Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Growth Week 2011: Country Session 4 – India-Bihar
1. Role of ICT
in Improving the Quality of School Education
in Bihar
Chirashree Das Gupta and Haridas KPN
Presentation for
IGC Growth Week: 19-21 September, 2011
2. Background
Method
Design
A Few Preliminary Results
Flagging Issues in Programme Delivery
3. Identification of Hard Spots
Category Sample Distribution Percentage of sample
No hard spot 1 0
One Subject 3237 82
More than one subject 327 8
Missing data 264 7
Inconsistent response 131 3
Total 3960 100
4. Identification of Hard Spots-Subject wise
Subjects Number Percentage Percentage of Percentage Percentage Percentage
of of Sample Students of students of Boys of Girls
Students having having
having difficulty only difficulty in
Difficulty in one other
in subject or
more along
with
1-Hindi 92 2 54 46 54 46
2-Urdu 150 4 82 18 54 46
3-Eng 1026 26 75 25 42 58
4-Sans 2070 52 88 12 46 54
5-Maths 388 10 76 24 35 65
6-Science 149 4 63 37 49 51
7- Other 77 2 … … 55 45
5. Role of e-Samarth in Addressing Hard Spots
Perception Gaps on Role of e-Samarth
Performance Analysis (Exam score) -
Perception/ Performance School Authority Teachers Comparison of 3 year exam scores
Increased Interest in learning 88 76
Increase in attention span 76 65
Increase in classroom
participation 88 48
Increase in classroom interaction 68 63
Correct answers/response 72 46
More clarity on topics taught
through CDS 60 39
Improved examination
performance 64 44 No significant improvement
Improved understanding of the
subject 56 41
Increase in enrolment (students
changing schools) 15
Note: All figures are in percentages
6. Role of e-Samarth in Addressing Hard Spots
Status of Trained Teachers in e-samarth
Trained under
CAL Trained Outside/ self trained
Trained Teachers 85 15
Training Hours
Not sure 7
15 hours 7
25 hours 4
30 hours 54
35 hours 13
40 hours 2
50 hours 11
126 hours 2
Note: All figures are in percentages
7. Role of e-Samarth in identifying Hard Spots
Status of Trained Teachers in e-samarth
Usage of Computer (Days in a week)
7 11
6 20
5 9
4 13
3 4
2 9
1 2
Sometimes 22
Never 11
Usage of Computer/Kyan
(computer aid) for Teaching
Yes 43
No 57
Note: All figures are in percentages
10. Some Preliminary Observations on Operational
Status of e-Samarth
School Level Operational Status of e-Samarth
Type of model
Classification Total
BEP BOOT ILFS
CAL programme operational on paper 1 2 13 16
CAL programme not operational 2 5 2 9
Total 3 7 15 25
CAL programme operational based on
1 2 11 14
observations on the day of visit
11. Some Preliminary Observations on Operational
Status of e-Samarth
District wise Operational Status of e-Samarth
Districts Bhojpur Muzaffarpur Samastipur Saran Gaya Total
BEP 1
CAL programme
operational on BOOT 2 16
paper
ILFS 1 5 3 3 1
BEP 1 1
CAL programme
BOOT 1 2 1 1 9
not operational
ILFS 1 0 0 1
Total 5 5 5 5 5 25
CAL programme BEP 1
operational
based on BOOT 2 14
observations on
the day of visit ILFS 1 5 2 2 1
13. Karthik Muralidharan &
Nishith Prakash
Introduction
Motivation
Background
Cycling to School: Increasing High Policy
Goals
School Enrollment for Girls in Bihar Empirical Strategy
Methodology
Data
Data
Karthik Muralidharan & Nishith Prakash Thank You
Thank You
University of California-San Diego & Cornell University
September 19, 2011 / IGC Growth Week - LSE
14. Motivation Karthik Muralidharan &
Nishith Prakash
Introduction
Increasing school attainment of girls is one of the Motivation
Millennium Development Goals Background
Policy
Improving female education directly contributes to Goals
“Inclusive Growth”: Empirical Strategy
Growth - by increasing human capital of labor Methodology
Data
force Data
Inclusive - by allowing people to participate in the Thank You
growth process Thank You
Returns to schooling is approximately 7-10% in
India (Duraisamy, 2000; Agrawal, 2011)
Despite high economic returns to education in
developing countries, there are:
Low school completion rates
High drop-out rates
Students absenteeism
15. Education in Bihar Karthik Muralidharan &
Nishith Prakash
Introduction
Motivation
Large gender gap in schooling in developing Background
countries (for e.g. enrollment, attendance, Policy
attainment, dropout etc.) Goals
