Project Report Anirvan

8/6/2019 Project Report Anirvan

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Performance and Efficiency-based Grants in

Education and Health: An Analytical Framework

Project Report

Anirvan Chowdhury7/17/2009

Intern

Thirteenth Finance Commission


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Performance and Efficiency-based Grants in Education and Health: An Analytical Framework 2

Acknowledgement

I would like to thank Dr. Rathin Roy, Economic Advisor to the Thirteenth FinanceCommission for his valuable guidance throughout the project. I am also grateful to

Mr. V. Bhaskar, Joint Secretary, for giving me the opportunity to work on

education and health and for his constructive comments at various stages. I would

also like to thank Mr. Shivdev Singh and Mr. Avik Sankar Maitra for time spent in

discussion and review.

Anirvan Chowdhury


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Abstract

The Twelfth Finance Commission introduced specific transfers in the fields of health and

education as a component of grants-in-aid to states lagging behind others in terms of

adjusted average per capita expenditure in these sectors. This paper examines the

possibility of linking these grants-in-aid with efficiency and performance of states, as

measured by various indicators, in ensuring better outcomes. The efficiency exercise is

conducted using the method of data envelopment analysis, while performance has been

evaluated through construction of composite indices comprising of relevant indicators in

health and education respectively. It is concluded that linking of grants to efficiency

would not be possible, due to both model and data inadequacies and the politicaleconomy repercussions of such a move. The connection of grants to performance,

however, is much more plausible and a suggestive model for this purpose has been

constructed. The scope of this paper is limited in the sense that it does not identify the

states eligible for the grant; it only outlines a model that may be used to accomplish the

above objective.


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Contents

1. Introduction ........................................................................................ 5

2. Grants in aid for education and health Approach of the Twelfth Finance Commission 6

3. Evaluation of performance ...................................................................... 8

4. Evaluation of efficiency ......................................................................... 12

5. Linkage of performance to grants-in-aid ..................................................... 18

6. Summary and Conclusion........................................................................ 20

7. Appendix .......................................................................................... 21

8. Bibliography ....................................................................................... 27

List of Figures and Tables

Figure 1 Comparison of different approaches to measuring efficiency using Data

Envelopment Analysis ................................................................................. 13

Figure 2 Comparison of efficiency and health outcomes for general category states ..... 17

Table 1- Composite index for Elementary (Primary and Upper Primary) Education based on

Gross Enrolment Ratio and Teacher-Student Ratio (2001-02 to 2005-06) ..................... 10

Table 2 Composite index for health based on IMR (2002-07) .................................. 11

Table 3 Efficiency scores for education for general category states ......................... 15

Table 4 Efficiency scores for health for general category states ............................. 16

Table 5 Allocation of incentive money to selected states based on performance in

education ............................................................................................... 19

Table 6 - Allocation of incentive money to selected states based on performance in health

........................................................................................................... 19

Table 7 Gross Enrolment Ratio (2001-02 to 2005-06) for General Category states ........ 21

Table 8 - Gross Enrolment Ratio (2001-02 to 2005-06) for Special Category states ......... 22

Table 9 - Student Teacher Ratio (2001-02 to 2005-06) for General Category states ...... 23

Table 10 Student Teacher Ratio (2001-02 to 2005-06) for Special Category states ...... 24

Table 11 Female Literacy Rate .................................................................... 25

Table 12 Infant Mortality Rate (2002-07) and Maternal Mortality Rate ...................... 26


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1. Introduction

The word federal comes from the wordfoedus meaning league or covenant. Hence, the

term federalism is used to describe a system of government in which sovereignty is

constitutionally divided between a central governing authority and constituent political

units. A federation may be formed when states surrender some powers to the federal

government (as in the case of the United States of America); alternatively, the centre

could establish a multi-tier system and delegate powers to sub-central units for efficient

discharge of assigned functions, for instance, India.

The Indian federal system can be said to be quasi-federal in nature and is characterised by

a tremendous mismatch of revenue generating capacities and expenditure responsibilities

between the centre and the states. The states are thus heavily dependent on the centre

for financing their expenditure. The Constitution of India has entrusted the Finance

Commission to make recommendations on the distribution of net proceeds of taxes

between the union and the states and its allocation between the states in order to move

towards the goals of vertical and horizontal equity. The Finance Commission employs

devolution and transfer mechanisms for achieving its purpose, one such tool being grants-

in-aid, which are given for equalization of post-devolution non-plan revenue deficit,

maintenance of roads and bridges, upkeep of buildings, heritage conservation, forest

maintenance, local bodies, calamity relief, for bridging the inter-state gap in service

delivery in the fields of health and education etc. The last component in the series was

introduced as a state-specific grant by the Twelfth Finance Commission, which recognized

health and education as important merit goods, whose prices do not reflect the complete

benefits derived from their consumption and as such tend to be under-provisioned in a

free market with private production. Moreover, they are essential components of human

development as per Streetens Basic Needs Approach, Sens Capabilities Approach and the

United Nations Development Programmes Human Development Index and are to beconsidered as ends in themselves and not merely as means to an end.


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2. Grants in aid for education and health Approach of the Twelfth FinanceCommission1

The Twelfth Finance Commission observed, Service standards in the provision of healthand education in the states in India are low on average and also characterized by large

inter-state disparities. These disparities are due to differences in fiscal capacity,

differences in revenue effort and differences in priority accorded to the concerned

sectors.2

The Commission followed a two-step normative approach to select states that were

eligible for equalizing transfers in education and health, with its aim as correcting for

differences in fiscal capacity but not in revenue effort and priority. The first step was to

calculate the ratio of revenue expenditure3 under the major head for education, 2202

(2210 and 2211 for health) to the adjusted total revenue expenditure4 for all states.

