1. Human Development and Growth Experience:
Considerations for Uttar Pradesh in the
Indian Canvas
Sacchidananda Mukherjee, NIPFP
Debashis Chakraborty, IIFT
For presentation at the Conference on, ‘Education and Health: Special
focus on Uttar Pradesh’, jointly organized by Glocal University and E&H
Foundation to be held during 25 and 26 October, 2013, Saharanpur

2. Structure of Presentation
•
•
•
•
•
•
•
Objective
Literature Review
Methodology
Data
Results
Concerns for UP
Observations

3. Objective
 Economic growth (EG) since Reforms in 1991 – focus on export-oriented
development strategy
 Growing rural-urban disparity in the growth process
 Importance of Human development (HD) in manufacturing and services sector
of the economy
 How to assess HD achievements over the last two decades?
 Recent HD Policies as part of unilateral initiatives as well as to comply with the
Millennium Development Goals (MDGs)
 Education:
Sarva Shiksha Abhiyan, Rashtriya Madhyamik Shiksha Abhiyan
(proposed) , creation of new IITs, IIMs and several universities etc.
 Health: National Rural Health Mission, Pradhan Mantri Swasthya Suraksha
Yojana etc.
 Indirect Implications? Mahatma Gandhi National Rural Employment Guarantee
Act (MGNREGA) for rural areas, Right of Children to Free and Compulsory
Education Act, the National Food Security Ordinance etc.
 What has been the Effect of Growth on Human Development over the last two
decades?

4. Literature Review: EQ and HD
•
Two-way relationship between EG and HD, implying that nations may enter either into a
virtuous cycle of high growth and large HD gains (Scandinavian countries), or a vicious
cycle of low growth and low HD improvement (several African states, Mexico) (Ranis,
2004; Ranis, et al., 2000; Mayer-Foulkes, 2007).
•
Strength of the EG-HD relationship influenced by public expenditure on social services,
female education, investment rate, income distribution etc. (Ramirez et al., 1997).
•
Role of government institutions and the governance mechanism in strengthening EG-HD
interrelationship (Amin, undated; Joshi, 2007).
•
Role of social capital formation through development initiatives, in addition to economic
growth, in determining the HD augmentation process (Christoforou, 2006).
•
On the other hand, higher initial level of HD may, in turn, augment governance mechanisms
(for example, lesser corruption) and indirectly fuel the process of EG (Costantini and
Salvatore, 2008)
•
Cutting expenditure on HD without improving services leaves an adverse impact on longrun growth opportunities (Patnaik and Vasudevan, 2002).

In a cross-country analysis, HD is positively and linearly related to both political openness
and the income level, indicating that the countries characterized by higher levels of
income and a better democratic set-up are likely to witness higher HD achievements
(Mukherjee and Chakraborty, 2010) .

5. Literature Review: EQ and HD in India
 NHDR ( 2001) ranked Kerala, Punjab and Tamil Nadu at the top on HD
achievement, while Bihar, Madhya Pradesh and Uttar Pradesh were placed
at the other extreme.
 The two-way causality between EG and HD holds good in India as well,
which indicates possibilities of vicious cycles (Ghosh, 2006).
 Non-farm growth process has been more pro-poor in states characterized
by higher HD achievements like a high initial literacy rate, higher farm
productivity, higher rural living standards (relative to urban areas), lower
landlessness and lower infant mortality (Ravallion and Datt, 2002).
 Extreme poverty is concentrated in the rural areas of northern States
while income growth has been dynamic in the southern States and urban
areas (Antony and Laxmaiah, 2008).
 Increased investment in human capital formation, with a higher priority
being accorded to secondary education, would ensure faster economic
growth and better income distribution (Ojha and Pradhan, 2006).

6. Methodology
 Following NHDR 2001, for calculation of the Human Development
Index (HDI) for Indian states, three variables - the per capita
consumption expenditure, composite index of educational
attainment, and composite index of health attainment - are
considered.
 The HDI score for the jth state is given by the average of the
normalized values of the three indicators: namely - inflation and
inequality adjusted per capita consumption expenditure (X1); the
composite indicator on educational attainment (X2); and the
composite indicator on health attainment (X3).
 The normalization is done by dividing the difference between any
variable ( Xij) within these categories and the minimum value of Xi to
the difference between the maximum and the minimum value of Xi
[i.e., (Xij – min(Xij))/(max(Xij)-min(Xij))]

7. Data

To understand the evolution in EG-HD relationship in India, five periods have been
considered - NSSO’s quinquennial surveys (38th Round: 1983, 50th Round: 1993-94,
55th Round: 1999-2000, 61st Round: 2004-05 and 66th Round: 2009-10)

The analysis has been conducted separately for rural and urban areas.

Income: database of the EPW Research Foundation (EPWRF, 2009), State Domestic
Product (State Series), Central Statistical Organization, Ministry of Statistics and
Programme Implementation, Government of India

Education: Population Census (1981, 1991 and 2001), 4th All-India Educational Survey
(NCERT, 1982); 6th All-India Educational Survey (NCERT, 1999), 7th All India
Educational Survey (NCERT, 2002), 8th All India School Education Survey (NCERT,
2013), NCERT (2006), Government of India (undated), Registrar General of India
and Census Commissioner (RGI & CC, 2006) for 2001.

