Performance Pay and Malnutrition: Evidence from an

Experiment targeting Child Malnutrition in West Bengal

Prakarsh SinghAmherst College/University of Pennsylvania

Sandip Mitra Indian Statistical Institute

RAND Health Seminar, 13th April 2015

Motivation-IChild undernutrition in India

• An estimated 1.27 million children die in India every year due to malnutrition

• Malnutrition levels are higher than in Sub-Saharan Africa and have remained relatively stagnant despite rapid economic growth

• Undernutrition related strongly to higher child mortality and lower labor productivity

Motivation-IIPublic economics and incentives

• Performance pay appears to have a positive effect on productivity of workers in the private sector (Lazear, 2001)

• Little evidence on impact of performance pay in the public sector in health in developing countries

• Rare to find an exogenous change in compensation schemes and a contemporaneous control group

• Mullen et al. (2010) find no adverse impact on quality in a P4P program in California but higher bonuses lead to better outcomes

• Review by Hasnain, Manning and Pierskalla (2012) for developing countries: The two studies they cite in this sub-field are Basinga et al. (2011) in Rwanda and Singh (2015) in India

Motivation – IIIHealth, incentives and development

• In developing countries, the role of performance pay to health providers is still in its infancy and there is scant evidence on howto optimally structure contracts on the supply-side (Miller and Babiarz, 2013).

• Performance incentives based on outcomes can help local providers use their knowledge productively even though the outcome is only partly under the control of the provider.

• Health outcomes can often be costly to measure as compared to inputs and providers may lackknowledge and skills to work towards obtaining the performance bonus.

• In our context, it is difficult to measure inputs objectively as the demand-side could collude with the providers when reporting their effort.

• Performance pay can be based on piece rates where a payout is linked to only individual productivity or output

• Marginal effects of piece rates are under-studied

• Aims of the project– Test for gradient of performance with respect to

absolute performance pay in the public sector– Test for the difference between a basic level of

absolute and relative performance pay

Incentive arms and control group

1. Basic Absolute Treatment2. High Absolute Treatment3. Basic Relative Treatment4. Control group

Background

• There are 1.31 million child day care centers in India under the Integrated Child Development Services (ICDS), a government-sponsored program.

• Each center is staffed by a childcare worker who is responsible for supervising children between ages 3-6 years during day-time, providing themmid-day meals, teaching mothers about child nutrition, imparting non-formal pre-school education and facilitating health check-ups by doctors.

• Workers can affect health of the child through two channels:– Providing mid-day meals to children– Advising mothers on a nutritious diet

• Yet, leakage of food to non-beneficiaries and almost no guidance to parents (Gragnolati et al. 2005, Hungama Report, 2011)

• "Although communication for behavior change through the childcare worker is a crucial weapon in the fight against malnutrition, it appears that the information the worker is conveying to the mothers is not being communicated effectively enough to positively affect mothers' behavior."

• Quality of service delivery has often come under scrutiny with experts describing expenditure on the program as if going into a bottomless pit(Chaudhury et al. (2006) and Das and Hammer (2005)).

• 96 percent of the villages are served by these centers, although only 50 percent provide food on the day of survey and 19 percent of the mothers report that the center worker provides nutrition counselling (HUNGaMA report, 2011).

Setting

• In our context, workers employed by the West Bengal government in Maheshtala Municipality

• In Maheshtala, total population is close to 400,000 and 11% of the population is under 6 years of age (Census, 2001)

Unique features of the project

• Based entirely within one geographic block• Same institutional setting• Similar tasks, quality of infrastructure and wages• No endogenous selection in to the treatment• Exogenous treatments assigned at the same time

with a pure control group• Treatments randomly assigned at the cluster level

to minimize any spillover effects between centers [34 clusters, 209 centers]

Main results

• High absolute treatment reduces severe malnutrition by 6.3% points and significantly increases average weight

• Low absolute and relative treatments have no effects on weight

• High absolute treatment effect driven by boys

In the Public Sector

• Relative may dominate absolute performance pay because:– Shocks to output may be salient– Workers may be more risk averse (Buurman, Dur

and Bossche, 2009)

Theory

• Under risk neutrality, there is no difference between absolute and relative incentives (Lazear and Rosen, 1981)

• Under risk aversion and common shocks, relative incentives can dominate absolute incentives (Green and Stokey, 1983)

• The reason is that relative pay filters the common shock making agents face lower risk as compared to absolute pay

Framework

• Agents choose effort levels 0, 1 or 2• Two possible individual outputs: 0 and 1• One risk neutral principal, n risk averse agents

Production function

• If agent chooses 0 effort, output is 0. • If agent chooses effort = 1, he gets output = 1

with probability 0.5 and output 0 with probability 0.5.

