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New Performance Indices for Indian States on Education and Health

22-Aug-2018Arvind Virmani

Section I: Introduction

What has been commonly observed while evaluating the standing of Indian States on various socio-economic and social indicators is that the absolute values of the indicators are presented (or alternatively the Human Development Index values) and conclusions are drawn based on the relative standing of the States. This approach we believe does not properly asses the complete picture as it ignores a vital aspect of the respective States, i.e. their per capita income levels. Higher per capita income levels generally imply that the respective regions are wealthier than those with lower per capita income levels. This also means that there will be more resources (either by personal contributions or through tax revenue) towards improving socio-economic/social indicators such as increasing education levels, higher life expectancy ratios, lower maternal mortality and infant mortality ratios etc.

To give an example, while both Bihar and Tamil Nadu are considered developing regions, Tamil Nadu is wealthier than Bihar in both its overall Gross State Domestic Product (GSDP) levels and also in per capita income levels. So, in a way it would be futile to compare the absolute performance of Bihar and Tamil Nadu because Tamil Nadu has more resources which it can deploy towards improving its standing on various education and health indicators vis-à-vis Bihar.

Based on the above discussion, this Paper here develops Performance Indices for Indian States on education and health indicators (taking into account the gender parity and rural-urban gap), based on the relative income level of the States.

The paper is organized as follows, Section II does a brief review of literature, Section III gives an introduction on the methodology used, Section IV discusses the results in Education indicators of the Indian States, Section V discusses the results in Health indicators of the Indian States and Section VI concludes. We also list in Appendix Ithe tables of the education and health indicators,Appendix II has the graphs of the States across education Indicators,in Appendix IIIthe regression results and in Appendix IVa consolidated list of available health indicators used in this paper for each State.

Section II: Literature Review

There have been attempts to measure the progress of the Indian States in social and socio-economic indicators and how they contribute to economic growth. While these papers do not necessarily follow the method outlined in this paper, they provide a useful and important benchmark of where the States are performing in social and socio-economic indicators.

Indrayan, Wysocki, Singh and Kumar(1999) in their paper compute the measure of progress made by Indian states in improving their Human Development Index (HDI) over a three decade period (1971, 1981, and 1991). Using census data they find that barring a few states, most have made progress over the 3 decade period in improving their HDI but that the gains have varied from State to State. Although barring 3 States, all of the others had at that point in time low or very low HDI.

Kumar (1991) also compute HDI values for the Indian States and as a measure of comparison of where the states stood then ranked the states along with the low and medium HDI countries as presented in the UNDP 1990 report. The results show us that most of the Indian States fall under low HDI category although most of them are not abysmally low and a few States fall under the medium HDI category.

Kurian (2000) surveying the status of social and socio-economic indicators among the States observed that despite the planning process in the initial decades of Independence some disparities remained among the Indian States. These disparities were only aggravated from the accelerated economic growth from the 1980s and widened with the reforms post 1991. This disparity among the States can be decreased through higher levels of investment in education, health, infrastructure among the backward States.

Nagaraj, Varoudakisand Veganzones(1998) in their paper outlined the various factors affecting economic growth across the Indian States. While investment in infrastructure has yielded high returns, investments on education (by raising the education levels) and investments in improving health conditions have also translated to increasing economic growth.

Prabhu, Sarkerand Radha(1996) critically evaluate the gender related development index (GDI) that was published alongside the HDI by UNDP. Their findings show that a variety of ranks of the Indian states can be given based on the various measures of wage rate and work force participation rates. They also point out that the aggregate nature of the index might tend the governments to focus on achieving the easier targets rather than solving the deeper underlying problems. They suggest using female-male ratio instead of using the GDI; publishing the GDI on a regular basis alongside the HDI and lastly, incorporate developing economies specific variables into the GDI to better understand the picture in the emerging economies.

Corrie (1994) following the trend for developing HDI for Indian States, created a HDI specifically for the Dalit child in India. Such an index is useful in gauging the success of public policy as it helps in following the social progress of the underprivileged sections of the Indian society. The relative ranking of 15 States were presented with Kerala, Punjab and Himachal Pradesh as the States with high HDIs and Madhya Pradesh and Bihar among the lowest.

The Educational Development Index (2008) has also been developed to develop a multi-faceted aspect of education in India. The indicator has four major components – Access, Infrastructure, Teachers and Outcome. Each of these four indicators is further subdivided to capture the performance of the respective States.

Section III: Method

Unlike most of the papers in the literature, we avoid developing a HDI, quoting the absolute value of the indicators for each of the State or developing an indicator specific index; we instead pose the questions – How are the States performing in the respective education and health indicators relative to their per capita income level.

As is generally observed, a higher per capita income level implies a wealthier State/Country/region – This by itself is translated to larger amount of resources towards socio-economic factors such as education, health etc.; by way of contributions of individuals towards their family or a greater availability of resources to the government by way of larger revenues. Given the income constraints faced by more or less all the States in the Country, by analysing how they fare in their education and health indicators compared to their income level gives us a better picture of how well the States are performing.

Following on the above - Instead of having per capita income level (NSDP per capita in this case) as the dependent variable as is normally the case, we run the regression with the education/health variable as the dependent variable and with NSDP per capita as the independent variable. As rising income levels is generally associated with better education and health outcomes, this method will help us understand how States are performing relative to their respective per capita level (as also explained above).

We initially run Ordinary Least Squares (OLS) regressions with the education/health variable being the dependent factor and NSDP per capita being the independent factor. Provided the result is significant we report the Performance Index (PI; defined here as derived from the residuals divided by the linear prediction and multiplied x 100 to ensure standardization; also in case of certain indicators such as Infant Mortality Rate (IMR), Maternal Mortality Rate (MMR) and Total Fertility Rate (TFR) etc. where the coefficient is reported negative, we multiply the indicators with negative (minus) 100 instead of 100, this is done because States are expected to have lower IMR, MMR and TFR etc. with rising incomes) and for where the results are not significant we report the variable for education and health indicators used as the dependent variable in the regression equation.

