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JOURNAL OFREGIONAL DEVELOPMENT AND PLANNING
Volume 1 Issue 2 December 2012
CONTENTS
Pages
Editorial Note i
Articles
Regional Disparity in Agricultural Development: ADistrict-Level Analysis for Uttar Pradesh
Rakesh Raman &
Reena Kumari
71
Economic Growth and Sectoral Linkages: EmpiricalEvidence from Odisha
Deepak Kumar Behera 91
Dispossession for Development in India: SomeExperiences on Land Acquisition
Bhaskar Majumder 103
Regional Origin of Manufacturing Exports: Inter-StatePatterns in India
Jaya Prakash Pradhan
& Keshab Das
117
Rural Infrastructure Availability and Wellbeing S. Chakraborty,A. Baksi & A.K.Verma
169
Book ReviewAn Introduction to Development and Regional Planningwith special reference to India;Jayasri Ray Choudhuri
Tanushree De 180
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JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING
Editorial Team
Chief Editor
Kalyanbrata Bhattacharyaformerly ofDepartment of Economics, University of Burdwan
Editor
Rajarshi MajumderDepartment of Economics, University of Burdwan
Managing EditorJhilam Ray
Department of Economics, University of Burdwan
Editorial Advisory Board
Aditya Chattopadhyay, Calcutta University
Ajit K Singh,Director, Giri Institute of Development Studies,
Amitabh Kundu,Jawaharlal Nehru University
Alakh N Sharma,Director, Institute for Human Development
Biswajit Chatterjee,Jadavpur University
Dinesh C Sah, Director, MPISSR
Kausik Gupta,Rabindra Bharati University
Rabindranath Bhattacharya,Kalyani University
Rajendra P Mamgain,Director, Indian Institute for Dalit 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
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Journal of Regional Development and Planning, Vol. 1, No. 1, 2012 i
Editorial Note
Journal of Regional Development and Planning received tremendous enthusiasm and
encouragement when it hit the stands six months back. It was acknowledged that JRDP has
succeeded in placing itself as a peer reviewed journal providing interdisciplinary and applied
perspective on regional development.
In the past six months, we have had evidence of expanding regional imbalance across the globe.
Spatial inequality is rising not only in terms of economic indicators like income and consumption,
but also in terms of human development parameters like educational standards and health
indicators. It may also come as a surprise to some, but not all, that disparity is rising not only in
geographically large countries of the third world, but also in EU and CIS countries. Even NAFTA
has shown marginally increasing regional disparity in recent times. This has serious implications
for not only global economic order, but social dynamics as well. Even world peace depends on a
sustainable balance between different regions and countries. This makes the study of regional
development all the more important.
We reiterate that Journal of Regional Development and Planning will continue to publish original
work that explores conceptual and empirical papers from all branches of social sciences with a
focus on regional development.
RM
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Journal of Regional Development and Planning, Vol. 1, No. 2, 2012 71
REGIONAL DISPARITY IN AGRICULTURAL DEVELOPMENT: A DISTRICT-LEVEL ANALYSIS for UTTAR PRADESH
Rakesh Raman & Reena Kumari1
The growth of agriculture is prerequisite for overall development of Indian economy. It
contributes significantly to the export earnings and affects the performance of other sectors of the
economy through forward and backward linkages. The present paper analyses district and
regional level disparity in agriculture development in Uttar Pradesh on a number of agricultural
parameters. It uses UNDP methodology (subsequently used by a number of others) to standardize
various indicators for agricultural attainment in the state of Uttar Pradesh using 13 agricultural
development indicators. A composite index has been constructed at the district level and also
regional level for two cross-section years 1990-91 and 2008-09. The relative variations and
changes in ranks of different districts have been computed during the period under consideration.
Evidence shows existence of high and persistent inter-state disparity in agriculture in the state
over the years. The transformation of some districts from the level of relatively underperformer to
the rank of better performer and vice versa has been witnessed and explained. The findings
encourage the authors to conclude that a more determined effort on the part of the policy makers
is needed if the development policy has to be made truly inclusive.
INTRODUCTION
Indian economy at the dawn of 21stcentury finds itself at the cross-roads. Last few years have seen
its transformation from an ailing agricultural economy to a rapidly growing one with services
sector emerging as the power house for the economy. The economy has experienced an average
annual growth rate of approximately 6 to 8 per cent during the last two decades. As is to be
expected, improvement in economic growth and per capita income has translated, at least partly,
into reduction in the level of poverty in the country and accelerated improvement in various
indicators of human development. However, there is a broad consensus among critics as regards
growth not being inclusive and balanced. It is claimed that there exist huge diversity and regional
disparity across the economy at state level. The gap between rich and poor regions that existed
even at the time of independence has widened over the years and significantly intensified during
the period of reforms.
There exists voluminous literature dealing with the issue of regional disparity. Most studies have
targeted state as unit for measuring disparity and have sought to gauge the impact of development
policy on relative development of the states. The findings of such studies have been used by
government agencies to frame policies to promote balanced regional development. These policies
have met with limited success and not only disparity has increased but has started showing its
ugliest face. One significant factor causing limited success to efforts of balanced developments has
been the neglect of variations within states and exclusive reliance on information relating to
disparity at the state level. For a huge country like India where some of the states are bigger than
1Associate Professor and Senior Research Fellow respectively at Department of Economics, Banaras Hindu
University, Varanasi 221005; contact: [email protected]
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many nations, it is very important to look at the disparity at the disaggregate level. This is an
account of a number of reasons. First, the regional development policy is framed by the
government by treating the state as a homogenous unit which it is not. Measurement of disparity at
the district level would help to frame area specific plans and policies in a better manner and adopt
policies suitable to tackle different regions within a state. Second, a study of disparity at the
disaggregated level is essential for ascertaining the level of development in agriculture, industry,infrastructure, per capita net state domestic product (NSDP), level of literacy among men and
women, health cover and other sectors across all the districts of a particular state and also for
analyzing the respective roles of physical/natural factors vis--vis man-made factors in causing (or
aggravating) interregional economic inequalities. Third, the widening gulf between advanced and
backward regions within a state leaves those living in backward regions disgruntled and
dissatisfied, creates an aversion towards the civic processes and raises doubt about the viability
and usefulness of the political system. This has destabilizing impact on district economy and
polity. Fourth,growth of developed pockets within a particular state promotes concentration of
economic units in the region, results in increased internal migration, causes environmental
backlash etc. Fifth, experience shows that cross-country comparisons of stage and pace of
development are impossible and, following the same logic, inter-state interregional comparisons
are also very difficult when the regions differ significantly in terms of size, principal features,
governance etc. A study at the disaggregated level is required for identification of the factors that
are instrumental in the controlling regional disparity and developing policy mix to promote the
same.
It is this realisation that has encouraged the present authors to attempt at analysing inter-district
agricultural disparity in Uttar Pradesh. Indian agriculture is known for its diversity which is
mainly the result of variations in resource endowments, climate, topography and historical,
institutional and socio economic factors. Policies followed in the country and nature of technology
that became available over the times has reinforced some of the variations resulting from natural
factors. As a consequence, production performance of agriculture sector has followed an uneven
path and large gaps have developed in productivity between different geographic locations across
the country. Being primarily agricultural, high growth in agriculture sector is a pre-requisite for
attaining higher growth in the overall economy of the state, as also for reduction in the incidence
of poverty. Unfortunately however, since the tenth plan the agricultural sector in the economy has
not been doing well and the growth rate in the sector has remained in the vicinity of a low 2 per
cent per annual. There is deceleration in the growth of agriculture along with the distressed state
of farmers, in general and that of small and marginal farmers, in particular. What is more
intriguing is that there is wide inter-region and inter-district disparity within the state. While the
districts of the Eastern and Central (Bundelkhand) regions are fighting tough situation riddled with
the problem of small size of land holding, farmers indebtedness, migration and poor access to
modern technology; those located in Western region are relatively better-off. This variation in
situation of agriculture is on the one hand causing lop-sided development of the state and
increasing dissatisfaction and disenchantment of farmers of the backward area, on the othermaking policy formulation extremely difficult. Policymakers can not apply one set of policy for all
the regions/districts of the state because the nature of the ailment, level of development and
complications differ. What is, therefore, required is to have firsthand detailed information of the
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variation among different districts of the state in agricultural development, their growth trend,
strength and weaknesses, so as to formulate right mix of policy that can resurrect the agricultural
sector of the State. It is this need that the present paper addresses. It attempts to see the extent of
variation among different districts of UP in the last two decades. It compares the districts at two
time periods 1990-91 and 2008-09 to see how the disparity is evolving over a period of time.