Empirical Strategy
In rural Bihar, currently 63% girls are enrolled Methodology
Data
against 81% boys in the age category 10–14. For Data
the age category 15–19, only 27% girls are Thank You
admitted against 40% boys (Azam, 2011) Thank You
In urban Bihar, currently 81% girls are enrolled
against 86% boys in the age category 10–14. For
the age category 15–19, only 55% girls are
admitted against 57% boys (Azam, 2011)
Low attendance and attainment among girls in
Bihar
16. Policy Intervention Karthik Muralidharan &
Nishith Prakash
Introduction
Motivation
Background
In April 2006, the Government of Bihar headed by
Policy
the Chief Minister Mr. Nitish Kumar decided to Goals
provide bicycles to all girl students studying in Empirical Strategy
Methodology
Class IX & X Data
Data
Approximately Rs. 2000 (45 USD) per girl student
Thank You
was allocated to purchase bicycles Thank You
This scheme was called “Mukhyamantri Balika
Cycle Yojana” and later “Mukhyamantri Cycle
Yojana”
Policy Questions
Does Cycle Scheme increase girls enrollment?
Does Cycle Scheme affect learning outcomes?
17. Policy Intervention Karthik Muralidharan &
Nishith Prakash
Introduction
Motivation
Background
In April 2006, the Government of Bihar headed by
Policy
the Chief Minister Mr. Nitish Kumar decided to Goals
provide bicycles to all girl students studying in Empirical Strategy
Methodology
Class IX & X Data
Data
Approximately Rs. 2000 (45 USD) per girl student
Thank You
was allocated to purchase bicycles Thank You
This scheme was called “Mukhyamantri Balika
Cycle Yojana” and later “Mukhyamantri Cycle
Yojana”
Policy Questions
Does Cycle Scheme increase girls enrollment?
Does Cycle Scheme affect learning outcomes?
18. Outcome Measures Karthik Muralidharan &
Nishith Prakash
Introduction
Motivation
Enrollment Background
Does this reduce gender inequality? Policy
Does this reduce gap across caste and religion? Goals
Empirical Strategy
Methodology
Learning outcomes (for e.g. share of students
Data
passing 10th grade, passing with 3rd division, 2nd Data
division, 1st division, distinction) Thank You
Thank You
Increased enrollment may reduce mean scores,
but may increase absolute number of girls at
higher levels of attainment
Possibility of a follow-up survey:
Female Empowerment-
Use of bicycles has been considered a sign of
self-confidence and empowerment in India
19. Difference in Difference Approach Karthik Muralidharan &
Nishith Prakash
Introduction
Motivation
Background
Policy
Difference in Difference Approach: Goals
Single Difference = [(Enroll)Girls
Post − (Enroll)Girls ]
Pre
Empirical Strategy
Boys Boys Methodology
D-D Bihar = A = [(Enroll)Girls −
Post (Enroll)Girls ] − [(Enroll)Post
Pre − (Enroll)Pre ]
This will control for changes in income, tastes and government policies that was Data
targeted towards school going children Data
Thank You
Thank You
Triple Difference Approach:
Boys Boys
D-D Jharkhand = B = [(Enroll)Girls
Post − (Enroll)Girls ]
Pre − [(Enroll)Post − (Enroll)Pre ]
D-D-D = [A - B]
This will control for remaining bias from differential time trend
Jharkhand is particularly compelling as it was part of Bihar till 2000
Boarder districts share similar socio-economic conditions
20. Map of Bihar Karthik Muralidharan &
Nishith Prakash
Introduction
Motivation
Background
Policy
Goals
Empirical Strategy
Methodology
Data
Data
Thank You
Thank You
21. Difference in Difference Design Karthik Muralidharan &
Nishith Prakash
Start with D-D type strategy Introduction
Motivation
Background
Policy
Goals
Empirical Strategy
Methodology
Data
Data
Thank You
Thank You
Enrollment - Boys
C
D
Enrollment/Test
Scores
B
IMPACT
A Comparison group trend
Enrollment-Girls
Pre- Cycle Scheme Post- Cycle Scheme
Year = 2006/07 Year = 2009/10
22. Enrollment in Bihar: Class 9 Karthik Muralidharan &
Nishith Prakash
Introduction
Motivation
Background
Policy
Goals
Empirical Strategy
Methodology
Data
Data
240,000 Thank You
220,000 Thank You
200,000
180,000
160,000
Enrollment
140,000
120,000
100,000
80,000
60,000
40,000
20,000
0
2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10
Enrollment (Class 9) Boys Enrollment (Class 9) Girls
23. Enrollment in Bihar: Class 10 Karthik Muralidharan &
Nishith Prakash
Introduction
Motivation
Background
Policy
Goals
