71

.4

Ser

vic

es

α10j

0.4

0.4

0.9

0.2

1.4

0.3

0.1

0.3

17

.9

39

.1

63

.2

1.9

20

8.4

0.7

En

erg

y

α11j

0.4

0.4

0.9

0.2

1.4

0.3

0.1

0.3

4.3

3.9

63

.2

1.9

20

.8

0.7

Lab

ou

r

α12j

4.4

4.2

0.9

0.2

1.4

0.3

0.1

0.3

1.8

39

.1

63

.2

19

4.3

2.1

0.7

Tax

es

α13j

0.4

0.4

0.9

0.2

1.4

0.3

0.1

0.3

17

.9

3.9

63

.2

1.9

0.0

0.7

Imp

ort

α14j

0.4

0.4

0.9

0.2

1.4

0.3

0.1

0.3

53

7.2

39

08

.8

63

24

.3

19

43

.5

20

84

.2

0.1

Source: Planning for Rural Industrial Development of Patna Region, 2011, A Dissertation

Report by Rashmi Kumari, IIT Roorkee.

Note: Coefficients are in 10-4 format


The Input-output model has been generated for quantitative analysis of the structure and the

function of the rural industrial system in the Patna region, which can be used to study synthetically

the quantitative relations between the natural reproduction, the economic reproduction of

agriculture, the structure and the function of an economic system and social system and their

relationships. The optimum potentiality of rural industries in the region has been established by

employing the input-output model for industries based on Wheat, Paddy, Sugarcane, Mango and

Dairy. The forecasting of output of commodities for the year 2031 is done on the basis of the

model generated. In the following table the Input-Output model for Wheat and Paddy has been

shown and the forecasting has been done using the validated model results (Refer to Tables 1, 2, 3

& 4). Similarly, the Input-Output models have been generated for the Sugarcane industry; Mango

based industry; and Dairy industry. The projected output of commodities has been calculated for

analyzing the future demand and supply scenario, based on which the surplus can be used to

generate capital by selling them in the market within and outside the region.

Table 3

Final Demand in 2031

Sl. No. Economic Activity Yi

(in `, base year 2001)

1.

Agriculture

Wheat 331559220

2. Rice/paddy 55259870000

3. Straw/Husk/Bran 276299350

4.

Manufacturing

Flour (Ata, Maida) 44484195350

5. Beaten Rice (Chuda) 16578000000

6. Packed food 414449025000

7. Snacks 552598700000

8. Fodder 110519740

9. Transport (10 per cent increase) 288138950

10. services (10 per cent increase) 10902980

11. Energy (10 per cent increase) 6491100

12. Labour (10 per cent increase) 15726700

13. Taxes (10 per cent increase) 23819950

14. Import (10 per cent increase) 729679500.00

15. Total

1085162927840



Note: Unit: In Rs., base year 2001

We get the equation,

where (i=1, 2, 3, …….., 14 & n=14)

Here, X1, X2, X3, X4, X5, X6, X7, X8, X9, X10, X11, X12, X13 & X14 represents the output of

wheat, rice, straw, flour, beaten rice, packed food, snacks, fodder, transport, services, energy,

labour, taxes and imports respectively. Using the above equation, the required outputs of products

in 2031 have been calculated.


Table 4

Required Output in 2031

Sl. No. Name of Items Symbols Output in `/Year (Base

Year 2001)

Output in

Kg/Year

1. Wheat X1 23549843720 1962486977

2. Rice/paddy X2 36807917394 1840395870

3. Straw/Husk/Bran X3 42103977 168415908

4. Flour (Ata, Meda) X4 88896390207 3865060444

5. Beaten Rice (Chuda) X5 24067270480 401121175

6. Packed food X6 446938870 2979593

7. Snacks X7 1083428530 5417143

8. Fodder X8 12457333 6228667

9. Total

174906350511 8252105777



RESULTS AND DISCUSSION

Input-output analysis has been done for industrial development in the study area. Demand

projection has been done for the year 2031. The required output for the projected demand has been

calculated using input output coefficients. Output feasibility has been analyzed according to yield

capacity. Thus, future output has been derived (Refer to Table 5). The land area required for a

particular amount of manufacturing good’s output has been calculated. Then locations for

concentration of rural industries based on resource availability, transportation facility, labour

availability, demand (market) availability has been suggested in the proposal. Area boundaries

have been defined which will provide resources for different industrial concentration (Please see

Figure 5). According to growth pole theory the concentrated industrial location would work as

poles, and secondary growth poles will be generated in the region by the influence of the poles

automatically. Thus, the industrial development would take place in the region and this would give

a boost to the development of all the subsystems of the regional system.

In support of these industries, market areas should also be identified. It has been recommended to

strengthen the post harvest infrastructure, to meet the present level of production as well as the

anticipated increased production, like: Collection Centres, Multi Product Processing Unit, Cold

Storage (for perishable food products), Rural Mandi (Marketing and Storage Facilities).

The main focus of the agro-processing industries should be on meeting the present as well as

projected future domestic market need of the region.

Potential in agro-based projects are processing of major and minor crops (wheat, paddy, pulses,

sugarcane and maize, processing of fruits and vegetables (vegetables, potato, mango and litchi),

processing of crop and agro industrial residue (straw, husk, bagasses, press mud, bran, corn shuck,

corn cobs and fodder), poultry and animal husbandry & dairy and milk processing.


Figure 5

Map showing Proposed Agro-Industrial Centres in the Patna region

A strategic approach is needed to enhance the agricultural income. The farmers have small land

holdings, thus, the agriculture productivity growth is highly essential to sustain. The sustainable

development of agricultural economy needs conservation of agricultural resources. The concepts

of organic farming and integrated farming can help in achieving the sustainable agriculture.

Organic farming uses organic fertilisers instead of harmful chemical fertilisers. Integrated farming

uses a combination of agriculture, horticulture, livestock, fisheries, apiculture, sericulture,

vermiculture along with multiple uses.

Potential in other small scale and cottage industries, like Matchstick, carpentry, pottery, stone

cutting and crushing, handmade paper, soft toys, Bindi (a forehead decorative product), beauty

products, handloom etc.; Bamboo products: furniture, baskets, musical instrument (bansuri),

vessels, decorative objects, are good in the study area. Art and handicraft materials (e.g.,

Madhubani Painting, lac work, bronze metal work etc.) may also contribute to the industrial

products in the study area.

Many R&D Works in the field of agro-processing has been carried out in India during the last five

decades. Some research work has also been done in the area of processing forest produce such as

collection and processing of resins, oil extraction from oil bearing materials, and production of

natural dyes, Ayurvedic medicinal products etc. Due to high export potential, R&D work on pre-

cooling, packaging, and transport of cut flowers and low cost designs of greenhouses has been

initiated in the field of floriculture at some centres. The Agro-processing models developed for

some of the agro-climatic regions for the development of tools and techniques for harvesting, pre-


cooling of freshly harvested produce; minimal processing cost; controlled ripening; juice

extraction; storage etc.

SUMMARY

The results of the SWOT analysis in the study area are as follows:

Strength

Two-third of the total land area of Patna region is used for agricultural purposes. The vast amount

of agricultural land availability is one of the major strengths for rural industrialization in the

region. The working population of the region which are facing persistent unemployment can be

considered as strength, as they would provide human resource for the industries. The favourable

agro-climatic conditions are also the strength of the region. The available water resource due to the

presence of Ganga and Sone rivers in the region is one of the most important factors required for

agricultural development. Patna region is very well connected with other regions of the country by

railways, roads and waterways. So, connectivity forms strength in industrialization. Rural

industries have always been in tradition in the region, so people are aware and have adequate skill

in rural industrial work. The agro-industrial products are basically commodities of basic needs. So,

the demand will never decrease. There is a vast domestic and global market for these products.

Weakness

The small size of land holding in the study area is a major weakness in terms of agricultural and

agro-industrial development. Lack of the infrastructure facility in terms of electricity and

sanitation in the rural areas of Patna region is another weak point. There is a lack of proper supply

chain in the region. This is one of the major constraints in rural industrialization. There is no

marketing management system within the study area. Least use of technology in agriculture is one

of the major reasons of less agricultural production. Industrial infancy and lack of industrial

training are also weaknesses. The lack of processing and inadequate storage of fruits and

vegetables result in huge wastages.

Opportunities

There is much scope of increase in crop yield by the employing new technologies, improved

HYVC seeds, fertilizers, pesticides, and other inputs. Patna region lies on the Indo-Gangetic

plains, one of the most fertile plains of the world. There is availability of rare varieties of crops in

this fertile region, which are in demand. There is an insured irrigation facility due to the canals.

The most part of Bihar is facing the curse of floods. Patna region is an exception, as it is less prone

to the flood hazards. Commercialization of milk products has been already done in a proper

manner and needed to develop it more in future. There is a vast increase in R/D works in the

region since 2005. Rajendra Agricultural University in Pusa is doing well in the research field.