This paper thus raises questions about the ability of decentralized planning to promote agriculturalequality in Uttar Pradesh. What are the levels of various districts of Uttar Pradesh in agricultural
development during the period 1990-91 to 2008-09? What are the causes and effects of disparity
which allow for both equality and growth? The paper is divided into four sections. Section-I
provides a brief review of literature. Section-II describes methodology and data source of the
study. Section-III analyses district and regional level attainment of agricultural in Uttar Pradesh in
terms of the indicators chosen and measures the inter-district and inter-region disparity. Section-
IV provides suggestions to make things better for the state.
CONCEPTUAL FRAMEWORK: A REVIEW
The literature on regional disparity relating to agricultural development is vast and varied. Here
we have divided the extent literature into three broad ways-
1.
Regional Disparity at State-level2.
Regional Disparity at District-level
A good number of writings and research papers have been carried out to identify disparity at state
level using different methods and indicators. There are a number of approaches that have tested
the convergence hypothesis for India. Their finding has been conflicting- We have on the one hand
the works of Dholakia (1994), Cashin and Sahay (1996), Nagaraj, et al. (1998 and 2000) and few
others who have tested for conditional and absolute convergence by including a number of
alternative variables and have observed that there has been conditional convergence for the states
of the Indian economy. We on the other hand have works of Bajpai and Sachs (1996), Rao et.al
(1999), Dipankar et.al (2000), Aiyar (2001), Trivedi (2002), Singh, et al. (2003), Bhattacharya &
Sakthivel, (2004) who claim that there has been divergence between states in the post
independence era. Nayyar (2008) in his generalised methods of moment method confirms thatthere is no evidence of any convergence in growth of Indian states. These authors have attempted
to identify factors that have caused divergence and are seems to be in unison so far as the negative
impact of structural reforms and liberalisation on disparity is concerned.
In sum, two key points emerge from the existing literature analyzing convergence across Indian
states. First, there is robust evidence for unconditional divergence or the lack of unconditional
convergence. Second, the evidence on conditional convergence is not entirely conclusive.
The alternative approach defines convergence as a reduction in the equality of regional incomes
over time. The simplest way to measure a reduction in regional income inequality is in terms of a
fall in the standard deviation of the logarithm of regional (per capita) incomes. This standard
deviation-based approach is also known in the literature as sigma convergence (Barro and Sala-i-
Martin, 1995). The list of works using different alternative methods of disparity such as Ginni
Coefficient, Theils entropy index, Coefficient of variation, Rank Analysis, Index of Rank
Concordance, Composite Indices using factor analysis etc. is very long. The important works
include the one by Nair (1971), Gupta (1973) Chaudhury (1974) Majumdar and Kapoor (1980),
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Cashin and Sahay (1996), Rao, Shand and Kalirajan (1999), Ahluwalia (2000), followed by
Bhattacharya and Sakthivel (2004), Sabyachi kar and Sakthivel etc. Almost invariably all the
works have found that disparity between states no matter which inequality concept is used has
increased since independence and has intensified since the launching of reforms. These works
have also sought to identify different factors especially government policies that have led t the
intensification of disparity.There is great dearth of studies measuring disparity in India at the disaggregated level. There are
very few works of quality available dealing with intra-state disparity. We can quote only a
handful. These include the one by Shaban (2006) for the state of Maharashtra, using Principle
Component Analysis (PCA) for the benchmark years 1972-73, 1982-83 and 1988-89. The study
finds that regions of Vidarbha and Marathwada and the district of Ratnagiri, Raigadh Dhule and
Jalgaon have been the least developed both at sectoral and the aggregate levels of development.
Shastri (1988) has examined the regional disparity for the state of Rajasthan which covers a period
of 23 years (1961-1984). The study delineates the developed and underdeveloped districts and
within the districts, the developed and underdeveloped sectors which require the attention of
the policy makers. It clearly brings out the existing inter-district imbalances in the economic
development of Rajasthan and makes the need for greater emphasis on regional approach todevelopment planning obviously. A recent study, by Diwakar examine the regional disparity at
disaggregate level, using district as a unit for the state of Uttar Pradesh and find that no district in
the Eastern and Bundelkhand regions were in the most developed category. At the same time,
many districts in the Western and Central regions were also on the lower rungs.
There are a number of attempts made at discussing backwardness of a particular region or
prevalence of crisis like situation in some other but the thrust on regional disparity in agricultural
development has been rather lacking. Clearly, the studies relating to backwardness of agriculture
have pointed out some major problems of the agriculture sector but have failed to compare the
variations in performance of different regions and the reasons thereof.
Among the works that investigate causes of backwardness of agriculture/crisis of agriculture in the
state and in selected regions mention may be made of the works of Vakulabharanam, Chand,Mishra and others. For example, Vakulabharanam (2005, 2008) has argued that the reduction of
domestic support in terms of subsidy and credit on the one hand, and drastic price fall of
agricultural commodities in the international market on the other hand, has led to distress in the
farming class of the state. Mishra, (2007), Reddy and Mishra, (2008) emphasise that crisis in
agriculture was well underway by the 1980s and economic reforms in the 1990s have only
deepened it. Decline in the supply of electricity to agriculture has been regarded as major cause of
distress by Chand et. al (2007); Chand (2005); and Chand and Kumar (2005).
Narayanamoorthy (2007) argues that fall in wheat and rice production is not due to technology
fatigue rather due to extensive mono crop cultivation and high use of fertilisers and faulty
agricultural pricing. Lack of allocation of funds to irrigation development after liberalisation has
also resulted in the stagnation of net area irrigated. This poor growth in surface irrigation hascompelled farmers to rely heavily on groundwater irrigation. The increased dependence on
groundwater irrigation increases the cost of cultivation and depletion of ground water resources
and in addition to this credit unavailability for investment on inputs put farmer in further crisis.
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Suri (2007) and Reddy (2006) argue that agrarian distress is result of the liberalisation policies
which prematurely pushed the Indian agriculture into the global markets without a level-playing
field; heavy dependence on high-cost paid out inputs and the other factors such as changed
cropping pattern from light crops to cash crops; growing costs of cultivation; volatility of crop
output; market vagaries; lack of remunerative prices; indebtedness; neglect of agriculture by the
government; decline of public investment have contributed further to agrarian crisis. Same time,they points out that technological factors, ecological, socio cultural and policy related factors have
contributed for the crisis.
Further, authors argue that extensive cultivation has led to decrease in productivity, which is due
to intensive use of fertilisers, which in turn resulted in increasing cost of inputs, ultimately leading
to decrease in profit margins. Ecological factors include decreasing quality of land and water
resources due to intensive chemical and fertiliser use. Socio and cultural factors include the effects
of globalisation and urban culture on villages had shown impact on health and education
consciousness in the rural agrarian families, in order to get the access of better facilities farmers
have changed their cropping pattern. Policy related factors like decrease in public investment from
4 per cent of agricultural GDP during 1980s to 1.86 during early 2000. Patnaik (2005) examined
how neo liberal policies introduced in the 1990s affected peasant community by examining thefund allocation to the rural development and concludes that fund allocation has come down from 4
per cent of NNP in 1990-91 to 1.9 per cent of NNP by 2001-02. Gulati and Bathla, (2001), Chand
and Kumar, (2004) have studied the impact of capital formation on Indian agriculture and have
found that growth in capital formation in Indian agriculture has been either stagnating or falling
since the beginning of 1980s. The process has been further aggravated by the macro economic
reforms that have squeezed public investment. Vyas (2001) examined the impact of economic
reforms on agriculture and claimed that Indian farmers mostly consists of small and marginal
farmer who mainly depend on agricultural price policies such as Minimum Support Prices (MSP)
subsidies on inputs and irrigation, however, after reforms the MSP has not been properly regulated
by the government leading to farmers distress.