Health: Government of India (2002), Ministry of Health and Family Welfare and the
Office of the Registrar General of India (1999), Sample Registration System (SRS)
Bulletins (various issues).

Three new states, Chhattisgarh, Jharkhand and Uttarakhand were created from
Madhya Pradesh, Bihar and Uttar Pradesh in 2001. For periods before 2001, we have
assumed the values of the variables are same for both the new and the existing
states.

8. Modified Indicator of Income (X1)
 UNDP methodology, the real GDP Per Capita in PPP USD is considered for
constructing the HDI.
 NHDR (2001) instead preferred the inflation- and inequality-adjusted average
monthly per capita consumption expenditure (MPCE) of a state, which has been
adopted in the current framework.
 The current analysis also considers inflation- and inequality-adjusted MPCE of a
state as an indicator of consumption (X1) for constructing the HDI.
 In order to understand the size of the economy and growth pattern of each of
the states, we have classified them into three categories with respect to their
PCGSDP at constant prices in the following manner: high-income states (PCGSDP:
greater than the 3rd quartile), medium-income states (PCGSDP: 1st to the 3rd
quartile) and low-income states (PCGSDP: lesser than the 1st quartile).
 In order to even out the yearly fluctuations in the per capita GSDP, the current
analysis considers the three years’ average per capita GSDP - for 1983 (average
for 1981-82 to 1983-84), for 1993 (average for 1992-93 to 1994-95), for 19992000 (average for 1998-99 to 2000-01), for 2004-05 (average for 2003-04 to
2005-06) and for 2009-10 (average for 2008-09 to 2010-11).

9. Composite indicator on educational attainment (X2)
 Two variables are considered, namely, the literacy rate for the
age group of 7 years and above (e1), and the adjusted intensity of
formal education (e2).
 The analysis assigns a weightage of 0.35 to e1 and of 0.65 to e2
to estimate X2, in line with the NHDR, 2001 methodology.
 Intensity of Formal Education (IFE) is the Weighted Average of
Enrolment (WAE) of students from class I to class XII (where
weight 1 is assigned for Class I, 2 for Class II, and so on)
expressed as percentage of Total Enrolment (TE) in Class I to
Class XII.
 The IFE is multiplied with the ratio of Total Enrolment (TE) to
Population in the age group 6-18 years (PC ) to get the Adjusted
Intensity of Formal Education (AIFE).
 The analysis has been conducted for rural and urban areas
separately.

10. Composite indicator on health attainment (X3)
 Composite indicator on health attainment (X3) is
determined by taking into account two variables,
namely, Life Expectancy (LE) at age one (h1), and the
inverse of Infant Mortality Rate (IMR) (h2).
 The current analysis assigns weightages of 0.65 and
0.35 to h1 and h2 respectively, to determine the
composite indicator (X3), in line with the NHDR 2001
methodology.
 Here again, the analysis has been carried out for rural
and urban areas, separately.

