regional development and planning

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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, Vol. 1, No. 2, 2012

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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JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING72

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:

[email protected], [email protected]


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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

regional development and planning

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