• If agent chooses effort = 2, he gets output = 1.• Common shock with probability γ, in which

case output = 0 regardless of the effort level

Public sector assumption

• We assume that workers get paid a minimum utility even when they input effort = 0

• This is relevant in our context as these are public sector workers who are on fixed wages

Results and Intuition

• The cost to principal of implementing high effort levels = 2 for all agents under a relative treatment does not depend on γ (immune to common shock)

• The cost to principal of implementing high effort levels = 2 for all agents under a absolute treatment increases with γ (no longer immune to common shock)

𝑈=ln (𝑥 )𝑈=𝑥1/2

𝑈=𝑥1/5

γ

Cost

Results and Intuition

• The cost of implementing relative and an absolute scheme is the same when there is no common shock

• However, when there is a common shock, relative treatment always dominates the absolute treatment with risk averse agents

• This is a surprising result that comes from combining the public sector assumption with existing theory on common shocks

How is malnutrition measured?

• Moderate (more than 2 SD away from the WHO sex-specific weight-for-age mean)

• Severe (more than 3 SD away from the WHO sex-specific weight-for-age mean)

• All Workers given goal cards listing target weights for each child in their AWC.

• Goal was the threshold for moderate if child is severely malnourished and normal if child is moderately malnourished

• If child was normal, a maximum threshold was provided below which the child would become malnourished

Absolute Incentives

• N for each worker = # children who jump at least one grade - # children who drop at least one grade in an Anganwadi

• What if more children get worse? [Solution: ignore if N<0]

• Payout in Basic Absolute = Rs. 100 * N• Payout in High Absolute = Rs. 200 * N

• AWW Salary is Rs. 4350 ($79.10) in Kolkata and increases to Rs. 4413 ($80.24) if she has 10 years of service.

• The average payout in Chandigarh for the basic absolute incentive with recipe book had been Rs. 291 per worker ($5.30) but worker salary was Rs. 2000 per month ($36.36) in 2010.

Relative Incentive

• N for each worker = # children who jump at least one grade - # children who drop at least one grade

• Let T = sum of all positive N in that treatment group

• Payout = 55 workers * 291 * (N/T) = 16000 (N/T)

• Manual randomization of clusters through slips by a lottery into 4 boxes.

• This process was to be carried out till each box had at least 50 centers allocated to it.

• When the total number of centers would cross 50, the assistant was asked to shut the box.

Groups

• Basic Absolute Incentive + Recipe Book – [50 AWCs/8 clusters]

• High Absolute Incentive + Recipe Book– [53 AWCs/8 clusters]

• Basic Relative Incentive + Recipe Book– [55 AWCs/8 clusters]

• Control group (no incentive or recipe book)– [51 AWCs/10 clusters]

Timeline

• Baseline: March – May, 2012 • Endline: August – September, 2012• At Baseline and Endline – a team of

enumerators measured weights of children, interviewed their mothers and Anganwadi workers

Summary statistics Normalized DifferencesVariables BA HA BR C BA-C HA-C BR-CMother's age 28.09 27.64 27.38 27.47 0.08 0.02 -0.01 [5.11] [5.43] [5.23] [5.67] Mother can read 0.73 0.67 0.75 0.73 0.00 -0.09 0.03 [0.44] [0.47] [0.43] [0.44] Monthly income 4556.27 4059.73 4400.02 3867.94 0.19 0.05 0.19 [2608.34] [2567.92] [2823.25] [2513.68] Number of rooms 1.43 1.39 1.43 1.40 0.02 -0.01 0.02 [1.08] [0.88] [0.90] [0.87] Mobile phone 0.84 0.66 0.83 0.66 0.30 0.00 0.28 [0.37] [0.47] [0.37] [0.47] Water tap at home 0.35 0.14 0.18 0.14 0.35 0.00 0.08 [0.48] [0.35] [0.39] [0.35] Weight of child 13.65 13.45 13.62 13.49 0.05 -0.01 0.04 [2.05] [2.09] [2.28] [2.10] Age of child 4.23 4.21 4.23 4.18 0.04 0.03 0.04 [0.83] [0.84] [0.81] [0.85] Fraction female 0.51 0.52 0.50 0.50 0.01 0.03 0.00 [0.50] [0.50] [0.50] [0.50] Total Siblings 1.29 1.15 1.21 1.43 -0.07 -0.15 -0.12 [1.35] [1.29] [1.26] [1.30] Toilet in AWC 0.39 0.30 0.49 0.39 0.00 -0.13 0.14 [0.48] [0.46] [0.50] [0.49] Drinking water in AWC 0.68 0.67 0.80 0.74 -0.09 -0.11 0.10 [0.47] [0.47] [0.40] [0.44]