A review of the studies reveals that the studies have highlighted major reasons for agriculturaldistress. These reasons include vagaries of nature (primarily, inadequate or excessive water), lack
of irrigation facilities, market related uncertainties such as increasing input costs and output price
shocks, emphasis on commercial and plantation crops due to agricultural trade liberalisation,
unavailability of credit from institutional sources or excessive reliance on informal sources with a
greater interest burden and new technology among other. In addition, decline in the area under
cultivation, which seems to be a result of expanding urbanization and industrialisation,
deterioration in the terms of trade for agriculture, stagnant crop intensity, poor progress of
irrigation and fertiliser have also been stressed.
Most of existing studies do not highlight the inter-district or inter-region variation in agricultural
development and talk mainly in terms of the overall state or just one region of it but, contribute in
finding the variables that should be taken to measure level of agricultural development in differentregions of the state. The present study gets hints and impetus from the study done so far in
identifying the appropriate variable and bridging the gap in the literature pertaining to
comprehensive treatment of agricultural disparity. It makes an attempt to identify the backward
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regions of Uttar Pradesh in agricultural development indicators at two cross-section periods 1990-
91 to 2008-09.
Methodology & Database
The present paper an attempt has been made to develop suitable indices involving appropriate
indicators to measure the extent of disparity in agricultural attainment in the state of Uttar Pradesh.
The indicators are different and heterogeneous across the district of the state. District level data onthe variables have been chosen keeping in the view the availability of information. There are two
problems related to methodological that the present author has come across. First, there are a
number of indicators of level of agricultural attainment, but the source of data for these indicators
are varied making it difficult to use all the indicators jointly to develop a composite index. Further,
the fact that the present study attempts to compare disparity in agricultural attainment at different
time periods cause additional problem. This is because the agencies providing the information
have been frequently changing the definition and coverage making it difficult to use data across
time period without involving considerable error. Second, the study seeks to compare regional
variation for the benchmark year 1990-91, and 2008-09. The year 1990-91 represents the turning
point of reform period and 2008-09 represents the latest year for which most of the information are
available. Between 1990-91 & 2008-09 a number of new districts have come up in UP. Althoughin most cases one big district has been bifurcated to form two new districts but in some stray cases
out of two big districts a third one has been carved out. For making comparisons as we try to
reconstruct the old districts in 2008-09, the ideal methodology would have been to find figures for
different blocks and add these to get figure of the whole old district. The non-availability of
relevant block level data however has forced us to shun this and go for adding the data of new
districts to get information of the old district in the process assuming that the new districts are
subset of the old one. This indeed involves some error but we are compelled to commit this
because of lack of information. The study thus takes only 54 districts and all newly created
districts have been merged accordingly on the basis of 1990-91 year. The merging of these new
districts for the year 2008-09 have been done by averaging all the indicators according to
population of districts. Data for regional development are mainly cited or calculated from the
latest available statistics, mostly from U.P. Planning Commission, Census of India and U.P.
District Development Report. The study computes composite index for agricultural development
which shows the pattern of development and rank of various districts in agricultural attainment.
First, the values of the selected indicators for all the 54 districts of the state were collected and
tabulated.
Then the tabulated data were transformed into standardised Xids, using equation 1, where Xidrstands for actual value of ithvariable for district drth(number of district) and Min Xidrstands for
minimum value of ith variable of all districts, Max Xidr stands for the maximum value of ith
variable within the all districts and Xidstands for the standard value of the ithvariable in the dth
district and dthruns from 1 to 54, representing the 54 districts of the state of Uttar Pradesh.
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If, however, Xi 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 equation 1
can be written as:
By giving the weight on the basis of HDI method we have averaged the value of all variables
according to the weight and find the composite index of agricultural sector. The following
indicators were used:
1. Per-capita Food-grain Production (PCFP)
2.
Distribution of Total Fertilizer per Hectare of Gross Area Sown (DTFGAS)
3.
Gross Irrigated Area as Percentage of Gross Sown Area (GIA)
4.
Percentage of Area Under Commercial Crops to Gross Sown Area (PCCGSA)
5. Availability of Gross Area Sown per Tractor (AGAST)
6. Cropping Intensity (CI)
7. Percentage of Area Under Forest to Total Reporting Area (PAUFTRA)
8.
Percentage of Net Area Sown to Total Reporting Area (PNASRA)
9.
Number of Regulated Mandies per Lakh of Population (NRASRA)
10. Percentage of Net Area Sown to Cultivable Land (PNASCL)
11. Percentage of Total Electricity Consumption in Agriculture Sector (PECASTE)
12. District-wise Percentage Distribution of Private Pumping Sets/Tube wells (DPDPPT)
13. District-wise Percentage Distribution of Government Tube wells (DPDGT)
Agriculture Development in Uttar Pradesh: overview
Uttar Pradesh, despite more than six decades of planned efforts and industrialization drives still
remains basically an agricultural and food producing state of India. Agriculture not only
contributes significantly to the states NSDP but, at the same time, is a major source of
employment in rural areas. Despite the prominence of agriculture the situation of agriculture in thestate is not something to be really proud of. Table-1 and Chart-1 provides a brief description of
how the UP economy and agriculture have grown vis--vis the country.
A brief perusal of the table and the chart reveals some important things. First, that barring Fifth
Plan (and marginally the Sixth Plan), the Annual Plans and the Tenth Plan, the growth rate of
agricultural sector in UP has remained considerably lower than that for the nation as a whole. For
a state where agriculture is the mainstay for bulk of population this shows the poor state of affairs
of the sector and also the apathy and lack of support of the government. Second, in all the plans in
which the growth rate of agriculture has exceeded that for the nation as a whole, the overall
growth rate of the UP economy has also exceeded the growth of the nation as a whole. This
reaffirms our hypothesis that Uttar Pradesh is basically an agricultural state. Third, the chart
clearly shows that the agricultural sector in the state has not grown in any consistent fashion.There has been regular fluctuation in the growth rate (Chart makes it very clear) with the rate of
growth varying between -0.09 per cent in the III Plan to 5.42 per cent during the Annual Plans.
The fluctuation shows the vulnerability of the sector to seasonal conditions.
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Table 1Growth Rate of Agriculture and Allied Sector during the Plan Period (in per cent)
PlanAgriculture & Allied Sector Overall Economy
UP India UP India
1 First Plan (1951-56) 1.86 2.71 2.12 3.60
2 Second Plan (1956-61) 1.48 3.15 1.75 3.95
3 Third Plan (1961-66) -0.09 -0.73 1.58 2.324 Three Annual Plan (1966-69) 0.62 4.16 0.32 3.69
5 Fourth Plan (1969-74) 0.94 2.57 2.23 3.25
6 Fifth Plan (1974-79) 5.23 3.28 5.70 5.30
7 Sixth Plan (1981-85) 2.54 2.52 4.11 4.10
8 Seventh Plan (1985-90) 2.69 3.47 5.70 5.80
9 Two Annual Plan (1990-92) 5.42 1.01 3.14 2.47
10 Eighth Plan (1992-97) 2.70 3.90 3.20 6.80
11 Ninth Plan (1997-02) 0.80 1.90 2.00 5.60
12 Tenth Plan (2002-07) 2.10 1.10 5.30 7.70
Sources: Uttar Pradesh Planning Commission
Besides uneven and rather tardy growth of the agricultural sector in the state, a permanent issue is
wide inter-region and inter-district variation in terms of almost all indicators of economic
development and human development. The state, fifth largest in size and first in terms of
population, UP is huge by any standard and variations in resource endowment, climate,
topography and historical, institutional and socio-economic parameters, besides apathetic attitude
and faulty policies of the government over a period of time, have taken together, resulted not only
in perpetuation of inter-district/region disparity but even its intensification.