Empirical Strategy
Methodology
Data
Data
200,000
Thank You
180,000 Thank You
160,000
140,000
120,000
Enrollment
100,000
80,000
60,000
40,000
20,000
0
2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10
Enrollment (Class 10) Boys Enrollment (Class 10) Girls
26. Data work so far Karthik Muralidharan &
Nishith Prakash
Introduction
Ministry of HRD, Government of Bihar Motivation
We have enrollment data for class 9 and 10 from Background
26 districts (2 incomplete) in Bihar, and 9 districts Policy
Goals
(3 incomplete) in Jharkhand from 2002/03 to
Empirical Strategy
2009/10 Methodology
District names in Bihar that have not sent Data
data: Aurangabad, Begusarai, Bhojpur, Data
Gopalganj, Khagaria, Kaimur, Lakhisarai, Patna, Thank You
Thank You
Purnea, Muzaffarpur, Saran, Siwan
District names in Bihar with incomplete data:
Vaishali, Dharbhanga
District names in Jharkhand with incomplete
data: Sahibganj, Palamu, Godda
Examination Board Data from Bihar and
Jharkhand
Detailed test scores data at individual level,
school level, and district level from 2004 to 2010
27. Thank You Karthik Muralidharan &
Nishith Prakash
Introduction
Motivation
Background
Policy
Goals
Empirical Strategy
We are grateful to the IGC-Bihar for providing Methodology
Data
financial support Data
We are grateful to Government of Bihar and Thank You
Thank You
especially Ministry of HRD without whom we
could not have started this project
28. Introduction Existing Evidence Research Question Empirical Strategy Data Trend Trend
Women Reservation in Bihar and Children’s
Health Outcomes
Santosh Kumar & Nishith Prakash
University of Washington & Cornell University
Sep 19, 2011 /IGC Growth Week (LSE)
India-Bihar Country Session
29. Introduction Existing Evidence Research Question Empirical Strategy Data Trend Trend
Motivation
• About 50 percent of world’s population are women
• However, their participation in political process is far below
than parity
• As per the latest estimate, women are accounted for
approximately 18.4% of parliamentarians worldwide (IPU,
2008)
• Barriers to political participation includes:Institutional
barriers; Cultural norms; Voter discrimination; Low
education
30. Introduction Existing Evidence Research Question Empirical Strategy Data Trend Trend
Motivation
• Many countries have adopted electoral gender quotas to
prevent the political under-representation of women
• Decentralization of governance
• Gender or minority reservation of political elected positions
is to improve targeting of developmental and welfare
programs to women and vulnerable groups.
31. Introduction Existing Evidence Research Question Empirical Strategy Data Trend Trend
Context
• In 1993, India introduced quota-based political reservations
for women in rural areas (73rd Constitutional Amendment)
• One of the broad objective was-
• To promote gender equality in human development by
making rural service provision and local governance
“inclusive” and “responsive” to the needs of women
32. Introduction Existing Evidence Research Question Empirical Strategy Data Trend Trend
Efficacy of Gender quotas
• The efficacy of these policies is still disputed by many
policy makers around the world
• Pro:
• Such policies needed to correct pre-existing gender
inequalities
• Better targeting of development programs
• Against:
• Undemocratic, less effective leaders, and elite capturing
• More evidence needed to truly evaluate the impact of
affirmative policies
33. Introduction Existing Evidence Research Question Empirical Strategy Data Trend Trend
Existing Evidence
• Chattopadhyay & Duflo - Women leaders are more likely to
invest in drinking water facilities across rural India
• Some recent papers report public good investments by female
leaders either on non-water related goods (Munshi and
Rosenzweig, 2008)
• Bardhan et al. (2010) exploit within-village (over time) variation
in reservation in West Bengal and find no impact of female
reservation
• Beamen et al. insignificant effect on the quality of public good
(water, education, transport, fair price shop, public health
facilities)
34. Introduction Existing Evidence Research Question Empirical Strategy Data Trend Trend
Research Question
• Does women reservation in panchayats in Bihar improved
health outcomes?
