Monograph Series No. - 105 Regional Disparity in Per Capita Income in India: A Study on Inter-state and Intra-state Analysis S V Hanagodimath Centre for Multi Disciplinary Development Research (CMDR) R.S.No. 9A2, Plot No. 82 Dr. B.R. Ambedkar Nagar Near Yalakki Shettar Colony Dharwad-580004 Karnataka State, India. www.cmdr.ac.in September - 2019
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Monograph Series No. - 105
Regional Disparity in Per Capita Income in India: A Study on Inter-state and Intra-state Analysis
S V Hanagodimath
Centre for Multi Disciplinary Development Research (CMDR) R.S.No. 9A2, Plot No. 82 Dr. B.R. Ambedkar Nagar
Near Yalakki Shettar Colony Dharwad-580004 Karnataka State, India.
No country/state is an exception for the challenge of regional imbalances. In the
recent years, in India, the problem of intra-state REGIONAL DISPARITY is more serious
than the inter-state disparity. In the present study inter-state and intra-state disparities
have been analysed for per capita state and district domestic products. This study is a
unique of its kind, which traces the inter-state, intra-state and intra-division regional disparity for Indian states.
The study found that inter-state disparity in per capita income has increased in
India over the period of time in India. With respect to intra-state disparity no state is an
exception for it. Quantum of imbalances differs, in some states it has become a serious
challenge. States like Uttar Pradesh, Bihar and Himachal Pradesh have higher
disparity. Whereas, states like Kerala, Punjab, Andhra Pradesh, Rajasthan and Jammu Kashmir have lower intra-state disparity.
To measure the regional disparity more meaningfully and to suggest the proper
policy, strong data base at different disaggregated level is the prerequisite. For this
purpose, first of all, district (as well as taluk) domestic product should be calculated /
estimated every year. At present, only some states like, Karnataka, Andhra Pradesh,
Telangana calculate district domestic product every year. Hence, CSO should make
proper guidelines and give appropriate training to the officials of Directorate of
Economics and Statistics of all states. Thus, one can see the per capita income level of
all the districts of the country and also these districts can be ranked. Through this, intra-
state disparity can properly be addressed more meaningfully.
The present study has observed that in most of the states, the divisions, which
have the higher per capita income, have the higher quantum of regional disparity. This
is because of centralisation of industrial units in one place. Moreover, economic
activities are concentrated only in some selected place. Hence, to achieve the balanced
regional development- proper infrastructure facilities (to increase the income and
employment opportunities) should be developed in all the regions/divisions based on
potentiality and necessity. Increasing of number of administrative divisions (wherever is
necessary) is needed for decentralised governance. Further, decentralised
administration will be helpful in reduction of regional imbalances. Hence, number of
administrative divisions should be increased based on agro-climatic zones. Along with
other policies and programmes, these initiatives will be helpful in achieving the BALANCED REGIONAL DEVELOPMENT.
1Assistant Professor, CMDR, Dharwad, Karnataka, India
Author is very much grateful to Prof. P R Panchamukhi, Prof. G K Kadekodi, Prof. V B Annigeri and Prof. N S Nayak for their useful comments and suggestions for this Monograph.
2
Introduction:
India is a vast country with diversification in geographical contours, languages and
also several socio-economic conditions. Further, diversification can be found not only
between states (inter-state) but also between districts and taluks (intra-state). Every region
has its own identity and uniqueness in consumption, spending patterns and economic
activities. In such circumstances, measurement of national accounts statistics becomes very
difficult2. However, we have a very good mechanism
3 for the national accounts calculation
thanks are due to Central Statistical Organisation (CSO). The contribution of CSO is highly
appreciated for its handling of systematic and scientific measurements of national accounts
statistics in India since independence. Further, at the state level, Directorate of Economics
and Statistics of many states are estimating the district domestic products for their respective
states under the guidance of CSO.
However, some states do not calculate district domestic product every year. In recent
years, several socio-economic policies and programmes are being planned implemented at the
grass-root level, even up to blocks and villages. Hence, availability of data on different socio-
economic measures at district and sub-district levels is important in general and per capita
income or domestic product in particular. This is helpful to understand the intra-state regional
disparity in economic growth. Further, it also improves the process of framing and
implementing of policies and programmes at the grass-root level.
Brief Review of Earlier Studies:
There are a plethora of studies on regional imbalances in India at the inter-state levels
[see among others, Ahluwalia (2002), Dholakia (1977), Dholakia (1985), Rao, Ric and
Kalirajan (1999), Sachs, Jeffrey, Bajpai and Ramaiah (2002), Singh (1999)]. Further there are
good number of studies, which have examined the intra-state disparities taking district as the
unit of the study for individual states. But there is a scarcity of studies, which have studied
the intra-state disparity in incomes taking into consideration of all Indian states.
However, there are studies, which have analysed the intra-state disparities taking into
consideration of more than one state (but not all states). Kanbur and Venables (2005) found
2 Major difficulties in calculation of national income are different consumption patterns of food and non-food
commodities, assigning weight to different commodities and so on. 3 CSO successfully modifies the methodology of calculation of National Income over the period of time.
3
that regional disparity in income and social indicators are increasing in most developing and
transition economies world over. India is not an exception for growing regional disparity.
Suryanarayana (2009) analysed the intra-state regional disparities in Karnataka and
Maharashtra. The study reveals that even though Karnataka and Maharashtra are in some
better-off positions in terms of mean-based estimates of average income, they have
experienced inter-regional disparities, interpersonal inequalities and intra-regional
deprivations. Dubey (2009) using the National sample survey (NSS) consumption data,
analysed the intra-state disparity for Gujarat, Haryana, Kerala, Orissa and Punjab. The study
found that not only inter-state disparities but also intra-state disparities are increasing in
India. Bhattachary (2009) has also observed increasing intra-state disparities in government
expenditure taking into consideration of six north Indian states. Using NSSO data, Chaudhuri
and Gupta (2009) estimated poverty ratios for districts, and found wide spatial disparity in the
levels of living of the Indian districts, both within and across the states. The study indicated
that the range of disparity at the sub-state level within a state is often more serious than the
disparity between the states. However, as it has been already mentioned that there is a
scarcity of studies, which have studied the intra-state disparity in per capita income, taking
into consideration of all Indian states (with comprehensive approach).There is a need for a
study, which should analyse the intra-state disparities for Indian states with per capita income
and its (intra-state disparity) association with economic growth of the nation. Hence, the
present study is an attempt to fulfil this research gap.