11. State-wise Consumption Index (X1) Scores and Ranks
1983
States /
UTs
Rural
1993-94
Urban
Rural
1999-2000
Urban
Rural
2009-10
2004-05
Urban
Rural
Urban
Rural
Urban
Andhra Pradesh
0.223
(18)
0.163
(20)
0.221
(15)
0.000
(28)
0.104
(20)
0.053
(21)
0.130
(26)
0.422
(19)
0.162
(24)
0.531
(11)
Arunachal
Pradesh
0.407
(9)
0.269
(11)
0.200
(17)
0.570
(6)
0.315
(10)
0.225
(15)
0.634
(5)
0.197
(26)
0.516
(12)
0.261
(24)
Assam
0.407
(9)
0.269
(11)
0.153
(19)
0.434
(9)
0.074
(22)
0.265
(13)
0.452
(14)
0.376
(21)
0.332
(17)
0.284
(23)
Bihar
0.000
(27)
0.044
(25)
0.004
(25)
0.080
(22)
0.056
(23)
0.032
(26)
0.201
(21)
0.093
(27)
0.122
(26)
0.176
(27)
Chhattisgarh
0.038
(24)
0.110
(23)
0.012
(23)
0.003
(26)
0.000
(27)
0.038
(24)
0.000
(28)
0.584
(11)
0.000
(28)
0.490
(13)
Goa
0.958
(2)
0.758
(2)
0.988
(2)
0.383
(11)
0.750
(2)
0.499
(5)
0.628
(6)
0.973
(2)
0.694
(3)
1.000
(1)
Gujarat
0.358
(15)
0.506
(6)
0.219
(16)
0.279
(15)
0.216
(15)
0.301
(10)
0.171
(24)
0.756
(5)
0.268
(19)
0.717
(6)
Haryana
0.732
(4)
0.392
(7)
0.301
(10)
0.299
(13)
0.384
(7)
0.275
(12)
0.582
(8)
0.413
(20)
0.581
(8)
0.422
(18)
Himachal Pradesh
0.767
(3)
1.000
(1)
0.229
(14)
0.626
(5)
0.335
(9)
0.590
(4)
0.550
(11)
0.966
(3)
0.737
(2)
0.727
(5)
Jammu & Kashmir
0.564
(6)
0.294
(10)
0.390
(8)
0.456
(8)
0.425
(6)
0.366
(7)
0.721
(4)
0.596
(10)
0.691
(4)
0.414
(20)
Jharkhand
0.000
(27)
0.044
(25)
0.004
(25)
0.080
(22)
0.056
(23)
0.032
(26)
0.274
(18)
0.600
(9)
0.252
(22)
0.342
(21)
Karnataka
0.237
(17)
0.218
(17)
0.125
(21)
0.087
(21)
0.153
(18)
0.182
(19)
0.206
(19)
0.602
(8)
0.253
(21)
0.709
(7)
Kerala
0.520
(7)
0.214
(18)
0.436
(5)
0.355
(12)
0.502
(4)
0.290
(11)
1.000
(1)
1.000
(1)
1.000
(1)
0.970
(2)
Madhya Pradesh
0.038
(24)
0.110
(23)
0.012
(23)
0.003
(26)
0.000
(27)
0.038
(24)
0.061
(27)
0.485
(15)
0.076
(27)
0.572
(10)
Maharashtra
0.181
(19)
0.367
(9)
0.105
(22)
0.258
(16)
0.153
(17)
0.206
(17)
0.152
(25)
0.749
(6)
0.302
(18)
0.820
(3)
Manipur
0.497
(8)
0.253
(15)
0.375
(9)
0.177
(17)
0.265
(11)
0.255
(14)
0.423
(15)
0.000
(28)
0.263
(20)
0.000
(28)
Meghalaya
0.407
(9)
0.269
(11)
0.403
(7)
0.775
(3)
0.357
(8)
0.631
(3)
0.752
(3)
0.341
(23)
0.578
(9)
0.210
(26)
Mizoram
0.625
(5)
0.753
(3)
0.744
(3)
1.000
(1)
0.574
(3)
0.689
(2)
0.562
(10)
0.495
(14)
0.411
(15)
0.471
(15)
Nagaland
0.407
(9)
0.582
(5)
1.000
(1)
0.805
(2)
1.000
(1)
1.000
(1)
0.853
(2)
0.729
(7)
0.499
(14)
0.230
(25)
Orissa
0.032
(26)
0.153
(22)
0.165
(18)
0.108
(19)
0.083
(21)
0.000
(28)
0.173
(23)
0.441
(16)
0.393
(16)
0.579
(9)
Punjab
1.000
(1)
0.382
(8)
0.532
(4)
0.402
(10)
0.426
(5)
0.308
(9)
0.613
(7)
0.497
(13)
0.638
(6)
0.448
(17)
Rajasthan
0.264
(16)
0.210
(19)
0.135
(20)
0.154
(18)
0.147
(19)
0.146
(20)
0.206
(20)
0.432
(17)
0.204
(23)
0.488
(14)
Sikkim
0.407
(9)
0.662
(4)
0.280
(11)
0.710
(4)
0.224
(14)
0.460
(6)
0.519
(12)
0.238
(25)
0.689
(5)
0.630
(8)
Tamil Nadu
0.113
(20)
0.158
(21)
0.268
(13)
0.102
(20)
0.257
(12)
0.198
(18)
0.453
(13)
0.811
(4)
0.564
(10)
0.799
(4)
Tripura
0.407
(9)
0.269
(11)
0.416
(6)
0.548
(7)
0.253
(13)
0.365
(8)
0.352
(16)
0.351
(22)
0.601
(7)
0.524
(12)
Uttar Pradesh
0.080
(22)
0.000
(27)
0.000
(27)
0.058
(24)
0.044
(25)
0.046
(22)
0.183
(22)
0.290
(24)
0.128
(25)
0.328
(22)
Uttarakhand
0.080
(22)
0.000
(27)
0.000
(27)
0.058
(24)
0.044
(25)
0.046
(22)
0.301
(17)
0.429
(18)
0.527
(11)
0.419
(19)
West Bengal
0.093
(21)
0.247
(16)
0.275
(12)
0.281
(14)
0.185
(16)
0.215
(16)
0.568
(9)
0.541
(12)
0.511
(13)
0.460
(16)