• Mother’s age, monthly income, occupation, child’s age, child’s weight: similar to Chandigarh

• Mother’s literacy is 30% points higher in Maheshtala

• Ownership of mobile phones (high) and water filters (low): similar to Chandigarh

Attrition

BA HA BR C

Baseline children 1333 1555 1369 1264

Endline children 971 1127 1031 933

Attrition (%) 0.27 0.28 0.25 0.26

Specification

weightict = αpostt + Σβitreatmentc + Σγipostt*treatmentc + θict + ε ict

ict = {individual, cluster, time}

γi = difference-in-difference estimates of treatments 1, 2 or 3

θict = individual-level and anganwadi-level controls

Table 2: Main Results without Control Variables(1) (2) (3) (4)

Weight Malnourished Grade Severe Malnourished

Post 0.283*** -0.00291 0.00517 0.00807(0.0611) (0.0206) (0.0249) (0.00835)

Basic Absolute (BA) 0.165 -0.0123 -0.0413 -0.0289(0.234) (0.0355) (0.0521) (0.0186)

High Absolute (HA) -0.0411 0.0195 0.0290 0.00946(0.168) (0.0247) (0.0409) (0.0191)

Basic Relative (BR) 0.126 -0.0231 -0.0404 -0.0172(0.173) (0.0318) (0.0491) (0.0202)

Post*BA -0.154 -0.00809 -0.00205 0.00604(0.153) (0.0258) (0.0346) (0.0149)

Post*HA 0.191** -0.0465 -0.0953** -0.0488**(0.0899) (0.0301) (0.0444) (0.0189)

Post*BR 0.107 0.00682 -0.00385 -0.0107(0.0842) (0.0239) (0.0300) (0.0136)

Constant 13.49*** 0.331*** 0.416*** 0.0848***(0.127) (0.0172) (0.0301) (0.0142)

Observations 9376 9376 9376 9376

Table 3: Main Results with Control Variables(1) (2) (3) (4)

Weight Malnourished Grade Severe Malnourished

Post 0.271** 0.0234 0.0317 0.00830(0.114) (0.0363) (0.0416) (0.0121)

Basic Absolute (BA) 0.0954 -0.0117 -0.0401 -0.0284(0.155) (0.0304) (0.0453) (0.0178)

High Absolute (HA) 0.176 -0.0174 -0.0177 -0.000215(0.126) (0.0227) (0.0373) (0.0182)

Basic Relative (BR) 0.0193 0.00793 -0.0160 -0.0239(0.145) (0.0372) (0.0512) (0.0187)

Post*BA 0.0398 0.00229 0.00103 -0.00126(0.176) (0.0430) (0.0551) (0.0194)

Post*HA 0.253* -0.0557 -0.119** -0.0630***(0.130) (0.0405) (0.0502) (0.0175)

Post*BR 0.225 -0.0439 -0.0530 -0.00906(0.141) (0.0437) (0.0518) (0.0156)

Constant 8.688*** 0.0624 -0.0232 -0.0856(0.341) (0.0695) (0.110) (0.0694)

Control Variables x x x x

Observations 5342 5342 5342 5342

Placebo Check

VARIABLES Weight

Basic Absolute (BA) 0.351(0.269)

High Absolute (HA) 0.016(0.192)

Basic Relative (BR) 0.223(0.206)

Placebo Post 0.291**(0.111)

Placebo Post*BA -0.187(0.163)

Placebo Post*HA -0.061(0.163)

Placebo Post*BR -0.094(0.183)

Constant 13.202***(0.110)

Observations 10021

Robustness checks

• Results robust to controlling for reversion-to-the-mean, pre-trends, Moulton correction, Lee bounds and Propensity Score Matching

• Do not find selective targeting (perhaps due to disincentive for lowering weights)

• Iron supplementation and deworming drugs have been amongst the most effective in reducing malnutrition.

