Enhancing nutrition security via India’s National Food Security act: Using an axe instead of a scalpel?

Sonalde Desai & Reeve Vanneman

Repeated Cross-Sections, Longitudinal Panels and Cohort Studies

• Description of changes over time• Useful snapshots when social/policy

changes taking place

Repeated Cross Section

• Effects of early life experiences on later outcomes

• Single cohort not suitable for studying social/policy changes

• Attrition a major challenge

Cohort Studies

• Combination of repeated cross-section and cohort studies

• Addition of new cohorts, within family analysis• Useful in changing context• Reinterviews major challenge, panels get old

Panel Studies of households

India’s National Food Security Act, 2013

Justification: High undernutrition and hunger

Solution: Two main pillars

Expansion of Public Distribution System (PDS) to cover 67% of the population for 5 kg of cereals at Rs. 1-3 per kg

Enhancement to Integrated Child Development Schemes (ICDS) to ensure children receive take home rations and hot cooked meals

Crucial Question:

Is NFSA the best strategy for addressing undernutrition?

Implicit assumptions:

GDP growth by itself is not sufficient.

Undernutrition is caused by hunger.

Therefore, solution is more calories.

Our empirical storyline

1. Our best estimate of current undernutrition. About 37% underweight

2. PDS use? Results presented here Increased cereal consumption,

Reduced milk & fruit consumption

No improvement in level of undernutrition

3. ICDS access? Results not presented, available on request.

Somewhat reduced undernutrition

But poor outreach

India Human Development Surveys I and II

Largest nationwide panel survey in India

Full rounds 2004-5 & 2011-12

83% recontact rate after 7 years

90% rural recontact

72% urban recontact

Similar questionnaires as IHDS-I

Urban sample refreshed by addition of 2,134 new households

IHDS-II (2011-12) Sample

33 States and UT

1474 villages and 988 urban

blocks

42,152 households

215,754 individuals

39,264 ever married

women 15-49

12,148 kids

age 8-11

12153 Youth

age 15-18

For this analysis the sample is:

1. 42,152 households for household based PDS analysis

2. 10,715 children ages 0-60 months for analysis of underweight, limited to:

Children for whom both month and years of birth are available

Whose weight-for-age z scores range from -6 to +5 SD

Public Distribution System (PDS)

Given to people holding ration cards for purchase through fair price shops

Subsidies for people holding Below Poverty Line (BPL cards)

PDS purchase by BPL card holders grew from 21% of the households in 2005 to 37% of the households in 2012 due to program expansion and increased efficiency in distribution

But still poorly targeted, allows for comparisons

Improvement in targeting & efficiency between 2005 and 2012

Use of PDS by poor households also increased

In 2004-5 poor households using PDS formed 20% of the population but by 2012 it was 37%

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Income Decile

Distribution of Households with BPL/Antyodaya Card by Income Decile

IHDS-I (2004-5)

IHDS-II (2011-12)

Leakage

40% excluded

Do we expect PDS to reduce malnutrition? From the literature..

Yes: increased caloric intake using NSS:

Lower decline in caloric consumption for the PDS users over time Himanshu and Sen (2013)

Higher caloric intake in areas where and when value of subsidy is higher Kaul (2014)

No: small or no impact on calories/weight:

Extremely low caloric elasticities (Kochar, 2005)

Introduction of TPDS did little to diminish nutritional outcomes in AP (Tarozzi, 2005)

But most of these studies are based on inadequate cross-sectional data

Propensity Score Matching:

Matching Households on:

State of residence, urban/rural residence, highest education level obtained by an adult above 21 in the household, household income and a squared term for income, number of adult equivalents in the households, number of married women in the household as a proxy for household structure as well as time availability, caste/religion categories (forward caste, OBC, SC, ST, Muslim, other religions), whether household has any toilet and whether it has indoor piped water.

When matching children add:

Child and mother characteristics including child’s gender, age, a dummy variable for infants, and number of children borne by the mother.

No improvement in weight for children from households that use PDS

PDS Users Non-Users Difference S.E. T-stat

Z score for weight-for-age

Matched -1.614 -1.542 -0.071 0.042 -1.70

Moderate Underweight (<2 SD)

Matched 0.400 0.373 0.027 0.013 2.01

Severe Underweight (<3 SD)

Matched 0.160 0.149 0.011 0.010 1.10

Two possible scenarios with PDS subsidies for cereals

Cheap Rice & Wheat

Substitution Effect

More calories from Cereals

Less calories from

fruits/milk

Income Effect

Same amount of cereal

consumption

Savings used for milk &

fruit

?

Age Adjusted Intake Per Person in matched sample

PDS Users

Non-Users

Difference S.E. T-stat

Quantity cereal (Kg)

Matched 20.473 19.276 1.197 0.166 7.19

Quantity milk (ltr)

Matched 4.372 5.254 -0.882 0.114 -7.77

But what if we are doing a poor job of matching?

PDS use is a function of program efficiency and household time availability

In many remote villages the PDS shops may not be available

Program use has been particularly poor in areas where most shopping is done by men

How do we match on unobservables?

Role of longitudinal data

2012 consumption for matched samples based on prior PDS use

Used PDS in 2012

Did not Use PDS in 2012

Difference

Cereal Consumption in 2012 (kg/mo per adult equivalent)

Used PDS in 2005 20.08 18.33 1.75

Did not Use PDS in 2005 20.73 19.61 1.12

Milk Consumption in 2012 (Ltr/Mo per adult Eqivalent)

Used PDS in 2005 3.95 4.10 -0.15

Did not Use PDS in 2005 4.41 5.37 -0.96

Key Debate: Is cash transfer better than food subsidy? (Law allows for cash transfers, strong govt. interest)

Possibly yes for food: A four country study by Hoddinott suggests that where markets function well, cash is likely to increase food security (Hoddinott 2013)

Possibly not so much for nutrition: An analysis of 15 programmes, combining conditional cash transfers and unconditional cash transfers, shows an average effect of 0∙04 in height-for-age Z score (Ruel and Alderman, 2013)

We really need better understanding of the key issues in the Indian context before undertaking any policy reformulation Classic Behrman and Deolalikar (1987) paper is a sobering reminder

that for India nutrient elasticity of income used to be near zero (and only .3-.4 for other countries)

Ongoing analysis compares the role of income gain to changes in PDS access in shaping… Household consumption patterns

Anthropometric growth curves for children over time