Data and methodology:
The study is entirely based on secondary sources of data. State-wise domestic product
and population data have been collected from ‘Hand book of statistics on Indian economy’ of
RBI (Reserve Bank of India). GSDP and per capita GSDP data have been used from 1993-94
to 2015-16 at constant prices of 2011-12. For this purpose base shifting and GSDP deflator
methods have been used. District wise domestic product and population data have been
collected from Directorate of Economics and Statistics (DES) of respective state
governments. All the states do not estimate the district domestic products every year. Among
the available district domestic product data, latest year data have been used (see appendix
table 1 for source of data for different states for district domestic product). Comparison of
districts ‘within the state’ has been made; not for ‘inter-state’. For intra-state analysis, only
those states are selected, which have the data on district level domestic product, are selected.
4
For more meaningful analysis districts are categorised into four groups namely Very
High, High, Above Average, Below Average, and Very Low. For this purpose all the states
are first divided into two groups on the basis of state average index values - one above the all-
India average and the other below the all-India average. Then two more averages are worked
out, one for the group of states whose values are above the all-India average and another for
the group of states whose values are below the all-India average. The states whose values are
above and below the former average are classified as ‘Very High’ and ‘Above Average’
states, respectively. The states whose values are above and below the latter average are
classified as ‘Below Average’ and ‘Very Low’ states respectively.
Different tools such as ratios, averages, percentage, compound annual growth rates
(CAGR), coefficient of variation (CV) and correlation coefficient are used. Further, for the
pictorial presentation line, bar and scatter diagrams have been used. Thematic maps have
been used to mark the regions on the basis of level of development and quantum of disparity.
This study has been divided into 4 sections; apart from introduction; section II is
devoted to inter-state imbalances in India; while in section III, quantum of regional disparity
at intra-state has been discussed; last section concludes the present study with way forward.
II. Inter-state Imbalances:
Before initiating the analysis on intra-state disparities in economic growth, a
discussion on inter-state disparities gives a proper picture of the regional disparity in India at
a macro level. This section provides the information related to it.
Per capita income is one of the good indicators of measurement of economic growth
of any region. In figure 1, per capita income of Indian states for the year 2015-16 (at 2011-12
prices) has been presented. It is found that Goa, Delhi, Chandigarh, Sikkim and Haryana are
found to be the top category states with per capita income of more than Rs. 1,30,000 in 2015-
16. On the other hand, states like, Assam, Madhya Pradesh, Manipur, Uttar Pradesh and
Bihar are observed in the bottom position with per capita income of less than Rs. 50,000 in
the same period. Through this figure, it is clear that there is existence of huge inter-state
disparity in India.
5
Source: Computed from the data available from Handbook of Statistics on Indian Economy, RBI
Box 1: State-wise Categorisation of PCI Low PCI Below average PCI Above average PCI High PCI
Bihar, Uttar Pradesh,
Manipur,Madhya
Pradesh, Assam,
Jharkhand,Odisha,
Meghalaya,Jammu&
Kashmir
(PCI Between Rs.
24572-Rs.60171)
[9 States, (329%)]
Nagaland, Tripura,
Chhattisgarh, Rajasthan,
Andhra Pradesh, Punjab,
Arunanchal Pradesh
(PCI Between Rs.
61363- Rs.99823)
[7 States, 23%]
Andaman & Nicobar Island,
Telangana, Tamil Nadu,
Karnataka, Himachal Pradesh,
Kerala, Maharashtra, Gujarat,
Uttarakhand, Puducherry, Haryana
(PCI Between Rs. 107873-
Rs.133591)
[11 States, (35%)]
Sikkim,
Chandigarh,
NCT of Delhi,
Goa
(PCI Between
Rs. 193569-
Rs.267329)
[4 States, (13%)]
24,572
36,850
45,652
46,324
48,465
50,817
58,165
59,373
60,171
61,363
64,173
67,185
68,048
86,118
99,372
99,823
107,873
111,454
113,303
114,478
119,777
121,514
122,148
126,306
126,880
133,591
193,569
193,604
234,328
267,329
0 30
00
0
60
00
0
90
00
0
12
00
00
15
00
00
18
00
00
21
00
00
24
00
00
27
00
00
Bihar
Uttar Pradesh
Manipur
Madhya Pradesh
Assam
Jharkhand
Odisha
Meghalaya
Jammu and Kashmir
Nagaland
Tripura
Chhattisgarh
Rajasthan
Andhra Pradesh
Punjab
Arunachal Pradesh
A & N Islands
Tamil Nadu
Karnataka
Himachal Pradesh
Kerala
Maharashtra
Gujarat
Uttarakhand
Puducherry
Haryana
Sikkim
Chandigarh
Delhi
Goa
Per Capita GSDP
Stat
es
Figure 1: State wise per GSDP for the year 2015-16 at constant prices capita of 2011-12
6
Map1: Thematic Map of Per Capita Income of Indian States, 2015-16
Legend: Very Low Below Average Above Average Very High No Data
Source: Computed from the data available from Handbook of Statistics on Indian Economy, RBI
The gap between the highest and the lowest per capita income among the states [Goa (Rs.
2,67,329) and Bihar (Rs. 24,572)] is around 11 times. Goa’s per capita income is 11 fold
higher than that of Bihar’s per capita income.
7
In figure 2, share of population and share of GDP of different states have been presented for
the year 2015-16 to see the performance of different states in domestic product. Out of the
selected 33 states and union territories, except 12 states (Sts) and Union Territories (Uts),
remaining 21
Sts and Uts
have higher
share of
GDP than
their
population
share in the
country. The
GDP
contribution
of Bihar is
only 3.07 per
cent,
whereas, its
population
share is 8.60
per cent to
the nation.
