attaining the millennium development goals in india: how likely & what will it take?
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Attaining the Millennium Attaining the Millennium Development Goals in India:Development Goals in India:
How Likely & What Will It How Likely & What Will It Take?Take?
Millennium Development Millennium Development Goals (MDGs)Goals (MDGs)
As you all know, the MDGs are a set of numerical and time-bound targets to measure achievements in human and social development.
Five MDGs analyzed in this Five MDGs analyzed in this ReportReport
• Child and infant mortality reduction• Reduction in child malnutrition• Universal primary enrollment• Elimination of gender disparity in school
enrollment• Reduction of hunger-poverty (calorie deficiency)
• Analysis has been at a highly aggregate level – typically the level of the country. This is meaningless in a large and heterogeneous country like India.
• The likelihood of attaining the MDGs hasn’t been usefully linked to the factors that influence MD indicators. This is necessary to address the question: what will it take to attain the MDGs?
Limitations of much of the MDG Limitations of much of the MDG discussion so fardiscussion so far
MDG Attainment in the Poor MDG Attainment in the Poor States of IndiaStates of India
The poorest states in India (e.g., Uttar Pradesh, Bihar, Rajasthan, Orissa, and Madhya Pradesh):• are among the most populous in the country, and• have among the worst MD indicators.
Owing to more rapid population growth, these states will account for an even larger share of India’s population in 2015.
Therefore, India’s attainment of MDGs will largely depend on the performance of these states.
Tremendous spatial variation in Tremendous spatial variation in levelslevels of & of & changeschanges in MD indicators in MD indicators
There are very large inter-state and intra-state variations in all MD indicators in India. For instance, the IMR for the country is 66 infant deaths per 1,000 live births. But it varies from a figure of 11 in Kerala to 90 in Orissa.
Intra-state variations in infant mortality and in primary school enrollment rates are even greater, as seen in the following map.
IMR (Regions)per 100 live births
100 to 130 (3)90 to 100 (10)80 to 90 (6)70 to 80 (15)60 to 70 (9)50 to 60 (8)20 to 50 (5)0 to 20 (2)
missing (21)
Infant Mortality Rate, 1997-99
Net primary enrollment rates also vary a great deal across regions …
And there is a great deal intrastate variation in IMR decline as well, with some regions showing
…
… … as in changes in net primary enrollments.as in changes in net primary enrollments.
Geographic Concentration of MD Geographic Concentration of MD indicatorsindicators
The wide disparity in MD indicators results in the geographical distribution of these indicators being heavily concentrated.
This indicates the need for targeting MDG-related interventions to poorly-performing states, districts, and perhaps even villages (if these could be identified).
Case of infant mortalityCase of infant mortality– Four states
Uttar PradeshMadhya PradeshBiharRajasthan
– Account for more than 50% of infant mortality in India
– Four more states account for another 21%, or a cumulative 72%
Contribution of the 21 larger states to national infant deaths, 2000979693
8983
76
67
43
57
25
6 5 5 5 4 4 3 3 3 2 2 2 1 0 0 0 0
9 89
0
10
20
30
40
50
60
70
80
90
100
Utt
ar P
rade
sh
Mad
hya
Pra
desh
Bih
ar
Raj
asth
an
And
hra
Pra
desh
Mah
aras
htra
Ori
ssa
Wes
t Ben
gal
Guj
arat
Kar
nata
ka
Tam
il N
adu
Ass
am
Jhar
khan
d
Chh
atis
garh
Har
yana
Pun
jab
Jam
mu
& K
ashm
ir
Del
hi
Utt
aran
chal
Him
acha
l Pra
desh
Ker
ala
Cum
ulat
ive
cont
ribu
tion
(%)
Cumulative share in total number of infant deaths nationally
Share in total number of infant deaths nationally
51% 21%
Infant deaths are even more concentrated at the district and the village levels.
Only one-fifth of the districts and villages in the country account for one-half of all infant deaths…
Cumulative distribution of infant deaths in India across districts and villages, 1994-98
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Cumulative % of districts or villages (ranked by infant deaths)
Cum
ulat
ive
% o
f na
tion
al in
fant
dea
ths
Villages
Districts
… and more than half of all underweight children are found in only a quarter of all villages and districts in the
country.