Threats

The law and order situation in the region is very volatile and needed to be improved. The

credit/deposit ratio is very less in the region as compared to the other regions of the country. There

is a lack of collective strength in the region. People are not willing to do collective effort for any

kind of development. There is very poor investment climate. Migration is also a major issue.

There is a lack of information technology and awareness due to the faulty information system.

There is no control over prices of agricultural goods, which makes the farmers insecure in terms of


economy (Need of Minimum Support Price). There is persistent unemployment which leads to

poverty, crime, starvation, and other social ills.

The impact of the agro-industrialization in support of the region will be positive. There will be a

situation of total gain for the people and government both. There will be gain of intellectual and

financial wealth in the organization of many small-scale producers. The wealth creation will lead

to more socially secure rural communities, and people will be better able to fulfil their basic needs

and desires which include food, clothes, shelter, and education, also they will be able to plan for a

secure future from the additional employment and incomes that will result from the investments

brought by industries and the profit generated due to value addition. There will also gains for the

environment as most of the agro-industries are eco-friendly. People will become less exploitive

and more responsible in the long-term issues of socioeconomic security. It will improve the

socioeconomic condition and give away to come across the regional imbalance and inequality

prevailing since long time.

Evolving set of Policy Guidelines

Plausible policies and guidelines can be evolved for the sustainable industrial development in the

study area based on the findings. Priorities should be the general agricultural development and

development of sectors in support of agriculture. Proposed measures should be taken in support of

general agro-industrial development includes: Improved use and service delivery of important

agricultural inputs. Investment in agricultural research and development (R&D) should be done.

Restoring, protecting and developing arable land and making it more productive. Setting minimum

support prices by the government for agricultural products is needed to ensure farmer’s goodwill.

Actual and potential yield gap should be minimized. Area under fruit crops like mango and litchi

should be extended. The production of green vegetables, spices, potato, and onion should be

increased. The experience of ‘Sudha Dairy’ should be multiplied. Near stagnation of poultry

development should be given a boost. Storage and transportation facility should be improved by

providing facilities at the proper location. Stores for food grains need to be equipped with

adequate facilities for materials handling, fumigation and aeration. Credit support by financial

institution should be ensured by helping the banking system in the recovery of loans. Law and

order should be improved to increase the investment climate. Improvement in supply chain has

been suggested.

CONCLUSION

The world’s economy is poised to achieve a high growth rate. Against this, the Patna region can be

termed as a sleeping giant of Indian agriculture based economy among the regions of India.

Though the study area has an enormous amount of potential for the development of industries, is

totally neglected, the available resources are not utilized properly. As a consequence, the study

area became backward in terms of socioeconomic condition. In this present investigation, at the

outset, an attempt has been made to have a thorough understanding about the socioeconomic

condition of the system. Subsequently, the available resources were quantified towards imparting

industries in the system, and recommendations are made.

The study concluded with plausible recommendations for imparting rural industrialization in the

study area. It is anticipated that, if the proposed plan model is implemented successfully in the

study area, it will ensure sustainable development in the system, definitely.


________________________________

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DEVELOPMENT AND DISPARITY IN BIHAR

Reena Kumari1

This paper addresses issue of inter-district disparity at district-level in Bihar. An attempt has been

made to identify the backward regions/districts of the state in terms of four development sectors

for instance, agriculture, services, education and health. The study has used 34 indicators which

explain the level of economic and social development. For measuring disparity and inter-district

variations in the state, Principal Component Analysis has been employed. On the basis of

composite score and the ranks of districts in terms of different sectors, an attention has been

drawn to see relationship between economic and social development sector. The analysis shows

that development is centred only in Patna due to being a capital city of the state and has been able

to pulling up resources and all the beneficiaries in the state. There is need of hour to allocate

resources at more sub-state level or disaggregated level so that balance regional development can

be achieved.

INTRODUCTION

Presently Bihar is the least urbanised state of India with an urban population of just about 10 per

cent. The agricultural sector employed about 73 per cent of the workforce in the state is very

backward with low productivity. The per capita agricultural income of Bihar is about half that of

India as a whole and about one-fifth that of Punjab. The productive employment in the non-

agricultural sector has not grown as much as in other states. Whatever few rural industries were

there in the state such as sugar, jute, etc, all have collapsed in recent years. The socio-economic

and political institutions of the state too have shown considerable degeneration. The academic

institutions have more or less collapsed and the administrative machinery, which was regarded as

one of the best in the country during the 1950s, is in complete disarray.

Things have however changed remarkably of late. Bihar during the last four-five years has

acquired considerable attention throughout the country and even abroad for its remarkable

performance on the development front. For a state which had suffered stagnation for long and

which had almost resigned to its perpetual backwardness, this has been a turning point, leading to

new hopes and aspirations. The changes have been possible because of the state government's firm

commitment to an agenda of development which is both speedy and inclusive. To fulfil this

agenda, the state government has not only utilised its limited resources most prudently, but

has also strengthened its administrative machinery and introduced a number of institutional

reforms. The results clearly show that the recent growth process of the state's economy is not a

short term phenomenon, but the beginning of a long term stable growth process.

The recent data on state income shows that the economy of Bihar has been showing a steady

growth trend for the last 6 years. During the first 5 years after separation of Jharkhand in 2000, the

economy had grown at an annual rate of 4.42 percent at constant prices. The already stagnating

economy of Bihar had become even more crippled after the bifurcation, thanks to the asymmetric

distribution of resources between Jharkhand and present Bihar. However, the economy witnessed

1 Senior Consultant, National University of Educational Planning and Administration, New Delhi-110016,

Email: [email protected]


a turnaround due to policies pursued by the present state government and, as a result; the economy

grew at an annual rate of 11.36 percent during the period 2004-05 to 2010-11. We can term the

recent growth process as 'revival of a stagnant economy'. This has been made possible by the fact

that the investment pattern showed a massive upsurge. From a small average annual plan size of

around Rs. 1200 crores during the Tenth Plan (2002-2007), the annual plan size climbed to more

than Rs. 15,000 crores during the Eleventh Plan period (2007-2012). The investment portfolio

also changed and there was a massive stress on infrastructural development and social delivery

system. Now, the economy can claim to be at a 'taking off' stage to a sustained

development path. The buoyancy in the economy can be easily sustained by the inter-linkages in

its various sectors.

The present study attempts to present inter-district and inter-zones disparity in the state economy

over the two time periods 2000-01 and 2010-11. An attempt has been made to build composite

indices for four sectors like agriculture, services, health and education to compare different

districts of the state. On the basis of score of indices the ranks of districts have been given for the

particular sector representing the relative position of districts therein. The Chapter is divided into

three broad sections- Section-I gives an Overview of the Economy of Bihar, highlighting its

distinguishing features in brief. Section-II describes methodology and indicator that have been

used in the study. Section-III deals with the issue of inter-district and inter-zone disparity in the

state separately in terms of the four sectors chosen for detailed discussion i.e. Agriculture,

Services, Education and Health Sector. Section-IV attempts to provide a detailed description of

position of districts in terms of level of development. It attempts to cross tab district ranking in

terms of different sectors to arrive at the actual picture of the districts of the state. Section V gives

conclusion of the study.

AN OVERVIEW OF BIHAR ECONOMY

To see the regional disparity in Bihar it will be meaningful to see the level of development of the

state in terms of various social and economic development indicators and the position of state in

different parameters. It provides brief details of some major sectors of the state of Bihar and

provides description of different economic and agro-climatic zones of the state.

Bihar as a political entity, either as a kingdom, or as a state within the republic of India, has its

own identity from the time written records were available (Thapar 1966; Rangarajan 1992). Noted

historian, Romila Thapar, describes the history of ancient India as the history of ancient Bihar.

Many achievements that India became renowned for, in education, governance, society, or

religion, have their roots in Bihar. Significant achievements of Bihar in trade and economic

engagement within the state and outside the Indian sub-continent emerge from a past that appears

to have left no living legacy in today’s Bihar-a past so alien as to be either simply forgotten or

treated as being completely incredible.

Contemporary Bihar, in terms of levels of output, has been one of the smallest among all the major

states in India. Not only in terms of economic output, but also in terms of almost each and every

indicator of relevance, the Human Development Index, access to infrastructure, healthcare,

education, law and order, the gap between Bihar and India’s achievements have been so large that

from the mid-1980s, many have institutionalized Bihar’s status as a `basket-case’ with little

expectation of growth through much of the latter half of the 20th Century. Of course, slower


growth does not mean complete stagnation. Nor does it imply a lack of structural change. Some of

that change was consistent with the rest of the Indian economy and in this overview we document

these trends. In India the first step to liberalise the economy was taken in 1980 and if we attempt

to divide the period 1980-2012 into three separate time periods, the best we can do would be to

identify the sub-periods as 1980-2000, 2000-2005, and post-2005. The basis of this classification

is analytical rather than statistical. Each of these gives periods in time when numbers can be

compared with each other, but it is not clear if they can be compared across these periods in an

obvious way.