On the other
hand, Goa
contributes
0.54 per cent
of GDP with
only 0.12 per
cent of
population
share. Uttar
Pradesh,
Madhya
Pradesh and Bihar are bigger states in terms of population, while they contribute lower share
Figure 2: State-wise share of GDP and Share of Population in Indian states,
2015-16 (constant prices of 2011-12)
Source: Source: Computed from the data available from Handbook of Statistics on Indian
Economy, RBI
8
of the national GDP than their population share. Maharashtra, Tamil Nadu and Gujarat are
bigger states in terms of population share, which contribute higher share of GDP to the
nation.
In figure 4, ratio between GSDP and Population has been presented. It is found from the
figure that Goa
(4.46) has the
highest4 GSDP -
population ratio
followed by
Chandigarh, Delhi,
Pondicherry, A & N
Islands and Sikkim.
On the other side,
Bihar (0.36) has the
lowest GSDP -
population ratio
followed by Uttar
Pradesh, Assam,
Manipur and
Madhya Pradesh.
To see the regional
imbalances,
computing of
coefficient of
variation (CV)5 is a
commonly used
method by many researchers, which has been presented in figure 4. Coefficient of variation
has been calculated for the years from 1993-94 to 2015-16. It is found from the figure that at
4GSDP-Population Ratio has been calculated using these steps, firstly, share of each state’s GDP has been
calculated dividing GSDP with GDP and multiplying it with 100. Secondly, share of each state’s population has been calculated dividing state population with national population and multiplying it with 100. Further, in the third step, share of GDP has been divided with share of population to arrive GDP population ratio. 5Calculation of Coefficient of Variation (CV) % =
, where, σ-Standard Deviation, µ-means
Source: Appendix Table 3
9
the initial years of the study period, inter-state disparity is low (CV%-50.48%), which
increased significantly in the year 1998-99 (CV-61.53%). Afterwards, it (CV %) started to
decrease, which reached to 52.95 per cent in the year 2013-14. Further, it again increased and
reached to 57.10 per cent in the year 2015-16. Totally, inter-state disparity has increased from
the initial year to the recent year. To see the trend for this data, a curve trend line has been
drawn. Trend line is found to be in inverted ‘U’ shape.
Source: Computed from the data available from Handbook of Statistics on Indian Economy, RBI
For more meaningful analysis, states have been categorised into four groups on the basis of
average of per capita GSDP and its growth rate from the year 1993-94 to 2015-16.
Categorisation has been made as follows,
Group I High Per capita Income
and High Growth Rate Best (Virtuous Cycle)
Group II High Per capita Income
and Low Growth Rate Lopsided Growth Rate
Group III Low per capita income
and High Growth Rate Lopsided Per capita Income
Group IV Low per capita income
and Low Growth Rate Worst (Vicious Cycle)
50.48
61.53
52.95
57.10
50
52
54
56
58
60
62
64
19
93
-94
19
94
-95
19
95
-96
19
96
-97
19
97
-98
19
98
-99
19
99
-00
20
00
-01
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
20
14
-15
20
15
-16
CV
(%)
Years
Figure 4: Inter-state imbalances in per capita GSDP from 1993-94 to 2015-16
10
Results from using above mentioned methodology have been presented in table 1. The table
reveals some of the interesting observations as follows,
It is found that 10 states (32%) are in the Best category, where both average Per
Capita Income and its Growth Rates are above the national average. This group can
also be called as virtuous cycle.
On the other hand, 13 states/union territories (42%) are observed in the worst
category. This category can also be called as vicious category, because in this
category both Per Capita Income and its Growth Rates are below the national average.
Six states (23%) are found in the Lopsided Growth Rate, (group II), where, High Per
Capita Income and Low Growth Rate can be seen.
Further, only Tripura is found in the Lopsided Per capita Income, (group III), where,
Low Per Capita Income and High Growth Rate is observed.
Table 1: Categorisation of states and union territories based on their average per capita
GSDP and average Growth Rate of GSDP from 1993-94 to 2015-16
↓G
row
th R
ate
fro
m 1
99
3-9
4 t
o 2
015-1
6↓
Hig
h G
row
th R
ate
↓
Tripura
Delhi, Gujarat, Haryana, Himachal
Pradesh, Kerala, Maharashtra,
Pondicherry, Sikkim, Tamil Nadu,
Uttarakhand
low per capita income and High
Growth Rate (1 State, 3%)
High Per capita Income and High Growth
Rate (10 Sts and Uts, 32%)
Low
Gro
wth
Rate
↓ Andhra Pradesh, Assam, Bihar,
Chhattisgarh, Jammu and Kashmir,
Jharkhand, Madhya Pradesh,
Manipur, Meghalaya, Nagaland,
Odisha, Rajasthan, Uttar Pradesh
A & N Islands, Arunachal Pradesh,
Chandigarh, Goa, Karnataka, Punjab
low per capita income and Low Growth
Rate (13 Sts and Uts, 42%)
High Per capita Income and Low Growth
Rate (6Sts and Uts, 23%)
Low Per capita GSDP ↑ High Per capita GSDP ↑
↑Per Capita GSDP from 1993-94 to 2015-16↑
Source: Calculated based on appendix Table 2
11
To see the
association
between Per
capita GSDP
and its growth
rates in the
selected time
period a scatter
diagram has
been prepared
and presented in
figure 5. From
the figure log
liner curve is
observed it is
found that there
is a positive
association
between per capita income and its growth rate.
Intra-state Imbalances:
In the recent years, policies and programmes are being framed and implementation at
the gross root level. In such situations, identification of the economic growth with respect to
sub-state level becomes very important to analyse. In the recent years, most of the states have
estimated the district domestic products. However, some of the states have not estimated the
district domestic products. Gujarat is the state, which does not have district domestic product.