12. State-wise Education Index (X2) Scores and Ranks
States /
UTs
1983
Rural
1993-94
Urban
Rural
1999-2000
Urban
Rural
2009-10
2004-05
Urban
Rural
Urban
Rural
Urban
Andhra Pradesh
0.087
(23)
0.165
(22)
0.088
(25)
0.515
(25)
0.272
(22)
0.237
(23)
0.267
(23)
0.198
(25)
0.001
(27)
0.195
(24)
Arunachal
Pradesh
0.000
(27)
0.238
(20)
0.128
(20)
0.656
(15)
0.138
(25)
0.408
(12)
0.142
(25)
0.452
(12)
0.029
(26)
0.731
(5)
Bihar
0.343
0.084
(12)
(24)
0.449
0.140
(11)
(23)
0.323
0.047
(15)
(26)
0.766
0.524
(8)
(22)
0.358
0.000
(17)
(28)
0.507
0.010
(10)
(27)
0.357
0.000
(17)
(28)
0.525
0.011
(8)
(26)
0.229
0.000
(18)
(28)
0.502
0.158
(11)
(26)
Chhattisgarh
0.109
(21)
0.259
(18)
0.100
(21)
0.644
(18)
0.385
(14)
0.387
(16)
0.390
(14)
0.403
(13)
0.185
(20)
0.436
(12)
Goa
Haryana
0.683
0.363
0.254
(3)
(10)
(15)
0.566
0.470
0.333
(7)
(10)
(15)
0.737
0.392
0.337
(2)
(11)
(13)
0.836
0.739
0.659
(6)
(11)
(14)
0.743
0.347
0.446
(3)
(19)
(12)
0.563
0.318
0.339
(7)
(19)
(18)
0.736
0.342
0.432
(3)
(20)
(12)
0.523
0.296
0.298
(9)
(19)
(18)
0.629
0.330
0.335
(4)
(14)
(12)
0.555
0.392
0.283
(10)
(16)
(22)
Himachal Pradesh
0.467
(4)
0.746
(4)
0.565
(4)
0.944
(3)
0.721
(4)
1.000
(1)
0.699
(4)
0.999
(2)
0.664
(3)
1.000
(1)
Jammu & Kashmir
0.077
(26)
0.000
(28)
0.138
(19)
0.000
(28)
0.128
(26)
0.028
(26)
0.121
(26)
0.000
(28)
0.106
(23)
0.000
(28)
Jharkhand
0.084
(24)
0.140
(23)
0.047
(26)
0.524
(22)
0.039
(27)
0.248
(22)
0.050
(27)
0.294
(20)
0.045
(24)
0.216
(23)
Karnataka
0.254
(16)
0.381
(13)
0.299
(16)
0.674
(13)
0.369
(16)
0.392
(15)
0.360
(16)
0.366
(15)
0.206
(19)
0.425
(13)
Kerala
1.000
(1)
1.000
(1)
1.000
(1)
0.988
(2)
1.000
(1)
0.877
(3)
1.000
(1)
0.779
(4)
1.000
(1)
0.715
(6)
Madhya Pradesh
0.109
(21)
0.259
(18)
0.100
(21)
0.644
(18)
0.309
(20)
0.355
(17)
0.347
(19)
0.504
(10)
0.122
(22)
0.392
(17)
Maharashtra
0.391
(8)
0.591
(6)
0.447
(5)
0.746
(10)
0.613
(5)
0.582
(6)
0.603
(5)
0.577
(7)
0.462
(9)
0.604
(8)
Manipur
0.396
(6)
0.311
(17)
0.444
(6)
0.648
(17)
0.497
(10)
0.405
(13)
0.488
(9)
0.377
(14)
0.462
(8)
0.399
(15)
Meghalaya
0.213
(18)
0.553
(8)
0.185
(18)
0.798
(7)
0.285
(21)
0.756
(4)
0.302
(21)
0.893
(3)
0.250
(17)
0.888
(3)
Mizoram
0.804
(2)
0.994
(2)
0.701
(3)
1.000
(1)
0.759
(2)
0.919
(2)
0.771
(2)
1.000
(1)
0.594
(5)
0.990
(2)
Nagaland
0.413
(5)
0.719
(5)
0.420
(10)
0.840
(5)
0.351
(18)
0.530
(8)
0.375
(15)
0.607
(6)
0.334
(13)
0.734
(4)
Orissa
Punjab
0.259
0.348
(14)
(11)
0.226
0.319
(21)
(16)
0.261
0.387
(17)
(12)
0.610
0.617
(21)
(20)
0.369
0.459
(15)
(11)
0.315
0.228
(21)
(24)
0.356
0.451
(18)
(10)
0.290
0.212
(22)
(24)
0.269
0.295
(16)
(15)
0.382
0.319
(18)
(19)
Rajasthan
0.000
(28)
0.051
(25)
0.000
(28)
0.515
(24)
0.262
(23)
0.205
(25)
0.278
(22)
0.261
(23)
0.033
(25)
0.170
(25)
Sikkim
0.237
(17)
0.334
(14)
0.421
(9)
0.713
(12)
0.533
(8)
0.393
(14)
0.554
(8)
0.346
(16)
0.559
(6)
0.285
(21)
Tamil Nadu
0.394
(7)
0.546
(9)
0.436
(8)
0.764
(9)
0.520
(9)
0.519
(9)
0.440
(11)
0.314
(17)
0.380
(10)
0.585
(9)
Tripura
0.385
(9)
0.896
(3)
0.440
(7)
0.851
(4)
0.574
(6)
0.693
(5)
0.582
(6)
0.672
(5)
0.686
(2)
0.661
(7)
Uttar Pradesh
0.110
(19)
0.030
(26)
0.100
(23)
0.436
(26)
0.222
(24)
0.000
(28)
0.225
(24)
0.011
(27)
0.163
(21)
0.013
(27)
Uttarakhand
0.110
(19)
0.030
(26)
0.100
(23)
0.436
(26)
0.573
(7)
0.472
(11)
0.573
(7)
0.467
(11)
0.495
(7)
0.424
(14)
West Bengal
0.294
(13)
0.391
(12)
0.332
(14)
0.650
(16)
0.441
(13)
0.318
(20)
0.431
(13)
0.293
(21)
0.338
(11)
0.289
(20)
Assam
Gujarat