General category states and special category states with ratio lower than their respective

group average were deemed to be having lower education (or health) expenditure

preference vis--vis other states in the same category. This low preference was then

corrected by assigning the respective group average ratio to the below-average states. In

the second step, the corrected per capita revenue expenditure on education was worked

out for each state and those states with lower per capita revenue expenditure than theirgroup average were selected as recipients of equalizing transfers for education or health

since their lower expenditure could be on account of low fiscal capacity. 15 per cent of

the gap between the states per capita expenditure and the group average was covered by

the grant in the case of education; 30 per cent of the corresponding gap was covered for

states lagging behind in healthcare provision. Full equalization was not possible due to

resource constraints.

However, the Commissions approach has been criticized on the grounds that,

expenditure equalization should be done in relation to equalizing standards of health

services rather than with reference to the average expenditure incurred (which) would

require analyzing the cost of providing essential services in each of the states on a

1Refer Report of the Twelfth Finance Commission (2005-10) pp 178-181 and (Srivastava, 2006)for

details2 (Srivastava, 2006)3 Includes expenditure on both plan and non-plan purposes4 Excludes expenditure relating to pensions, interest payments and other adjustment items deemed

as inadmissible


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normative basis5. Keeping this in mind, the National Health Systems Resource Centre

(NHSRC), in an approach paper submitted to the Thirteenth Finance Commission, has

suggested the adoption of a normative expenditure approach6, wherein the cost of a

minimum healthcare (allopathic) package to be guaranteed by the sate government was

evaluated for an average district. The per capita expenditure associated with this

approach was worked out to be Rs. 1240, assuming that two-third of hospitalisation at the

block level and half the hospitalisation at the district/sub-district level occurs in public

hospitals. This approach would however imply a massive burden on available resources,

and would not be feasible,at least in the short run. Another shortcoming is that the group

average calculated in the first step (ratio of revenue expenditure on education to adjusted

total revenue expenditure) will understate state preference, precisely because it includes

below-average states. Instead of this, a normatively superior method could be to take the

best performing states as the benchmark. This is the normative average methodsuggested

by NHSRC.

Other criticisms of the Twelfth Finance Commissions approach include that the amount of

the transfer is too small to make any significant change in service delivery and that the

conditions under which they are to be given are too restrictive resulting in poorer states

losing out.

A perennial problem of unconditional Finance Commission grants has been that of a moralhazard, wherein, states at the low end of the performance spectrum do not have enough

incentive for improving quality and quantity of service delivery as they would be assured

of revenues from the same source in subsequent time periods as well. This problem

assumes even more significance when the opportunity cost of grants is taken into account

- the Commission should ideally look at efficient distribution of available resources, and

although equalizing transfers are in the spirit of horizontal equity, there is little intrinsic

motivation for states to use the given resources optimally.

This paper thus examines the possibility of connecting equalizing transfers in the fields of

education and health to efficiency and performance of states in delivering the required

outcomes, with better-performing states getting a larger share than their poor-performing

counterparts. A normative argument for this is that such a mechanism would incentivize

states to take an active interest in utilization of given resources, as also the resultant

outputs and outcomes, and to take corrective action in required areas. However, it must

be kept in mind at all times that grants-in-aid are a form of need-based assistance and

5 Rao & Choudhury, 20086

Please refer Chakraborty, Nair, & Dhawan, 2009 for a detailed explanation of the approach


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should go only to states with the highest requirement. Hence, even if transfers can be

linked to efficiency and performance in practice, it would make little sense (as also

increase inter-state disparities) to give even more resources to the best performers. The

approach to follow in this case would be to identify needy states with a mechanism (like

the one followed by the Twelfth Finance Commission or the normative average approach

suggested by NHSRC), and then link a part of the grants to the selected states to

efficiency and/or performance.

3. Evaluation of performance

Performance in education and healthcare has been assessed through improvement (or

deterioration) in composite indices as measured by the trend growth rate for each state. Itis imperative that the indicators used to create the index be available in a regular time

series, preferably annually or at least biennially. Though several such indicators were

available for education, there was a serious dearth of accredited data in the health

sector, with maternal mortality rates being available only for a few select states and that

too with unacceptably long periodicity. Projections of female life expectancy and under

five mortality rates were available, but it was felt that it would not be appropriate to use

them since they were generated from a model and not based on actual survey. Similarly,

data on health infrastructure, for instance, beds to population ratio, number of primary

health centres etc. were not available regularly for all states. Hence, only the infant

mortality rate has been used in creating the health index. The indicators used in the

education index include the gross enrolment ratio and teacher-student ratio for primary

and upper primary (middle) schools. Secondary school data was not used since the India

mean for gross enrolment ratio was not available. It has, however been used in efficiency

evaluation.

The methodology underlying the construction of the education index7

for the years 2001-02 to 2005-06 is as follows:

1. The raw gross enrolment ratio figure for each state in primary and upper primaryschools was normalized through dividing by the corresponding mean value for India.

7 Data source for education index components State Profiles published by the Ministry of Human

Resource Development


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The normalized data for the two sections was then combined using a weighted

average8 to obtain the gross enrolment ratio index.

2. The procedure was repeated to obtain the teacher-student ratio index.3. The education index for a state was derived by taking the simple arithmetic mean of

the gross enrolment ratio index and the teacher-student ratio index.

4. The improvement (or deterioration) rate was calculated as the trend growth rate ofthe index over the period 2001-02 to 2005-06. Note that in this case, the trend growth

rate indicates the relative improvement of the state with respect to its previous

performance as well as the average improvement for India as a whole.9

8 Weights were applied in accordance to the number of classes in each section, i.e., 5/8 for

primary and 3/8 for upper primary9An alternative method that only takes a states individual performance as a basis for calculating

the improvement rate could be to suitably combine the trend growth rates of the raw gross

enrolment ratio and teacher-student ratio.