Though, most of the major states have estimated the district domestic product, very less
numbers of states estimate it every year. Hence, comparison of district domestic product at
inter-state level has not been carried out in the present study. The comparison has been made
‘within the state’ not for ‘inter-state’ comparison. First of all, the quantum of regional
imbalances, which exist in different states has been discussed. For this purpose, coefficient of
variation of per capita district domestic products of each state has been calculated and
presented in figure 6 (appendix table 3). It is found from the figure that out of 18 selected
Figure 5: Per capita GSDP and its growth rate for selected Indian
states
Source: Appendix Table 2
12
16.82
17.57
20.84
25.3
25.37
28.01
28.43
32.93
33.98
35.78
39.25
42.65
43.48
45.4
48.94
56.55
73.2
90.35
0 20 40 60 80 100
Kerala
Punjab
Andhra Pradesh
Rajasthan
Jammu Kashmir
Jharkhand
Haryana
Tamil Nadu
West Bengal
Madhya Pradesh
Maharashtra
Uttarakhand
Karnataka
Odisha
Telangana
Himachal Pradesh
Bihar
Uttar Pradesh
CV %
Stat
es
Figure 6: Intra-state Regional Imbalances in Different States in India for Per capita District Domestic Product (CV %)
Indian states, Bihar has the highest intra-district disparity and Kerala has the lowest intra-
state disparity.
Income disparity
of Uttar Pradesh
is 5.4 fold higher
than that of the
disparity of
Kerala. Among
the selected 18
states, Uttar
Pradesh, Bihar
and Himachal
Pradesh have
higher intra-state
disparity. These
states have the
coefficient of
variation more
than 45 per cent.
On the other
hand, states like
Kerala, Punjab,
Andhra Pradesh,
Rajasthan and
Jammu Kashmir
have lower intra-
state disparity.
These states have
the coefficient of
variation less than
26 per cent.
Source: Appendix Table 3
13
Map 2: Thematic Map of Intra-State Disparity in India (Selected States)
Legend: Very Low Below Average Above Average Very High No Data
Box 2: Categorisation State in Intra-State Disparity in PCI (Selected States)
Low Intra-State
Disparity
Below average Intra-
State Disparity
Above average Intra-
State Disparity
High Intra-State
Disparity
Kerala, Punjab,
Andhra Pradesh,
Rajasthan,
Jammu Kashmir
[5 States, 28%]
Jharkhand, Haryana,
Tamil Nadu, West
Bengal, Madhya
Pradesh
[5 States, 28R]
Telangana, Odisha,
Karnataka,
Uttarakhand,
Maharashtra
[5 States, 28%]
Uttar Pradesh,
Bihar, Himachal
Pradesh
[3 States, 17%]
14
Each State-wise Analysis:
In this section, each state-wise intra-state disparity has been analysed. Many states
have grouped the districts into different administrative divisions to implement the
government policy and programmes more effectively with decentralised approach. Some
states have no administrative setup between district and the state government. Some states
have been excluded in the analysis of inter-district disparity and inter-division disparity due
to non-availability of the data. Based on the developmental status (per capita income),
districts have been categorised into four different categories namely, ‘Very High Per capita
Income,’ ‘Above Average Per Capita Income’, ‘Below Average Per Capita Income’ and ‘Very
Low Per Capita India’ per capita income . They have been depicted in the thematic maps. For
this purpose, ‘QGIS’ software has been used.
Andhra Pradesh:
ANDHRA PRADESH is found in the group of medium developed states with the population
share of 4.10 per cent and GDP share of 4.37 to the nation. The state has less intra-state
disparity compared to other states. Its position is 3rd
out 18 selected Indian states.
Table 4: Per Capita District Domestic Product, Andhra Pradesh, 2015-16 (2011-12 prices)
Districts PCI (Rs.) Rank
Srikakulam 63411 13
Vizianagaram 65320 12
Visakhapatnam 121373 1
East Godavari 88021 6
West Godavari 98477 4
Krishna 108924 2
Guntur 89242 5
Prakasam 83796 7
S.P.S.Nellore 99204 3
Y.S.R 73706 9
Kurnool 69821 10
Ananthapuramu 68479 11
Chittoor 80986 8
State 87217
Average 85570
CV (%) 20%
Source: Appendix Table 3
District wise per capita income has been presented in table 4 and its categorisation has been
presented in thematic map 3. There are thirteen districts in Andhra Pradesh among them,
Visakhapatnam is in the first position and Srikakulam is in the last position.
15
Categorisation in per capita income of different districts within the states reveals that,
Two districts (15.4%) are found in the high per capita income category, they are
Visakhapatnam and Krishna.
East Godavari, Guntur, West Godavari and Sri Potti Sriramulu Nellore are the four
(30.8%) districts, which are found in the category of above average per capita
income.
Three districts (23.1%) namely, Y.S.R., Chittoor and Prakasam observed in below
average Per capita income category.
Remaining four districts (30.8%) are in the last category i.e., Very low per capita
income, the districts are Srikakulam, Vizianagaram, Anantapur and Kurnool.
Thematic Map 3: Categorisation of Districts in Per capita Income (PCI) of Andhra
Pradesh (within the state)
Legend: Very Low Below Average Above Average Very High No Data
16
BIHAR is the least developed state in India. It ranks last in per capita GSDP. Further, it should
be noted that with respect of intra-state disparity the state is found in the 17th
position out of
18 selected Indian states. The state contributes 8.60 per cent of population and only 3.07 per
cent of GDP to the nation. The state has the lowest per capita income and higher intra-state
disparity among Indian states.