The first period captures Bihar’s pre-bifurcation economy. This represents a period when the

structure of the economy, its endowments, and its politics was markedly different from the Bihar

in existence after November of 2000. The districts that constitute Bihar and Jharkhand today have

always been socially and economically different; thus, for example, while Jharkhand’s population

is largely tribal with limited caste identity, caste has historically been the basis for polarization and

exclusion in Bihar (Sharma 1976). In addition, with a substantial portion of its land on the Chota

Nagpur Plateau, Jharkhand is rich in mineral deposits and has been the home for manufacturing

activities. On the other hand, districts constituting Bihar have large swathes of alluvial soil, often

replenished by flood waters, which are particularly suitable for agriculture. Since systematic and

reliable information on the Bihar economy for the 1980s is not available we have excluded this

phase in our discussion below.

The period 2000-2005 captures Bihar’s immediate post-bifurcation economy. Social dynamics,

political demands for separation, and political expediency, on the part of Rashtriya Janta Dal

(RJD) in Bihar, and the National Democratic Alliance (NDA) government at the national level,

provided the Jharkhandi movement an opportunity in the 1990s that it had not found in decades

(Rorabacher 2008). While the economy of the bifurcated Bihar could no longer be compared with

that of the 1980-2000 Bihar, RJD continued in power and this provided a period of political and

policy continuity with the past that was important. Bihar’s economy was substantially transformed

when it bifurcated into Bihar and Jharkhand under the Bihar Reorganization Act of 2000. Most of

the manufacturing units and capacity to generate power were located in Southern Bihar, and these

went to Jharkhand. Thus, the share of industry (excluding construction) dropped from 22.5% to

4.6% of NSDP, and there was a parallel increase in the share of the services sector from 36% to

50%, in a matter of a year. The share of the agricultural sector in the economy increased modestly

from 36.5% to 40.4%. A natural consequence of the loss of the industrial sector was a substantial

drop in the state’s own share of non-tax revenue from this sector. Thus, over the 1991-95 years,

the industrial sector in Bihar contributed Rs. 61,119 crore to the state, i.e. about 10% of total

revenue. This declined marginally to 7% of total revenue for the 1995-2000 period. However, over

the 2000-05 period it accounted for a mere Rs. 12,344 crore, and this was no more than 1% of

total revenue (Economic Survey, Government of Bihar, various rounds).

A natural consequence of the bifurcation was that it shrank the fiscal space within which the state

could finance development, relief and poverty alleviation activities. The bifurcation artificially

reinforced Bihar’s transformation into a services-led economy that has become more dependent on

the services sector than the Indian economy and yet remains one of its poorest states. In terms of

economic development 2000-2005 were bad years. The third period is the period after 2005. This

period saw major changes in policy, administrative, and overall governance changes as well as


rapid economic growth. This period marks a clear break from the past, in both a statistical and

qualitative sense. While many of the structural changes seen in the past continue, and the relative

position of Bihar amongst other states remains as is, there is distinct increase in economic growth.

During the period 1997-99 the position of Bihar in growth in SDP and per capita SDP was the

lowest among 14 states and only 21.5 per cent of the PCNSDP of second most populous state of

the country Maharashtra, and 22.7 per cent of Gujarat respectively. After the division of the state

(Bihar) the condition improved with growth rate bouncing to 5.5 per cent pa. However, still it was

the third lowest among the states in 2003-05. The dramatic change in the performance of the state

occurred since 2007. For the triennium ending 2009 growth rate for the state was 14.1 per cent,

highest among the 15 major states of India. While growth of Bihar has increased, on the other

hand some other significant sectors still show signs of underdevelopment.

INTER-DISTRICT AND INTER-REGIONAL DISPARITY IN BIHAR

Methodology

For measuring inter-district disparity in Bihar, we have selected 34 indicators for measuring

disparity at district level. These indicators represent the level of development of the state at

district-level and also explain the extent of disparity among them over two time periods 2001 and

2010-11 (latest year for which data was available). There are two important omissions as regards

the treatment of inter-district disparity in Bihar-

First, we have taken only four sectors for Bihar for the reference period. The industrial sector that

normally occupies important place in any economy has been left out due to non-availability

district level data for the state (something that speaks of very poor position of industrial sector in

the state).

Second, we have not attempted to measure disparity for the year 1991. This has again been done

for two reasons-(i) there is lack of reliable district level statistics for Bihar for 1991. Computation

of disparity incorporating insufficient statistics would not have given true picture for the state for

1991 and further would not have made inter-period comparison possible. (ii) Bihar was divided in

2000 and there was reorganisation of state in the year of division. The erstwhile Bihar had a

number of districts like Jamshedpur, Dhanbad etc. that had number of industries. Had we

attempted to compare disparity of that period with the one prevailing after 2000 it would not give

us the correct picture.

A number of variables has been used to build sub-indices for different sectors. Poor/insufficient

data for state of Bihar has however made us compromise on two fronts-i) the study has reduced

number of sectors covered to four only. Industrial sector has been kept out since Bihar lacks data

for different indicators of industrial sector; ii) the study was forced to reduce the number of

indicators for constructing sub-indices (Table 1).

The study aims at computing different sub-indices and then using them computes overall index of

development of different districts and regions. The methodology for preparing the indices is

explained as follows. First, the values of the selected indicators for all the 37 districts of Bihar

have been collected and tabulated. Then the tabulated data were transformed into standardised

Yid’s, by using the ratio of distance of Xid from minimum with the range, where Xid stands for

actual value of ith

variable for district d. If, however, Xid is negatively associated with


development, as, for example, the infant mortality rate or the unemployment rate which should

decline as the district develops and then Yid is suitable inverted to reflect distance from maximum

Xid.

Table 1

List of Economic and Social Indicators

Sr. No Abbreviation Indicators

Agricultural Sector

X1 CI Cropping intensity

X2 PCFP Per capita food-grain production

X3 II Irrigation intensity

X4 EI Extent of irrigation

X5 NSC Net sown area per cultivator

X6 NEPNSA No. of electric pump-sets per unit of net sown area

X7 NITNSA Net area irrigated by tube-wells to net sown area

Services Sector

X8 CDR Credit-deposit ratio

X9 PEVTH Percentage of electrified villages to total habitant

X10 NHABF No. of household availing banking facility per lakh of

population

X11 NTC No. of telephone connection per lakh of population

X12 CB No. of commercial banks per lakh of population

X13 CBGA No. of commercial banks per 100 sq. Km of the geographical

areas

Educational Sector

X14 RLR Rural literacy rate

X15 ULR Urban literacy rate

X16 LR Literacy rate

X17 MLR Male literacy rate

X18 FLR Female literacy rate

X19 SPLP No. of schools per lakh of population

X20 TPRPS Teacher-pupil ratio in govt. primary schools

X21 GPS No. of govt. Primary schools per lakh of population

X22 SDWF No. of schools with drinking water facility per lakh of

population

X23 PTT Percentage of trained teachers to total teachers

X24 PSGA Percentage of schools per 100 sq. Km of the geographical areas

X25 GPSGA No. of govt. Primary schools per 100 sq. Km of the

geographical areas

Health/Medical Sector

X26 IMR Infant mortality rate

X27 CBR Crude birth rate

X28 TFR Total fertility rate

X29 PHCP No. of PHC per lakh of population

X30 PHCGA No. of PHC per 100 sq. Km. Of the geographical areas

X31 HDP No. of hospital and dispensaries per lakh of population

X32 HDGA No. of hospital and dispensaries per 100 sq. Km. Of the

geographical areas

X33 HDB No. of hospital and dispensaries having beds per lakh of

population

X34 HBP No. of hospital beds per lakh of population


Thereafter, Principal Component Method was used to derive composite sectoral development

indices. In cases where first principal component explains less than 70 per cent of variation, then a

combined component score has been computed from the first and second principal component

scores using the per cent of variation explained as the weights. Districts have been then ranked

according to Combined Component Score (CCS).

INTER-DISTRICT DISPARITY IN BIHAR

This section provides clear picture of inter-district disparity at district level in four sectors i.e.

agriculture, services, education and health in Bihar (Table 2). On the basis of composite index we

find that Rohtas was the top and Patna was the least developed in terms of agriculture

development in 2000-01 in Bihar (table-5). Patna is capital of the state and as such it is highly

urbanised (67.57%) and most developed in terms of services and manufacturing sector. In 2010-

11, the rank of districts of the top and bottom performer in this sector has not changed. The

district-wise analysis for Bihar shows that districts which fall under top five developed category in

agricultural sector were Rohtas, Kaimur, Nawada, Gaya and Jehanabad, In contrast, the districts

which fall into bottom five developed category were Patna, Jamui, Darbhanga, Bhojpur and

Sheikhpura all the top and bottom performer districts except Darbhanga belong to the central

region and no districts from the northern Bihar. Among the bottom five developed districts Jamui

and Sheikhpura were very backward and affected by poverty which created social problems in

terms of naxalite movement and other law and order problems. These affects the farmer’s

condition and other problems related to agricultural production like insecurity, marketing system

and local problems. In Bihar, the districts are not split in the manner. While districts of North

Bihar have not done extremely well, they are not at the bottom either. These districts fall in North

Gangetic Plain and have highly fertile land, but the poor economic condition of farmers and low

size of agricultural holdings prevent use of modern technology. The central Bihar has both

advanced and backward districts. Hence, while inter district disparity is high in Bihar, inter region

disparity in not. Like UP, Bihar cannot be geographically divided into advanced and backward

regions.