Chart 1
Growth Rate of Agriculture and Allied Sector during the Plan Periods
Sources: Uttar Pradesh Planning Commission
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Table 2
Region-wise Comparative Status of Development in UP
Source: 11th five year plan document of Uttar Pradesh, Mishra, 2007(Row 19 and 20) and Statistical
Abstract, Uttar Pradesh, 2010
The primary focus of the present work is to talk about inter-region and inter-district
variations/disparity in agricultural development in the state. The state is divided into four
administrative/economic zones and nine agro-climatic zones. Since, for overall policy formulation
administrative division is giving credence, we have also provided explanting of variation in terms
of economic zones. Table 2 provides a summary picture of different zones of the state in terms of
some important indicators. It has been noticed that Bundelkhand was the most backward region in
almost all the agricultural and allied indicators except road length (infrastructure indicator) in the
period 2008-09. In contrary, Western region was the most advanced region in several sameindicators only except road length. The Bundelkhand followed by Eastern region of Uttar Pradesh
were less developed regions compared to Western followed by Central region of the state in
agricultural parameters. The reasons behind backwardness of these states are the low financial
Indicator Year Western Central EasternBundelkh
andU P
(1) (2) (3) (4) (5) (6) (7) (8)
I. Agriculture andAllied
1. Area under marginalholdings less than one(hect.)
2000-01 1906.9 1374.2 3003.5 362.9 6647.7
2. Percentage of totalfertilizer distribution togross cropped area(Kg.)
2008-09 17.9 15.4 15.9 4.3 15.5
3. Cropping Intensity 2008-09 162.4 153.4 154.8 125.0 153.8
4 Length of roads perlakh of population(Kms.)
2008-09 76.8 80.5 84.8 118.3 82.7
5. Percentage of Netirrigated area to net area
sown
2008-09 91.7 84.5 76.4 56.4 81.1
I.1 Productivity of Major Crops (qtls /hect)
6. Average yield of food-grain
2008-09 27.8 23.6 22.6 14.5 23.6
7. Wheat 2008-09 34.0 30.3 26.9 23.8 30.0
8. Rice 2008-09 22.5 20.5 22.1 13.2 21.1
9. Potato 2008-09 223.8 184.2 157.3 205.5 205.5
10 Pulses 2008-09 8.6 9.2 9.0 9.0 9.0
11. Oilseeds 2008-09 12.6 7.8 6.9 4.5 8.9
12. Sugarcane 2008-09 564.5 477.4 444.2 369.9 524.7
13. Monthly Returns fromCultivation per farmer
Households (Rs)
2002-03 1398.0 815.0 572.0 1011.0 836.0
13. Average HouseholdSize of Farmer
2002-03 6.1 5.6 6.3 5.7 6.1
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assistance, high indebtedness of farmers, crisis of agriculture and most concrete problem is
colonial policy of development. In spite of several government policies that is launched by central
and state government, huge climatic condition for agricultural production and located in indo-
gangetic plains notwithstanding, these regions are failed in agricultural production. Another
problem of the Eastern region is population pressure and high dependence of workers on
agriculture which creates marginal size of holdings. On the other hand low income and highpoverty was next cause for lower performance of agriculture in this region. When we see the
physical quantities of food-grains crops, Bundelkhand region followed by Eastern region were
again less developed compared to Western followed by Central region of Uttar Pradesh in the
period 2008-09. Average yield of food-grains production was highest in Western region that was
also higher than state average in the same period. In 2002-03, monthly returns from cultivation per
farmer household was high in Bundelkhan region, due to some specific production of crops like
potato and some-how influenced by positive policy implication and government subsidy
assistance.
Regional Disparity: Inter-district and Regional Analysis
Disparity in agricultural productivity in Uttar Pradesh across different regions and districts is a
matter of deep concern. In spite of planned efforts, the gap between developed and backwardregions has not been bridged. The variation in agricultural productivity across various regions of
the state may be attributed to differential resource endowment in terms of soil fertility, land
pattern, average annual rainfall, irrigation and infrastructure and also socio-cultural and economic
conditions of farmers. In the current era of liberalization and privatization and free play of market
forces, many foresee that regional disparity may increase due to the logic of the survival of the
fittest.
Table 3 & Table 4 together provide a picture of inter-region disparity in terms of agricultural
development in the state. Table-3 classifies the districts of the state into three categories on the
basis of percentile and index scores. The percentile score has been computed on the basis of the
score of the best performing district of the state. The first category of high performers have a
percentile score of 0.8 and above (the index score spread of the categories have been shown incolumn -2), the districts with a percentile score falling in the range 60 per cent and 80 per cent
have been put in the category of moderate performers, while districts with index score of less than
60 per cent have been branded as low performers. The Table reveals some very interesting results.
First, there exist wide variations among districts with respect to agricultural development. In both
time periods we have on the one hand some districts that have done very well while on the other
there are some who have lagged behind.
Second, the Western region overall has been the best performing region of the state in terms of
agricultural development. Out of a total 14 high performing districts in 1990-91, 12 belonged to
the Western region. Similarly for 2008-09 out of 25 districts in this category 17 were from the
Western Region. None of the districts of this region fell in the low performer category. The
relative position of the districts of this region has also improved with time as is evident fromshifting of 5 districts of this category from moderate performer category to high performer
category.
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2 in 2008-09. Mainpuri, Etah and Farukkabad have also shown relative progress. The positions of
Aligarh, Mathura and Meerut have deteriorated in the intervening period. Mathura was in 2008-09
standing at 44th position out of 54 districts. This shows that although overall the Western region
has made progress over time and the inter-district variation as judged by CV has gone down, but
the gap in the performance of best performing districts and the lagging district within the region
has widened.Table 4
Level of Development of Agriculture in Different Districts of Uttar Pradesh
S.N.Districts
1990-91 2008-09
Index R Index R
Western Region
1 Saharanpur 0.615 2 0.551 6
2 Muzaffarnagar 0.591 4 0.549 7
3 Bijnor 0.547 7 0.534 12
4 Moradabad 0.595 3 0.555 3
5 Rampur 0.545 8 0.552 5
6 Meerut 0.588 5 0.531 13
7 Ghaziabad 0.49 15 0.487 198 Buland Shahar 0.621 1 0.58 1
9 Aligarh 0.514 10 0.478 20
10 Mathura 0.426 32 0.389 44
11 Agra 0.455 26 0.449 30
12 Firozabad 0.459 25 0.475 22
13 Etah 0.499 14 0.548 8
14 Mainpuri 0.467 22 0.548 9
15 Budaun 0.539 9 0.554 4
16 Bareilly 0.477 19 0.501 15
17 Pilibhit 0.55 6 0.546 10
18 Shahjahanpur 0.509 11 0.557 2
19 Farrukhabad 0.484 18 0.509 14
20 Etawah 0.453 27 0.455 28
WR Average 0.521 0.517
WR S.D. 0.059 0.048
WR C.V. 11.31 9.329
Central Region
21 Kheri 0.472 21 0.536 11
22 Sitapur 0.391 41 0.495 16
23 Hardoi 0.392 40 0.473 23
24 Unnao 0.338 46 0.388 45
25 Lucknow 0.332 48 0.355 47
26 Rae Bareli 0.44 31 0.444 33
27 Kanpur Dehat 0.402 37 0.443 34
28 Kanpur Nagar 0.36 44 0.395 43
29 Fatehpur 0.425 33 0.418 3830 Barabanki 0.397 39 0.459 26
CR Average 0.395 0.441
CR S.D 0.044 0.054
CR C.V. 11.11 12.25
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region. The CV (Coefficient of variation) of index score for the region was 24.22% in 1990-
1(20.57% in 2008-09) symbolising very high variation. If the best performing district of the region
has a low average score of 0.335 the position of other districts with such high CV can be easily
ascertained. Lalitpur district of the state the lowest overall had a score of only 0.18 in 1990-91,
3.45 times less than the best performing district of the state Bulandsahar.
The reasons for agricultural backwardness of Bundelkhand are not difficult to understand. We maymention some important ones here. The regions agricultural sector is heavily dependent on
rainfall which has been erratic. It is supplemented by groundwater which has been receding.
Agriculture here is diverse, complex, under-invested, risky and vulnerable. The region lacks
alternate sources of water for irrigation. A depleted groundwater table and the high costs
associated with building and operating irrigation infrastructure are putting the region in deep
trouble.