Table 5: Per Capita District Domestic Product, Bihar, 2015-16 (2011-12 prices)
Districts/Divisions PCI (Rs.) Rank
Districts/Divisions PCI (Rs.) Rank
Patna 59531 1
Gaya 10570 13
Nalanda 11186 8
Jehanabad 9941 17
Bhojpur 11026 10
Arwal 8123 34
Buxar 9950 15
Nawada 8563 29
Rohtas 12303 6
Aurangabad 9739 18
Kaimur 9216 24
Magadh Division
Patan Division
Average 9387
Average 18869
CV (%) 10.79
CV (%) 105.72
Saran 9407 23
Muzaffarpur 13797 5
Siwan 9571 20
E.Champaran 9510 22
Gopalganj 10794 12
W.Champaran 8860 28
Saran Division
Sitamarhi 8512 31
Average 9924
Sheohar 6333 38
CV (%) 7.63
Vaishali 11152 9
Tirhut Division
Darbhanga 9696 19
Average 7638
Madhubani 8243 32
CV (%) 26.25
Samstipur 9565 21
Darbhanga Division
Begusarai 15601 3
Average 9168
Munger 18860 2
CV (%) 8.76
Sheikhpura 8539 30
Lakhisarai 11666 7
Bhagalpur 15332 4
Jamui 8872 26
Banka 8218 33
Khagaria 10202 14
Bhagalpur Division
Munger Division
Average 11775
Average 12290
CV (%) 42.72
CV (%) 33.47
Purnea 9048 25
Saharsa 10807 11
Kishanganj 8865 27
Supaul 7542 37
Araria 7875 35
Madhepura 7642 36
Katihar 9949 16
Kosi Division
Purnia Division
Average 8664
Average 8934
CV (%) 21.43
CV (%) 9.52
Source: Appendix Table 1
District wise per capita income has been presented in table 5 and its categorisation has been
presented in thematic map 4. Out of 38 districts in the state, Patna is found in the first
position and Sheohar is found in the last position in per capita income. Categorisation in per
capita income of different districts within the states reveals that,
17
Thematic Map 4: Categorisation of Districts in Per capita Income (PCI) of Bihar
(within the state)
Legend: Very Low Below Average Above Average Very High No Data
Categorisation in per capita income of different districts within the states reveals that,
Patna is the only district, which is found in the very high per capita income category.
Lakhisarai, Rohtas, Muzaffarpur, Bhagalpur, Begusarai and Munger are the six
districts (15.8%), which are observed in the
above average category.
42 per cent (16) of districts are found
in the below average category.
15 (40%) district are observed in the
Very low per capita income category.
This state has nine administrative divisions,
among them Patana division has higher per
capita income and Kosi has the lowest per
capita income (table 5). Further, it should be
noted that Patana division has the highest
inter-district disparity and Saran division has the lowest inter-district disparity (Figure 7).
7.63
8.76
9.52
10.79
21.43
26.25
33.47
42.72
105.72
0.00 30.00 60.00 90.00
Saran
Darbhanga
Purnia
Magadh
Kosi
Tirhut
Munger
Bhagalpur
Patna
Figure 7: Division-wise Regional Imbalances in Per capita GSDP, Bihar
18
HARYANA is another north Indian state, which is found to be in the top group of states with
respect to per capita income. The state is found in the 7th
position in intra-state disparity out
of 18 selected Indian States. The state contributes 2.09 per cent of population with 3.53 per
cent of GDP to the nation.
Table 6: Per Capita District Domestic Product, Haryana, 2002-03 (1993-94 prices)
Districts/Divisions PCI (Rs.) Rank
Ambala 19637 3
Kurukshetra 11463 16
Panchkula 15527 5
Yamuna 14058 9
Average: Ambala Division 15171
CV% 22.53
Faridabad 14837 7
Gurgaon 24737 1
Mahendragarh 7900 19
Rewari 18270 4
Average Gurgaon Division 16969
CV% 50.05
Fatehabad 13213 10
Hisar 14441 8
Jind 11623 15
Sirsa 12932 12
Average Hisar Division 13052
CV% 8.86
Kaithal 12106 14
Karnal 14852 6
Panipat 21410 2
Average Karnal Division 16123
CV% 29.65
Bhiwani 10805 17
Jhajjar 10615 18
Rohtak 12123 13
Sonipat 13099 11
Average Rohtak Division 11661
CV% 10.48
Source: Appendix Table 3
District wise per capita income has been presented in table 6 and its categorisation has been
presented in thematic map 5. Gurgaon district has the highest per capita income and
Mahendragarh has the lowest per capita income among the 19 districts. Categorisation in per
capita income of different districts within the states reveals that,
Rewari, Ambala, Panipat and Gurgaon are found in the very per capita income
category (4 districts, 21%)
Same percentage, i.e., four districts namely, Hisar, Faridabad, Karnal and Panchkula
are found in the above average category.
32 per cent of districts (6) are observed in the category of below average, they are
Kaithal, Rohtak, Sirsa, Sonipat, Fatehabad and Yamunanagar.
19
Remaining, six districts (26%) can be seen in very low per capita income category,
they are Mahendragarh, Jhajjar, Bhiwani, Kurukshetra and Jind
This state has been divided into administrative
divisions. Among them, Gurgoan has higher
per capita income and Rohtak has the lower
per capita income (table 6)
Inter-district disparity has been presented for
different administrative divisions of the states
in figure 8. It is found from the figure that
Gurgaon division has the highest inter-district
disparity and Hisar division has the lowest
inter-district disparity.
Thematic Map 5: Categorisation of Districts in Per capita Income (PCI) of Haryana
(within the state)
Legend: Very Low Below Average Above Average Very High No Data
8.86
10.48
22.53
29.65
50.05
0.00 20.00 40.00 60.00
Hisar
Rohtak
Ambala
Karnal
Gurgaon
Figure 8: Division-wise Regional Imbalances in Per capita GSDP, Haryana
20
Himachal Pradesh:
HIMACHAL PRADESH is found in the group of medium developed state with the population
share of 0.57 per cent and GDP share of 0.84 per cent to the nation. With respect to intra-state
disparity its position is 17th
out 18 selected Indian states.