Before we begin, a caveat in order – A high performance index (unless stated otherwise) implies the State is performing better in that respective social indicator. A lower performance index indicates otherwise. The categorization of States vis-a-vis the performance index in the different education and health indicators can give the States an idea of where they stand (relative to their income level) and where public resources can be focussed on and public policy frameworks can be re-looked at for improving their results.

The data on the education and literacy indicators are taken from the Statistics of School Education (SSE), 2011-12 as published by the Ministry of Human Resource Development and NITI Aayog (citing Census 2011 India). The data on the health indicators for the Indian States was taken from the Health and Family Welfare Statistics in India 2015. The data on the per capita income level is captured by the Net State Domestic Product [NSDP per capita] (constant prices, 2004-05) as given in the Reserve Bank of India’s Handbook of Statistics on the Indian Economy.

To measure the performance of India globally, we have taken the education, health and per capita income data from the World Development Indicators (WDI), 2016 of the World Bank.

Section IV: Education

Education is a vital part of any developmental story. Most of the previous attempts to measure the progress the States have made in education has involved the education/literacy variable being a part of the Human Development Index (HDI), ranking the states in the literacy rates, enrolment rates or in some cases creation of an education development index (which includes a number of education and schooling specific variables). As a departure from the above the present paper will attempt to gauge how the States are faring in their respective enrolment rates and reducing gender disparities in education with respect to their relative income level to account for their respective State’s capacity to deliver.

In this paper we have created a rough estimate of the completion index (defined as the Gross Enrolment Ratio of a particular cohort minus the Dropout rate of that particular cohort) to give us an idea how States are faring in making the students to complete their education within a given cohort. We also report on the Gross Enrolment Ratio for those cohorts where dropout rates are not available. We also present the ranking of India globally on primary and secondary levels and the discrepancies observed in the figures given in the WDI and SSE.

We here also present the gender parity in enrolment as a measure to see how the States are faring in bridging the gender gap in education. The gender parity in enrolment is defined as the gross enrolment of girls over the gross enrolment of boys in a given cohort. A gender party in enrolment of 1 implies equal enrolment rates, above one implies greater participation of girls over boys; below one implies vice versa.The ranking of India globally and the ranking of the States are in the Tables 1 – 6 listed in Appendix I

In Table 1 we observe that in primary education the country is doing all right with a relatively high ranking and not being far off from South Asia in its enrolment ration. However the Country is not doing so well in Secondary Education with its performance index at 91 out of 141 countries.

Before we move on to the Indian States, there are some differences between the numbers given for India in WDI and the national figure given in the Statistics of School Education (SSE) of the HRD Ministry as seen in Table 2. These difference may be due to different classifications, different periods of counting etc.

Moving to the performance of the Indian States, first, in Table 3 we can notice that there does not appear to be a strong geographical location to the results; i.e. the states in a region are not clustered together. Second, we see that the States in the bottom rungs are performing badly with high dropout rates, particularly worrisome are Bihar, Assam and Nagaland. Given that we have taken into account the relative per capital income level of the State, these results highlight an area where the States performing poorly must focus the attention of public resources to stem the poor performance. In fact, regardless of how well a State is performing in this index, high dropout rates need to be stemmed as they can nullify any gains made from rising gross enrolment rates. We next turn to the gender parity in enrolment to see if all the States maintain a similar performance listed in Table 4.

We observe in Table 4 here that most States have managed to maintain relatively good gender parity in enrolment across the entire cohort. However we can also notice that there does not appear to be a similarity between the gender parity in enrolment and female literacy levels. States with high gender parity do not necessarily have high female literacy rates. This is due to the large group captured in the female literacy and also perhaps the conscious effort by state education departments to increase the gender parity in enrolment. This will be shown positively later on in future census records. Among the poor performing States, Rajasthan’s performance is the most worrying. States from Odisha onwards must focus on improving their gender parity levels in education. This highlights an area of focus for school education in the States.

Turning the Gross Enrolment Ratio for Classes XI-XII given in Table 5, we notice here that the States which were high up in the performance index in Table 3 do not appear high in the performance index in Table 5. The same can be said of the bottom rung. This may be attributed to the perceived benefits of education in the different States. States which score high in the performance index in Table 5probably face high returns to education beyond I-X and therefore there is interest interested in educating the students further (among the parents and students themselves), given the better economic rewards that they may get.

This perhaps shows the heterogeneous nature of the Indian education system wherein the respective local factors play an important role in determining the levels and returns to education. Another reasons maybe the commitment of the respective education departments to increase the schooling years of the students which may result in developing higher quality of human capital in the respective State. We now turn to gender parity in enrolment across the XI-XII cohort (Table 6).

We notice here that the results in Table 6 are not exactly aligned with the results on Gender Parity in Enrolment, Classes I-X (Table 4) and Gross Enrolment Ratio, Classes XI-XII (Table 5); i.e. the better performing states mostly do not repeat themselves. The reasons for this maybe similar to those offered for the results given for Gross Enrolment Ratio, Classes XI-XII, namely – economic factors, individual education department policies and cultural factors. The States must re-orient education policy to ensure that gender parity in enrolment rates is achieved across all levels of education to reap gains from the demographic dividend the nation is currently in.

In summary, we find that there does not appear to be any clustering of performance of the States according to the region; there also does not appear to be any consistency in the performance across cohorts and gender parity in cohorts. This holds important implications towards the efficacy of public policy in education across the Indian States. We now turn to the performance of the States in the health indictors.

Section V: Health

Health plays a crucial role in the long run development of human capital in the country. Poor life expectancies at birth, high levels of infant and maternal mortality rates all reflect negatively on the long run labour productivity in the country thereby forestalling the development of human capital. Performance on health indicators is therefore crucial as they affect the long term health and human capital formation in an economy.