Further harsh and worsening biophysical conditions such as low soil fertility, combined with more
frequent extreme events such as droughts caused by climate variability and change, further
exacerbate the regions vulnerability. Of late, climate change that is being reflected in high rainfall
intensity coupled with decrease in winter precipitation has resulted in high runoff and higher rivers
flow making flood and erosion an eventuality.The region has a population of approximately 21 million, out of which 82.32 per cent is rural and
more than one third of the households in these areas are considered to be Below the Poverty Line
(BPL). The condition of the farmers in the region is very bad; they are in debt which is mounting.
They neither have the resources not adequate governmental assistance to take up the agricultural
work well. Low resources here have forced farmers to go for solo cropping and cultivate only 20%
of the net shown area in the Kharif season. About 60% of the gross cropped area remains irrigation
less. Gradual decrease in the area cultivated during the Kharif season is also easily visible. It was
around 33% of the gross cropped area in the year 1977-78 and which got reduced to 26% in the
year 1993-94 and remained only 23% in the year 1998-99 to around 20% at present.
75% of the farmers are small and marginal with average land holding of up to 2 hectares and most
of them can only think of mere survival. Their continued existence is by and large reliant on theblend of produces of their own land and daily wage earning. Whereas gradual growing cost of the
agriculture ingredients which is largely because of change in agricultural practices and adaptation
of high water consuming varieties. This is also another critical component that is responsible for
increasing vulnerability of the small and medium cultivators due to reason of entire control of big
landlords on water in Bundelkhand.
Land rights in the region are also not very clear. Land shown in records to be in the possession of
weaker sections, or as part of the village commons, has been encroached upon by big landowners.
Many landless families have been given land on paper, but, for various reasons, have not been able
to occupy the land. There are several allottees who do not know exactly which plot of land has
been allotted to them. They cultivate a plot only to be told later that it is not their land.
All these factors taken together make the situation of agriculture in Bundelkhand really precarious
and increase the inter-region variation substantially.
The Eastern Region of the state, where a bulk of population resides also fair badly in terms of
agricultural development. Table-4 shows that the region had an average score of 0.422 in 1990-
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1(0.4.24 in 2008-09) with a CV of 16.39%. Only two districts Mau and Ghazipur of the region
could find a place in the high performing districts in 1990-91. The number however increased to
05 in 2008-09. Most of the districts were placed in moderate performer category with the
exception of Sonebhadra and Mirzapur which in both time periods stood in the category of low
performers.
The Central Region of the state that comprises of Kanpur, Kheri, Sitapur etc. have been by andlarge moderate performers over the years.
Regional Disparity in terms of Key Indicators
Regional variation among different districts of Uttar Pradesh in terms of key indicators of
agricultural development is depicted in Table 5 & Table 6. They also show how the variation has
changed since the launching of period of reforms. The table is split into two parts the upper part
shows the indicators in terms of which over the intervening period disparity has widened while the
lower half shows indicators in terms of which it has gone down. There are some very interesting
things to note.
Table 5
Some Statistical facts about Regional Disparity in Agricultural Indicators
Indicators1990-91 2008-09
Mean S.D. C.V. Mean S.D. C.V.
Declined
PCFP 270.73 87.6 32.35 220.93 112.52 50.92
AGAST 241.43 311.1 128.85 171.54 249.41 145.39
DTFGAS 89.15 34.42 38.61 153.39 64.79 42.23
NRASRA 1.47 0.6 40.72 1.71 0.71 41.9
PNASCL 84.88 8.4 9.9 69.22 10.22 14.77
PECASTE 47.79 21.7 45.4 22.49 11.9 52.89
Improved
GIA 59.89 19.62 32.76 46.18 13.01 28.18
PCCGSA 19.67 14.36 72.99 17.85 12.87 72.09
PNASRA 69.03 10.45 15.14 69.22 10.22 14.77
CI 148.19 15.63 10.55 155.64 16.26 10.44
PAUFTRA 6 9.04 150.63 5.48 8.15 148.54
DPDPPT 1.83 1.08 59.17 1.56 0.83 54.64
DPDGT 1.84 1.1 59.81 1.52 0.83 54.64
Source: Authors Calculations
First, for a number of indicators the disparity across the districts has widened over a period of
time. A deeper look reveals that in terms of indicators that work as proxy for technology such as
distribution of fertilizer per hectare of gross area sown, tractor use, electricity use etc., the gap has
widened (coefficient of variation of these indicators among districts has increased with time). This
means that in terms of technology used while the advanced regions are marching ahead the
backward ones are lagging further behind.
Second, while there has been increase in the average value of a number of indicators, for some
other decline has been witnessed. For example there is decline in percentage of electricity
consumption in agriculture sector to total consumption; number of regulated mandies per lakh of
population, percentage of net area sown to cultivable land, per-capita food-grain production,
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percentage of area under commercial crops to gross sown area etc. This shows that because of
poor performance of the backward regions of the state, the overall position of the state has
worsened over a period of time. This calls for immediate attention to be paid on the backward
regions and more appropriate measures for the particular indicator where the performance of the
state is sliding down
Table 6Top and Bottom Ranking Districts in Agriculture Development in Uttar Pradesh
Indicators1990-91 2008-09
Top 2 Districts Bottom 2 Districts Top 2 Districts Bottom 2 Districts
PCFPPilibhit,Shahjahanpur
Kanpur Nagar,Lucknow
Pilibhit,Shahjahanpur
Ballia, Badaun
GIA Meerut, GhaziabadBahraich,Sonebhadra
Mainpuri,Bulandsahar
Sonebhadra,Hamirpur
PCCGSAMeerut,Muzafarnagar,
Banda,Siddarthnagar
Muzzafernagar,Bijnor
Siddarthnagar, Mau
AGAST Mau, Rae Bareilly Agra, Meerut Maharajganj, Ballia Varanasi, Agra
PNASRASiddarth Nagar,Moradabad
Sonebhadra,Mirzapur
Muradabad, RampurSonebhadra,Lalitpur
NRASRABulandsahar,Saharanpur Basti, Azamgarh Rampur, Saharanpur
Azamgarh,Mathura
PNASCL Rampur, SaharanpurLalitpur,Sonebhadra
Meerut, Ghaziabad Sonebhadra, Jhansi
CI Bulandsahar, Mau Hamirpur, Jhansi Mainpuri, Rampur Hamirpur, Banda
DTFGASKanpur Nagar,Pilibhit
Sonebhadra,Hamirpur
Varanasi, KanpurNagar
Lalitpur, Hamirpur
PAUFTRASonebhadra,Mirzapur
Varanasi,Azamgarh
Sonebhadra, Kheri Ballia, Ghazipur
PECASTE Hamirpur, AzamgarhSonebhadra,Lalitpur
Ghazipur, BadaunKanpur Nagar,Lucknow
DPDPPT Moradabad, Basti Jalaun, Sonebhadra Pratapgarh, SitapurLalitpur,Sonebhadra
DPDGT Varanasi, Allahabad Lalitpur, Mathura Badaun, Allahabad Mathura, Lalitpur
Source: Authors calculations
Third, top two and bottom two districts in terms of major indicators at the two points of time
chosen indicate that while the leading districts have by and large maintained their position over the
period of eighteen years (between 1990-91 and 2008-09), the bottom place districts have been
changing their position. Apart from few exceptions here and there, normally the districts from
Western region have occupied the top two positions in all the indicators.
Fourth, the table reveals that over the years the government has been to some extent successful in
providing irrigation facility in backward regions. The disparity in terms of all the indicators of
irrigation facility such as district-wise percentage distribution of private and government pumping
set/tube wells, gross irrigated area as percentage of gross sown area etc. has gone down. This is
indeed a welcome sign. However, explored more intensively we could notice that the expansion is
not so high in the most deficient region i.e. Bundelkhand.