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Table 1- Composite index for Elementary (Primary and Upper Primary) Education based on

Gross Enrolment Ratio and Teacher-Student Ratio (2001-02 to 2005-06)

S.No. StateEducation index Improvement

Rate2001-02 2002-03 2003-04 2004-05 2005-06

1 Andhra Pradesh 0.844 0.891 0.885 0.885 0.881 1.0082 Bihar 0.621 0.521 0.547 0.558 0.538 0.978

3 Chhatisgarh 0.888 0.851 0.879 0.889 0.913 1.010

4 Goa 1.160 1.267 1.309 1.242 1.183 1.002

5 Gujarat 0.895 0.936 0.944 0.887 0.885 0.992

6 Haryana 0.937 0.864 0.862 0.837 0.845 0.976

7 Jharkhand 0.663 0.585 0.592 0.628 0.616 0.992

8 Karnataka 0.975 0.971 1.000 0.996 0.959 0.999

9 Kerala 1.100 1.054 1.069 1.090 1.060 0.996

10 Madhya Pradesh 0.922 0.883 0.972 1.009 1.005 1.031

11 Maharashtra 0.972 0.936 0.955 0.921 0.919 0.987

12 Orissa 0.920 0.883 0.925 0.905 0.870 0.991

13 Punjab 0.952 0.885 0.896 0.860 0.839 0.972

14 Rajasthan 0.895 0.831 0.895 0.891 0.900 1.008

15 Tamil Nadu 0.973 1.008 1.051 1.007 1.011 1.008

16 Uttar Pradesh 0.668 0.716 0.735 0.721 0.719 1.015

17 West Bengal 0.752 0.716 0.749 0.725 0.691 0.984

18 Arunachal Pradesh 1.011 0.990 0.944 0.963 1.000 0.995

19 Assam 1.036 1.011 1.016 1.010 1.019 0.997

20 Himachal Pradesh 1.219 1.315 1.285 1.279 1.343 1.01721 J & K 1.119 1.088 1.087 1.068 1.206 1.013

22 Manipur 1.194 1.349 1.240 1.199 1.191 0.988

23 Meghalaya 1.102 1.150 1.066 1.155 1.112 1.002

24 Mizoram 1.554 1.441 1.567 1.702 1.633 1.027

25 Nagaland 1.148 1.165 1.014 1.042 1.039 0.969

26 Sikkim 1.334 1.437 1.177 1.280 1.305 0.984

27 Tripura 1.093 1.149 1.163 1.061 1.080 0.990

28 Uttaranchal 1.053 1.106 1.175 1.190 1.240 1.041

As can be seen from Table 1, the best performers among the general category states and

special category states, in terms of relative improvement rates, are Madhya Pradesh and

Mizoram respectively. Bihar, Punjab and Haryana have actually witnessed relative

deterioration through the years, though Punjab and Haryana are much better off (than

Bihar) in terms of absolute educational attainments.


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The construction of the health index10 is analytically similar to the procedure outlined

above, except for the fact that it includes only one indicator, i.e., the infant mortality

rate11, through the years 2002 to 2007. A more comprehensive index could be constructed

using the procedure outlined earlier, if regular data for any other suitable indicator were

available.

Table 2 Composite index for health based on IMR (2002-07)

S.No. States/UTsHealth Index Improvement

Rate2002 2003 2004 2005 2006 2007

1 Andhra Pradesh 1.016 1.017 0.983 1.018 1.018 1.019 1.001

2 Bihar 1.033 1.000 0.951 0.951 0.950 0.948 0.984

3 Chhatisgarh 0.863 0.857 0.967 0.921 0.934 0.932 1.017

4 Goa 3.706 3.750 3.412 3.625 3.800 4.231 1.022

5 Gujarat 1.050 1.053 1.094 1.074 1.075 1.058 1.0026 Haryana 1.016 1.017 0.951 0.967 1.000 1.000 0.997

7 Jharkhand 1.235 1.176 1.184 1.160 1.163 1.146 0.988

8 Karnataka 1.145 1.154 1.184 1.160 1.188 1.170 1.005

9 Kerala 6.300 5.455 4.833 4.143 3.800 4.231 0.912

10 Madhya Pradesh 0.741 0.732 0.734 0.763 0.770 0.764 1.010

11 Maharashtra 1.400 1.429 1.611 1.611 1.629 1.618 1.032

12 Orissa 0.724 0.723 0.753 0.773 0.781 0.775 1.017

13 Punjab 1.235 1.224 1.289 1.318 1.295 1.279 1.011

14 Rajasthan 0.808 0.800 0.866 0.853 0.851 0.846 1.012

15 Tamil Nadu 1.432 1.395 1.415 1.568 1.541 1.571 1.025

16 Uttar Pradesh 0.788 0.789 0.806 0.795 0.803 0.797 1.00317 West Bengal 1.286 1.304 1.450 1.526 1.500 1.486 1.035

18 Arunachal Pradesh 1.703 1.765 1.526 1.568 1.425 1.486 0.964

19 Assam 0.900 0.896 0.879 0.853 0.851 0.833 0.984

20 Himachal Pradesh 1.212 1.224 1.137 1.184 1.140 1.170 0.990

21 Jammu & Kashmir 1.400 1.364 1.184 1.160 1.096 1.078 0.945

22 Manipur 4.500 3.750 4.143 4.462 5.182 4.583 1.033

23 Meghalaya 1.033 1.053 1.074 1.184 1.075 0.982 0.997

24 Mizoram 4.500 3.750 3.053 2.900 2.280 2.391 0.874

25 Nagaland 0.000 0.000 3.412 3.222 2.850 2.619 0.912

26 Sikkim 1.853 1.818 1.813 1.933 1.727 1.618 0.978

27 Tripura 1.853 1.875 1.813 1.871 1.583 1.410 0.949

28 Uttaranchal 1.537 1.463 1.381 1.381 1.326 1.146 0.951

10 Data source for health index components National Health Profiles (2005 to 2008) published

annually by the Central Bureau of Health Intelligence andwww.indiastat.com11 The reciprocal of the infant mortality rate was used to calculate the index.
http://www.indiastat.com/http://www.indiastat.com/http://www.indiastat.com/http://www.indiastat.com/