In case of Bihar inter-district disparity in agriculture sector has declined from 20.04 in 2000-01 to

19.71 in 2010-11. It shows that the districts of the state have been benefited from agricultural

policy that is initiated by the government. The economy has adopted two strategies to strengthen

agriculture these are research and extension i.e. from labs to farms. Delivery system to make

available quality seeds, pesticides and extension system to farmers is also being implemented

across the state which has decreased the gap between richer and poor districts and overall

agricultural disparity. It will be praiseworthy to note that the recent growth rate of economy is

very high which has influenced the well-being of some districts that have improved their position

in agricultural sector.

In terms of services sector, again Patna was the top performer but Lukhisarai come to occupy the

bottom. Lakhirarai is located in the Central region of the state. It is agriculture base districts whose

contribution in manufacturing and services sector is very low. The district has small saving, low

credit-deposit ratio, low access to insurance services to the poor household, less participation in

non-farm activities and moreover, poor access to financial services in the district. Thus, all these

issues are responsible for the poor financial rank of the district in 2010-11.


Table 2

Inter-District Disparity in Different Sectors in Bihar

Agriculture Services Education Health

Districts 2000-01 2010-11 2000-01 2010-11 2000-01 2010-11 2000-01 2010-11

Index Rank Index Rank Index Rank Index Rank Index Rank Index Rank Index Rank Index Rank

Rohtas 0.49 1 0.49 1 0.77 1 0.33 20 0.64 2 0.57 2 0.33 21 0.28 19

Kaimur 0.49 2 0.48 2 0.33 16 0.36 15 0.56 8 0.50 10 0.46 5 0.28 20

Nawada 0.41 3 0.42 4 0.15 37 0.28 31 0.42 21 0.40 21 0.41 11 0.30 17

Gaya 0.39 4 0.39 9 0.26 21 0.31 26 0.49 14 0.45 15 0.41 12 0.32 12

Jehanabad 0.39 5 0.39 10 0.22 27 0.29 29 0.51 12 0.48 12 0.46 4 0.43 5

Kishanganj 0.39 6 0.42 5 0.20 34 0.32 24 0.30 30 0.29 29 0.18 37 0.15 36

Aurangabad 0.38 7 0.38 14 0.23 26 0.23 35 0.59 6 0.52 7 0.44 6 0.39 7

Sheohar 0.38 8 0.44 3 0.43 3 0.50 3 0.23 36 0.23 37 0.34 17 0.25 26

Begusarai 0.37 9 0.38 13 0.39 6 0.44 8 0.45 18 0.42 19 0.44 7 0.50 3

Supaul 0.36 10 0.40 7 0.22 29 0.41 11 0.35 26 0.34 26 0.26 33 0.22 32

W.Champaran 0.36 11 0.39 12 0.26 22 0.32 25 0.30 29 0.28 30 0.30 28 0.21 33

Samastipur 0.36 12 0.41 6 0.38 8 0.44 7 0.46 17 0.42 18 0.31 26 0.20 34

Sitamrhi 0.35 13 0.40 8 0.25 23 0.26 33 0.29 31 0.27 32 0.28 31 0.24 28

Khagaria 0.35 14 0.36 19 0.21 31 0.24 34 0.38 24 0.37 23 0.34 18 0.34 10

Buxar 0.35 15 0.35 20 0.34 12 0.41 13 0.58 7 0.54 5 0.34 19 0.29 18

Munger 0.35 16 0.34 25 0.43 4 0.41 12 0.59 5 0.55 4 0.59 2 0.51 2

Araria 0.34 17 0.37 15 0.16 35 0.30 27 0.25 33 0.25 33 0.23 35 0.06 37

Siwan 0.34 18 0.36 17 0.38 7 0.44 6 0.63 3 0.57 3 0.41 13 0.39 8

Muzaffarpur 0.33 19 0.37 16 0.49 2 0.59 2 0.49 15 0.44 16 0.33 22 0.27 23

Vaishali 0.32 20 0.36 18 0.35 11 0.46 4 0.51 11 0.47 13 0.36 15 0.31 14

Madhubani 0.32 21 0.39 11 0.28 20 0.33 21 0.38 23 0.35 24 0.38 14 0.31 13

Saharsa 0.31 22 0.31 27 0.21 32 0.33 22 0.27 32 0.28 31 0.29 30 0.22 30

E.Champaran 0.31 23 0.34 24 0.36 10 0.38 14 0.32 28 0.31 28 0.24 34 0.28 21

Banka 0.31 24 0.34 23 0.16 36 0.21 36 0.36 25 0.34 25 0.30 27 0.26 24

Nalanda 0.31 25 0.31 28 0.34 14 0.43 9 0.55 9 0.51 9 0.41 10 0.35 9

Madhepura 0.31 26 0.34 21 0.21 30 0.33 23 0.24 35 0.23 35 0.29 29 0.22 31

Katihar 0.30 27 0.31 30 0.21 33 0.29 30 0.25 34 0.24 34 0.27 32 0.18 35

Purnia 0.30 28 0.31 29 0.24 24 0.31 26 0.22 37 0.23 36 0.21 36 0.31 15

Gopalganj 0.30 29 0.32 26 0.40 5 0.46 5 0.50 13 0.47 14 0.50 3 0.45 4

Bhagalpur 0.30 30 0.34 22 0.37 9 0.41 10 0.44 20 0.40 20 0.44 8 0.43 6

Saran 0.28 31 0.31 31 0.31 19 0.34 18 0.53 10 0.48 11 0.36 16 0.34 11

Lakhisarai 0.26 32 0.28 32 0.23 25 0.18 37 0.45 19 0.43 17 0.33 23 0.23 29

Sheikhpura 0.25 33 0.27 33 0.32 18 0.34 19 0.48 16 0.52 8 0.33 20 0.26 25

Bhojpur 0.22 34 0.20 36 0.34 15 0.36 16 0.60 4 0.54 6 0.43 9 0.30 16

Darbhanga 0.21 35 0.24 35 0.34 13 0.34 17 0.34 27 0.32 27 0.32 25 0.27 22

Jamui 0.21 36 0.25 34 0.22 28 0.27 32 0.39 22 0.37 22 0.32 24 0.25 27

Patna 0.19 37 0.17 37 0.72 1 0.77 1 0.65 1 0.63 1 0.76 1 0.78 1

Average 0.33

0.35

0.32

0.36 0.43

0.40

0.36 0.31

CV 20.0

19.7

42.5

30.3 29.9

28.4

30.1 39.9

Source: Author’s calculations

The position of Nawada improved from 2000-01 to 2010-11 to 37th to 31st. It is due to better

performance in infrastructure and service delivery system. On the other hand, since the opening of

The South Bihar Railway, on which it is stationed, Nawada has been growing into an important

trade centre. Earlier Nawada was the main market place for most of the small villages around.

These are the reasons which uplift the position of district in the decade.


When we see the top five and bottom performer districts in services sector development for Bihar,

we find that Patna, Muzaffarpur, Sheohar, Munger and Gopalganj were placed as the top five

performer while Nawada, Banka, Araria, Kishanganj and Katihar as the bottom five performers in

2000-01. Among the top five performer districts Patna, Munger and Gopalganj are located in the

central region and Muzaffarpur and Sheohar in the north region of the state. Similarly, under the

bottom five developed districts in services sector Nawada and Banka are in the central and

remaining three from the north region. It shows that the districts of north Bihar are much

backward in comparison to central Bihar due to low literacy rate i.e. Patna has highest Literacy

Rate of 63.82% followed by Rohtas (62.36%) and Munger (60.11%). Kishanganj has lowest

Literacy Rate of 31.02% followed by Araria (34.94 %) and Katihar (35.29%). High literacy rate is

an important indicator which makes people aware about financial access and all the information

related to saving, credit-deposit and transaction related information. During the period 2010-11,

the top five performer districts were the same except Munger which rank has declined from 4th in

2000-01 to 12th in 2010-11. It is very surprising to note that the districts which belong to under

the five bottom performer in 2000-01 have improved their position except Banka. Banka is a

district of central Bihar which has a very few potential of improvement because of high poverty,

low literacy (only 58.4%) and being in naxalite belt. It is bifurcated from Bhagalpur due to

backwardness but still there is no effect of policy on that. The districts those belong to five bottom

performer in 2010-11 were Lakhisarai, Banka, Aurangabad, Khagaria and Sitamarhi. In these

districts there is shortage of bank branches per lakh of population, low literacy rate, low demand

and supply of financial services, uncertainty of market, less information about running program

and backwardness in other social and economic development indicator like less electrified

villages, number of rural and cooperative banks, high dependency of loan on other sources like

intermediaries, relatives etc.