13. State-wise Health Index (X3) Scores and Ranks
States /
UTs
1983
Rural
1993-94
Urban
Rural
1999-2000
Urban
Rural
2009-10
2004-05
Urban
Rural
Urban
Rural
Urban
Andhra Pradesh
0.424
(7)
0.583
(8)
0.379
(8)
0.315
(11)
0.377
(11)
0.361
(11)
0.375
(11)
0.354
(11)
0.377
(9)
0.358
(9)
Arunachal
Pradesh
0.126
(20)
0.233
(22)
0.096
(26)
0.234
(19)
0.080
(23)
0.328
(14)
0.081
(24)
0.328
(14)
0.076
(22)
0.341
(11)
Bihar
0.126
0.172
(19)
(12)
0.233
0.311
(20)
(11)
0.096
0.268
(25)
(11)
0.234
0.371
(20)
(9)
0.080
0.240
(26)
(13)
0.324
0.342
(21)
(13)
0.081
0.237
(26)
(14)
0.326
0.326
(19)
(21)
0.075
0.238
(26)
(12)
0.339
0.329
(16)
(19)
Chhattisgarh
0.066
(23)
0.243
(14)
0.000
(27)
0.129
(23)
0.000
(27)
0.102
(25)
0.000
(27)
0.093
(25)
0.000
(27)
0.103
(24)
Goa
Haryana
0.520
0.379
0.515
(3)
(8)
(5)
0.602
0.282
0.796
(7)
(13)
(4)
0.470
0.348
0.475
(4)
(10)
(3)
0.638
0.161
0.500
(3)
(22)
(6)
0.492
0.365
0.502
(6)
(12)
(5)
0.667
0.241
0.499
(3)
(23)
(8)
0.498
0.358
0.502
(6)
(12)
(5)
0.672
0.233
0.484
(2)
(23)
(8)
0.501
0.354
0.511
(4)
(10)
(3)
0.681
0.245
0.489
(2)
(21)
(8)
Himachal Pradesh
0.000
(28)
0.000
(25)
0.141
(14)
0.000
(25)
0.588
(4)
0.472
(9)
0.594
(4)
0.466
(9)
0.151
(15)
0.001
(26)
Jammu & Kashmir
0.000
(25)
0.000
(25)
0.141
(14)
0.000
(25)
0.588
(3)
0.471
(10)
0.594
(3)
0.466
(10)
0.151
(16)
0.000
(27)
Jharkhand
0.172
(12)
0.311
(11)
0.268
(11)
0.371
(9)
0.240
(14)
0.342
(12)
0.237
(13)
0.326
(18)
0.238
(11)
0.330
(18)
Karnataka
0.505
(6)
0.903
(3)
0.389
(7)
0.436
(8)
0.405
(9)
0.528
(7)
0.404
(9)
0.521
(7)
0.412
(7)
0.518
(7)
Kerala
1.000
(1)
0.952
(2)
1.000
(1)
1.000
(1)
1.000
(1)
1.000
(1)
1.000
(1)
1.000
(1)
1.000
(1)
1.000
(1)
Madhya Pradesh
0.066
(23)
0.243
(14)
0.000
(27)
0.129
(23)
0.000
(28)
0.102
(26)
0.000
(28)
0.093
(26)
0.000
(28)
0.103
(23)
Maharashtra
0.520
(4)
0.602
(6)
0.470
(5)
0.637
(4)
0.491
(7)
0.666
(4)
0.496
(7)
0.671
(3)
0.499
(5)
0.678
(3)
Manipur
0.127
(15)
0.234
(16)
0.097
(19)
0.235
(14)
0.081
(20)
0.325
(17)
0.083
(19)
0.327
(15)
0.077
(19)
0.342
(10)
Meghalaya
0.126
(17)
0.233
(19)
0.096
(24)
0.235
(14)
0.080
(25)
0.324
(18)
0.081
(25)
0.326
(20)
0.075
(25)
0.339
(17)
Mizoram
0.126
(16)
0.234
(17)
0.096
(21)
0.235
(16)
0.081
(20)
0.326
(15)
0.082
(21)
0.328
(12)
0.076
(24)
0.340
(12)
Nagaland
0.126
(18)
0.234
(18)
0.096
(20)
0.234
(17)
0.081
(19)
0.326
(16)
0.082
(20)
0.328
(13)
0.076
(20)
0.340
(15)
Orissa
Punjab
0.187
0.656
(11)
(2)
0.175
1.000
(24)
(1)
0.126
0.672
(18)
(2)
0.258
0.718
(12)
(2)
0.125
0.685
(18)
(2)
0.231
0.675
(24)
(2)
0.121
0.687
(18)
(2)
0.223
0.670
(24)
(4)
0.128
0.691
(18)
(2)
0.226
0.677
(22)
(4)
Rajasthan
0.167
(14)
0.320
(10)
0.192
(13)
0.242
(13)
0.228
(15)
0.277
(22)
0.225
(15)
0.270
(22)
0.232
(13)
0.282
(20)
Sikkim
0.126
(20)
0.233
(23)
0.096
(22)
0.234
(18)
0.080
(24)
0.324
(18)
0.081
(22)
0.327
(16)
0.076
(23)
0.340
(14)
Tamil Nadu
0.298
(10)
0.456
(9)
0.429
(6)
0.476
(7)
0.462
(8)
0.536
(6)
0.462
(8)
0.531
(6)
0.459
(6)
0.527
(6)
Tripura
0.126
(22)
0.233
(21)
0.096
(23)
0.234
(21)
0.080
(22)
0.324
(18)
0.081
(22)
0.326
(17)
0.076
(21)
0.340
(13)
Uttar Pradesh
0.000
(26)
0.000
(27)
0.141
(16)
0.000
(27)
0.148
(17)
0.000
(28)
0.150
(17)
0.000
(28)
0.151
(17)
0.000
(28)
Uttarakhand
0.000
(26)
0.000
(27)
0.141
(16)
0.000
(27)
0.148
(16)
0.001
(27)
0.150
(16)
0.001
(27)
0.151
(14)
0.001
(25)
West Bengal
0.323
(9)
0.690
(5)
0.374
(9)
0.516
(5)
0.394
(10)
0.545
(5)
0.393
(10)
0.549
(5)
0.401
(8)
0.555
(5)
Assam
Gujarat