We first start with some global comparisons of India on certain health indicators. The ranking of India globally and the ranking of the States are in the Tables 7 – 16as listed in Appendix I. Given the difference time periods for each of the indicators, they were regressed with NSDP per capita of different years. The same is elaborated below.

In Table 7 we give the ranking of India (in percentile) across the various health indicators (We omit the Maternal Mortality Ratio as the sample was too small to be considered, the same is given in Appendix V). As we can observe the country performs within its income range in more or less all the health indicators. This is perhaps the result on the back of robust economic growth the country has had for 2 decades plus.

In Tables 8 and 9 we report the expectation of life at birth and infant mortality rate for the total population for the respective States. The indicator expectation of life at birth covers the years 2009-13, the same was regressed with the NSDP per capita income of the States for the year 2009-10. The Infant mortality rate is reported for the year 2013 and the same was regressed with the NSDP per capita income for the year 2012-13.

With regard to the results of the expectation of life at birth we find some interesting and surprising results. States normally regarded as developed compared to their peers – Gujarat and Haryana are among the poorer performing States in our index with the performance of Assam particularly worrisome. Contrast the same to the performance of Bihar which is regard as one of the less developed States doing comparatively better in this matter along with West Bengal, Jammu and Kashmir and Kerala. The performance of the States in the middle - point towards room for improvement but lesser than the poorer performing States who have a lot to catch up given their respective income level.

Turning our attention next to the Infant Mortality rate (per 1,000 live births), along with Gujarat and Haryana, Delhi is another surprise inclusion to the poor performing States. What we are noticing combined with the results in Table 8 is that higher average per capita income levels do not necessarily translate into better health outcomes, to put it another way – the populace on average does not necessarily become better off in health outcomes with rising income levels on an average. Contrast the performance of Haryana with Punjab its neighbour and roughly similar geographical terrain, economic performance and resource endowments and we can rule out any geographical influence in the results. What appears here is that in terms of maintaining a lower infant mortality ratio with respect to its relative income level, many States (including the relatively developed ones) are faring poorly. In terms of public health policy, it would suggest a revaluation and realignment of health goal and outcomes.

We next turn to the gender parity in life expectancy at birth and infant mortality rate (Tables 10 and 11). A gender parity of more than one in life expectancy at birth indicates a high life expectancy of women. Gender parity above 1 for infant mortality rate indicates a high infant mortality of female children over male children.

With regard to gender parity in life expectancy we observe that well developed States such as Tamil Nadu and Maharashtra are performing poorly along with States such as Bihar and West Bengal whereas joining Kerala and a few other better performing States, Assam (a relatively under developed State) is a surprise inclusion. Most of the other States are performing relatively ok highlighting additional room for improvement.

With reference to the gender parity in infant mortality rate, most States are not performing too badly, except perhaps Kerala where it appears to be quite high. While States should focus on reducing any disparity in healthcare treatment for infants, the relatively small disparity among most of the States is an encouraging sign.

We next turn to the Total Fertility Rate [TFR] and Maternal Mortality Ratio [MMR] (per 1,00,000 live births) for the States (given in Tables 12 and 13). The latest TFR is for the year 2013 and its corresponding per capita NSDP was taken for the year 2012-13. The latest MMR was given for the time period 2011-13 and its corresponding NSDP per capita was taken for the year 2011-12.

TFR refers to the number of children per woman (on an average) within a given area. A lower TFR is a good thing as it ensures more resources are devoted per child leading to better health and social outcomes.

Focussing on the TFR, we again observe Gujarat, Haryana and Delhi regard as relatively prosperous States as performing poorly in reducing the TFR with respect to their income level. Bihar which was among the better performing States in table 1 is among the poorer performing States in TFR. Among the better performing States we find Himachal Pradesh during well, given its income level.

With regard to the MMR, the four States – Gujarat, Haryana, Assam and Rajasthan have performed poorly. This coupled with their poor performance in the other indicators shows some significant areas of improvement in their health policy. But before conclusions are drawn, it must be stated that given the smaller pool of States under MMR to drawn upon the results may be skewed and not presenting a complete picture. None the less some key inferences with respect to the Standing of the States in reducing the gender bias in health outcomes can be drawn upon. Also West Bengal is the only State to have performed highly in both TFR and MMR

It is not only important that the gender bias in health outcomes be reduced. It is vital that the rural-urban gap be minimised to the maximum extent possible for equitable health outcomes across the States. It is to this we turn to next.

With regard to Expectation of Life at birth a Rural-Urban ratio (Table 14) above 1 indicates a bias in favour of the rural areas, below 1 indicates otherwise. For Total Fertility Rate a rural-urban ratio (Table 15) of above 1 indicates a higher TFR in rural areas (compared to urban areas) and below 1 indicates otherwise.

With respect to the Expectation of Life at Birth , while there does exist a bias, it does not appear to be quite high except in the case of Assam, Madhya Pradesh and to a certain extent Andhra Pradesh. Turning to the rural-urban ratio in TFR, Kerala and Tamil Nadu continue to be among the better performing States, whereas Assam along with Delhi are consistently seen in many of the tables among the poor performers. This highlights important areas of focus for both Assam and Delhi in their health policy objectives (particularly with regard to the female populace and reducing the rural-urban gap).

We also give in Table 16 the rural-urban ratio in Infant mortality ratio (as with TFR an IMR of more than 1 indicates a higher infant mortality rate in rural areas). The picture here is noticeably different from the previous tables as the data was available for all the States and Union territories. The Union territories and smaller States occupy both the top and bottom end of the table. Many of the Indian States occupy the middle rung of the table.

Section VI: Conclusion

This paper is an attempt to rank the Indian States in certain education and health indicators (covering both the gender parity and rural-urban gap). While for many of the indicators (particularly Health), all of the States were not covered, thereby not giving us a complete picture, it nonetheless gives us an idea of where the States stand.