It is observed that inter district disparity in terms of educational sector is high in Bihar in both the

time periods 2000-01 and 2010-11. It is interesting to point out that inter district disparity in

educational sector over the periods have decreased marginally in the state. Coefficient of variation

denotes that inter district disparity in educational sector has decreased from 29.99 in 2000-01 to

28.40 in 2010-11 in Bihar.

Location of comparing the top performing districts in educational development in Bihar gives a

very interesting result. All the better performing districts in Bihar have been seated in central

Bihar. Thus, a clear cut demarcation in Bihar is seen-central Bihar is developed while north Bihar

is backward in education. The achievement of Bihar too, in educational development is not

praiseworthy. Although, the condition of the state in terms of infrastructure has improved but still

the level of disparity in the state at intra-state level is not ignorable. In the state, the gap between

Central and North region is very high. In the Northern part of the state disparity in educational

sector is not only high but has increased over the time. The important cause for the low

development of the districts of Northern region may be the region is highly dependent on

agriculture and complete absence of manufacturing. In this region due to less productivity, low

and uncertain income and absence of any other source of livelihood except agriculture has resulted

in large scale migration from this region. The migrants leave their family behind and the

uncertainty of their income discourages them to send their children to school. Even otherwise they

are in a low literacy trap. They know that at the most their children can get primary education of


very poor quality supplied in government schools. They know that this education is not productive

and the opportunity cost of it is also very high. These things discourage demand for education and

depress educational attainment of the region. The important cause for lower performance in

education sector in the state may be high dependency on public sector schools where quality of

education is very low. In many schools teacher-pupil ratio are too high which make teaching

meaningless. In most of cases it has been seen that a number of public schools are not in position

to provide teaching facility because of infrastructure and sometimes lack of teachers.

There exists wide inter-district disparity in health sector in Bihar. In health sector, district-level

analysis shows that Patna stands at the top and Kishanganj the bottom position in 2000-01. The

Ministry of Minority Affairs (GOI) has identified 90 minority concentrated backward districts

using eight indicators of socio-economic development and amenities based on 2001 census data,

Kishanganj, one of the most backward districts of Bihar, stands at the bottom of the 90 minority

concentration districts. Rural areas of the district are lacking proper health facilities. One-fourth of

the villages of district Kishanganj have a PHC and only 15 per cent have MCW centre. Health

facilities are very inadequate, accessibility to health facilities is not satisfactory and Development

and welfare orientation organizations are lacking in most of the villages of the district.

It has been found that in case of Bihar, inter-district disparity has increased from 30.1 in 2000-01

to 39.90 in 2010-11. Increasing disparity in Bihar shows that there is some problem and ambiguity

in the allocation of resources toward backward areas. Due to low performance in education and

less reform in institution the effect of ongoing programs on the population is not significant and

most of the people are disadvantaged regarding health facility. Only few districts which are

politically powerful are able to get benefit and rest of the districts lag behind.

Table 3

Classification of Districts according to Economic and Social Development - 2001

Economic Development Human/Social Development

Category Index

Score Districts

Index

Score Districts

High

(>_70%)

More

than

0.323

Patna, Kaimur, Rohtas,

Muzaffarpur, Sheohar, Munger,

Begusarai, Samastipur, Siwan,

Gopalganj, Buxar, E. Champaran,

Vaishali, Bhagalpur, Gaya,

Nalanda (Central – 09, North – 07)

More than

0.483

Patna, Munger, Aurangabad, Siwan,

Bhojpur, Kaimur, Gopalganj,

Jehanabad, Nalanda (Central – 09, North – 00)

Moderate

(69-50%)

Between

0.323 &

0.275

W. Champaran, Jehanabad,

Aurangabd, Sitamarhi,

Madhubani, Kishanganj, Saran,

Supaul, Sheikhpura, Nawada,

Khagaria, Bhojpur, Darbhanga (Central – 06, North – 07)

Between

0.483 &

0.360

Rohtas, Buxar, Gaya, Begusarai,

Saran, Bhagalpur, Vaishali, Nawada,

Sheikhpura, Muzaffarpur,

Lakhisarai, Samastipur, Madhubani,

Khagaria (Central – 07, North – 07)

Low

(49% <_)

Less than

0.275

Purnia, Saharasa, Madhepura,

Katihar, Araria, Lakhisarai,

Banka, Jamui (Central – 03, North – 05)

Less than

0.360

Jamui, Banka, Darbhanga, Supaul,

W. Champaran, Sitamarhi, Sheohar,

Saharasa, E. Champaran,

Madhepura, Katihar, Araria,

Kishanganj, Purnia (Central – 02, North – 12)



CLASSIFICATION OF DISTRICTS ACCORDING TO LEVEL OF DEVELOPMENT

The study has categorised the four sectors e.g. agriculture, services, health and education into two

broad sectors; economic development and human/social development. Economic development

includes development in terms of agriculture and services sector and social sector includes health

and education. We have classified the attainment of different sectors in three levels of

development on the basis of highest variation proportion. We assume that there are errors in

making general expectation about the development of the different regions and districts of the state

because of some limitation of data for the two time periods 2000-01 and 2010-11. However, an

attempt has been made to emphasise the overall performance and trend of 37 districts of the state

in terms of these two development sectors and their changes over the periods.

Table 3 presents level of development of different districts in economic and social development in

2000-01. In terms of economic development the role of industrial sector is missing because of

non-availability of data for the corresponding years. On the basis of percentage value we rank the

entire district in descending order. Thus, the value ranges between three categories, highest score

ranges equal or up to 70%, medium category ranges between 69% to 50% and Low category

ranges below or equal to 49%.

The districts which fall in high developed category (greater than 70% of the highest) in terms of

economic development were only 16 out of 37. Among them nine districts are located in the

Central and seven in the North. The districts which ranges in this category were Patna, Kaimur,

Rohtas, Munger, Siwan, Gopalganj, Buxar, Gaya (from central), Muzaffarpur, Sheohar, Begusarai,

Samastipur, E. Champaran, Vaishali and Bhagalpur (from north). In the same way, in terms of

social sector development which includes health and education, there were nine districts that fall

in the high developed category. All the districts are located in Central Bihar and no district from

north region. The districts that fall in this category were Patna, Munger, Aurangabad, Siwan,

Bhojpur, Kaimur, Gopalganj, Jehanabad and Nalanda. Thus, the central region of the state is much

developed in comparison to northern in terms of economic as well as social development during

the period 2000-01.On the other hand the Northern districts has done relatively poor in the overall

and sectoral development.

In terms of medium developed category there were thirteen districts whose score fall between

0.380>_0.276 and explain 69-50% of the highest score variation. Out of thirteen districts six were

located in the central and remaining seven in the northern region of the state. The districts placed

in this category and located in Central region were Jehanabad, Aurangabad, Saran, Sheikhpura,

Nawadaand Bhojpur and the districts of northern region were W. Champaran, Sitamarhi,

Madhubani, Kishanganj, Supaul, Khagaria and Darbhanga. The districts of northern regions are

very advanced in services sector development but poorer in agricultural development. This is the

reason they are moderate performer in overall economic development. In terms of social sector

development there were fourteen districts that fall in moderate developed category and their score

vary between 0.483 and 0.360. The districts belonging to the Central region in social development

were Rohtas, Buxar, Gaya, Saran, Vaishali, Sheikhpura, Lakhisarai, and Nawada. These are the

districts that are very developed in agriculture development but low in services sector. On the

other hand, Begusarai, Bhagalpur, Muzaffarpur, Samastpur, Madhubani and Khagaria were

located in the north region of the state they are doing moderately in economic development.


The districts that fall in low developed category in economic sector were eight whose score is less

or equal to 0.271 and explain 49 percent of highest score. The districts that were located in this

category were Purnia, Saharasa, Madhepura, Katihar, Araria, Lakhisarai, Banka and Jamui. All the

districts have low rank in agricultural and services sector that is the reason their aggregate

performance of economic development was poor in 2000-01. Purnia is a district that is affected by

flood. Other economically low placed districts are lagging behind in agricultural inputs, seeds,

fertilizer, low area for agriculture and low intensity of irrigation. They are also backward in

services sector with low credit for agriculture, low access to banking, no. of telephone connection,

and other services which make the position of district in backward developed category in this

sector. In terms of social sector development, fourteen districts fall into low developed category.

Among them two districts are from the Central region which include Jamui and Banka. Another

eight districts were from the North region those have done badly in this sector were i.e. Purnia,

Darbhanga, Supaul, Kishanganj, Araria, Madhepura, W. Champaran, Sitamarhi, Sheohar, E.

Champaran and Katihar. The districts of northern region have poor health and educational

attainment which push down the rank of the districts. Due to high poverty and poor socio-

economic condition people have low resources for health and education, there is low admission in

standard public schools, the guardian found it difficult to afford tuition fees, text book and other

related expenditure. On the other hand, the supply side variable like govt. expenditure on

education related to facility and infrastructure is below standard and not distributed evenly across

the region. Whatever facilities are available these are only concentrated in some advanced districts

like Muzaffarpur, Vaishali, Bhagalpur and few other districts. Similarly, health services like

hospital with medical instrument, hospital facility, no. of PHCs, and service delivery system and

other infrastructure facility related to health system is poor in these districts. All the conditions

apply for the poor performance of services sector in these districts. Thus, in terms of economic and

social development majority of districts from northern region fall into low developed category

during the period 2000-01.