• Bobonis et al. (2006) find that an increase in weight of 0.5 kg in five months for 2-6 year old slum children in Delhi due to iron supplementation and deworming.

• In the HA treatment, the average weight gain per month is 84 gms as opposed to 100 gms per month in the iron and deworming treatment.

• The cost for our treatment is much lower than the World Bank (2006) figures for a nutrition education program of $2.50 per person per year at $1.80 per child per year.

• The estimated net benefit-cost ratio for the HA treatment turns out to be 12.8.

Diminishing returns of repeated treatments

• Mechanical diminishing returns due to fewer remaining malnourished children in the Anganwadi.

• Participation rates (and thereby wages) are unlikely to increase as a child becomes normal weight.

• Biological diminishing returns as the body adapts to increased calorie intake.

• Workers may need to be motivated with higher incentives if their intrinsic motivation keeps getting crowded out.

Table 8: Main Results for Girls after including Control Variables(1) (2) (3) (4)

Weight Malnourished Grade Severe Malnourished

Post 0.359** 0.00229 0.00207 -0.000212(0.137) (0.0479) (0.0593) (0.0159)

Basic Absolute (BA) 0.167 -0.0394 -0.0983 -0.0589**(0.198) (0.0424) (0.0601) (0.0223)

High Absolute (HA) 0.255* -0.0278 -0.0699 -0.0421*(0.147) (0.0334) (0.0513) (0.0221)

Basic Relative (BR) 0.157 -0.0111 -0.0693 -0.0582**(0.176) (0.0476) (0.0647) (0.0228)

Post*BA -0.0711 0.0245 0.0373 0.0128(0.171) (0.0542) (0.0705) (0.0272)

Post*HA 0.0984 -0.0204 -0.0566 -0.0361(0.173) (0.0531) (0.0661) (0.0215)

Post*BR 0.239 -0.0358 -0.0424 -0.00659(0.175) (0.0589) (0.0731) (0.0220)

Constant 7.399*** 0.191** 0.191 -0.000154(0.475) (0.0922) (0.136) (0.0818)

Control Variables x x x x

Observations 2748 2748 2748 2748

Table 9: Main Resultsfor Boys after including Control Variables(1) (2) (3) (4)

Weight Malnourished Grade Severe Malnourished

Post 0.173 0.0488 0.0661 0.0174(0.130) (0.0321) (0.0508) (0.0300)

Basic Absolute (BA) 0.0289 0.0131 0.0111 -0.00196(0.201) (0.0371) (0.0527) (0.0208)

High Absolute (HA) 0.0901 -0.00723 0.0315 0.0387(0.204) (0.0331) (0.0485) (0.0247)

Basic Relative (BR) -0.150 0.0328 0.0450 0.0123(0.185) (0.0396) (0.0561) (0.0211)

Post*BA 0.150 -0.0220 -0.0361 -0.0141(0.220) (0.0439) (0.0727) (0.0396)

Post*HA 0.428*** -0.0966** -0.189*** -0.0920**(0.148) (0.0406) (0.0627) (0.0350)

Post*BR 0.205 -0.0548 -0.0645 -0.00973(0.156) (0.0380) (0.0557) (0.0312)

Constant 9.707*** -0.0945 -0.302* -0.207**(0.513) (0.116) (0.158) (0.0784)

Control Variables x x x x

Observations 2594 2594 2594 2594

Table 12: Gender Difference(1) (2) (3) (4)

Weight Malnourished Grade Severe Malnourished

Post*BA 0.142 -0.0226 -0.0339 -0.0113(0.216) (0.0428) (0.0712) (0.0391)

Post*HA 0.432*** -0.0989** -0.191*** -0.0924**(0.145) (0.0397) (0.0620) (0.0350)

Post*BR 0.219 -0.0548 -0.0682 -0.0133(0.164) (0.0371) (0.0548) (0.0307)