14. Observations
 X1: Stark difference in terms of consumption pattern within the
states.
 In 2009-10, while Arunachal Pradesh was ranked 24th in terms of
urban consumption, it was ranked 12th in terms of rural
consumption scores. On the other hand, during the same year,
while Maharashtra ranked 3rd in terms of urban consumption, it
was ranked 18th in terms of rural consumption scores.
 Marked transformation in relative positions - while Kerala’s
ranking has improved over the period 1983-2005, the same has
deteriorated for the urban sector in Haryana.
 X2: Rural-Urban disparities - in 2009-10, Chattisgarh secured the
12th ranking in terms of urban educational achievements, but it was
placed in the 20th position in terms of performance in the rural
belt.
 X3: Intra-state divergence - in 2009-10, while Gujarat ranked 21st
in terms of urban health achievements, it has been ranked 10th in
terms of rural health scores.

15. State-wise Human Development Index Scores and Ranks
States /
UTs
1983
Rural
1993-94
Urban
Rural
1999-2000
Urban
Rural
2009-10
2004-05
Urban
Rural
Urban
Rural
Urban
Andhra Pradesh
0.245
(17)
0.303
(17)
0.229
(16)
0.277
(23)
0.251
(18)
0.217
(20)
0.257
(21)
0.325
(21)
0.180
(22)
0.361
(19)
Arunachal
Pradesh
0.178
(20)
0.247
(19)
0.141
(21)
0.487
(11)
0.178
(22)
0.320
(17)
0.286
(20)
0.325
(20)
0.207
(21)
0.444
(12)
Bihar
0.292
0.085
(13)
(23)
0.317
0.165
(16)
(24)
0.191
0.106
(19)
(23)
0.478
0.325
(14)
(20)
0.171
0.098
(23)
(28)
0.365
0.128
(14)
(27)
0.297
0.146
(18)
(26)
0.409
0.143
(14)
(27)
0.212
0.120
(20)
(26)
0.375
0.221
(18)
(26)
Chhattisgarh
0.071
(25)
0.204
(20)
0.037
(27)
0.259
(24)
0.128
(25)
0.175
(24)
0.130
(28)
0.360
(18)
0.062
(28)
0.343
(21)
Goa
Haryana
0.720
0.366
0.500
(2)
(7)
(5)
0.642
0.419
0.507
(3)
(12)
(8)
0.732
0.320
0.371
(2)
(10)
(7)
0.619
0.393
0.486
(4)
(17)
(12)
0.661
0.310
0.444
(2)
(12)
(7)
0.576
0.287
0.371
(5)
(19)
(12)
0.620
0.290
0.505
(2)
(19)
(5)
0.723
0.428
0.398
(3)
(13)
(16)
0.608
0.317
0.476
(2)
(13)
(5)
0.745
0.451
0.398
(2)
(11)
(16)
Himachal Pradesh
0.411
(6)
0.582
(4)
0.312
(12)
0.523
(10)
0.548
(3)
0.687
(2)
0.615
(3)
0.811
(2)
0.517
(4)
0.576
(6)
Jammu & Kashmir
0.214
(19)
0.098
(26)
0.223
(18)
0.152
(28)
0.380
(10)
0.288
(18)
0.479
(6)
0.354
(19)
0.316
(14)
0.138
(27)
Jharkhand
0.085
(23)
0.165
(24)
0.106
(23)
0.325
(20)
0.112
(26)
0.207
(22)
0.187
(24)
0.407
(15)
0.178
(23)
0.296
(23)
Karnataka
0.332
(10)
0.501
(9)
0.271
(14)
0.399
(16)
0.309
(13)
0.367
(13)
0.323
(17)
0.497
(9)
0.290
(17)
0.551
(7)
Kerala
0.840
(1)
0.722
(1)
0.812
(1)
0.781
(1)
0.834
(1)
0.722
(1)
1.000
(1)
0.926
(1)
1.000
(1)
0.895
(1)
Madhya Pradesh
0.071
(25)
0.204
(20)
0.037
(27)
0.259
(24)