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4. Evaluation of efficiency

Efficiency, in its simplest form, may be defined as the ratio of output(s) produced with

respect to input(s) used in the production process. However, it is difficult to obtain a

single measure of efficiency when there are multiple outputs and inputs, which leads to

problems when trying to compare the efficiencies of different units, or states as in this

case. Hence, instead of the ratio procedure, the method of Data Envelopment Analysis

(DEA) has been used to evaluate the efficiency of service delivery of states in the fields of

education and health.

The technique of DEA was pioneered by Charnes, Cooper and Rhodes in 1978 as an

extension of linear programming. According to this, if a given producer (decision making

unit, or DMU), A, is capable of producing YA units of output with XA inputs, then other

producers should also be able to do the same if they were to operate efficiently. DEA thus

captures the efficiency of the state under consideration, relative to the optimal point that

it could reach. The optimal point, in turn, is defined by the most efficient point(s)12 in the

period of the analysis. The main advantages of DEA over the standard ratio method include

the ability to handle multiple inputs and outputs, independence of units of measurement

and its non-parametric nature, i.e., elimination of the need to assume a certain

production function relating outputs and inputs.

The Charnes, Cooper and Rhodes model was originally a constant returns to scale model,

which was later modified by Banker, Charnes and Cooper13 to encompass variable returns

to scale as well. A priori reasons suggest that education and health would be subject to

variable returns, i.e., if inputs were uniformly increased by a factor , outputs would

increase by a factor different from. A graphical comparison of the two models assuming

a single input and a single output for five firms, A, B, C, D and E is shown below. The

efficiency frontier in the CCR model is a straight line from the origin and passing through

point B. On the other hand, the efficiency frontier when variable returns to scale is taken

into account, is the envelope XABEY, a convex set. It may be noted that efficiency can be

measured in two ways, input-oriented and output-oriented. The former method assesses

by how much a firm can reduce its input used while keeping output constant, if operating

at maximum efficiency. Output-oriented measures address the opposite question.

12 A DMU is to be rated as fully efficient on the basis of available evidence if and only if the

performances of other DMUs does not show that some of its inputs or outputs can be improved

without worsening some of its other inputs or outputs. (Cooper, Seiford, & Zhu, 2004)13 The constant returns to scale model is referred to as the CCR model in literature and the variable

returns to scale as the BCC model.


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Figure 1 Comparison of different approaches to measuring efficiency using Data EnvelopmentAnalysis

Efficiency measures for firm C in the Figure 1 are calculated as follows:

1. Case 1 - Constant returns to scale (input-oriented)1 =

2. Case 2 - Constant returns to scale (output-oriented)2 =

3. Case 3 - Variable returns to scale (input-oriented)3 =

4. Case 4 - Variable returns to scale (output-oriented)4 =

DEA thus captures the efficiency of the state as the ratio of weighted sum of outputs to

weighted sum of inputs, with the weights being the variables. The weights are adjustedfor each DMU in order to get the maximum possible efficiency score for that DMU.


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The subsequent efficiency analysis on education and health service delivery is analogous

to Case 4 above, i.e., it is an output oriented model that assumes variable returns to scale

and was carried out using the program DEAP (version 2.1). The detailed mathematical

analysis of the approach may found in Coelli; and Pascoe, Kirkley, Grboval, & Morrison-

Paul, 2003. As opposed to performance, where regularity of data publication is a must,

efficiency is evaluated at one point in time and hence, restrictions on the type of data

that can be used are less severe. However, the analysis depends heavily on the choice of

inputs and outputs, which should be closely related to each other for best results.

Education

The variables chosen as indicators of educational achievement of states for the year 2005-

06 were literacy rate14 of women between the age 15 and 49 (from the third round of the

National Family Health Survey) teacher-student ratio and gross enrolment ratio for

primary, upper primary, secondary and senior secondary schools. Per capita revenue

expenditure on elementary, secondary and adult education under the head 2202 of state

finance accounts was taken as the input15.

Table 3 below shows the results of the exercise for general category states. The results

clearly indicate that Bihar is lagging behind other states by a huge margin in terms ofconverting expenditure into educational outcomes, and that Madhya Pradesh, despite

being a member of the so-called BIMARU states has managed to spend its resources

efficiently vis--vis most other states. Other low performers from this perspective include

Jharkhand, West Bengal and Uttar Pradesh. An interesting conclusion from this exercise is

that some economically backward states, a case in point being Orissa, Rajasthan and

Chhatisgarh, have performed a little better than some richer states like Punjab and

Haryana mainly because the latter states have not been able to raise the gross enrolment

ratio despite much higher expenditure. However, it must be noted that this is only a

partial picture; there may be many other factors exogenous to the model that once

accounted for, could change the scenario significantly. For instance, information related

to retention rates and dropout rates could give a more comprehensive view of the relative

efficiency of states. Efficiency scores would also depend on the priority accorded to the

level and type of education, for instance, Punjab has the lowest expenditure among all

14 According to NFHS-3, a person who has either completed at least standard six or passed a

simple literacy test conducted as part of the survey is said to be literate.15Per capita revenue expenditure was calculated using the population projection for the year 2005

as given in the educational statistics released by the Ministry of Human Resource Development.