Fifth, a look at Table 7 shows the variation among the different agro-climatic zones of the state. It
reveals that there exists wide variation among the zones, with Western Plain Zone and Mid-
Western Plain Zone leading and Bundelkhand and Vindhya Regions lagging behind. However,
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there has been no perceptible increase in disparity if judged from this angle. Chart-2 given below
plots the coefficient of variation among districts of the zones between the two time periods. The
primary reason for backwardness of the lagging regions is that the climate of both these regions is
dry sub-humid and soil mixed red and black and medium black respectively that require more
water. Non-availability of assured irrigation facilities in the regions chiefly accounts for the poor
performance of agriculture there.Table 7
Agro-Climatic Zones of Uttar Pradesh & Performance of Districts in Agriculture
SN Agro-Climatic Zones Districts1990-91 2008-09
Mean S.D Mean S.D
1 Central Plain
Kheri, Sitapur, Hardoi, Farrukhabad,Etawah, Kanpur Nagar, Kanpur Dehat,Unnao, Lucknow, Rae Bareilly,Fatehpur, Allahabad, Pratapgarh
0.401 0.051 0.443 0.05
2Southern WesternSemi Arid Zone
Aligarh, Etah, Mainpuri, Mathura Agra,Firozabad
0.47 0.031 0.481 0.06
3 Bundelkhand ZoneJhansi, Lalitpur, Banda, Hamirpur andJalaun
0.273 0.66 0.247 0.55
4 Eastern Plain ZoneBarabanki, Faizabad, Sultanpur,Pratapgarh, Jaunpur, Azamgarh, Ballia,Ghazipur , Varanasi, Mau
0.443 0.058 0.453 0.02
5North-Eastern PlainZone
Gonda, Bahraich, Basti, Gorakhpur,Deoria, Siddarth Nagar, Maharajganj,
0.43 0.034 0.427 0.04
6 Vindhyan Zone Mirzapur, Sonebhadra 0.285 0.078 0.289 0.07
7 Bhabhar & Tarai Zone Bijnour, Rampur, Bareily, Pilibhit 0.529 0.354 0.533 0.02
8 Western Plain ZoneMuzzafar Nagar, Saharanpur, Meerut,Ghaziabad, Bulandsahar
0.582 0.047 0.541 0.03
9Mid Western PlainZone
Budaun, Shahjahanpur, Moradabad 0.547 0.043 0.555 0.1
Source: Authors Calculations
Conclusions and Suggestions
The study has shown that development of agriculture in Uttar Pradesh over the year has remained
polarised in Western region followed by Central region. Bundelkhand region has been the least
developed over the periods 1990-1991 to 2008-09. The empirical evidence suggested that
maximum number of district have scored best record in the attainment, located in western and
central region of the state, where agriculture is commercialised, technology is also advanced. This
was the region that was much influenced to green and technical revolution, resulted high
contribution in export and food production of the state. The disparity existing in agricultural
development is high and alarming. A series of measures are needed on the part of the government
to bridge the yawning gap. We give three suggestions to alleviate the problem-
First, there is need for region specific policies in this state which is huge in size. For the high
density eastern regions where excessive dependence of population is causing adoption of
backward technology and small size of holding, more that resurrecting agriculture we need to
create alternative employment opportunities in rural areas in form of Rural Non Farm Sector.
Once, the surplus population shifts in the non-agricultural sector and is able to generate some
surplus there, it would be possible to pool back the surplus in agriculture and higher farm-nonfarm
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linkages which work in both the direction would pull the agricultural sector up. For Bundelkhand
region, long term policy and planning is required. Apart from shifting the population away from
agriculture, the government need to provide cheap finance and dependable source of irrigation in
the region. Agriculture extension activities are required to educate farmers to adopt cheap, suitable
and effective technology and crop variety. In the Western region where the signs of crisis of the
nature in Andhra Pradesh and Vidarbha are gradually appearing, suitable interventions in form offuture trade in agriculture through involvement of banks, less water intensive agricultural
technology etc. are required.
Second, Despite all efforts by the RBI on promoting financial inclusion and all toll claims of its
success, non-availability of cheap, dependable and easy finance remains a chief concern for
farmers in the backward regions. Micro-finance has its own limitations which are well known. We
need to develop a mechanism that ensures credit and subsidy to the neediest region.
Third, There is need to identify the agro-climatic zones that have problems. Table 7 clearly reveals
that the two most backward zones are Bundelkhand and Vindhya. Specific efforts should be made
for these regions.
Agriculture in Uttar Pradesh has stagnated and grown in uneven fashion. Since for most part of the
next couple of decades agriculture is going to remain as the mainstay of population and so if thisunevenness and disparity are allowed to persist it will be putting bulk of the population of the state
under duress. The state government in consultation with experts and the Central government
should adopt a long term policy for giving a direction to the states agriculture. Formulation of
area/region specific plans with emphasis on direct assistance to the most needy and plugging the
leakages in government sponsored schemes are going to be the key in this regard. We all hope that
the present government of Uttar Pradesh under the stewardship of a young and energetic leader
would take appropriate steps to bridge the disparity and resurrect the backward sectors.
_____________________________
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ECONOMIC GROWTH AND SECTORAL LINKAGES: EMPRICAL EVIDENCEFROM ODISHA
Deepak Kumar Behera1
The present paper analyses the trends in sectoral shares in state domestic product and inter-sectoral linkages in Odisha for the period 1980-81 to 2011-12. Results drawn from Granger
causality test suggest that there is a weak linkage between primary and secondary sectors in the
growth process. In the case of primary and tertiary sector services, though the primary sector
does not show linkages with the tertiary sector as a whole, it does have linkages with some
important sub-services like trade, hotel and restaurant services. Between secondary and sub-
sector of tertiary sectors, there is an independent relationship of industry with trade, hotel and
restaurant, and community, social and personal services. However, there is a unidirectional
causality between secondary to finance, insurance, real estate and business services on one hand
and transport, storage and communication to secondary sector on the other. The long-run
cointegration results show a strong relationship between secondary and TSC services in the
economy on one hand and independent long run relationship within FIRB on the other. However,
results based on error correction model indicate a weak association between the sectors in the
short run. Though the linkage is significant between the sectors, but it is not linked with threesector analysis where primary sector is completely missing for a relatively faster adjustment
towards long run equilibrium rate of growth.
INTRODUCTION
Odishas economy has been following a high growth trajectory in recent years as shown by
acceleration in terms of the gross state domestic product (GSDP). The evidence clearly shows that
the economy is poised for a take-off to a high growth phase, almost similar to that at the national
level (Panda, 2008). In real terms at 1999-2000 prices, Odisha reported an average annual growth
rate of 9.51 per cent for the 10thFive Year Plan against a target of 6.20 per cent and achievement
of 5.30 per cent for the 9thPlan. The economy has grown, in real terms at 2004-05 prices, at anaverage annual rate of 9.57 per cent during the first three years of the 11thPlan. This bounce-back
is remarkable and is in line with national trends (Economic Survey, 2010-11). Similar to the other
states, the economy of Odisha has been going through structural changes away from agriculture in
favour of industry and services, where service sector becoming more and more pronounced. In
2011-12, the service sector accounted for nearly 50 per cent of the Gross State Domestic Product
(GSDP) followed by secondary sector (29 per cent) and primary sector (21 per cent). The high
growth rate recorded by the State in the first decade of this century comes mainly from that in the
industrial sector. The growth in the agriculture sector continues to be highly volatile due mainly to
adverse impacts of natural shocks such as cyclones, droughts and floods. The service sector has
been growing in a comparatively stable manner.