0.103
(27)
0.165
(26)
0.136
(27)
0.361
(17)
0.066
(27)
0.356
(20)
Maharashtra
0.364
(8)
0.520
(6)
0.340
(8)
0.547
(8)
0.419
(8)
0.485
(7)
0.417
(11)
0.666
(4)
0.421
(9)
0.701
(3)
Manipur
0.340
(9)
0.266
(18)
0.305
(13)
0.353
(18)
0.281
(15)
0.328
(16)
0.331
(16)
0.235
(26)
0.267
(18)
0.247
(25)
Meghalaya
0.249
(16)
0.352
(15)
0.228
(17)
0.603
(5)
0.241
(19)
0.570
(6)
0.378
(13)
0.520
(8)
0.301
(16)
0.479
(10)
Mizoram
0.518
(4)
0.660
(2)
0.514
(4)
0.745
(2)
0.471
(6)
0.645
(3)
0.472
(7)
0.608
(5)
0.360
(12)
0.600
(5)
Nagaland
0.315
(11)
0.512
(7)
0.505
(5)
0.627
(3)
0.477
(5)
0.619
(4)
0.437
(10)
0.555
(6)
0.303
(15)
0.434
(14)
Orissa
Punjab
0.159
0.668
(21)
(3)
0.185
0.567
(23)
(5)
0.184
0.530
(20)
(3)
0.325
0.579
(19)
(6)
0.193
0.523
(21)
(4)
0.182
0.404
(23)
(10)
0.217
0.583
(23)
(4)
0.318
0.460
(23)
(11)
0.263
0.541
(19)
(3)
0.396
0.481
(17)
(9)
Rajasthan
0.144
(22)
0.194
(22)
0.109
(22)
0.304
(22)
0.212
(20)
0.209
(21)
0.236
(22)
0.321
(22)
0.156
(24)
0.313
(22)
Sikkim
0.257
(15)
0.410
(13)
0.266
(15)
0.552
(7)
0.279
(16)
0.392
(11)
0.385
(12)
0.304
(24)
0.441
(8)
0.418
(15)
Tamil Nadu
0.268
(14)
0.387
(14)
0.378
(6)
0.447
(15)
0.413
(9)
0.418
(9)
0.451
(9)
0.552
(7)
0.468
(6)
0.637
(4)
Tripura
0.306
(12)
0.466
(10)
0.317
(11)
0.544
(9)
0.302
(14)
0.461
(8)
0.338
(15)
0.450
(12)
0.454
(7)
0.508
(8)
Uttar Pradesh
0.064
(27)
0.010
(27)
0.080
(25)
0.165
(26)
0.138
(24)
0.015
(28)
0.186
(25)
0.101
(28)
0.147
(25)
0.114
(28)
Uttarakhand
0.064
(27)
0.010
(27)
0.080
(25)
0.165
(26)
0.255
(17)
0.173
(25)
0.341
(14)
0.299
(25)
0.391
(11)
0.281
(24)
West Bengal
0.237
(18)
0.443
(11)
0.327
(9)
0.482
(13)
0.340
(11)
0.359
(15)
0.464
(8)
0.461
(10)
0.416
(10)
0.435
(13)
Assam
Gujarat

16. Observations
 It has been observed from the table that the HD level has been
consistently high for states like Kerala, Goa, Mizoram, and Himachal
Pradesh, which are otherwise also performing well in the constituent
categories.
 On the other hand, Chhattisgarh, Uttar Pradesh, Uttarakhand, Bihar,
and Orissa have always remained among the bottom liners.
 Some interesting movement across the states has been noticed over the
period of analysis.
 For instance, Punjab and Haryana started with an appreciable HD
scenario in 1983, but their performance in the urban areas declined
considerably during the last period.
 A similar worsening effect has been noticed for Arunachal Pradesh at
the bottom end of the spectrum as well.
 On the other hand, J&K and West Bengal managed to improve their HD
level to some extent over the period.
 Interestingly, Jharkhand has shown a marked improvement in terms of
HD achievements in the urban belt after its separation from Bihar.