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states (for the year 2005-06) on elementary education as a proportion of total revenue

expenditure on general education (24.28 per cent). However, its expenditure on secondary

education as a proportion of total revenue expenditure on general education (64.53 per

cent) is the highest. The only other state with an expenditure pattern remotely similar to

this is Goa; most other states have accorded higher priority to elementary education, at

least in terms of expenditure.

Table 3 Efficiency scores for education for general category states

S.No. State CRS Efficiency VRS Efficiency

1 Andhra Pradesh 0.842 0.933

2 Bihar 0.794 0.796

3 Chhatisgarh 0.689 0.914

4 Goa 0.441 1.0005 Gujarat 0.816 0.861

6 Haryana 0.713 0.855

7 Jharkhand 0.688 0.693

8 Karnataka 0.704 0.914

9 Kerala 0.981 1.000

10 Madhya Pradesh 1.000 1.000

11 Maharashtra 0.686 0.951

12 Orissa 0.893 0.901

13 Punjab 0.760 0.863

14 Rajasthan 0.523 0.859

15 Tamil Nadu 0.987 1.000

16 Uttar Pradesh 0.866 0.870

17 West Bengal 0.904 0.914

Health

The variables chosen as indicator of health outcomes were Infant Mortality Rate and

Maternal Mortality Rate16 for the year 2006, while per capita revenue expenditure on

medical and public health (major head 2202 of state finance accounts) was taken as the

input. Maternal mortality figures were available for only fifteen states; hence, this

exercise is restricted to only those general category states for which complete data was

available. The efficiency scores are indicated below:

16 MMR figures were taken from SRS 2004-06 available at

www.mohfw.nic.in/NRHM/Health_Profile.htm
http://www.mohfw.nic.in/NRHM/Health_Profile.htmhttp://www.mohfw.nic.in/NRHM/Health_Profile.htmhttp://www.mohfw.nic.in/NRHM/Health_Profile.htm


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Table 4 Efficiency scores for health for general category states

S.No. State CRS Efficiency VRS Efficiency

1 Andhra Pradesh 0.782 0.796

2 Bihar 0.892 1.000

3 Chhatisgarh 0.639 0.6854 Gujarat 0.801 0.826

5 Haryana 0.693 0.702

6 Jharkhand 0.747 0.870

7 Karnataka 0.627 0.629

8 Kerala 1.000 1.000

9 Madhya Pradesh 0.547 0.570

10 Maharashtra 0.952 0.956

11 Orissa 0.645 0.684

12 Punjab 0.534 0.542

13 Rajasthan 0.402 0.415

14 Tamil Nadu 1.000 1.000

15 Uttar Pradesh 0.488 0.551

16 West Bengal 1.000 1.000

The efficiency outcome figure below gives a concise visual representation of the relative

position of each state with respect to health outcomes and efficiency. Note that the

Health Index on the vertical axis of the graph is based on both IMR and MMR and thus is

not comparable to the one mentioned in the section on performance, which is based only

on IMR. The horizontal line represents the health index for India as a whole, while the

vertical line is the average variable returns to scale efficiency of the general category

states, excluding Goa. States lying in Quadrant I are clearly the best performers in both

spheres, while those in Quadrant II are being able to achieve good outcomes despite their

efficiency being lower than the group average. This is diametrically opposite to states in

Quadrant IV, which are using their resources better than others in the group, but are not

being able to translate this into better educational attainments for the population.

Quadrant III comprises of states lagging behind in both efficiency and outcomes.


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Figure 2 Comparison of efficiency and health outcomes for general category states

However, there are many practical constraints in trying to associate grants-in-aid with

efficiency. Problems include data inadequacy, methodological shortcomings and political

economy repercussions. A relevant issue that can be presented here is that for efficiency

evaluation to be as accurate as possible, regardless of the method used, outputs (or

outcomes) and inputs should be as closely linked as possible. Hence, if one is unable to

adequately select and filter inputs and outputs, one is liable to get counter-intuitive

results. As mentioned earlier, since DEA estimates relative efficiency of a state, it

compares individual performance to that of the best performer(s). A problem with this

approach is that there is a high probability that an output choice that is heavily skewed infavour of a single outcome will get a high efficiency score, when a normatively preferred

balanced (but high) outcome will get a lower score. In addition, DEA can explain how well

a state is performing with respect to its peers but not compared to a theoretical

maximum. Efficiency in health and education depends on many exogenous factors

including topography, sociology, level of basic physical and social infrastructure etc.,

which cannot be suitably incorporated in the model. Hence, it would be inequitable to link

grant-in-aid with efficiency, at least, as per this model. However, the efficiency exercise

provides interesting insights into how states are being able to translate expenditure into


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selected for the education and health grants by the Twelfth Finance Commission. An

incentive pool of Rs. 100 crores on education would be divided as per Table 5.

Table 5 Allocation of incentive money to selected states based on performance in education

S.No. StateEducation Index Share Calculation

1 ImprovementRate () . 1 Share (Si) Rank1 Assam 1.243 1.003 1.246 16.654 1

2 Bihar 0.560 0.969 0.542 7.245 8

3 Jharkhand 0.704 0.993 0.699 9.345 7

4 Madhya Pradesh 1.139 1.018 1.159 15.495 2

5 Orissa 1.018 0.989 1.006 13.452 4

6 Rajasthan 1.055 1.007 1.062 14.198 3

7 Uttar Pradesh 0.890 1.014 0.902 12.060 5

8 West Bengal 0.866 0.998 0.864 11.551 6

Similarly, in the case of health, an incentive pool of Rs. 100 crores would be shared

amongst selected states as per Table 6.