While previously most States were ranked solely in accord with their performance on the education and health outcomes, the method proposed here by ranking the States via a performance index (based on their relative income levels) can lead to different results (as a measure of comparison we report the correlation between the health outcome indicator and the performance index below each table), highlighting areas of focus with the education and health policy mandate for each State.

For education we find that due to the heterogeneous nature of the Indian states there may be a variety of exogenous reasons for the performance among the Individual States. Pertaining to the education infrastructure, reasons may include – poor quality of teachers, parents not invested enough to educate their child, poor schooling infrastructure etc.

While education is a concurrent subject, school education is primarily driven by the States. Low completion ratesand performance index precludes negative impact on the education of school going age children and thus act as a barrier towards the development of human capital over the long run. Even the flagship programs of India such as Make in India, Digital India etc., cannot be a success in the long run without an adequate pool of skilled and trained manpower to draw upon.

Despite the shortcomings and constraints faced by the States, a cohesive and integrated approach must be adopted towards increasing the completion index in primary and secondary education across all States.

Turning to health, across each of the respective health indicator including the gender gap and the rural-urban gap, we observe that while a few States tend to repeat themselves within a particular rank range, many of the other States shift in their rankings. This is an important point to bear in mind as it shows the divergence of policy outcomes across the different health indictors in each of the respective States. It is highlights the areas of importance for the States in fulfilling its health policy objectives. This is a pertinent point to note as given the complex nature of health in our country, by identifying where States are performing well/ok/bad can help in realigning public health policy accordingly. With reference to some of the poorer States repeating themselves, it was observed that in terms ofNSDP per capita levels they were relatively prosperous, but thishigher income level has not translated itself into better health outcomes.

While due to certain infrastructure constraints the rural areas may not be as well serviced as the urban areas, care must be taken through public health policy and infrastructure development that the gap be reduce to the maximum level possible to prevent lopsided human capital development.

In short, this new index shows that despite progress being made over time, the varied performance of the States and the gender gap and rural-urban divide within the States showcases the myriad of challenges that the education and health sector faces in our country.

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(The author acknowledges inputs received from Dr. Charan Singh and research assistance from Vishnu Das Gupta. The author also acknowledges funding from The Policy Foundation (New Delhi) towards the stipend of Vishnu Das Gupta.)

References

Corrie, B.P. Soc Indic Res (1995) 34: 395. doi:10.1007/BF01078695

Educational Development Index (2008). National University of Education Planning and Administration (NEUPA)and Ministry of Human Resource and Development

Health and Family Welfare Statistics in India 2015, Ministry of Health and Family Welfare, Government of India

Indrayan, A., Wysocki, M., Chawla, A. et al. Social Indicators Research (1999) 46: 91. doi:10.1023/A:1006875829698

Kumar, A. K. Shiva (1991) “UNDP’s Human Development Index: A Computation for Indian States” Economic and Political Weekly, Vol. 26, No. 41, (Oct 12, 1991), pp. 2343 – 2345

Kurian, N. J. (2000), “Widening Regional Disparities in India: Some Indicators”, Economic and Political Weekly, Vol. 35, No. 7, (Feb 12-18, 2000), pp. 538-550

Nagaraj, Rayaprolu, Varoudakis, Aristomeneand Veganzones, Marie-Anges (1998) “Long Run Growth Trends and Convergence among Indian States” Organization of Economic Cooperation and Development (OECD) January 1998, CD/Doc (98)1

Prabhu, K. Seeta, Sarker, P. C. and Radha, A. (1996) “Gender-Related Development Index for Indian States: Methodological Issues” Economic and Political Weekly, Vol. 31, No. 43, (Oct 26, 1996), pp. WS72 – WS79

Reserve Bank of India: Handbook of Statistics on the Indian Economy

Statistics for School Education 2011-12, Human Resource Development Ministry, India

World Development Indicators 2016, World Bank

Appendix I: Tables of India and Indian States on Education and Health Indicators

Table 1: India’s ranking in Primary and Secondary Education Enrolment, 2011

Country/Region

Gross Enrolment Rate

Percentile

Gross Enrolment Ratio, Primary Education, 2011

India

108.37

72.33 (out of 159 Countries)

Performance Index, Secondary Education, 2011

Country

Gross Enrolment Rate

Performance Index (Percentile)

India

66.42

-5.0 (36.17 out of 141 countries)

Source: World Development Indicators, 2016, the World Bank

Table 2: Differences between WDI and SSE (various years)

Education Level

WDI, 2008

SSE, 2008-09

WDI 2009

SSE 2009-10

WDI 2010

SSE 2010-11

WDI 2011

SSE 2011-12

Primary Education

110.86

92.9

109.57

93.6

109.18

96.2

108.37

91.3

Secondary Education

60.56

34.5

59.79

36.1

63.29

39.3

66.42

45.9

Source: World Development Indicators, 2016, the World Bank and Statistics for School Education 2011-12, Human Resource Development Ministry