Table 7: Per Capita District Domestic Product, Himachal Pradesh, 2015-16 (2011-12
prices)
Districts PCI (Rs.) Rank
Bilaspur 125958 7
Chamba 98006 11
Hamirpur 102217 9
Kangra 86637 13
Kinnaur 217993 2
Kullu 119231 8
L & S 192292 3
Mandi 96052 12
Shimla 152230 4
Sirmaur 145597 5
Solan 394102 1
Una 100295 10
HP 135621 6
Average 152550
CV% 56.55
Source: Appendix Table
21
Thematic Map 6: Categorisation of Districts in Per capita Income (PCI) of Himachal
Pradesh (within the state)
Legend: Very Low Below Average Above Average Very High No Data
District wise per capita income has been presented in table 7 and its categorisation has been
presented in thematic map 6. There are thirteen districts in Himachal Pradesh. Solan is in the
first position and Kangra is in the last position. Categorisation in per capita income of
different districts within the states reveals that,
Only Solan district is found in the category of very high per capita income.
L & S and Kinnaur are the two districts, which are found in the category of above
average.
Four (33%) districts, namely, Kullu, Bilaspur, Sirmaur and Shimla are observed in the
category of below average per capita income.
Kangra, Mandi, Chamba, Una and Hamirpur are the five districts which can be seen
in the category of very low per capita income.
22
Jammu and Kashmir:
JAMMU AND KASHMIR is found in the group of lower middle developed states in per capita
income among Indian states. The state contributes population share of 1.04 per cent and GDP
share of 0.81 per cent to the nation. With respect to intra-state disparity its position is 5th
out
18 selected Indian states.
Table 8: Per Capita District Domestic Product, Jammu and Kashmir, 2005-06 (1999-00 prices)
District/Divisions PCI (Rs.) Rank
Doda 31118 1
Jammu 27095 3
Kathua 20954 9
Punch 15511 13
Rajouri 16862 11
Udhampur 27232 2
Average Jammu Division 23129
CV% 27.24
Anantnag 25022 7
Badgam 16803 12
Baramula 21617 8
Kupwara 11757 14
Pulwama 25286 6
Srinagar 26481 5
Average Kashmir Valley Division 21161
CV% 27.38
Kargil 18603 10
Leh - ladakh 26981 4
Average Ladakh Division 22792
CV% 25.99
Source: Appendix Table 1
There are three administrative divisions in the state among them Jammu has higher
average per capita income, followed by Ladak and Kashmir Valley. Further, all the divisions
have more or less similar intra-division disparity, which is between 5 per cent and 28 per
cent.
23
Thematic Map 7: Categorisation of Districts in Per capita Income (PCI) of
Jammu Kashmir (within the state)
Legend: Very Low Below Average Above Average Very High No Data
District wise per capita income has been presented in table 8 and its categorisation has been
presented in thematic map 7. Out of 23 districts of Jammu and Kashmir, we have the data for
only 14 districts on per capita income. Even this data is for the year 2005-06. Doda is in the
first position and Kupwara is in the last position. Inter-district per capita income
categorisation within the state reveals that,
Three districts, namely, Jammu, Udhampur and Doda are found in the category of
very high per capita income.
In the category of above average there are four districts namely Anantnag, Pulwama,
Srinagar and Leh - Ladakh
Kargil, Kathua and Baramula are the three districts, which are found in the category
of below average.
In the very low per capita income category, there are four districts viz., Kupwara,
Punch, Badgam and Rajouri.
24
Jharkhand:
JHARKHAND is found in the group of least developed states in per capita income among
Indian states. The state contributes population share of 2.73 per cent and GDP share of 1.94
per cent to the nation. With respect to intra-state disparity its position is 6th
out 18 selected
Indian states.
Table 9: Per Capita District Domestic Product, Jharkhand, 2005-06 (1999-00 prices)
Districts/Divisions PCI (Rs.) Rank
Dumka 10079 13
Jamtara 9641 16
Deoghar 12621 10
Godda 8334 21
Pakur 15327 4
Sahebganj 14314 5
Hazaribagh 13555 9
Koderma 12561 11
Chatra 8477 20
Giridih 8957 18
Bokaro 14146 6
Dhanbad 19761 1
Ranchi 15359 3
Lohardaga 9643 15
Gumla 10218 12
Simdega 9569 17
Palamu 8712 19
Latehar 9657 14
Garhwa 7090 22
East Singhbhum 17951 2
West Singhbhum 13627 8
SaraykelaKharsawa 13703 7
Average 11968
CV% 28.01
Source: Appendix Table 1
25
District wise per capita income has been presented in table 9 and its categorisation has been
presented in thematic map 8. Out of 24 districts of Jammu and Kashmir, we have the data for
only 22 districts on per capita income. Even, this data is for the year 2005-06 at 1999-00
prices. Dhanbad is in the first position and Garhwa is in the last position. Inter-district per
capita income categorisation within the state reveals that,
Three districts, namely, Pakur, Ranchi, East Singhbhum and Dhanbad are found in the
category of very high per capita income.
In the category of above average, there are seven districts namely, Koderma,
Deoghar, Hazaribagh, West Singhbhum, Saraykela Kharsawa, Bokaro and Sahebganj.
In below average category also are the three districts, which are seven districts, viz.,
Giridih, Simdega, Jamtara, Lohardaga, Latehar, Dumka and Gumla
In the very low per capita income category, there are four districts viz., Garhwa,
Godda, Chatra and Palamu.
Thematic Map 8: Categorisation of Districts in Per capita Income (PCI) of Jharkhand
(within the state)
Legend: Very Low Below Average Above Average Very High No Data
26
Karnataka:
KARNATAKA is found in the group of medium developed state with the population share of
5.05 per cent and GDP share of 5.69 per cent to the nation. With respect to intra-state
disparity its position is 14th
out 18 selected Indian states.