Cumulative distribution of all underweight 0-35 month old children in India across villages and districts, 1998-99
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Cumulative % of villages or districts (ranked by number of underweight children)
Cum
ulat
ive
% o
f al
l und
erw
eigh
t chi
ldre
n in
the
coun
try Districts Villages
Out-of-school children are even more concentrated. Nearly three-quarters of all out-of-school children in the country are found in a mere 20% of villages (and 50% of districts).
Cumulative distribution of all out-of-school 6-11 year olds in India across villages and districts, 1999-2000
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Cumulative % of villages or districts (ranked by number of out-of-school 6-11 year olds)
Cum
ulat
ive
% o
f al
l out
-of-
scho
ol 6
-11
year
old
s in
th
e co
untr
y Districts Villages
Identification of villages with poor Identification of villages with poor MD indicatorsMD indicators
Unfortunately, currently-available data cannot allow identification of specific villages that account for most of the infant deaths, underweight children, or out-of-school children in the country, because most sample surveys are not large or representative enough at the village level.
But new, emerging methodologies are available to do this.
Most Deprived Regions in IndiaMost Deprived Regions in India
But we can identify the most-deprived regions in the country.
There are two regions in the country that are the most deprived in terms of all the 5 MDG indicators we have analyzed (Southwestern M.P. and Southern Rajasthan).
There are another 6 regions that are most deprived in terms of 4 of the 5 indicators we have analyzed.
MDG attainmentMDG attainment
Clearly, attaining the MDGs will require action in the poorest states, districts and villages.
How can it be done? What will it take?
Estimation of household, Estimation of household, behavioral models of MD indicatorsbehavioral models of MD indicators Using household survey data from various
sources, we have attempted to quantify the factors associated with the reduction of infant mortality, child malnutrition, schooling enrollment, gender disparity, and hunger-poverty.
These models are used to project changes in MD indicators in the poor states by 2015 under certain intervention scenarios.
We have considered:General Interventions
Economic growthExpanded adult male and female
schoolingIncreased access to water & sanitationImproved electricity coverageIncreased access to pucca roads
Sectoral Interventions
Increased government spending on health and family welfare, nutrition, and elementary education
Various sector-specific interventions, such as– More professionally-assisted deliveries– Antenatal care coverage and tetanus toxoid
immunization for pregnant women– Increased number of primary schools per child
aged 6-11– Reduction in the pupil-teacher ratio– Greater irrigation coverage– Increased foodgrain production per capita.
Results of the SimulationsResults of the Simulations
Large improvements in all the MD indicators are possible with concerted action in many areas.
Both general and sector-specific interventions will be important in attaining the MDGs.
Infant mortality could decline by 50% if the poor states were to be brought up to the level of the non-poor states
Projected decline in the infant mortality rate in the poor states by 2015 under different intervention scenarios (Base IMR=76 in 2000)
757474
7173
67
71
62
68
51
67
46
65
43
64
39
35
45
55
65
75
National average Average of the non-poor states
Poor states are brought up to the:
Sanitation coverageElectricity coverageRegular electricity coverageAdult female schoolingGovernment expenditure per capita on health and family welfarePucca road coverageTetanus toxoid immunization coverageAntenatal care coverage
Intervention
Any single intervention won’t go very far in attaining the MDGs.
What is needed is a ‘package’ of interventions.