Table 3: Completion Index, Total, 2011-12

S.no

State

Completion Index

Performance Index

GER, I-X

Dropout I-X

1

HimachalPradesh

97.03

90.0

104.2

7.1

2

Chhattisgarh

67.24

81.0

97.0

29.8

3

MadhyaPradesh

62.79

81.0

105.1

42.3

4

UttarPradesh

44.51

42.0

91.7

47.2

5

Mizoram

60.54

38.0

105.1

44.5

6

Andaman and Nicobar Islands

84.22

34.0

103.6

19.4

7

Tripura

56.63

26.0

106.3

49.6

8

Karnataka

56.21

22.0

93.5

37.3

9

TamilNadu

65.83

18.0

104.0

38.1

10

Haryana

60.96

3.0

82.3

21.3

11

ArunachalPradesh

42.05

-1.0

103.5

61.4

12

Uttarakhand

51.86

-2.0

88.1

36.2

13

Manipur

32.79

-4.0

103.9

71.1

14

Maharashtra

56.16

-4.0

93.4

37.3

15

Jammu and Kashmir

36.42

-5.0

80.6

44.2

16

Goa

93.77

-8.0

110.4

16.6

17

WestBengal

35.24

-13.0

95.8

60.6

18

Sikkim

49.38

-26.0

106.7

57.4

19

Odisha

25.10

-29.0

87.0

61.9

20

Rajasthan

27.02

-30.0

88.8

61.7

21

Meghalaya

28.39

-32.0

102.9

74.5

22

Gujarat

36.38

-35.0

90.5

54.1

23

Jharkhand

21.51

-40.0

92.3

70.7

24

Nagaland

19.58

-60.0

73.2

53.6

25

Bihar

10.06

-65.0

81.4

71.3

26

Assam

-0.36

-101.0

72.1

72.5

Standard Deviation

24.16

45.0

10.78

18.79

Correlation with GER I-X

0.67

0.59

-

-

India

41.0

-0.20

91.3

50.3

Note: States not included due to lack of data – Chandigarh, Delhi, Kerala, Puducherry and Punjab. Andhra Pradesh was also excluded as the Handbook of Statistics gave the NSDP numbers for both Andhra Pradesh and Telengana while the SSE gave the number for undivided Andhra Pradesh.

Source: Statistics for School Education 2011-12, Human Resource Development Ministry, India and Handbook of Statistics on the Indian Economy 2016, Reserve Bank of India

Table 4: Gender Parity in Enrolment (I-X) and Female Literacy Rates

S.no

State

Gender Parity in Enrolment

Gross Enrolment Rate, Boys

Gross Enrolment Rate, Girls

Female Literacy Rate (7 yrs , per cent )

1

Haryana

1.09

79.0

86.2

66.77

2

Meghalaya

1.08

99.1

106.9

73.78

3

Sikkim

1.07

103.0

110.5

76.43

4

WestBengal

1.07

92.6

99.2

71.16

5

Assam

1.06

69.9

74.4

67.27

6

Manipur

1.04

102.0

106.0

73.17

7

Chandigarh

1.02

103.4

105.0

81.38

8

Delhi

1.02

108.4

110.7

80.93

9

Jharkhand

1.02

91.5

93.1

56.21

10

Nagaland

1.02

72.6

73.9

76.69

11

TamilNadu

1.02

103.0

105.0

73.86

12

Uttarakhand

1.02

87.4

88.9

70.70

13

Tripura

1.01

105.9

106.6

83.15

14

HimachalPradesh

1.00

104.1

104.2

76.60

15

Jammu and Kashmir

1.00

80.5

80.7

58.01

16

MadhyaPradesh

1.00

105.3

104.8

60.02

17

Punjab

1.00

96.1

96.0

71.34

18

Karnataka

0.99

94.0

92.9

68.13

19

Kerala

0.99

93.1

92.2

91.98

20

Puducherry

0.99

110.7

109.4

81.22

21

Andaman and Nicobar Islands

0.98

104.5

102.8

81.84

22

Bihar

0.98

82.3

80.3

53.33

23

Maharashtra

0.98

94.2

92.5

75.48

24

UttarPradesh

0.98

92.8

90.5

59.26

25

Odisha

0.97

88.4

85.7

64.36

26

Chhattisgarh

0.96

98.9

95.1

60.59

27

Goa

0.96

112.5

108.0

81.84

28

Gujarat

0.96

92.2

88.4

70.73

29

Mizoram

0.96

107.2

102.9

89.40

30

ArunachalPradesh

0.95

105.9

101.0

59.57

31

Rajasthan

0.93

91.7

85.5

52.66

Standard Deviation

0.04

10.90

10.72

10.36

India

0.99

91.6

91.0

65.46

Note: States not included due to lack of data – Chandigarh, Delhi, Kerala, Puducherry and Punjab. Andhra Pradesh was also excluded as the Handbook of Statistics gave the NSDP numbers for both Andhra Pradesh and Telengana while the SSE gave the number for undivided Andhra Pradesh.

Source: Statistics for School Education 2011-12, Human Resource Development Ministry, India and Handbook of Statistics on the Indian Economy 2016, Reserve Bank of India

Table 5: GER, Classes XI-XIIth, 2011-12

S.no

State

Gross Enrolment Ratio

Performance Index

1

HimachalPradesh

81.98

64.0

2

Kerala

78.27

51.0

3

MadhyaPradesh

54.22

45.0

4

Andaman and Nicobar Islands

83.51

40.0

5

Chandigarh

83.18

27.0

6

UttarPradesh

43.55

25.0

7

Uttarakhand

62.28

20.0

8

Rajasthan

47.83

18.0

9

Haryana

65.80

17.0

10

Puducherry

73.91

13.0

11

Jammu and Kashmir

45.03

13.0

12

Manipur

40.59

10.0

13

Bihar

35.33

9.0

14

ArunachalPradesh

46.81

8.0

15

Punjab

50.88

5.0

16

Mizoram

46.10

4.0

17

WestBengal

42.97

3.0

18

Maharashtra

57.21

2.0

19

Delhi

76.96

-2.0

20

Karnataka

45.34

-2.0

21

Chhattisgarh

37.05

-6.0

22

TamilNadu

49.87

-8.0

23

Goa

70.73

-21.0

24

Odisha

28.74

-24.0

25

Tripura

33.51

-26.0

26

Gujarat

37.20

-31.0

27

Sikkim

37.96

-39.0

28

Nagaland

27.54

-43.0

29

Jharkhand

15.80

-59.0

30

Assam

13.11

-64.0

31

Meghalaya

15.07

-65.0

Standard Deviation

20.13

32.0

Corr between indicator and PI

0.78

-

India

45.9

-0.16

Note: States not included due to lack of data – Chandigarh, Delhi, Kerala, Puducherry and Punjab. Andhra Pradesh was also excluded as the Handbook of Statistics gave the NSDP numbers for both Andhra Pradesh and Telengana while the SSE gave the number for undivided Andhra Pradesh.