Gender*BA*Post -0.197 0.0475 0.0678 0.0203(0.163) (0.0469) (0.0887) (0.0548)

Gender*HA*Post -0.345* 0.0830* 0.140* 0.0567(0.193) (0.0483) (0.0780) (0.0435)

Gender*BR*Post 0.0188 0.0202 0.0283 0.00811(0.176) (0.0426) (0.0726) (0.0424)

Constant 8.784*** 0.0442 -0.0635 -0.108(0.349) (0.0699) (0.109) (0.0708)

Control Variables x x x x

Observations 5342 5342 5342 5342

(1) (2) (3) (4) (5)Pulses Fish Meat Green Sweet

Post -0.0523 0.0271 -0.0308 -0.0466 -0.123**(0.0435) (0.0470) (0.0499) (0.0362) (0.0516)

Basic Absolute (BA) 0.0617 0.122 0.0330 0.0900 -0.0252(0.0742) (0.0882) (0.0767) (0.0700) (0.0608)

High Absolute (HA) -0.117 0.0373 -0.0446 -0.0309 -0.0874(0.0931) (0.0872) (0.0815) (0.0906) (0.0648)

Basic Relative (BR) 0.0752 0.133 0.0183 0.0291 0.00818(0.0735) (0.105) (0.0701) (0.0730) (0.0793)

Post*BA 0.0797 -0.00203 0.101 0.0189 0.0607(0.0964) (0.100) (0.0989) (0.0914) (0.100)

Post*HA 0.217** 0.0169 0.127* 0.000472 -0.00706(0.0803) (0.106) (0.0716) (0.0876) (0.0706)

Post*BR 0.109 -0.102 0.0221 0.0342 -0.0183(0.0689) (0.0790) (0.0695) (0.0583) (0.111)

Constant 0.235 0.177 -0.156 0.345** 0.130(0.179) (0.166) (0.164) (0.152) (0.0972)

Control Variables x x x x x

Observations 5421 5430 5446 5441 5328

Table 7: Number of Visits with Control Variables(1) (2) (3)

Total Visits Worker Visits Home Visits

Post 0.548 0.128 0.412(1.272) (0.393) (0.889)

Basic Absolute (BA) -0.573 -0.113 -0.400(0.648) (0.237) (0.481)

High Absolute (HA) 1.032 0.716** 0.347(0.820) (0.264) (0.587)

Basic Relative (BR) 1.022 0.448 0.567(0.821) (0.346) (0.537)

Post*BA 0.651 0.176 0.429(1.695) (0.757) (1.035)

Post*HA -0.906 -0.380 -0.541(1.290) (0.406) (0.906)

Post*BR -0.726 -0.0807 -0.631(2.080) (0.905) (1.228)

Control Variables x x x

Constant 5.666*** 2.754*** 2.947***(0.978) (0.431) (0.655)

Observations 5365 5420 5397

Channels

• Food at home goes up for both boys and girls• Why does it go up? Recipe books + Worker

tells mothers to increase food at home [though she does not increase visits to home]

• Weight goes up only for boys• Food must have gone up for boys in the AWC

where workers have high absolute incentives

Why?

• Boys have greater appetite or ask for more (so are able to get more food from the incentivized worker)

• Expectation that boys will show more weight gain• Expectation that mothers will be less likely to cut

down on food for boys leading to complementarity

• A gender preference for food provision that gets accentuated with the incentives

Conclusion

• High Absolute incentive works to reduce malnutrition by about 6.5% points along with information to mothers and this effect is driven by the severely malnourished moving to moderately malnourished

• First order effects important but gender inequality may be exacerbated

Related work• Informational Spillovers (Singh, 2014) • Training of workers and its interaction with the recipe

treatment in rural villages of Punjab (Singh, 2015) • Ongoing Gates Foundation project testing different

performance incentive schemes and informational spillovers in Chandigarh – Staggered phase-in of different incentive schemes to capture

long-run effects– Better measures of Intrahousehold allocation, food distribution

at centers and worker effort– Randomize the intensity of informational treatment by center

(No/Low/Medium/High)

Change in weight0

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ensi

ty

-5 0 5 10changeinweight

ControlBasic AbsoluteHigh Absolute

Basic Relative

kernel = epanechnikov, bandwidth = 0.1870

Kernel density estimate