The child underweight rate could decline by 40% if the poor states were to be brought up to the level of the non-poor states
Projected decline in the in the child underweight rate in the poor states by 2015 under different intervention scenarios (Base rate=51 in 2000)
504950
4849
4748
43
47
40
44
34
43
31
43
30
25
30
35
40
45
50
National average Average of the non-poor states
Poor states are brought up to the:
Sanitation coverageElectricity coverageRegular electricity coverageAdult female schoolingImproved living standards (consumption expenditure per capita)Government expenditure on nutrition programs per child aged 0-6 years Pucca road coverageMedical attention at birth
Intervention
Projected increase in the net primary attendance rate for 6-11 year olds in the poor states by 2015 under different intervention scenarios (Base rate=50% in 2000)
50 515051
54
63
54
64
54
64
54
64
56
68
56
69
56
69
45
50
55
60
65
70
National average Average of the non-poor states
Poor states are brought up to the:
Adult male schoolingAdult female schoolingImproved living standards (consumption expenditure per capita)Government expenditure on elementary education per child 6-15 yearsCrime against women and girlsPucca road coverageElectricity coverageNumber of primary schools per 1,000 children aged 6-11Pupil teacher ratio in primary schools
Intervention
The net primary enrollment rate in the poor states could increase from 50% to 69% if the poor states were to be brought
up to the level of the non-poor states
Trajectory of Selected MD Trajectory of Selected MD Indicators to 2015Indicators to 2015
We have also made some assumptions about how the various policy interventions might change over time, and
then traced out the path of the MD indicators to 2015.
Assumptions about policy Assumptions about policy interventions to 2015interventions to 2015
Assumptions about various interventions to reduce the infant mortality rate in the poor states, 1998-99 to 2015
Intervention Starting value Assumed change per year Ending value in 2015
Population with no access to toilets (%) 76.5 -2% points 42.5
Population coverage of regular electricity supply 27.7 1% point 44.7
% villages having access to pucca roads 59.5 1% point 76.5
Consumption expenditure per capita 422 3% 698
Adult male schooling years 4.5 0.25 8.5
Adult female schooling years 2.0 0.3 6.8
Government expenditure on health and family welfare per capita 95 4% 185
Government expenditure on nutrition programs (ICDS) per child 0-6 years 51 4% 98
Government expenditure on elementary education per child 6-14 years 955 4% 1,789
Assumptions about various interventions to reduce the infant mortality rate in the poor states, 1998-99 to 2015
Intervention Starting value Assumed change per year Ending value in 2015
Coverage of antenatal care 55.5 1% point 72.5
% of pregnant women obtaining tetanus toxoid immunization 70 1% points 87
% of professionally-attended deliveries 32.3 1.5% points 57.8
Crime against women (number of female kidnappings and rapes per 100,000 population) 1.65 -0.05 0.85
Crime against women (number of female kidnappings and rapes per 100,000 population) 1.65 -0.05 0.85
Number of primary schools per 1,000 children aged 6-11 years 5.1 .2 8.3
Pupil-teacher ratio in primary schools 91 -1 75
Share of secondary education in total government expenditure on education 36 1% 52
% of area irrigated 29.2 1% point 45.2
Food grain production per capita in districts 186 2% 255
The simulations suggest that attaining the infant mortality MDG in the poor states will be challenging but not impossible
with a package of interventions …
Projected infant mortality rate in the poor states to 2015, under different intervention scenarios
(graph shows cumulative effect of each additional intervention)
20
30
40
50
60
70
80
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
20
30
40
50
60
70
80
Tetanus toxoid immunizationReal gov't health exp. per capitaAccess to sanitationRegular electricity coverageMean schooling years of adult femalesVillage access to pucca roadsAccess to antenatal care
Intervention
MDG for poor states
Likewise, it would be possible to reach the child malnutrition MDG in the poor states with a package of interventions …
Projected % of children 0-3 who are underweight in the poor states to 2015, under different intervention scenarios
(graph shows cumulative effect of each additional intervention)
20
25
30
35
40
45
50
55
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
20
25
30
35
40
45
50
55
Medical attention at birthReal gov't exp. on nutrition per childAccess to sanitationReal income growthRegular electricity coverageMean schooling years of adult femalesVillage access to pucca roads
Intervention
MDG for poor states
… but attaining the 100% net primary enrollment goal by 2015 will be problematic in the poor states
Projected net primary enrollment rate in the poor states to 2015,under different intervention scenarios
(graph shows cumulative effect of each additional intervention)
45
50
55
60
65
70
75
80
85
90
95
100
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
45
50
55
60
65
70
75
80
85
90
95
100
Reduction in the primary pupil teacher ratioIncreased number of primary schools per 1,000 children aged 6-11Reduction in crime against womenReal income growthIncrease in the mean schooling years of adult femalesIncrease in the mean schooling years of adult malesIncreased electricity accessGreater gov't exp on elementary schooling per child 6-14
InterventionMDG
Likewise, it will be very difficult for the poor states to attain the 100% primary completion goal by 2015
Projected primary completion rate (%) in the poor states to 2015, under different intervention scenarios
(graph shows cumulative effect of each additional intervention)
45
50
55
60
65
70
75
80
85
90
95
100
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
45
50
55
60
65
70
75
80
85
90
95
100
Reduction in the primary pupil teacher ratioReduction in crime against womenImproved road accessReal income growthIncrease in mean schooling years of adult femalesIncrease in mean schooling years of adult malesGreater gov't exp on elementary schooling per child 6-14Increased electricity access
InterventionMDG
Note that increasing the net primary enrollment rate to 100% (the MD goal) is different from getting all children aged 6-11 in school.