• Studies the effect of political reservations in local
governments in favor of women
• Specifically, do districts with more female leaders perform
better compared to districts with fewer female leaders?
• Why Bihar?
• Geographic coverage: No other study has covered Bihar so
far; and it is important to examine whether findings of
existing studies are specific to their respective geographic
contexts.
35. Introduction Existing Evidence Research Question Empirical Strategy Data Trend Trend
Women Reservation in Bihar
• Bihar has been a laggard in implementing 73rd
Constitutional Amendment
• The first panchayat election was held in April 2001 after a
gap of 23 years
• Fifty per cent seats are reserved for women since the 2006
panchayat election
• No reservation in 2001 panchayat election for ”Ekal” or
”Solitary” position
36. Introduction Existing Evidence Research Question Empirical Strategy Data Trend Trend
Outcome Measures
• Most of the existing studies have analyzed availability of
public goods and services as the outcomes measure
• Very few of them have really looked at utilization of these
public goods and services as outcomes
• Outcomes analyzed in this study:
• Health care utilization: Ante-natal care (ANC 4)
• Children vaccination (DPT3, Measles), Institutional
deliveries
37. Introduction Existing Evidence Research Question Empirical Strategy Data Trend Trend
How to measure the causal impact?
• Policy was implemented state-wide, in all districts of Bihar
• All districts are treated, none in control
• Use Jharkhand districts or UP border districts as control
• Use the variation in the program intensity
38. Introduction Existing Evidence Research Question Empirical Strategy Data Trend Trend
Empirical Strategy- DID
Design 1: Employ double-difference (DID)
2007-08 (DLHS 3) 2001-02 (DLHS 2) Difference
Jharkhand (Control) A B A- B
Bihar (Treatment) C D C-D
Difference C-A D-B DID: C-D- (A-B)
Design 2: Exploit the variation in policy intensity
39. Introduction Existing Evidence Research Question Empirical Strategy Data Trend Trend
Data
• Household survey: 2nd and 3rd rounds District level
household survey
• DLHS 2 was conducted in 2001-02 (Pre-program period)
• DLHS 3 was conducted in 2007-08 (Post-program period)
• Panchayat-level will be collected from Ministry of
Panchayati Raj, Govt of Bihar
40. Introduction Existing Evidence Research Question Empirical Strategy Data Trend Trend
Trend in health outcomes in Bihar
• ANC utilization, Children’s Immunization and Institutional
deliveries have increased tremendously from 2002- 2008
in Bihar
• Percent increase vary across districts
41. Introduction
10
20
30
40
50
0
Bihar
Araria
Aurangabad
Banka
Existing Evidence
Begusarai
Bhagalpur
Bhojpur
Buxar
Darbhanga
Gaya
Gopalgunj
Jamui
Jehanabad
Kaimur
Katihar
Khagaria
Kishangunj
Lakhisarai
Madhepura
Madhubani
Research Question
Munger
Muzaffarpur
Nalanda
Nawada
West Champaran
Patna
East Champaran
Purnea
Rohtas
Saharsa
Samastipur
ANC utilization
Saran
Sheikpura
Sheohar
Sitamarhi
Empirical Strategy
Siwan
Supaul
Vaishali
Data
Women receiveing at least
Women receiveing at least
three visits for ANC DLHS 3
three visits for ANC DLHS 2
Trend
Trend
44. Introduction Existing Evidence Research Question Empirical Strategy Data Trend Trend
Future work
• To establish the causal effect of women reservation on
these health outcomes
• To identify the causes of heterogeneous performance of
districts in Bihar
45. Introduction Existing Evidence Research Question Empirical Strategy Data Trend Trend
Thank You
• We are grateful to the IGC-Bihar for providing financial
support
46. Education Policies and Practices: What
Have We Learnt and the Road Ahead
Nishith Prakash & Priya Ranjan
Cornell University & University of California-Irvine
September 19, 2011 / IGC Growth Week - LSE
47. Objective of the Paper
• Survey the literature on the effectiveness of
education policies adopted in different parts of the
world to improve both the “quantity” and “quality”
of education.
• Survey the policies adopted by the government of
Bihar towards improving educational outcomes in
the state.
– Place these policies appropriately in our broader
survey framework to make this work a contextual
survey.