17. Relationship between HDI and PCGSDP across Indian States
HDI Score vs. PCGDP: 1993
HDI Score vs. PCGDP: 1983
0.800
0.700
0.700
0.600
0.600
HDI Score
0.900
0.800
HDI Score
0.900
0.500
0.400
0.500
0.400
0.300
0.300
0.200
0.200
0.100
0.100
0.000
5,000
0.000
7,000
9,000
11,000
13,000
15,000
17,000
19,000
5,000
10,000
15,000
PCGDP (Rs.)
Rural
Urban
Rural
Log. (Rural)
30,000
Urban
Log. (Urban)
Log. (Rural)
HDI Score vs. PCGDP: 2004-05
1.000
0.900
0.900
0.800
0.800
0.700
0.700
HDI Score
0.600
HDI Score
25,000
PCGDP (Rs.)
Log. (Urban)
HDI Score vs. PCGDP: 1999-2000
0.500
0.400
0.300
0.600
0.500
0.400
0.300
0.200
0.200
0.100
0.100
0.000
5,000
20,000
0.000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
5,000
10,000
15,000
20,000
25,000
PCGDP (Rs.)
Rural
Urban
Log. (Urban)
30,000
35,000
40,000
45,000
50,000
PCGDP (Rs.)
Log. (Rural)
Rural
Urban
Log. (Urban)
Log. (Rural)
55,000

18. Relationship between HDI and PCGSDP
across Indian States (2009-10)

19. Observations
 Positive relationship between EG and HD has been observed during




all the five periods under consideration.
Relationship between EG and HD is non-linear in nature, that is,
the rising level of income is associated with a lesser degree of
increase in terms of HD achievements beyond a critical level.
Barring a few exceptions, the urban HDI score is generally higher
than the rural HDI score for all the periods in the current
analysis.
On one hand in the case of Goa, a high-income state, the rural
HDI score has been found to be higher than the urban HDI score
for the years 1983, 1993 and 1999-2000, but an opposite scenario
emerges in 2004-05.
On the other hand, for high-income states like Punjab and
Haryana (1999-2000, 2004-05), the rural HDI score is higher
than urban HDI score.

20. Scenario in UP: Rural Education

21. Scenario in UP: Urban Literacy

22. Characteristics on Human development parameters – Profiles of Select States
Criteria
Year
2011
2011
Uttar
Pradesh
199.58
22.28
Andhra
Pradesh
84.67
33.49
Population (in Million)
Urban Population (% of Total
Population)
Literacy Rate (7 Years &
Above): Rural
Literacy Rate (7 Years &
Above): Urban
Per Capita NSDP (at Constant
Prices, 2004-05 Base, Rs.)
Percentage of Population Below
Poverty Line: Rural
Percentage of Population Below
Poverty Line: Urban
HDI Score: Rural
HDI Score: Urban
Gini Ratio of Per Capita
Consumption Expenditure: Rural
Gini Ratio of Per Capita
Consumption Expenditure:
Urban
Unemployment Rate: Rural
Unemployment Rate: Urban
Infant Mortality Rate (Per
Thousand): Rural
Infant Mortality Rate (Per
Thousand): Urban
Average Per Capita Social
Sector Expenditure (Rs.)
Average Per Capita
Development Expenditure (Rs.)
2011
67.55
2011
Bihar
Madhya
Pradesh
72.60
27.63
Chhatti
sgarh
25.54
23.24
Odisha
Kerala
103.80
11.30
Rajastha
n
68.62
24.89
41.95
16.68
33.39
47.72
61.14
61.83
62.34
65.29
66.76
70.78
92.92
77.01
80.54
78.75
80.73
84.09
84.79
86.45
94.99
2011-12
18,099
42,685
13,971
27,421
24,598
29,635
26,900
53,427
2009-10
39.36
22.75
55.33
26.42
41.98
56.13
39.20
12.00
2009-10
31.67
17.70
39.40
19.94
22.92
23.79
25.93
12.07
2009-10
2009-10
2009-10
0.147
0.114
0.231
0.180
0.361
0.269
0.120
0.221
0.215
0.156
0.313
0.213
0.066
0.356
0.276
0.062
0.343
0.234
0.263
0.396
0.248
1.000
0.895
0.350
2009-10
0.395
0.353
0.316
0.316
0.365
0.305
0.376
0.399
2009-10
2009-10
2009
1.0
2.9
66
1.2
3.1
54
2.0
7.3
53
0.4
2.2
65
0.7
2.9
72
0.6
2.9
55
3.0
4.2
68
7.5
7.3
12
2009
47
35
40
35
45
47
46
11
2005-10
1,685
3,155
1,597
2,472
1,252
3,396
2,348
2,821
2005-10
2,628
5,547
2,217
3,450
2,048
4,449
3,145
3,727

23. Some Observations ..
 Relationship Development expenditure and HD (Mukherjee and Chakraborty, 2011)
 The association between per capita development/social expenditure and HD was
stronger during the early 1980s and 1990s, but the same became weaker during
2004-05.
 PCSE had a larger impact on HD as compared to PCDE.
 The association between PCSE/PCDE and achievement in HD has been stronger in
urban areas as compared to rural areas.
 On policy front, the lower value of the expenditure coefficients in the rural areas
indicates the presence of a vicious cycle, owing to the lower initial HD scenario
and other bottlenecks, which deserve immediate government attention.
 Therefore, the state governments need to urgently acknowledge the underlying
relationship between development expenditures and human development, on one
hand, and the relationship between human development and economic growth, on
the other.
 Fiscal Space? In 2004-05, both the middle- and high-income states registered an
increment in the tax-GSDP ratio; but in the low-income states, this figure
declined
 Inequality - Role of government in ensuring balanced growth process