Table 6 - Allocation of incentive money to selected states based on performance in health

S.No. StateHealth Index Share Calculation

1

ImprovementRate (

)

.

1 Share (Si) Rank

1 Bihar 0.948 0.984 0.933 16.919 3

2 Jharkhand 1.146 0.988 1.132 20.532 1

3 Madhya Pradesh 0.764 1.010 0.771 13.994 6

4 Orissa 0.775 1.017 0.788 14.293 5

5 Uttar Pradesh 0.797 1.003 0.799 14.500 4

6 Uttaranchal 1.146 0.951 1.090 19.764 2


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6. Summary and Conclusion

The Twelfth Finance Commission deserves much credit for recognising the importance of

health and education as key social variables in determining a variety of outcomes and for

devising and implementing a system of sector-specific equalising transfers for the

backbenchers in order to reduce inter-state disparities. However, despite these efforts,

it will be long time before India even comes close to fulfilling the long-term goal of

spending 6 per cent of GDP on health and education individually. Keeping this in mind, and

depending on the resources available, the normative average approach may be considered

as a suitable alternative to the methodology adopted by the Twelfth Finance Commission.

Until now, grants-in-aid have been given based on need and to reduce inter-state

disparities. There is thus a possibility of a moral hazard problem being associated with

these grants. Simultaneously, the efficiency criterion suggests that instead of continuous

financing for poor performance, resources should be targeted at other areas. It is thus

proposed that a part of equalising transfers to states selected for transfers be linked to

improvement in outcomes in education and health. This would give states appropriate

incentive to develop the required physical and human capital and to monitor outcomes at

the state level and to take corrective action when needed. A central monitoring body

could be set up to evaluate state performance and to allocate funds to states as per the

suggested model.


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7. AppendixTable 7 Gross Enrolment Ratio (2001-02 to 2005-06) for General Category states

Gross Enrolment Ratio General Category States

S.No. StatePrimary School Upper Primary (Middle) School Secondary

2001-02

2002-03

2003-04

2004-05

2005-06

2001-02

2002-03

2003-04

2004-05

2005-06

2001-02

2002-03

2003-04

2004-05

2005-06

1

Andhra

Pradesh 103.97 95.93 87.72 96.71 94.87 52.28 63.12 64.86 71.76 73.91 34.22 40.12 44.61 47.66 48.93

2 Bihar 78.7 73.52 72.57 83.75 87.2 30.07 24.98 25.33 32.43 34.27 15.27 17.39 16.9 32.23 16.02

3 Chhatisgarh 116.12 104.45 123.29 131.84 122.26 68.01 71.12 70.52 79.87 69.13 30.67 31.13 35.92 37.3 31.47

4 Goa 62.86 104.22 97.96 110.13 107.74 70.54 105.34 101.23 100.61 98.04 46.76 63.04 62.55 57.82 56.52

5 Gujarat 122.29 111.5 113.41 118.65 119.44 70.67 75.94 70.4 73.77 74.24 39.44 40.2 40.01 38.64 39.5

6 Haryana 76.43 80.98 75.25 82.23 79.61 65.84 67.33 65.51 76.39 74.83 46.4 47.52 45.53 43.6 42.22

7 Jharkhand 88.56 74.79 79.09 94.8 105.19 37.56 31.46 37.54 43.41 45.77 13.52 20.71 14.8 14.8 15.54

8 Karnataka 112.74 110.65 108.91 107.1 106.09 73.93 74.28 76.2 85.47 84.64 38.82 37.95 41.66 46.4 45.19

9 Kerala 85.5 98.11 96.92 93.61 93.85 97.77 97.07 93.64 98.19 97.94 57.17 62.24 48 60.15 64.63

10MadhyaPradesh 111.24 95.02 106.59 132.16 143.67 59.27 63.5 63.3 83.29 91.67 28.07 30.61 34.89 35.74 37.64

11 Maharashtra 108.27 106.55 107.6 110.37 112.34 90.14 86.97 87.55 98.08 100.64 53.07 53.08 53.86 55.6 56.78

12 Orissa 115.64 103.02 110.91 129.69 118.15 55.89 56.43 54.01 74.11 64.55 35.76 31.09 32.74 43.43 42.82

13 Punjab 76.91 71.12 73.45 77.2 77.46 64.88 59.09 60.06 65.42 67.53 41.78 39.12 39.03 39.6 39.76

14 Rajasthan 112.15 97.25 115.07 121.24 121.69 76.19 55.67 61.54 70.67 74.12 27.39 29.29 32.6 33.06 34.3215 Tamil Nadu 97.81 115.5 116.51 118.41 120.07 92.57 99.08 100.41 107 106.81 48.36 55.15 56.85 62.08 63.79

16 Uttar Pradesh 65.72 91.25 94.75 107.54 110.57 35.91 46.84 48.64 52.43 53.02 21.46 36.52 37.93 36.32 35.9

17 West Bengal 109.8 102.99 107.33 112.11 104.91 53.88 58 64.28 66.46 66.71 26.24 30.07 32.61 31.39 35.46

India 96.3 95.3 98.2 107.8 109.4 60.2 61 62.4 69.9 71

Source - Educational statistics released by Ministry of Human Resource Development


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Table 8 - Gross Enrolment Ratio (2001-02 to 2005-06) for Special Category states

Gross Enrolment Ratio Special Category States

S.No. StatePrimary School Upper Primary (Middle) School Secondary

2001-02

2002-03

2003-04

2004-05

2005-06

2001-02

2002-03

2003-04

2004-05

2005-06

2001-02

2002-03

2003-04

2004-05

2005-06

1

Arunachal

Pradesh 114.43 105.93 109.56 123.12 132.16 70.02 65.69 63.6 75.53 81.1 35.04 38.14 38.68 42.37 42.552 Assam 117.43 86.83 88.16 105.2 107.11 70.63 51.22 63.65 69.7 72.83 35.98 29.65 40.83 32.23 32.08

