Debashis hdi & economic growth

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Debashis hdi & economic growth

  1. 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. 2. Structure of Presentation • • • • • • • Objective Literature Review Methodology Data Results Concerns for UP Observations
  3. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 18. Relationship between HDI and PCGSDP across Indian States (2009-10)
  19. 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. 20. Scenario in UP: Rural Education
  21. 21. Scenario in UP: Urban Literacy
  22. 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. 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

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