In this way the overall performance of North Bihar is poor in comparison to Central region of the

state. The poor performance of this North region in economic and social development is primarily

due to agriculture not done well. Agricultural output has also been highly volatile due to shocks

from drought and periodic monsoon flooding in the region. Services sectors are not performing

well and the programs that are launched to remove financial sector reform are not functioning well

in the region. The region is not only backward in economic development i.e. agriculture and

services but social sector outcome is also low in comparison to Central region. The main reason

for poor social sector outcomes is deficiencies in service delivery, particularly in services that

affect the poor and where the government plays a dominant role. Administrative deficiencies

compound the problems; there is a lack of monitoring, frequent use of teacher in other work

capacities, inadequate resources, and slow recruitment of teachers. As a result, the pupil-teacher

ratio has risen to more than 90:1 in primary school in the North Bihar. In this region, a similar

situation exists in the health sector. There is a serious shortfall of health sub-centers and primary

health clinics compared to the Central region. More importantly, existing clinics are beset by

endemic problems relating to quality standards: poor maintenance of facilities, idle equipment and

short supply of medicines and vaccines, particularly in the rural area of the region. Public

subsidies often fail to reach the poor. Both education and health subsidies are skewed in favour of


the upper economic groups, and all the money spent reaches the front line provider due to leakages

and corruption. The region has low demand for public services due to high cost and time required

in accessing them, is affected by local cultural factors like undervaluation of girl’s education.

Table 4

Classification of Districts according to Economic and Social Development - 2011

Economic Development Human/Social Development

Category Index

Score Districts

Index

Score Districts

High

(>_70%)

More

than

0.370

Patna, Kaimur, Rohtas,

Muzaffarpur, Sheohar, Munger,

Begusarai, Supaul, Samastipur,

Siwan, Gopalganj, Buxar,

Vaishali, Bhagalpur, Nalanda,

Kishanganj (Central – 08, North – 08)

More than

0.428

Patna, Munger, Aurangabad, Siwan,

Gopalganj, Jehanabad, Nalanda,

Rohtas, Begusarai (Central – 08, North – 01)

Moderate

(69-50%)

Between

0.369 &

0.292

E. Champaran, Madhubani, W.

Champaran, Nawada, Gaya,

Jehanabad, Araria, Madhepura,

Sitamarhi, Saran, Saharasa,

Purnia, Katihar, Darbhanga,

Aurangabad, Sheikhpura, Katihar (Central – 06, North – 11)

Between

0.427 &

0.329

Bhojpur, Buxar, Bhagalpur, Saran,

Kaimur, Vaishali, Sheikhpura, Gaya,

Khagaria, Muzaffarpur, Nawada,

Lakhisarai (Central – 08, North – 04)

Low

(49% <_)

Less than

0.291

Bhojpur, Banka, Jamui,

Lakhisarai (Central – 04, North – 00) Less than

0.328

Madhubani, Jamui, Samastipur,

Banka, Darbhanga, E. Champaran,

Supaul, Purnia, Sitamarhi, Saharasa,

W. Champaran, Sheohar,

Madhepura, Kishanganj, Katihar,

Araria (Central – 02, North – 14)


Table 4 shows that during the period 2010-11 the districts whose position was in high developed

category in economic development were sixteen. Among them eight districts were from the central

region i.e. Patna, Kaimur, Rohtas, Munger, Siwan, Gopalganj, Buxar, and Nalanda. The index

score of these districts were greater or equal to 0.370 which explained 70 percent of the highest

variation. Another eight districts were belonging to northern region these include Muzaffarpur,

Sheohar, Begusarai, Supaul, Samastipur, Vaishali and Kishanganj. Muzaffarpur is the district

which ranked 2nd in services sector and 12th in agricultural development. Sheohar is always

ranked under top five developed category in terms of agriculture and services sector that is the

reason this district was positioned in the highly economic developed category. In terms of social

sector development there were nine districts out of 37 whose position was high in socially

developed category. Out of nine high developed districts, eight belonged to Central and one

(Begusarai) from North region of the state. Begusarai is a district which has done well in health

indicator in comparison to other districts. In this district, the number of PHCs per lakh of

population is highest (1.32) after Sitamarhi (2.74) and Munger (1.41). The number of hospital and

dispensaries having beds are also higher (3.09) than all the districts of state except Sitamarhi

(7.76) and Munger (3.62). Infant mortality is lowest (46) in Begusarai after Patna (39). Apart from

health indicator the district has done well also in educational development indicator i.e. low pupil-

teacher ratio, higher number of schools with safe drinking water facility, trained teacher in primary


and upper primary schools etc. It ranked highest in female literacy rate and was second best

performer (66.23%) in overall literacy rate after Vaishali (68.56%) among the districts of northern

region.

At the same time, there were seventeen districts which fell in moderate developed category in

terms of economic development and their index score varied between 0.369-0.292. In this category

six districts were located in the Central region. These were Nawada, Gaya, Jehanabad, Saran,

Aurangabad and Sheikhpura. Remaining eleven districts were from the North Bihar these included

E. Champaran, Madhubani, W. Champaran, Araria, Madhepura, Sitamarhi, Saharasa, Purnia,

Katihar, Darbhanga, and Katihar. In terms of social sector, the districts which were located in

moderate developed category were twelve. Among them eight belonged to Central region i.e.

Bhojpur, Buxar, Saran, Kaimur, Sheikhpura, Nawada and Lakhisarai while four from North

region. Northern districts included Bhagalpur, Vaishali Khagaria and Muzaffarpur. The score of

these districts fall between 0.429-0.329 which explained 50%of the highest variation.

In 2010-11, number of districts which fell into low developed category in economic development

declined. It was eight in 2000-01 and now it is only four in 2010-11. Among the eight, five

districts have improved their position from low economic development to medium development

category those were, Purnia, Saharasa, Madhepuara, Katihar and Araria. The districts that fall in

this category were belong to the central region and were located in agro-climatic zone III that is

not favourable for agriculture and that is the reason the overall performance of the districts was

low in economic development. It will be worth-noting that in terms of social sector development

sixteen districts that fall into this category and among them two districts are located in the Central

region of the state and remaining in the North region. The districts from the central region and

falling under the low developed category in social development which index score lying to equal

or less than 0.328 were Banka and Jamui. The poor development in social sector refers to the

backwardness in health and education of these four districts. Banka is a district that has a very low

rural literacy is very low that is (59.61%), lowest percentage of school with drinking water facility

per lakh of population and low in number of government primary school per lakh population.

The above analysis shows that the state is suffering not only from huge inter-district and inter-

regional disparities in terms of economic and social development but the number of district have

changed their position in different sectors. The position of North region is poor relatively to

Central region. The public service norms in the region are poor defined, political inferences exist,

and the bureaucratic system is largely non-meritocratic. There are some additional unique factors

that contribute to the governance problems facing the region. All these are responsible and turn as

bottleneck in the development of the region.

RELATIONSHIP BETWEEN ECONOMIC AND SOCIAL SECTORS

In this section an attempt is to make to establish relationship between economic development and

social development of different districts of Bihar. Economic theory believes that economic and

social sector attainments normally go hand in hand. Hence, districts that are doing well in

economic parameters should also perform well in social sector indicators. Present work did a

clustering of districts of Bihar on the basis of their performance on economic and social sectors in

the two time period as mentioned above. The results obtained on the basis of composite index are


really very shocking in some cases. Thus the result shows that there are a large number of districts

that reflect desired correlation in the two development sectors over the time periods.

Table 5 shows some very important findings. It shows that out of 37 districts of the state only six

districts have done very well in both the sectors and fall into high developed category during the

period 2000-01. These include Patna, Munger, Siwan, Kaimur, Gopalganj and Nalanda. There are

seven districts which are rated low in terms of both sectors- economic and social. These districts

are Jamui, Banka, Araria, Katihar, Madhepura, Saharasa and Purnia. It is interesting to quote here

that there are no districts that have done well in terms of social development but have done worse

in terms of economic development in this period. We can thus argue that economic development

automatically leads to social development. The districts that fall in low developed category are

located in northern region of the state and no district of central region fall into this category. The

districts of northern region always suffer from flood as a result agricultural production has failed

to provide food-grain rural people. All these have also affected the well-being of people and have

created health related problems in the region.

Table 5

Cross-tabulating Districts by Economic and Social Development - 2000-01

Social Development Economic Development

High Medium Low

High

Patna, Munger, Siwan,

Kaimur, Gopalganj,

Nalanda

Aurangabad, Bhojpur,

Jehanabad ..