• Identify best practices in education policies and
make policy recommendations for Bihar
48. Status of Education in Bihar:
Quantity measures
Out of School Rate (source: ASER)
Gross Enrollment Ratio (DISE)
Net Enrollment Ratio (DISE)
In all graphs-
Dashed lines – minimum and maximum of all states with non-missing data
Solid black line – median of all states with non-missing data
Solid red line – Bihar
49. Status of Education in Bihar
Out of school rate, by gender
Male Female
.3
.2
.1
0
2007 2008 2009 2010 2007 2008 2009 2010
50. Status of Education in Bihar
Out of school rate, by age group
5 to 7 8 to 10
.3
.2
.1
0
2007 2008 2009 2010 2007 2008 2009 2010
11 to 13 14 to 16
.3
.2
.1
0
2007 2008 2009 2010 2007 2008 2009 2010
55. Summary of Evidence on Quantity
• Out of school rate higher than the median, but
declining over time and converging to the
median
– Gap with the best performing states significant
• Enrolment ratio at primary level above the
median starting in 2006-07
– Near universal primary enrolment
• Enrolment ratio at upper primary level still
very low (right at the bottom in India)
56. Status of Education in Bihar:
Quality measures
Can read long paragraph,
Can solve division problem
(Source: ASER)
57. Status of Education in Bihar
Can read long paragraph, by gender
Male Female
0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
2007 2008 2009 2010 2007 2008 2009 2010
58. Status of Education in Bihar
Can read long paragraph, by class
Std I Std II Std III Std IV
0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
2007 2008 2009 2010 2007 2008 2009 2010 2007 2008 2009 2010 2007 2008 2009 2010
Std V Std VI Std VII Std VIII
0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
2007 2008 2009 2010 2007 2008 2009 2010 2007 2008 2009 2010 2007 2008 2009 2010
59. Status of Education in Bihar
Can solve division problem, by gender
Male Female
0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
2007 2008 2009 2010 2007 2008 2009 2010
60. Status of Education in Bihar
Can solve division problem, by class
Std I Std II Std III Std IV
0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
2007 2008 2009 2010 2007 2008 2009 2010 2007 2008 2009 2010 2007 2008 2009 2010
Std V Std VI Std VII Std VIII
0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
2007 2008 2009 2010 2007 2008 2009 2010 2007 2008 2009 2010 2007 2008 2009 2010
61. Summary of evidence on quality
• In “reading” Bihar slightly below the median
– Looking at reading by class, Bihar seems to be
above the median in all classes
• In math skills, Bihar very close to the median
– Again, looking at math skills by class, Bihar seems
to be above the median for all classes
• In both reading and math skills, the gap with
the best performers is substantial
– Some evidence of narrowing of gap in recent years
– In absolute terms, not very satisfactory
62. Proximate Determinants of Low Schooling Attainment:
Schooling Inputs
pupil-teacher ratio,
student-classroom ratio,
no. of teachers per school,
% schools with common toilet,
% schools with girls’ toilet,
% schools with drinking water facility
Source: DISE
63. Summary of evidence on schooling inputs
• Primary schools
– Highest pupil-teacher ratio as well as student-
classroom ratio among Indian states
– Number of teachers per school low, but has
become higher than the median
– % of schools with toilets or separate girls toilet
well below the median
– Surprisingly, % of schools with drinking water
facility has gone down from above median to
below it
• Somewhat similar story for upper primary schools
64. Overall summary
• Bihar has made substantial progress on the “quantity” front at
primary level
• Enrolment at upper primary level still very low
• In reading and math, Bihar’s performance satisfactory in
relative terms, but weak in absolute terms
– For example, 30% of students in class VI could not read a
paragraph taken from a class II textbook
– 50% of class V students cannot solve a simple division
problem
• Record on the schooling input front weak in both relative and
absolute terms
• Quantity – Quality trade off?
71. IGC India – State of Bihar
Development Priorities of the
Government of Bihar and
Consequent Research Possibilities
Aishani Roy
IGC India – State of Bihar
72. IGC India – State of Bihar
Objective
• Acquaint us with the objectives and goals
stated by the government in their mission
documents.
• Try and identify principle areas of research
that might be of interest to the government.
• Match the identified areas with the
appropriate themes as stated by the IGC.