1Assistant Faculty, Entrepreneurship Development Institute of India, Gandhinagar, Gujarat - 382428, E-mail:
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Such sectoral composition has undergone a structural shift over the year. With the declining share
of agricultural income, the shift in the composition is likely to cause substantial changes in the
production and demand linkages among various sectors and in turn, could have significant
ramifications for the growth and development process in the economy. Now the question is
whether agriculture is more important for acceleration in the rate of growth of the economy or
industry should be considered as the engine of growth? And how tertiary is linked up with the twosectors have also been another debatable issue in the development literature. A number of studies
have been made to analyse the sectoral linkages in context to India. Like Rangarajan (1982) who
found a strong degree of association between the agricultural and industrial sectors. He claimed
that the consumption linkages are much more powerful than the production linkages between
sectors. Kanwar (1996) found that the process of income growth in manufacturing and
construction gets significantly affected not only by agriculture but also by infrastructure and
services. Bhattacharya and Mitra (1997) provided empirical evidence in support of a positive
linkage among the broad sectors. It established that many services activities are significantly
associated with the agricultural and industrial sectors and this helps in overall employment
generation. Hansda (2001), in his study, found that services and agriculture do not seem to share
much interdependence; industry is observed to be the most services-intensive. Sustained services-
growth requires a growing industry too. Bhanumurthy and Mitra (2003) have found that a shift in
value added mix towards industry and tertiary activities have caused a larger decline in the
incidence of poverty in the nineties compared to that in the eighties. Sastry et al (2003) maintained
that due to modernisation of agriculture the dependence of agriculture on the industry for inputs
has grown. As for the services sector, they found a movement of production linkages from the late
1960s to the early 1990s moderately in favour of agriculture, and sharply in favour of the services
sector.
From the above discussion, it has seen that the importance of sectoral linkages is useful to
understand the association between different sectors in the economy. However, there is a
significant gap in the literature because the inter-sectoral linkage studies were mainly concentrated
on the national economy. The studies at the state or region level have not received comparable
attention. With this backdrop, an attempt has been made in this paper to examine whether a
significant inter-sectoral causal relationship does exist in the state of Odisha, and if it does, what is
the nature of long-run relationship between them. Since developments in the liberalization of
agriculture, industry and services are understood to have brought a structural shift, an empirical
investigation of inter-sectoral growth linkages is essential to divulge meaningful directions for
prioritisation of reforms across the sectors.
The analysis is based on National Accounts data on gross domestic product (GDP) at 2004-05
from 1980-81 to 2011-12. However, the data set are available from 2004-05 onwards but the back
series of state GSDP have not been provided by CSO at the same base year. Therefore, for the
purpose of the study, GSDP series with 2004-05 base have been built by applying splicing method
for the period 1980-81 to 2004-05.
The outline of the paper follows; section II revisits the structure and growth of states income
across major economic activities. Section III examines the inter-sectoral linkages between the
sector where Granger-causality, cointegration and error correction technique has been used.
Finally, summary and policy implications of the paper are given in Section-V.
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STATES STRUCTURE AND GROWTH OF OUTPUT: SECTORAL ANALYSIS
Prior to analysing the sectoral linkages in Odisha economy, it would be useful to review the
changes in the sectoral composition of the gross domestic product, in terms of share of primary,
secondary and tertiary sector. Sectoral shares, at 2004-05 prices, are given in Figure 1 and Table 1.
From the table it depicts that the average share of states GSDP to all-India GDP has gone down
from 3.55 per cent in 1980-90 to 2.81 per cent in 1991-00 and further declined to 2.59 per cent in2001-11. This suggests that despite the states own GDP has increased, the share from those
states whose contribution are quite higher to the all-India GDP has taken into to a higher level
and hence the level of share of Odisha has gone down. On sectoral basis, over the period the
average share of real income of agriculture plus mining i.e. primary sector has declined from 47.25
per cent in 1980-90 to 36.14 per cent in 1991-01 and further declined to 27.86 per cent in 2001-11.
In contrast, manufacturings share together with electricity, gas, water, sanitation and construction
activities considered under the secondary sector has accelerated from 24.43 per cent in 1980-90 to
a maximum 27.63 per cent in 1991-01 and surprisingly come down to 27.42 per cent in 2001-1
due to a 4 per cent point in share decline in construction sector. Tertiary (services) has witnessed a
continuous expansion with a share in total income rising from 28.32 per cent to 44.72 per cent
over time. Within services, share of transport, storage, communication has become doubled and
that of trade, hotel, restaurant and social, community, personal services has increased its share by
almost one and half times. And the share of finance, insurance, real estate and business services
along with community, social and personal services has risen by one per cent change in point from
1991-00 to 2001-11. The skewed pattern of economic growth has been observed where the relative
share of agriculture is declining, industry nearly constant and services rising in the gross domestic
product.
Figure 1
Percentage Share of States Income by Sector (at 2004-05 prices)
47.2
5
24.4
3
28.3
2
36.1
4
27.6
3
36.2
327.8
6
27.4
2
44.7
2
0
10
20
30
40
50
Primary Secondary Tertiary
PercentageShare
1980-90 1991-00 2001-11
Source:National Account Statistics
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Table 1
Average Percentage Share of States GDP by Sector
Sector1980-81 to
1990-911991-92 to
2000-012001-02 to
2011-121980-81 to
2011-12Primary Sector 47.25 36.14 27.86 34.03
Agriculture and allied 45.34 31.67 20.57 28.59
Mining & Quarrying 1.91 4.47 7.29 5.44Secondary Sector 24.43 27.63 27.42 26.85
Manufacturing 7.75 8.96 13.71 11.24
Electricity, Gas and Water supply 3.74 4.30 3.44 3.73
Construction 12.94 14.37 10.26 11.89
Tertiary Sector 28.32 36.23 44.72 39.11Trade, Hotel and Restaurant 6.95 8.77 12.04 10.13
Transport, Storage and Communication 3.15 4.59 8.27 6.25
Finance, Insurance and Real Estate 8.67 9.57 10.38 9.81
Community, Social and Personal Services 9.55 13.30 14.04 12.92
Total GSDP 100 (3.55) 100 (2.81) 100 (2.59) 100 (2.80)Note: Bracketed figures are average percentage share of Odisha GSDP to All India GDPSource:National Account Statistics
While analysing the rate of growth of the state, figure 2 plots the 3-year moving average series of
the annual growth rates in GSDP. This figure clearly reveals a rising trend since 2001-02. There
thus seems to be an upturn for a high growth phase in Odisha. The only other time when above 7
per cent average growth had been achieved earlier was the 3-year period ending 1989-90. The
1990s clearly was a lost decade for Odisha from economic growth point of view when it could not
take advantage of the benefits of reforms.
Figure 2
Three Year Moving Average Series of GSDP Growth
-4
-2
0
2
4
6
8
10
12
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
GrowthRat
GSDP
Source:National Account Statistics
The semi-log regression on a time trend1in table.2 suggests that since 1980 to as of now, the long
term average GSDP growth rate of Odisha is growing at a rate of 4.58 per cent against all-India
growth of 6.15 per cent. The states growth of output has peaked at a rate of 9.1 per cent during
2001-11 over 3.6 per cent in 1991-00. A major development during the 2001-11 phases is
1 Semi-log Regression: Ln(GSDP) = + T, where, T stands for time trend, and are thecoefficients of the model. A positive value of coefficient of time, , for a particular sector indi-cates a positive trend of that sector, while a negative value of the coefficient would mean anegative trend.
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accompanied by much higher growth in the non-agricultural sectors, particularly in tertiary sector.
In a sectoral approach, primary sector growth rate was below 2 per cent in 1990s and 2001, but
witnessed a higher rate of growth i.e. 5.23 per cent during 2001-11. Such an acceleration growth
occurs due to a significant growth in agricultural sector. For the secondary sector, it witnessed a
declining trend in 2000 compared to 1990, but recorded a highest growth rate of 11.25 per cent in
2001-11. This is because of a tremendous shift of growth occurs in manufacturing sector followedby construction sector. In tertiary sector, it has witnessed a phenomenal growth from 5.81 per cent
in 1980-90 to 6.19 per cent in 1991-00 and 10.39 per cent in 2001-11. Almost all the activities that
fall under the services, except community, social and personal services, all have grown
significantly. Though Tertiary sector has not recorded the highest growth rates in 2001-11 under
study, but this sectors growth rate has been showing a consistently rising trend.