Medium

Rohtas, Buxar, Gaya,

Begusarai, Bhagalpur,

Vaishali, Muzaffarpur,

Samastipur

Madhubani, Saran,

Sheikhpura, Nawada,

Khagaria

Lakhisarai

Low .. Supaul, W. Champaran,

Sitamarhi, Kishanganj

Jamui, Banka, Araria,

Katihar, Madhepura,

Saharasa, Purnia


Table 6

Cross-tabulating Districts by Economic and Social Development - 2000-01

Social Development Economic Development

High Medium Low

High

Patna, Jehanabad,

Gaya, Nalanda, Rohtas,

Buxar, Muzaffarpur,

Bhojpur, Kaimur

Munger, Siwan, Nawada,

Gopalganj, Begusarai,

Saran, Vaishali,

Bhagalpur, Aurangabad,

Sheikhpura, Khagaria

..

Medium

.. Samastipur, Darbhanga,

E. Champaran,

Lakhisarai, Jamui, Banka,

Madhubani, Supaul, Purnia,

Saharasa,

Low

.. .. W. Champaran, Kishanganj,

Sitamarhi, Araria, Madhepura,

Sheohar, Katihar


Table 6 reveals a significant relationship between economic and social development during the

period 2010-11. The cross-tabulation explains that there are nine districts which fall into high

developed category in terms of economic and social development. The districts include Patna,


Jehanabad, Gaya, Nalanda, Rohtas, Buxar, Muzaffarpur, Bhojpur and Kaimur. All the districts in

this category belong to Central region of the state except Muzaffarpur. This result shows that the

districts that are economically advanced and well performing in social development at the time. In

contrast there are seven districts which keep their position in low development category. These

include W. Champaran, Kishanganj, Sitamarhi, Araria, Madhepura, Sheohar and Katihar in both

the sector in 2010-11. In this category all the districts are located in Northern region of the state. It

proves that the districts who performed badly in economic development are poor performer in

social development at the same time. It is thus important to look at the backward districts of the

state in economic and social development and formulate policy regarding and take action about

them.

CONCLUSION

The above analysis shows that the state’s fluctuating growth rates has not kept pace with the

national average. The state has low rank in per capita SDP among the several states and lags

behind in many development indicators related to economic and social development. There exists

wide regional disparity as districts of Central Bihar are more developed than that of North region

in all the four sectors i.e. agriculture, services, health and education. On the other hand, inter-

district disparity is low and declined from 2000-01 to 2010-11 in all the sectors except that of

health sector. Region-wise result revealed that central region has done well in comparison to north

region in both the years and its rank was also higher than state average. The study has established

correlation between economic and social development. It shows that out of 37 districts of the state

only five districts have done very well in both the sectors and consisting into high developed

category during the period 2000-01. What we are experiencing in Bihar is that the districts of

Jamui, Sheohar, E. Chapmaran, W. Champaran, Sitamarhi, Madhepura, Supaul, Araria, Katihar,

Kishanganj, Saharasa and Purnia have done unremarkably poor in terms of both the sectors that

need to be thoroughly investigated. A significant relationship between economic and social

development during the period 2000-01 and 2010-11 explained that there were only few districts

which fall into high developed category in terms of economic and social development.

_______________________________

Reference Alam, M. and Raju, S. (2007). “Contextualising Inter, Intra-Religious and Gendered Literacy and

Educational Disparities in Rural Bihar”, Economic and Political Weekly, May 5, pp. 1613-1622. Chakravarty, A. (2001). “Caste and Agrarian Class: A View from Bihar”, Economic and Political Weekly,

Vol. 36, No. 17, p.p. 1449-1462.

Chaudhary, P.K. (1988). “Agrarian Unrest in Bihar: A Case Study of Patna District 1960-1984”, Economic

and Political Weekly, Vol. 23, No 1/2, p.p 51-56.

Gupta, C.D. (2010). “Unravelling Bihar’s ‘Miracle Growth’”, Economic and Political Weekly, Vol. XLV No

52.

Rangarajan, L. N., (1992). “ Kautilya: The Arthashastra”. Penguin Classics, India

Ranjan and Prakash (2012). “Education Policies and Practices: What Have We Learnt and the Road Ahead

for Bihar”, Discussion Paper Series, Discussion Paper No. 6614IZA DP No. 6614.

Rorabacher, J. A. (2008). “Gerrymandering, Poverty and Flooding: A Perennial Story of Bihar”, Economic

and Political Weekly, 43 (7), 45-53. February 16th.

Sharma, K. L. (1976). “Jharkhand Movement in Bihar”, Economic and Political Weekly, XI (1/1), p.p. 37–43.

Thapar, R., (1966), A History of India, Volume 1, Penguin Books, London. (Reprinted in 1990, Penguin

India, Delhi).


INDIAN JOURNAL OF HUMAN DEVELOPMENT

The Indian Journal of Human Development (IJHD) is a peer-reviewed multi disciplinary Journal, published bi-annually by the Institute for Human Development, New Delhi. It provides an open platform for promoting debate and discussions from a human development perspective and also promotes critical engagement with human development discourse. IJHD publishes articles, reviews, perspectives, research notes/commentaries, statistics relating to human development and book reviews on India and developing world. The Journal welcomes expressions of all shades and opinions.

CURRENT ISSUE

The current issue brings together works of internationally renowned scholars and Indian researchers

on issues such as human development indicators and social exclusion, social sector expenditures and

impacts on human development, the primacy of politics in poverty reduction and development,

citizenship and displacement, social investments and interpretation of care needs, interdependence

between growth and inequality and poverty and inequality in high growth periods in the Indian

context.

Some of the articles published recently in IJHD include:

Amartya Sen: Children and Human Rights Arjun Sengupta: A Rights-Based Approach to Removing Poverty Amitabh Kundu: Achieving Diversity in Socio-economic Space: An Alternate Strategy of Intervention through the Diversity Index Ashwani Saith: Downsizing and Distortion of Poverty in India: The Perverse Power of Official Definitions Guy Standing: Reviving Egalitarianism in the Global Transformation: Building Occupational Security Jan Breman: The New Poverty Line: A Poor Deal Jean Drèze, Reetika Khera and Sudha Narayanan: Early Childhood in India: Facing the Facts Ravi Kanbur: What's Social Policy Got to Do with Economic Growth? Sabina Alkire and Suman Seth: Determining BPL Status: Some Methodological Improvements Sukhadeo Thorat: Social Exclusion in Indian Context Zoya Hasan: Equal Opportunity Commission and the Possibilities of Equality

SYMPOSIUM VOLUMES

IJHD publishes scientific papers and articles from symposiums and seminars on key aspects

of human development. Some of the issues covered in recent volumes of IJHD includes

Reports of the Expert Groups on Equal Opportunity Commission and Diversity Index (July-

December 2009), Estimation of Poverty and Identifying the Poor (January-June 2010), and

The Idea of Justice (January-June 2011). Details of papers in these volumes can be found at

the Journal website.

All correspondence should be addressed to :

The Editor

Indian Journal for Human Development

Institute for Human Development

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Email:[email protected]; Website : http://www.ihdindia.org/ihdjournal

http://www.ihdindia.org/#_blank


Research Perspective

WORKING CONDITIONS OF HANLOOM WEAVERS IN MADURAI CITY

R Mayamurugan1

The Textile industry has occupied a unique place in our country and its contribution to industrial

production, employment and export earning is very significant. While Indian handloom weavers

had a wider market in ancient times but have faced several challenges with the advent of textile

mills. At present the industry is passing through a crucial juncture – it is trying to gain niche

markets through its unique product style and modernisation of the craftsmanship. However, the

condition of workers in this sector continues to be bleak and unless they are taken care of, the

sector will die just because of lack of skilled manpower. Handloom industry in Tamil Nadu has in

its fold more than five lakh handlooms providing direct employment to about 13 lakh people and

livelihood to about 30 lakh people in associated areas. The industry has different types of

handlooms such as: looms for weaving cotton clothes, producing silks, art silks and other cotton

products. A survey in Madurai district of Tamil Nadu which is third largest handloom producing

district of the state throws up interesting perspective on this issue.

Majority of respondents work for 8-10 hours per day, while about ten per cent of workers were

observed to be working for 12-14 hours per day. The wages of handloom sector workers are based

mostly on piece rate. However the rates are quite low and therefore most of the respondents

belong to the low income group with income ranging between ` 500 to ` 1000 per month. Just

about two per cent of the respondents have income above ` 3000 per month. The remunerations

are therefore much below even those under MGNREGS. This shows that the handloom weavers

have very low bargaining capacity while deciding the remuneration rates. As a result we find that

the handloom weavers not only suffer from lack of nutritious food and low standard of living, but

also most of them suffer from debts. The working conditions are also not very supportive with

majority of workers having only a day’s leave in a month. Basic facilities in the workplace is also

lacking and the women workers face additional hardships. Effective steps should be taken both by

the co-operative society and the master weavers now towards improving remunerations and

working conditions of the actual weavers – the workers.

While this small survey highlights the basic problems faced by the workers in particular, this also

points to a malady of the sector in general. Because of the pathetic outcome, young people are not

interested in taking up this as an occupation. As a result skill formation is coming to a grinding

halt and it would not be long that the sector would face shortage of adequately skilled weavers.