Source: Statistics for School Education 2011-12, Human Resource Development Ministry, India and Handbook of Statistics on the Indian Economy 2016, Reserve Bank of India

Table 6: Gender Parity in Enrolment, Classes XI-XIIth, 2011-12

S.no

State

Gender Parity in Enrolment

Performance Index

Gross Enrolment Rate, Boys

Gross Enrolment Rate, Girls

1

Meghalaya

1.33

38.84

13.0

17.2

2

TamilNadu

1.28

25.88

44.0

56.2

3

Assam

1.25

18.83

65.8

82.5

4

Kerala

1.2

17.32

34.5

41.5

5

Puducherry

1.18

16.04

72.0

84.7

6

Sikkim

1.1

13.24

12.5

13.8

7

Karnataka

1.09

11.61

43.4

47.5

8

Punjab

1.07

8.18

49.4

52.7

9

Mizoram

1.07

6.47

74.7

79.7

10

Jharkhand

1.06

5.90

68.8

72.9

11

WestBengal

1.04

3.93

81.7

85.1

12

HimachalPradesh

1.03

2.36

45.5

46.7

13

Jammu and Kashmir

1.03

0.65

64.9

66.9

14

Haryana

1.03

0.12

82.5

84.7

15

Bihar

1.02

-0.40

81.3

82.8

16

Uttarakhand

1

-0.52

62.3

62.3

17

Andaman and Nicobar Islands

0.99

-1.52

15.9

15.7

18

Manipur

0.99

-1.82

43.2

42.7

19

Nagaland

0.96

-2.94

28.1

27.0

20

Chandigarh

0.95

-3.52

46.3

43.7

21

ArunachalPradesh

0.92

-5.33

59.3

54.8

22

Delhi

0.91

-6.52

42.4

38.7

23

Chhattisgarh

0.91

-7.42

48.9

44.7

24

UttarPradesh

0.9

-8.31

36.9

33.3

25

Maharashtra

0.87

-10.47

39.5

34.5

26

Goa

0.84

-11.90

47.1

39.6

27

Tripura

0.82

-16.65

40.5

33.4

28

MadhyaPradesh

0.81

-18.25

37.0

29.8

29

Gujarat

0.76

-19.26

60.9

46.5

30

Rajasthan

0.69

-27.06

55.7

38.7

31

Odisha

0.67

-28.18

34.4

23.0

Standard Deviation

0.16

14.77

19.16

21.81

Corr between Indicator and PI

0.91

-

-

-

India

0.92

-

47.6

43.9

Note: States not included due to lack of data – Chandigarh, Delhi, Kerala, Puducherry and Punjab. Andhra Pradesh was also excluded as the Handbook of Statistics gave the NSDP numbers for both Andhra Pradesh and Telengana while the SSE gave the number for undivided Andhra Pradesh.

Source: Statistics for School Education 2011-12, Human Resource Development Ministry, India and Handbook of Statistics on the Indian Economy 2016, Reserve Bank of India

Table 7: Ranking of India, Globally (various years)

Year

Indicator

Performance Index

Percentile

2014

Life Expectancy at Birth, Total

0.04

38.76 (out of 178 countries)

2014

LifeExpectancyatBirth for Females

-1.20

34.27 (out of 178 Countries)

2014

Fertilityrate, total (births per woman)

24.95

61.8 (out of 178 countries)

2014

Infant Mortality Rate (per 1000 live births)

-20.96

25.56 (out of 180 countries)

2014

GDPpercapita,PPP(constant 2011 international $)

-

25.56

(out of 180 countries)

Source: World Development Indicators, 2016, World Bank.

Table 8: Life Expectation at Birth (Total), 2009-13

S.no

State

Life Expectation at Birth (years)

Performance Index

1

Jammu and Kashmir

72.00

6.42

2

Kerala

74.80

6.19

3

Bihar

67.70

3.31

4

WestBengal

69.90

2.65

5

Punjab

71.10

1.81

6

HimachalPradesh

71.00

1.54

7

Odisha

67.80

0.95

8

Rajasthan

67.50

0.21

9

Maharashtra

71.30

-0.09

10

TamilNadu

70.20

-0.35

11

Karnataka

68.50

-0.86

12

Gujarat

68.20

-3.51

13

UttarPradesh

63.80

-3.77

14

Haryana

68.20

-4.57

15

MadhyaPradesh

63.80

-4.65

16

Assam

63.30

-5.29

Std. Dev.

3.17

3.67

Corr between Indicator and PI

0.80

-

India

67.50

Source: Health and Family Welfare Statistics in India 2015, Ministry of Health and Family Welfare, Government of India

Table 9: Infant Mortality Rate (Total) (per 1,000 live births), 2013

S.no

State

Infant Mortality Rate

Performance Index

1

Kerala

12.00

63.23

2

Tamil Nadu

21.00

33.74

3

Punjab

26.00

26.41

4

West Bengal

31.00

22.62

5

Maharashtra

24.00

18.26

6

Karnataka

31.00

16.03

7

Jammu and Kashmir

37.00

10.84

8

Bihar

42.00

10.50

9

Himachal Pradesh

35.00

-2.98

10

Chhattisgarh

46.00

-9.08

11

Uttar Pradesh

50.00

-10.02

12

Rajasthan

47.00

-14.02

13

Gujarat

36.00

-14.59

14

Odisha

51.00

-18.10

15

Assam

54.00

-22.21

16

Madhya Pradesh

54.00

-24.75

17

Haryana

41.00

-37.95

18

Delhi

24.00

-85.07

Std. Dev.