Table 2
Rate of Growth of Sectoral GDP at 2004-05 Prices
Sector1980-81 to
1990-911991-92 to
2000-012001-02 to
2011-121980-81 to
2011-12
Primary Sector 1.18 1.60 5.23 2.04Agriculture and allied 0.77 0.33 3.69 0.83
Mining & Quarrying 10.47 11.72 10.36 11.45Secondary Sector 6.51 2.83 11.25 5.24
Manufacturing 7.70 3.80 17.05 7.36
Electricity, Gas and Water supply 5.63 3.07 5.73 3.64
Construction 6.85 0.03 8.83 4.25
Tertiary Sector 5.81 6.19 10.39 6.82Trade, Hotel and Restaurant 4.80 4.80 13.46 7.14
Transport, Storage and Communication 7.94 6.94 14.69 9.30
Finance, Insurance and Real Estate 4.34 4.64 9.14 5.43
Community, Social & Personal Services 7.21 7.94 6.90 6.62
Total GSDP 3.83 (5.29) 3.60 (6.36) 9.10 (8.08) 4.58 (6.15)Note:Bracketed figures are all-India GDP growth.Source:Same as Table.1
To assess the fluctuations in growth an instability index is calculated. In this study, Instabilityindex (I) suggested by Parthasarathy (1984) is used where; the instability index is calculated using
from the residuals of the exponential trend equation for the various sectoral real incomes and for
the state economys GSDP in the following manner.
Instability Indexkn
e
I
n
i
i
=
=1
2
, where ei= residual of ithobservation, N =number of observations,
K = number of parameters estimated.
The results are presented in the Table 3, where it shows that in 1980-81, secondary sector, which
registered the highest growth rate showed the second highest instability of 0.02374. By the 1991-
2000 and 2001-11, the service sector had the highest growth rate, but showed the lowest value of
instability among the various sectors. For the entire period under study, industrial sector showed
the highest instability followed by primary sector. Though the primary sector is least volatile, its
growth rate being negligibly low, is not very relevant. Among the remaining sectors, service sector
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is less volatile and hence more stable. Since this sector contributes nearly 50 per cent of the state
income and its growth rate has shown a consistently growing and stable trend, the next section
studies whether the service sector growth is autonomous or has linkages with the other sectors in
the economy.
Table 3
Index of Instability for the Major Sectors in Odisha (1980-81 till 2011-12)Time Period Primary Sector Secondary Sector Service Sector Total GSDP1980-90 0.03459 0.02374 0.01127 0.018231991-00 0.02151 0.01830 0.00749 0.011142001-11 0.01611 0.02186 0.00479 0.00951
1980-11 0.02116 0.02406 0.01609 0.02026Source:Same as Table.1
INTER-SECTORAL LINKAGES IN ODISHA
Having observed the pattern of structural change in the state of Odisha economy, the paper now
explores the linkages among the major sectors of the state economies. The structural linkages
among the sectors in an economy are generally examined in different ways. The literature largely
focuses on estimating sectoral output growth multiplier, elasticity of sectoral output, forward and
backward linkages, etc. Over the years different methodologies have been developed for theseestimates, such as input-output (I-O) analysis, econometric modelling and statistical causality
tests, etc. (Saikia, 2011). In this regard, the present paper used the standard econometric tool of the
Granger causality test for the short-run behavioural analysis and followed by co-integration and
error correction model for long run and short run adjustment in long run respectively. This paper
proposes to examine the nature and direction of linkages between primary, secondary and tertiary
sectors and their long-run equilibrium relationship from 1980-91 to 2011-12.
Table 4
Unit Root Test for various Sectors of Odishas economy from 1980-2011 (at 2004-05 prices)ADF Test PP Test
Variable Name Level 1stDifference Level 1stDifference
Ln(Primary) 0.275 -9.399* 0.-867 -10.318*
Ln(Secondary) 0.571 -6.514* 0.855 -6.514*
Ln(Tertiary) 3.380 -6.523* 4.231 -4.938*
Ln(THR) 1.394 -6.546* 2.190 -6.467*
Ln(TSC) 2.325 -2.958*** 2.214 -4.096*
Ln(FIRB) 5.117 -3.014** 5.608 -3.100**
Ln(CSP) 0.301 -5.943* 0.861 -6.708*
Note: * is 1 per cent, ** is 5 per cent, *** is 10 per cent level of significanceSource:Authors calculations
The nature and direction of causality and long-run equilibrium relationship between primary,
secondary and tertiary sectors are examined using GDP data from 1980-81 to 2011-12 in a log-
linear specification. The causality between the sectors is tested in a bivariate analysis based on
Granger Test. Long-run relationship between three sectors and their short run error correctionmechanism are examined in a multivariate framework using co-integration and vector error
correction model. Before going into the econometric analysis, first determine the order of
integration of variables using Augmented Dickey Fuller (ADF) and Phillips-Perron (PP) unit root
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test; if the variables are integrated, they are converted into stationary series. The result for
stationary test in Table 4 suggests that all the variables are non-stationary at level so the null
hypothesis of unit root at level cannot be rejected. However, at first difference null hypothesis of
unit root is rejected for all the variables and all the variables are integrated of order one.
Granger Causality Test
Granger Causality test helps in determining the direction of causal relationship between differentvariables. It is based on a premise that if forecasts of some variable, say X, obtained by using both
the past values of X and the past values of another variable, say Y, is better than the forecasts
obtained using past values of X alone, Y is then said to cause X. To test the causality relationships
following model is used.
tjt
n
j
iit
n
i
it YXY 111
++=
=
=
tjt
n
j
iit
n
i
it YXX 211
++=
=
=
Where, Xi and Yi are two stationary time series with zero mean: 1and 2 are two uncorrelated
series, n is assumed to be finite and shorter than the time series considered.
Since the series of the variable are usually non-stationary and integrated of order I (1), first
difference of the variable (growth rate) is normally taken which is stationary. The optimal lag
length of the variables is determined by minimizing Akaikes Information Criterion. Based on the
equations1 and 2, unidirectional causality from X to Y (i.e. X granger causes Y) is indicated if the
estimated coefficients on the lagged X in equation 1 is statistically different from zero as a group
(i.e. i0) and the set of estimated coefficients on the lagged Y in equation 2 is not statistically
different from zero (i.e. j= 0). Similarly, unidirectional causality from Y to X (i.e. Y granger
causes X) exists if the set of lagged X coefficients in equation 1 is not statistically different from
zero (i.e. i= 0) and the set of the lagged Y coefficients in equation 2 is statistically different
from zero (i.e. j 0). Feedback or mutual causality (bi-directional) occurs when the set of
coefficients on the lagged X variable in equation (1) and on lagged variable Y in equation (2) are
statistically different from zero. Finally, independence exists when the coefficients of both X and
Y variables are equal to zero.
Unit root test based on Augmented Dickey Fuller Test confirms that the GDP series of Primary,
secondary and tertiary sectors are difference-stationary and integrated of order one. The Service or
the Tertiary sector is included in greater detail by taking all its sub sectors as given in the System
of National Accounts. Thus four broad components of the services viz. (a) Trade-Hotel-
Restaurant (THR), (b) Transport- Storage- Communication (TSC), (c) Financial- Insurance, real
estate- Business (FRB) and (d) Community-Social-Personal services (CSPD) are also examined.
Based on RBI guidelines, one can classify, THR as consumer services, TSC and FBR as Producer
services and CSS as government services. In view of varied nature of services, one can group them
into two i.e. marketed and non-marketed services. Marketed services may indicate NSDP derived
from a, b and c sectors and non- marketed services can represent social, community and other
services that are provided by the government to the society at large. At the outset, causality is
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checked between primary and secondary, primary and sub-sectors of tertiary sectors and
secondary with sub-sectors of tertiary sectors by taking first difference of the natural logarithms of
each GDP series. Causality between the sectors is estimated from 1980 to 2011.
Results obtained from the table.5 indicate that in a bivariate case, causality between primary and a
secondary sector is independent, indicating a weak linkage between the sectors in the growth
process. Inadequate technological progress, declining productivity of food crops and low rate ofpublic investment, a weak linkage of agriculture with industry was, thus inevitable. In the case of
primary and tertiary sector services, though the primary sector does not show linkages with the
tertiary sector as a whole, it does have linkages with some important sub-services within the
service sector. There is a strong linkage between primary and trade, hotel and restaurant sector
over 32 years. For other three services viz. transport-storage-communication (TSC), finance,
insurance, real estate and business services (FIRB) and social and community services (CSPD) an
independent relationship exists with the primary sector. In case of causality bet