Table 10: Per Capita District Domestic Product, Karnataka, 2014-15 (2011-12 prices)
Districts/Divisions PCI (Rs.) Rank
Districts/Divisions PCI (Rs.) Rank
Belagavi 61675 24
Bengaluru 230240 1
Vijayapura 60661 26
Bengaluru(R) 102434 6
Bagalkot 90033 12
Ramanagara 95599 8
Dharawad 91113 11
Chitradurga 64267 23
Gadag 73144 18
Davanagere 67126 21
Haveri 65050 22
Kolar 76212 17
Uttara Kannada 83700 14
Chikkaballapura 72318 19
Average: Belagavi Division 75054
Shivamogga 105609 5
CV% 17.6
Tumakuru 92919 10
Average: Bengaluru Division 100747
Chikkamagaluru 130634 4
CV% 50.56
Dakshina Kannada 182829 2
Udupi 149653 3
Ballari 93473 9
Hassan 87824 13
Bidar 56349 29
Kodagu 71780 20
Kalaburagi 56336 30
Mandya 97284 7
Yadgiri 56597 28
Mysuru 76229 16
Raichur 61213 25
Chamarajanagar 78034 15
Koppal 59807 27
Average: Mysuru Division 109283
Average: Kalaburagi Division 63963
CV% 37.21
CV% 22.83
Source: Appendix Table 1
In Karnataka, there are four administrative
divisions. Among them Bengaluru division
has the highest per capita income and
Kalaburagi division has the lowest per
capita income (table 10).
To see the inter district disparity in these
four administrative divisions; coefficient of
variation has been calculated and presented
in figure 9. It is found from the figure that
Bengaluru division has the highest inter-
district disparity and Belagavi division has
the lowest inter-district disparity.
17.60
22.83
37.21
50.56
0 20 40 60
Belagavi
Kalaburagi
Mysuru
Bengaluru
Figure 9: Division-wise Regional Imbalances in Per capita GSDP, Karnataka
27
District wise per capita income has been presented in table 10 and its categorisation has been
presented in thematic map 9. Bengaluru Urban district is in the first position and Kalaburagi
is in the last position. Inter-district per capita income categorisation within the state reveals
that,
Only three (10%) out of 30 districts are in the category of very high per capita income
namely, Bengaluru, Dakshina Kannada and Udupi.
There are seven (23%) districts, namely Tumakuru, Ballari, Ramanagara, Mandya,
Bengaluru(R), Shivamogga and Bagalkot in the category of above average.
Thematic Map 9: Categorisation of Districts in Per capita Income (PCI) of Karnataka
(within the state)
In the category
of below average there
are eight districts
namely Kodagu,
Chikkaballapura,
Gadag, Kolar, Mysuru,
Chamarajanagar, Uttara
Kannada and Hassan.
10 districts,
namely Kalaburagi,
Bidar, Yadgiri, Koppal,
Vijayapura, Raichur,
Belagavi, Chitradurga,
Haveri and Davanagere
are found in the last
category that is very low
per capita income.
Legend: Very Low Below Average Above Average Very High No Data
28
Kerala:
Among the south Indian states, performance of KERALA is in the better-off position in all the
socio-economic indicators. Among the selected 30 states and union territories, Kerala is
found the 10th
position in per capita GSDP. The population and GDP shares of Kerala to the
nation are 2.76 per cent and 4.00 per cent respectively.
Table 11: Per Capita District Domestic Product, Kerala, 2015-16 (2011-12 prices)
Districts PCI
(Rs.) Rank
Districts PCI
(Rs.) Rank
Districts PCI
(Rs.) Rank
Ernakulam 152318 1
Kannur 109632 8
Alappuzha 136804 2
Idukki 132107 4
Kasaragod 100198 10
Kollam 136282 3
Kottayam 126238 6
Kozhikode 109602 9
Pathanamthitta 96134 12
Thrissur 122679 7
Malapuram 89357 14
Thiruvananthapuram 129922 5
Palakkad 100128 11
Wayanad 92353 13
Average:
Central Kerala
Division
133336
Average:
North Kerala
Division
100212
Average: South
Kerala Division 124786
CV% 9.93
CV% 8.04
CV% 15.51
Source: Appendix Table 1
A point is to be noted that intra-state
imbalances in Kerala is very low, it is in the
first position with lower intra-state
disparity among major Indian states (table
11).
Further, this state has three administrative
divisions. South Kerala has the highest
inter-district disparity and North Kerala has
the lowest inter-district disparity.
Information related to this has been
presented in figure 10.
8.04
9.93
15.51
0.00 5.00 10.00 15.00 20.00
North Kerala
Central Kerala
South Kerala
Figure 10: Division-wise Regional Imbalances in Per capita GSDP, Kerala
29
District wise per capita income has been presented in table 11 and its categorisation has been
presented in thematic map 10. Ernakulam district is in the first position and Malapuram is in
the last position. Inter-district per capita income categorisation within the state reveals that,
Idukki, Kollam, Alappuzha and Ernakulam are the four districts, which are found in
the category of very high per capita income.
Three (21%) districts are found in the category of above average in per capita income
they are Thrissur, Kottayam and Thiruvananthapuram.
In the category of below average there are four districts namely Palakkad, Kasaragod,
Kozhikode and Kannur
4 districts, namely, Malappuram, Wayanad and Pathanamthitta are found in the last
category that is very low per capita income
Thematic Map 10: Categorisation of Districts in Per capita Income (PCI) of Kerala
(within the state)
Legend: Very Low Below Average Above Average Very High No Data
30
MADHYA PRADESH is observed in the group of bottom category states in per capita GSDP
among Indian states. This state contributes 4.07 per cent of GDP with the 6 per cent of
population to the nation.