3HimachalPradesh 90.01 116.42 106.47 108.9 108.89 92.88 104.06 98.24 108.5 107.84 61.9 68.97 69.78 131.26 131.51

4 J & K 89.85 84.39 71.52 83.72 100.49 74.39 60.93 50.6 60.28 64 42.24 33.38 32.6 35.38 35.74

5 Manipur 99.13 146.88 137.51 151.69 157.92 77.86 80.46 84.33 94.69 97.92 40.49 51.32 46.24 48.61 49.43

6 Meghalaya 112.42 116.19 105.51 147.62 162.37 60.83 53.08 61.14 76.45 86.34 28.13 32.61 28.09 33.27 35.71

7 Mizoram 119.07 128.7 120.17 127.53 169.06 79.95 78.47 76.98 81.77 117.99 45.92 40.61 43.66 44.67 41.91

8 Nagaland 105.7 65.22 80.48 87.94 88.82 60.26 35.1 44.66 55.6 60.31 28.17 13.54 18.06 21.28 24.07

9 Sikkim 114.93 121.68 116.51 143.58 151.15 66.55 65.19 56.75 66.7 74.38 27.78 32.83 27.51 33.3 34.76

10 Tripura 101.88 123.85 122.76 131.03 143.35 67.59 71.42 72.84 78.16 82.5 33.33 36.89 38.16 38.86 39.86

11 Uttaranchal 100.65 107.87 106.85 117.74 119.89 73.71 78.84 80.36 88.08 89.88 48.24 56.31 56.12 58.03 62.03

India 96.3 95.3 98.2 107.8 109.4 60.2 61 62.4 69.9 71



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Table 9 - Student Teacher Ratio (2001-02 to 2005-06) for General Category states

Student - Teacher Ratio General Category States

No. StatePrimary Schools Upper Primary Schools Secondary Schools Sr. Secondary School

2001-02

2002-03

2003-04

2004-05

2005-06

2001-02

2002-03

2003-04

2004-05

2005-06

2001-02

2002-03

2003-04

2004-05

2005-06

2001-02

2002-03

2003-04

2004-05

2005-06

1AndhraPradesh 41 33 35 33 32 39 30 31 31 30 34 29 31 33 34 38 32 34 33 33

2 Bihar 73 83 74 104 104 54 73 65 75 78 45 48 48 55 58 23 30 30 28 24

3 Chhattisgarh 44 43 47 48 41 44 37 45 46 47 42 29 45 38 49 28 32 33 25 13

4 Goa 20 21 20 21 32 16 16 16 17 33 25 25 26 24 10 18 23 20 21 175 Gujarat 68 31 32 35 34 38 38 39 39 38 28 30 30 34 31 43 36 39 35 39

6 Haryana 39 41 45 44 42 22 26 25 30 26 25 28 28 27 26 29 30 29 27 26

7 Jharkhand 65 59 73 81 79 53 57 60 61 63 44 42 46 54 52 25 32 29 20 29

8 Karnataka 30 26 34 26 26 39 37 39 37 32 25 27 17 18 24 58 35 35 47 47

9 Kerala 28 28 29 28 27 28 28 27 27 26 29 27 28 27 27 19 30 21 15 20

0MadhyaPradesh 44 36 41 43 49 29 28 27 30 33 29 25 29 32 36 27 28 18 16 16

1 Maharashtra 39 36 37 37 37 30 37 38 37 36 54 34 34 35 35 41 39 41 42 43

2 Orissa 39 40 56 53 42 36 38 28 44 38 23 23 24 22 23 51 21 20 31 37

3 Punjab 44 38 42 43 44 17 18 18 19 20 26 25 27 28 28 29 27 30 29 30

4 Rajasthan 51 41 46 49 47 40 31 33 34 31 29 28 30 27 23 29 29 30 24 29

5 Tamil Nadu 33 34 35 33 34 37 40 37 41 38 36 30 28 29 26 34 33 32 33 32

6 Uttar Pradesh 44 55 57 58 57 30 35 37 35 35 43 40 48 61 60 43 50 47 45 45

7 West Bengal 56 53 55 54 50 51 50 49 44 62 49 55 57 63 58 47 50 58 50 51India 43 42 45 46 46 34 34 35 35 34

ource - Educational statistics released by Ministry of Human Resource Development


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Table 10 Student Teacher Ratio (2001-02 to 2005-06) for Special Category states

Student - Teacher Ratio Special Category States

No. StatePrimary Schools Upper Primary Schools Secondary Schools Sr. Secondary School

2001-02

2002-03

2003-04

2004-05

2005-06

2001-02

2002-03

2003-04

2004-05

2005-06

2001-02

2002-03

2003-04

2004-05

2005-06

2001-02

2002-03

2003-04

2004-05

2005-06

1ArunachalPradesh 34 27 39 34 32 28 25 28 30 30 26 27 27 28 26 30 29 31 31 30

2 Assam 38 30 40 42 45 25 16 17 16 15 21 18 20 20 19 32 21 24 24 24

3HimachalPradesh 23 22 21 24 23 16 15 17 30 15 28 24 28 26 30 28 24 26 20 27

4 J & K 31 19 33 34 32 19 18 16 16 15 18 19 12 14 11 20 25 17 17 14

5 Manipur 22 21 28 30 31 19 17 19 20 21 20 19 23 24 25 24 20 22 23 22

6 Meghalaya 34 22 36 44 46 17 17 14 16 18 17 18 19 24 27 30 23 36 16 23

7 Mizoram 21 19 18 17 25 9 11 10 8 11 15 13 13 12 11 19 22 16 12 12

8 Nagaland 19 12 19 19 20 18 13 18 16 16 24 20 23 23 23 39 27 34 35 32

9 Sikkim 16 12 19 22 22 18 15 22 25 27 20 18 21 11 11 18 19 21 18 16

0 Tripura 31 23 30 54 36 18 20 16 15 19 23 23 25 25 27 22 23 24 25 26

1 Uttaranchal 35 29 27 25 24 34 19 19 18 17 19 22 18 18 15 20 29 30 29 28

India 43 42 45 46 46 34 34 35 35 34



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Table 11 Female Literacy Rate