12.32

32.36

Corr between Indicator and PI

-0.48

-

India

40.0

Source: Health and Family Welfare Statistics in India 2015, Ministry of Health and Family Welfare, Government of India

Table 10: Gender Parity in - Life Expectation at Birth, 2009-13

S.no

State

Gender Parity in Life Expectation at Birth

Performance Index

1

Rajasthan

1.07

2.29

2

Kerala

1.08

1.51

3

Assam

1.05

0.85

4

MadhyaPradesh

1.05

0.77

5

Karnataka

1.07

0.76

6

UttarPradesh

1.04

0.39

7

Haryana

1.08

0.28

8

Jammu and Kashmir

1.05

-0.02

9

Gujarat

1.07

-0.09

10

Punjab

1.06

-0.10

11

HimachalPradesh

1.06

-0.42

12

WestBengal

1.05

-0.59

13

TamilNadu

1.06

-0.69

14

Odisha

1.03

-1.16

15

Maharashtra

1.06

-1.50

16

Bihar

1.01

-2.27

Std. Dev.

0.02

1.14

Corr between Indicator and PI

0.63

India

1.05

Source: Health and Family Welfare Statistics in India 2015, Ministry of Health and Family Welfare, Government of India

Table 11: Gender Parity in - Infant Mortality Rate, 2013

S.no

State

Gender Parity in Infant Mortality Rate

1

Andhra Pradesh

1.03

2

Assam

1.04

3

Odisha

1.04

4

Chhattisgarh

1.04

5

Haryana

1.05

6

Tamil Nadu

1.05

7

Madhya Pradesh

1.06

8

Uttar Pradesh

1.06

9

Jammu and Kashmir

1.06

10

Gujarat

1.06

11

Karnataka

1.07

12

West Bengal

1.07

13

Punjab

1.08

14

Bihar

1.08

15

Rajasthan

1.09

16

Himachal Pradesh

1.09

17

Maharashtra

1.09

18

Delhi

1.09

19

Kerala

1.30

Std. Dev.

0.06

India

1.08

Source: Health and Family Welfare Statistics in India 2015, Ministry of Health and Family Welfare, Government of India

Table 12: Total Fertility Rate, 2013

S.no

State

TotalFertilityRate

Performance Index

1

WestBengal

1.60

31.79

2

JammuandKashmir

1.90

21.02

3

Punjab

1.70

20.85

4

HimachalPradesh

1.70

18.73

5

Odisha

2.10

15.19

6

TamilNadu

1.70

14.82

7

Karnataka

1.90

14.19

8

Kerala

1.80

11.55

9

Assam

2.30

8.65

10

Maharashtra

1.80

5.18

11

Chhattisgarh

2.60

-6.83

12

Jharkhand

2.70

-10.23

13

Haryana

2.20

-14.97

14

Gujarat

2.30

-15.91

15

MadhyaPradesh

2.90

-16.92

16

Rajasthan

2.80

-16.96

17

UttarPradesh

3.10

-20.60

18

Bihar

3.40

-29.16

19

Delhi

1.70

-40.11

Std. Dev.

0.55

20.01

Corr between Indicator and PI

-0.65

India

2.30

Source: Health and Family Welfare Statistics in India 2015, Ministry of Health and Family Welfare, Government of India

Table 13: Maternal Mortality Ration (per 1,00,000 live births), 2011-13

Table 13: Maternal Mortality Ration (per 1,00,000 live births), 2011-13

S.no

State

Maternal Mortality Ratio

Performance Index

1

Kerala

61.00

43.68

2

West Bengal

113.00

42.54

3

Karnataka

133.00

15.14

4

Tamil Nadu

79.00

12.19

5

Maharashtra

68.00

5.65

6

Odisha

222.00

3.17

7

Punjab

141.00

-3.64

8

Rajasthan

244.00

-17.55

9

Gujarat

112.00

-21.82

10

Assam

300.00

-24.35

11

Haryana

127.00

-80.94

Std. Dev.

77.26

34.67

Corr between Indicator and PI

-0.36

India

167.0

Source: Health and Family Welfare Statistics in India 2015, Ministry of Health and Family Welfare, Government of India

Table 14: Rural Urban Ratio in Life Expectancy at Birth, 2009-13

S.no

State

Life Expectancy by Birth

1

Kerala

1.00

2

Bihar

0.96

3

Maharashtra

0.96

4

Rajasthan

0.96

5

TamilNadu

0.96

6

WestBengal

0.96

7

Haryana

0.95

8

Punjab

0.95

9

Gujarat

0.94

10

Jammu and Kashmir

0.94

11

HimachalPradesh

0.93

12

Karnataka

0.93

13

Odisha

0.93

14

UttarPradesh

0.93

15

AndhraPradesh

0.92

16

MadhyaPradesh

0.91

17

Assam

0.89

Std. Dev.

0.02

India

0.93

Source: Health and Family Welfare Statistics in India 2015, Ministry of Health and Family Welfare, Government of India

Table 15: Rural Urban Ratio in Total Fertility Rate, 2013

S.no

State

Total Fertility Rate

Performance Index

1

Tamil Nadu

1.00

18.54

2

Punjab

1.06

17.63

3

Kerala

1.06

15.13

4

Uttar Pradesh

1.32

9.79

5

Rajasthan

1.30

6.22

6

Bihar

1.40

5.96

7

Karnataka

1.25

5.10

8

Haryana

1.15

3.67

9

Maharashtra

1.19

0.01

10

Gujarat

1.25

-2.22

11

Odisha

1.47

-2.95

12

Madhya Pradesh

1.55

-8.67

13

West Bengal

1.50

-9.40

14

Jammu and Kashmir

1.54

-10.23

15

Chhattisgarh

1.56

-10.54

16

Assam

1.60

-10.98

17

Himachal Pradesh

1.42

-11.82

18

Delhi

1.06

-16.78

Std. Dev.