Table 12: Per Capita District Domestic Product, Madhya Pradesh, 2012-13 (2004-05 prices)
Districts/
Divisions
PCI
(Rs.) Rank
Districts/
Divisions
PCI
(Rs.) Rank
Districts/
Divisions
PCI
(Rs.) Rank
Bhind 17607 37
Betul 22483 17
Rewa 16590 43
Morena 17650 36
Harda 32421 6
Satna 20093 29
Sheopur 17549 38
Hoshangabad 30393 8
Sidhi 30085 9
Average:
Chambal
Division
17602
Average:
Narmadapuran
Division
28432
Average: Rewa
Division 22256
CV% 0.29
CV% 18.47
CV% 31.46
Bhopal 49979 2
Chhatarpur 17674 35
Raisen 21374 23
Damoh 20495 28
Datia 23442 16
Rajgarh 19598 31
Panna 16884 40
Guna 22047 21
Sehore 19909 30
Sagar 22395 18
Gwalior 36223 4
Vidisha 20818 25
Tikamgarh 16107 44
Shivpuri 16828 41
Average: Bhopal
Division 26336
Average: Sagar
Division 18711
Average: Gwalior
Division 24635
CV% 50.26
CV% 14.13
CV% 33.42
Dewas 24454 15
Barwani 17446 39
Mandsaur 27477 11
Dhar 22095 20
Neemuch 27475 12
East Nimar 22129 19
Ratlam 29011 10
Indore 55348 1
Balaghat 21739 22
Shajapur 20797 26
Jhabua 16735 42
Chhindwara 30884 7
Ujjain 32567 5
West Nimar 18197 33
Dindori 18715 32
Average: Ujjain
Division 26964
Average: Indore
Division 25325
Jabalpur 41462 3
CV% 14.88
CV% 58.8
Katni 24620 14
Mandla 14123 45
Shahdol 25779 13
Narsimhapur 20649 27
Umaria 17798 34
Seoni 21275 24
Average:
Shahdol Division 21789
Average: Jabalpur
Division 24183
CV% 25.9
CV% 35.01
Source: Appendix Table 1
District wise per capita income has been presented in table 12 and its categorisation has been
presented in thematic map 11. Out of 50 districts of Madhya Pradesh, we have the data for
only 45 districts on per capita income. Indore is in the first position and Mandla is in the last
position. Inter-district per capita income categorisation within the state reveals that,
Five (11%) districts, namely, Ujjain, Gwalior, Jabalpur, Bhopal and Indore are found
in the category of very high per capita income.
In the category of above average there are 10 (22%) districts.
36 per cent (16) districts are in the category of below average.
31
In the very low per capita income category, there are 14 districts (31%).
With respect to intra-state disparity the
Madhya Pradesh stands in the 10th
position out of 18 states in India. Madhya
Pradesh has 10 administrative divisions
Narmdapuram has the highest per capita
income, whereas, Chambal has the lowest
per capita income (table 12). Indore
division has the highest inter-district
disparity and Chambal division has the
lowest inter-district disparity.
Information related to administrative
division wise inter-district disparity has
been presented in figure 12.
Thematic Map 11: Categorisation of Districts in Per capita Income (PCI) of Madhya
Pradesh (within the state)
Legend: Very Low Below Average Above Average Very High No Data
0.29
14.13
14.88
18.47
25.90
31.46
33.42
35.01
50.26
58.80
0 20 40 60 80
Cha…
Sagar
Ujjain
Nar…
Shah…
Rewa
Gwal…
Jabal…
Bhopal
Indore
Figure 12: Division-wise Regional Imbalances in Per capita GSDP, Madhya
Pradesh
32
MAHARASHTRA is found in the 9th
position with respect to per capita income, out of 30
selected Indian states. This state contributes 15.8 per cent of GDP with 9.29 per cent of
population.
Table 13: Per Capita District Domestic Product, Maharashtra, 2015-16
Districts/ Divisions PCI
(Rs.) Rank
Districts / Divisions PCI (Rs.)
Mumbai 256391 1
Nashik 131288 8
Thane 215180 2
Dhule 104965 17
Raigad 171584 5
Nandurbar 65211 34
Ratnagiri 130829 9
Jalgaon 97084 20
Sindhudurg 136891 7
Ahmednagar 120368 14
Average: Konkan Division 182175
Average: Nashik Division 103783
CV% 29.3
CV% 24.4
Pune 202407 3
Buldhana 67863 31
Satara 124988 12
Akola 101853 18
Sangli 130053 10
Washim 66049 33
Solapur 129720 11
Amravati 98961 19
Kolhapur 151654 6
Yavatmal 82176 27
Average: Pune Division 147764
Average: Amravati Division 83380
CV% 21.82
CV% 20.13
Aurangabad 122961 13
Jalna 82210 26
Wardha 116134 15
Parbhani 82465 25
Nagpur 178036 4
Hingoli 66856 32
Bhandara 95989 21
Beed 78480 29
Gondia 94022 22
Nanded 85115 24
Chandrapur 112948 16
Osmanabad 78793 28
Gadchiroli 70947 30
Latur 88879 23
Average: Nagpur Division 111346
Average: Aurangabad Division 85720
CV% 32.73
CV% 19.1
Source: Appendix Table 1
District wise per capita income has been presented in table 13 and its categorisation has been
presented in thematic map 12. Out of 34 districts of Maharashtra, Mumbai is in the first
position and Nandurbar is in the last position. Inter-district per capita income categorisation
within the state reveals that,
Raigarh, Nagpur, Pune, Thane and Mumbai are the districts, which are found in the
category of very high per capita income.
In the category of above average there are 10 (28%) districts.
22 per cent (8) districts are in the category of below average.
In the very low per capita income category, there are 11 districts (34%).
33
With respect to intra-state imbalances this
state is found in the 12th
position out of 18
selected states. Maharashtra has 6
administrative divisions, among them
Konkan division has the highest per capita
income, whereas, Aurangabad has the
lowest per capita income (table 13). With
respect to inter-district disparities,
Aurangabad division has the lowest
regional imbalances and Nagpur division
has the highest regional imbalances (see
figure 11 for more details).
Thematic Map 12: Categorisation of Districts in Per capita Income (PCI) of
Maharashtra (within the state)
Legend: Very Low Below Average Above Average Very High No Data
19.10
20.13
21.82
24.40
29.30
32.73
0 10 20 30 40
AURANGA…
AMRAVATI
PUNE
NASHIK
KONKAN
NAGPUR
Figure 11: Division-wise Regional Imbalances in Per capita GSDP,
Maharahstra
34
ODISHA is also one of the underdeveloped states in India. The state contributes 2.43 per cent
of GDP to the nation with 3.47 per cent of population. This state is also not an exception for
the intra-state imbalances. The state is found in the 15th
position in intra-state disparity among
the selected 18 Indian states.
Table 14: Per Capita District Domestic Product, Odisha, 2010-11 (2004-05 prices)