That would surely mark deterioration in quality of the products and demise of the sector.

1 Lecturer, Department of Economics, Alagappa University Evening College, Thondi, Tamil Nadu, India, E-

mail: [email protected]


ANVESAK

A bi-annual Journal of SPIESR VOL. 42, NO.1 & 2 JANUARY-DECEMBER 2012

Key Note Address: Problems and Prospects Yoginder K. Alagh

Economic Viability and Sustainability of Small Scale Farming: A Study in

the Irrigated Gangetic Plains of UP

Ajit Kumar Singh

Food Security Aspects and Diversification of Demand in the Context of

Gujarat

Niti Mehta

Rationalisation of Agricultural Subsidies: Study of Electricity and

Fertiliser Subsidies in Karnataka and Tamil Nadu

Elumalai Kannan

Institutional Reform for Water Use Efficiency in Agriculture Jharna Pathak

Political Economy of the Energy-Groundwater Nexus in India: Exploring

Issues and Assessing Policy Options

Tushaar Shah, Mark Giordano

and Aditi Mukherji

Positive and Normative Aspects of Price and the Market in Indian

Agriculture-A Look at Government Policy Interventions in Food Management in an Unchanging Narrative of Traditional Agriculture

Munish Alagh

Land, Livelihoods, and State in India: Issues and Challenges Sukhpal Singh

Sustainability of Rice Cultivation in the Kole Land of Kerala Jeena T. Srinivasan

Growth of Paddy Production in India’s North Eastern Region: A Case of

Assam

Komol Singha

Determinants of Non-Farm Employment in Rural Uttar Pradesh Vachaspati Shukla

How Sustainability Can be Ensured in Uncomfortable Nexus of Water, Agriculture and Institutions?

Dalbir Singh


BOOK REVIEW

High Growth Trajectory and Structural Changes in Gujarat Agriculture: edited by

Ravindra H. Dholakia and Samar K Datta, 2010; 174 pages: price `175, ISBN:

0230330010.

Gujarat’s agricultural sector has performed phenomenally high during the last decade particularly

after 2003-04. Till then agriculture in the state was largely viewed as a relatively low performing

segment combined with high level of fluctuations, uncertainties and wide regional disparities. The

high growth process has attracted interest of many researchers to examine the process of growth

and its sustainability over long and medium term. Gujarat has emerged as one of the four major

states having attained higher labour productivity in agriculture (along with Punjab, Haryana and

Kerala) in the past few years. During 2003 and 2007 agriculture in the state grew at a

phenomenally high rate of 11 per cent, which was by far the highest among all the states in the

country. To a large extent, the ‘growth miracle’ has been driven by bt-cotton revolution that has

spread to large parts of the state as pointed out by Tushar Shah (2010). It was also noted as

‘Agriculture miracle of Gujarat’ by the government of Gujarat in the published volume. The

success of Gujarat’s agricultural growth, has taken place at a time when the sector, in several other

states in India were yet to attain a significant breakthrough in the growth performance. No wonder

therefore, the high growth experience of Gujarat’s agriculture came to be widely acknowledged

and being upheld as a potential `role model’ to follow by several of the agriculturally lagging

states in the country.

An attempt has been made to examines the agricultural growth pattern in Gujarat during the recent

period and the factors responsible for the growth by Dholakia and Datta in their edited volume.

The book was relevant as it provides evidence and explanation for the high growth performance of

agricultural sector in Gujarat. Many eminent scholars have contributed their research work for the

volume. The first chapter by Dholakia begins by examining the overall and agricultural growth

trajectory over the fifty years in Gujarat. The growth miracle of agricultural sector in Gujarat was

statistically proved by Dholakia by using sophisticated econometric tools like Bai-perron test and

quandt method. The agricultural sector in Gujarat has witnessed the structural break during 2001-

02 fallowed preceded by structural break point of the overall economy-GSDP during 2002-03.

Hence he concluded that the recent spurt in agricultural growth signifies a structural break that

was set in since the beginning of the century, hence preceded the high growth rate in overall

economy in the state. There could be variations in the interpretation of agriculture sector leading

or following higher rate of growth especially in industry and infrastructure in the post-1997 period

as suggested by Morris [2007], the fact remains that agriculture in Gujarat has taken-off to a high

growth trajectory, which undoubtedly may have exerted significant impacts on rural economy in

general and poverty reduction in particular. The rest of the chapters explains factors responsible

for the success story of agricultural sector.

The second chapter by Pathak and Shah discusses the features of agricultural sector in Gujarat and

interventions made during the last decade which led to the phenomenal growth of the sector.

Several factors like watershed development, irrigation expansion due to the jyotogram yojana


(uninterrupted powder supply in the village) and the innovative extension program of the Gujarat

government (Krishi Mahostav) are the factors responsible for the high growth. While most of

these seem to have exerted fairly positive impact on the sector’s growth performance, there is little

by way of deeper understanding on the structural dynamics or the sources of growth, which

essentially, may have significant bearing on the developmental outcomes of the high rate of

growth in agriculture.

The third chapter by Gandhi and Namboodiri discusses the role of bt-cotton in the growth miracle

of the agricultural sector. There was increase in area, yield and production of cotton in Gujarat

compared to other cotton producing states in India. The primary survey that the authors conducted

in order to substantiate the macro picture shows that the yield and revenue from the bt cotton was

higher than non bt-cotton. The yield of bt cotton was higher than non-bt among all the land

holding groups and significantly higher compared to the non-bt production. The state government

policy and strong market system has substantially supporter the promotion ob bt cotton in Gujarat.

However the issue of sustainability of the bt-cotton production by maintaining the natural

resources and environment has not been discussed in full length in the chapter.

The fourth chapter discusses the commercial crop sector performance in Gujarat. The chapter

examines the value chain of two major commercial crop (castor and isabgol) in Gujarat and their

contribution to the growth process. The analysis shows that the growth in the commercial crops is

inclusive of nature as the small and marginal farmers have also gained out of those crops. Sukhpal

Singh claims that the developed marketing infrastructure and higher demand in the export market

are the factors leading for the higher and stable production. Value addition in the local area is

another important factor for the increase in the production. For the better market linkage and

higher remuneration for the farmers he has suggested mainly three important interventions,

contract farming, functioning of open regulated market (APMC) and organic farming.

The fifth chapter by Samar Datta discusses the importance of the fruits and vegetable sector as one

of the major factor for the high agricultural performance. The author presents the result by

conducting case studies as the secondary data from various government sources unable to explain

the differential performance of the major fruits and vegetables across various districts/regions. The

results from the case studies are presented by visiting various cooperatives. The author points out

that in absence of pro active policy the growth in the fruits and vegetable sector might not sustain

for longer period.

Livestock is one of the integral parts of the agricultural sector as it constitutes around one fourth of

the total income from agriculture and allied sector. Gujarat being a dryland region the importance

of livestock is prominent. The growth in livestock sector has positive impact on the income of the

small and marginal farmers. Sharma and Thaker in the sixth chapter, has discussed both the

demand (changing in food demand) and supply side factors (producer’s cooperatives which has

helped to connect the rural farmers to the urban consumer) for the livestock development.

However the author has mentioned as animal products are high income elasticity the food price

inflation has adversely affected the livestock sector. What is overlooked in this chapter is that over

time, dairy sector has undergone certain important structural shifts in terms of composition of

livestock from small ruminants and cows and then to buffalos, the increasing concentration from

dry to relatively water abundant areas and enhancing the share of relatively better off households,


often with land and irrigation as compared to the landless and the marginal farmers [Shah, 2006].

This poses a serious doubt that the small and marginal farmers might have got excluded from the

growth process.

The role of irrigation in agriculture crop production has been analyses by Parthasarathy in the

seventh chapter. The chapter addresses the pertinent issue of water management for the better

agricultural productivity. He has argued that there is a need to expand the surface irrigation and at

the same time there is a need for proper management of the ground water. The authors argues that

there is a need to extent the irrigation system besides Narmada.

The last chapter establishes the relationship between agricultural export and infrastructure

development. The chapter shows that along with the increase in the production the export also has

increased. Rastogi and Dholakia pointed out that with the increase in the production the export

market has also expanded in Gujarat mainly due to the infrastructure development in terms of

transport, support, distribution and information.

Overall the book has explained in detail the major interventions during the recent period and their

contributions to the growth miracle of the agricultural sector. It explains clearly the growth model

of Gujarat. However it is equally important to analyse the whether the faster growth is inclusive of

nature or not. What have been the actual processes and what kind of improvements are necessary

to make the growth inclusive as well as environmentally sustainable? These issues however, are

yet to be unraveled in the light of detailed probing.

Itishree Pattnaik

Assistant Professor

Gujarat Institute of Development Research

Ahmedabad


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ISSN: 2277-9108 JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING · Journal of Regional Development and Planning, ... No. 2, 2014 ISSN: 2277-9108 JOURNAL OF REGIONAL DEVELOPMENT AND