73. IGC India – State of Bihar
Themes
Water
State Capabilities - Power Roads
Resources
Urba
Agriculture Rural
nizati
and Allied Non
Migration on
Farm
Health Governance
Service Delivery &
Social Inclusion - Food
Education
security
74. IGC India – State of Bihar
Agenda
• Agriculture
– Low productivity – role of institutional challenges, minimum
support price, credit availability, diversification of livelihood
patterns
• Infrastructure and Urbanization
– Decentralized Renewable Energy (Husk Power Systems,
Barefoot Solar Engineers), Captive Power Policy, Roads
• Natural Resources
– Water Resources Management, Irrigation
• Human Capital
– Health, Education, Migration
• State Capabilities
– Rural Development, Food Security
• Governance
75. Food Security - some numbers
2005 2011
• National Sample Survey • Ratio of Purchases to
and Food Corporation Entitlements (2011)
of India data on Offtake
Diversion Rate • Nationwide Sample
Average – 84%
• Best – Tamil Nadu 7% • Best – Chhatisgarh,
• National Average – 54% Andhra Pradesh - >90%
• Bihar – 92% • Bihar – 45%
76. IGC India – State of Bihar
Objectives of Bihar Government
• A state level BPL commission will be constituted which will identify all BPL
families and redress their grievances with this respect.
• All the BPL families will be provided with food grains or equivalent cash in its
lieu.
• By running the procurement activities through all the Primary Agricultural
Cooperatives (PACSs) of the state, the produce of farmers will be procured
easily, paying the minimum support price to them.
• By strengthening the institutions involved in the activity of procurement as
well as the PDS, their working capacity and coverage will be adequately
enhanced.
• Developing the storage capacity in the state, concrete shape will be given to
full potential of procurement
77. IGC India – State of Bihar
Who are the players?
Clients Providers State
• BPL families Intermediaries through which the •Regulation
grains reach the targeted
• BPL + APL households. •Monitoring and
families accountability
•Individual suppliers through state
• Everyone instituted Fair Price Shops •Ensure that grains
(Universalized reach the targeted
PDS) •Community based supply models households from the FCI
(Primary Agricultural godowns
Cooperatives)
•Ensure that the
•Private sellers beneficiaries are
correctly identified
78. IGC India – State of Bihar
Client
• How will the government ensure proper identification of
the beneficiaries?
– Recommendations of the N.C Saxena Committee
– Is there a reliable way to identify poor households based on
proxy indicators?
• Is targeting divisive?
– Prevents emergence of united public demand for a functional
PDS
– Tamil Nadu – Universalized PDS – consistent good performer
• In the absence of adequate identification measures – what
are the arguments regarding the feasibility of universalizing
the PDS?
– Chhattisgarh – 80% coverage
– Estimated cost – 1 lakh crore (1.5% of GDP)
79. IGC India – State of Bihar
Provider
Problems Measures
Duplicity of Coupons are being bar coded. Bar code will be a
food coupons mix of Customer BPL card,Unique coupon, Dealer
shop
Illegal Sale at • Coupons for the whole year will be distributed
the in camps with tight surveillance (Century Rice
distribution Festivals – Bihar)
level • Strict accountability measures for errant
officials.
Quality of Coupons can be used to buy essential
food grains commodities from any shop
80. Provider - Questions
• Who will be the final seller of subsidized
essentials to minimize diversion?
– Single owners through Fair Price Shops ?
– Community based models (Primary Agriculture
Cooperatives)? Will procurement and distribution
of essentials be less prone to leakage, diversion
and scams?
– Private stores ? Food coupons can be used to
purchase from any shop – will it ensure quality of
grains?
81. State : Chhattisgarh Model
Role Practice
Correctly identify •Not using UID but entire beneficiary database
beneficiary digitized by NIC
households and •Bogus cards are being eliminated through door to
ensure effective door physical verification
targeting
Ensure that grains • Does not allot distribution to individuals but to a
reach the targeted PAC or self help groups
households from •Use vehicles for transportation of foodgrains
the FCI godowns directly to PDS shops and message would be
circulated to targeted people via sms.
•Does not use food coupons
82. IGC India – State of Bihar
State - Questions
• The finance minister of Bihar talked about
emulating the Chhattisgarh model – will that
mean a shift from the current system of Food
coupons?
• Success of conditional cash transfers ( Bicycle
Yojana, Uniform Scheme, kerosene) – replace
subsidy with cash transfers? (As mentioned in the
manifesto – ‘’All BPL families will be provided
with subsidized food grains or equivalent cash in
its lieu.” )