The simulations suggest that getting all children aged 6-11 in school is attainable with the same set of interventions discussed earlier.
Projected % of children aged 6-11 attending school in the poor states to 2015, under different intervention scenarios
(graph shows cumulative effect of each additional intervention)
50
55
60
65
70
75
80
85
90
95
100
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
50
55
60
65
70
75
80
85
90
95
100
Increased electricity coverageIncrease in mean schooling years of adult malesIncrease in mean schooling years of adult femalesReal income growthReduction in crime against womenReduction in the primary pupil teacher ratioExpansion of number of primary schools per child 6-11
Intervention
Other MDGsOther MDGs
What about:
– Gender disparity in schooling, and
– Hunger poverty?
Complete elimination of the gender disparity in primary and secondary school enrollment also appears difficult in the poor
states.
Projected male-female difference (in percentage points) in school attendance rate of children aged 6-18 in the poor states to 2015, under different intervention scenarios
(graph shows cumulative effect of each additional intervention)
0
5
10
15
20
25
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
0
5
10
15
20
25
Real income growthExpanded road accessIncrease in share of secondary educ. in total gov't exp. on educ.Increase in mean schooling years of adult femalesIncrease in mean schooling years of adult malesReduction in crime against womenExpanded electricity access
Intervention
MD goal
But elimination of hunger-poverty in the poor states is very likely with a package of interventions, especially since hunger-
poverty appears to be very responsive to economic growth.
Projected incidence of hunger-poverty (calorie deficiency) (%) in the poor states to 2015, under different intervention scenarios
(graph shows cumulative effect of each additional intervention)
20
25
30
35
40
45
50
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
20
25
30
35
40
45
50
Increased access to safe waterImproved road accessIncrease in mean schooling years of adult malesIncrease in mean schooling years of adult femalesIncreased foodgrain production per capitaIncreased irrigation coverageReal income growth
InterventionMDG Target in 2015
Summing UpSumming Up Meeting the MDGs will be challenging, especially for
the poor states in India.
A number of interventions, including
– economic growth– improved infrastructure (especially water and sanitation,
electricity, and road access)– expansion of female schooling, and– scaling up of public spending on the social sectors
will be needed in order to attain the MDGs.
Also important will be a number of sectoral interventions, such as
– improved access to antenatal care– Immunization– nutritional supplementation– home-based neonatal services– increasing the density of schools– lowering the pupil-teacher ratio– raising agricultural production.
Targeting interventions, public spending, and economic growth opportunities to the poor states and, within those, to the poor districts and villages will be critical.
Finally, the importance of – systematically monitoring MD outcomes at
disaggregated levels and – evaluating the impact of public programscannot be overemphasized.
Currently, there is no system for monitoring progress toward attainment of the MDGs at the sub-national level.
In addition, most public interventions, such as the Integrated Child Development Services and the District Primary Education Program, have not been subjected to rigorous, independent evaluation.
In order to choose the right set of interventions with which to attain the MDGs, it is critical to know which programs have been successful in improving MD indicators and which have not.
CaveatsCaveats
Estimations and simulations subject to usual problems of measurement error, estimation bias, etc.
Therefore, projections are indicative and should be used in “rough-order” planning.
Simulations focus on quantitative variables and not on qualitative variables, such as governance. Does not mean that governance is not important, just that it is difficult to take that into account in the simulations.
The simulations assume “business as usual”. Any improvements in governance will result in speedier attainment of MDGs.