S.No. States Female Literacy Rate

1 Andhra Pradesh 49.6

2 Bihar 37.0

3 Chhatisgarh 44.9

4 Goa 83.6

5 Gujarat 63.8

6 Haryana 60.4

7 Jharkhand 37.1

8 Karnataka 59.7

9 Kerala 93.0

10 Madhya Pradesh 44.4

11 Maharashtra 70.3

12 Orissa 52.213 Punjab 68.7

14 Rajasthan 36.2

15 Tamil Nadu 69.4

16 Uttar Pradesh 44.8

17 West Bengal 58.8

18 Arunachal Pradesh 52.7

19 Assam 63.0

20 Himachal Pradesh 79.5

21 Jammu & Kashmir 53.9

22 Manipur 72.6

23 Meghalaya 69.5

24 Mizoram 94.0

25 Nagaland 75.2

26 Sikkim 72.3

27 Tripura 68.5

28 Uttaranchal 64.6

India 55.1

Source National Family Health Survey Round 3 (2005-06) Report


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Table 12 Infant Mortality Rate (2002-07) and Maternal Mortality Rate

S.No. StatesIMR MMR

2002 2003 2004 2005 2006 2007 SRS (2004-06)1 Andhra Pradesh 62 59 59 57 56 54 154

2 Bihar 61 60 61 61 60 58 312

3 Chhatisgarh 73 70 60 63 61 59 335

4 Goa 17 16 17 16 15 13

5 Gujarat 60 57 53 54 53 52 160

6 Haryana 62 59 61 60 57 55 186

7 Jharkhand 51 51 49 50 49 48 312

8 Karnataka 55 52 49 50 48 47 213

9 Kerala 10 11 12 14 15 13 95

10 Madhya Pradesh 85 82 79 76 74 72 335

11 Maharashtra 45 42 36 36 35 34 130

12 Orissa 87 83 77 75 73 71 303

13 Punjab 51 49 45 44 44 43 192

14 Rajasthan 78 75 67 68 67 65 388

15 Tamil Nadu 44 43 41 37 37 35 111

16 Uttar Pradesh 80 76 72 73 71 69 440

17 West Bengal 49 46 40 38 38 37 141

18 Arunachal Pradesh 37 34 38 37 40 37

19 Assam 70 67 66 68 67 66 480

20 Himachal Pradesh 52 49 51 49 50 47

21 Jammu & Kashmir 45 44 49 50 52 51

22 Manipur 14 16 14 13 11 12

23 Meghalaya 61 57 54 49 53 56

24 Mizoram 14 16 19 20 25 23

25 Nagaland 17 18 20 21

26 Sikkim 34 33 32 30 33 34

27 Tripura 34 32 32 31 36 39

28 Uttaranchal 41 41 42 42 43 48 440India 63 60 58 58 57 55 254

Source National Health Profiles (2005 to 2008) published by the Central Bureau of Health

Intelligence andwww.indiastat.comfor IMR

SRS 2004-06 available atwww.mohfw.nic.in/NRHM/Health_Profile.htmfor MMR
http://www.indiastat.com/http://www.indiastat.com/http://www.indiastat.com/http://www.mohfw.nic.in/NRHM/Health_Profile.htmhttp://www.mohfw.nic.in/NRHM/Health_Profile.htmhttp://www.mohfw.nic.in/NRHM/Health_Profile.htmhttp://www.mohfw.nic.in/NRHM/Health_Profile.htmhttp://www.indiastat.com/


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8. Bibliography

1. Beasley, J. E. (n.d.). Operations Research Notes - Data Envelopment Analysis.Retrieved July 2009, from http://people.brunel.ac.uk/~mastjjb/jeb/or/dea.html

2. Chakraborty, G., Nair, A. B., & Dhawan, R. (2009). Equalising Public HealthExpenditure by Thirteenth Finance Commission of India - An Analysis of the Approach.

New Delhi: National Health Systems Resource Centre.

3. Coelli, T. (n.d.).A Guide to DEAP Version 2.1: A Data Envelopment Analysis(Computer) Program. Retrieved July 2009, from

http://www.une.edu.au/econometrics/cepawp.htm.

4. Cooper, W. W., Seiford, L. M., & Zhu, J. (2004). Data Envelopment Analysis - History,Models and Interpretations.

5. Pascoe, S., Kirkley, J. E., Grboval, D., & Morrison-Paul, C. J. (2003). Measuring andassessing capacity in fisheries - Issues and methods; Appendix D Data Envelopment

Analysis Retrieved July 2009, from

http://www.fao.org/docrep/006/y5027e/y5027e00.HTM

6. Rao, M. G., & Choudhury, M. (2008). Inter-State Equalisation of Helath Expendituresin Indian Union. New Delhi: National Institute of Public Finance and Policy.

7. Report of the Twelfth Finance Commission (2005-10). New Delhi: Ministry of Finance,Government of India.

8. Srivastava, D.K. (2006, July). Equalizing Health and Education: Approach of theTwelfth Finance Commission, Working Paper No. 7/2006, Madras School of Economics,

Chennai.

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