0.20

10.92

Corr between Indicator and PI

-0.64

India

1.39

Source: Health and Family Welfare Statistics in India 2015, Ministry of Health and Family Welfare, Government of India

Table 16: Rural-Urban Ratio in Infant Mortality Ratio, 2013

S.no

State

Infant Mortality Ratio

1

Daman and Diu

0.65

2

Lakshadweep

0.71

3

Goa

0.80

4

Chandigarh

0.86

5

Nagaland

0.95

6

Manipur

1.00

7

Meghalaya

1.20

8

Punjab

1.22

9

WestBengal

1.23

10

Chhattisgarh

1.24

11

Bihar

1.27

12

Puducherry

1.33

13

Haryana

1.38

14

UttarPradesh

1.39

15

Odisha

1.39

16

Jammu and Kashmir

1.39

17

TamilNadu

1.41

18

Jharkhand

1.41

19

Karnataka

1.42

20

Tripura

1.42

21

Kerala

1.44

22

HimachalPradesh

1.52

23

AndhraPradesh

1.52

24

Sikkim

1.53

25

MadhyaPradesh

1.54

26

D and NHaveli

1.55

27

Uttarakhand

1.55

28

Delhi

1.59

29

Rajasthan

1.70

30

Assam

1.75

31

Maharashtra

1.81

32

Gujarat

1.95

33

Andaman and NicobarIslands

2.23

34

Mizoram

2.32

35

ArunachalPradesh

2.57

Std. Dev.

0.42

India

1.63

Source: Health and Family Welfare Statistics in India 2015, Ministry of Health and Family Welfare, Government of India

Appendix III: Regression Results

Education and Health Indicators (Dependent Variable)

GDP Per Capita PPP (International $), 2011

GDP per capita, PPP(Constant, 2011 International $), 2012

GDP per capita, PPP(Constant, 2011 International $), 2014

NSDP Per Capita (Constant, 2004-05) 2009-10

NSDP Per Capita (Constant, 2004-05) 2011-12

NSDP per capita income (Constant, 2004-05) 2012-13

Primary Education (Global), 2011

-0.000072

-

-

-

-

-

Secondary Education (Global), 2011

0.000707***

-

-

-

-

-

Life Expectancy at Birth (Global), Total, 2014

-

-

0.0002389***

-

-

-

Life Expectancy at Birth for Females (Global), 2014

-

-

0.0002421***

-

-

-

Fertilityrate, total (births per woman), (Global), 2014

-

-

-0.000033***

-

-

-

Infant Mortality Rate (per 1000 live births), (Global) 2014

-

-

-0.0006537***

-

-

-

Maternal Mortality (national estimate, per 100,000 live births), 2012

-

-0.0117328**

-

-

-

-

Completion Index, Total, 2011-12

-

-

-

-

0.0006286***

-

Gender Parity in Enrolment (I-X), 2011-12

-

-

-

-

0.0000000167

-

GER, Classes XI-XIIth, 2011-12

-

-

-

-

0.0004918***

-

Gender Parity in Enrolment, Classes XI-XIIth, 2011-12

-

-

-

-

0.00000258**

-

Life Expectation at Birth (Total), 2009-13

-

-

-

0.0001337**

-

-

Infant Mortality Rate (Total) (per 1,000 live births), 2013

-

-

-

-

-

-0.0003462**

Gender Parity in - Life Expectation at Birth, 2009-13

-

-

-

0.000000913***

-

-

Gender Parity in - Infant Mortality Rate, 2013

-

-

-

-

-

0.000000575

Total Fertility Rate, 2013

-

-

-

-

-

-0.0000145**

Maternal Mortality Ratio (per 1,00,000 live births), 2011-13

-

-

-

-

-0.0042793**

-

Rural Urban Ratio in Life Expectancy at Birth, 2009-13

-

-

-

0.000000641

-

-

Rural Urban Ratio in Total Fertility Rate, 2013

-

-

-

-

-

-0.00000593***

Rural-Urban Ratio in Infant Mortality Ratio, 2013

-

-

-

-

-

-0.00000189

***significant at 0.01 %

** significant at 0.05%

* significant at 0.10%

Appendix IV: Data Availability for Health Indicators across Indian States (Various Years)

State

Life Expectancy at Birth (Total and Females)

Total Fertility Rate (TFR)

Maternal Mortality Rate (MMR)

Infant Mortality Rate (Total and Females)

Infant Mortality Rate (Rural and Urban Areas)

Andaman and Nicobar Islands

x

x

x

x

Andhra Pradesh (pre division)

Arunachal Pradesh

x

x

x

x

Assam

Bihar

Bihar/Jharkhand

x

x

x

x

Chandigarh

x

x

x

x

Chhattisgarh

x

Dadarand Haveli

x

x

x

x

Daman and Diu

x

x

x

x

Delhi

x

x

Goa

x

x

x

x

Gujarat

Haryana

Himachal Pradesh

x

Jammu and Kashmir

x

Jharkhand

x

x

x

Karnataka

Kerala

Lakshadweep

x

x

x

x

Madhya Pradesh

Madhya Pradesh/Chhattisgarh

x

x

x

Maharashtra

Manipur

x

x

x

x

Meghalaya

x

x

x

x

Mizoram

x

x

x

x

Nagaland

x

x

x

x

Odisha

Others

x

x

x

Puducherry

x

x

x

x

Punjab

Rajasthan

Sikkim

x

x

x

x

Tamil Nadu

Tripura

x

x

x

x

Uttarakhand

x

x

x

x

Uttar Pradesh

x

Uttar Pradesh/Uttarakhand

x

x

x

x

West Bengal

Source: Health and Family Welfare Statistics in India 2015, Ministry of Health and Family Welfare, Government of India

Appendix V: Ranking of India in Maternal Mortality Ratio

Year

Indicator

Performance Index

Percentile

2012

Maternal Mortality(national estimate, per 100,000 live births)

-9.48

18.52 (out of 54 countries)

Source: World Development Indicators, 2016, The World Bank