Minimum Wage Policies and Child Nutritional Status in LMICs

Ninez Ponce, MPP, PhDUCLA Center for Global and Immigrant Health

UCLA World Policy Analysis Center

Milan, ITALY | 15 July 2015Health Economics and NUTRITION

Coauthors

Riti Shimkada UCLA Center for Global & Immigrant Health

Amy Raub UCLA Center for World Health

Linda Richter Human Sciences Research Council

Arijit Nandi MACHEquity, McGill University

Adel Douad Max Planck Institute & University of Gothenburg

Jody Heymann UCLA Center for World Health

The Problem

Globally in 2013…

• 161 M under-five year olds were stunted (25%)• 2000 2013 stunting 33% 25%

• 51 M under-five year olds were wasted (8%)

• 45% of all child deaths are

linked to malnutrition ~2.8 M deaths

Sources: (Black et al. 2013); (UNICEF et al. 2014)

Sources: WHO & UNICEF

Focus on LMICs

• Low-income: GNI pc <$1,045 • Middle-income: GNI pc [$1,045, $12,746]

• In 2015 Italy $34,280, US $55,200 • Malawi $250 , Norway $103,050

4 Mal(under)nutrition Measures

1. Stunting: HAZ < - 2SD

– HAZ = Height-for-age Z-score

2. Underweight: WAZ < - 2SD

– WAZ = Weight-for-age Z-score

3. Wasting: WHZ < - 2SD

– WHZ = Weight for height Z-score.

4. Anthropometric Failure~ any of these indicators

• Based on WHO (2006) guidance on reference population and omission of outliers

Low wages poverty food insecurity undernutrition

Why Examine Minimum Wage Impacts in LMICs?

• Impact on undernutrition not overweight and obesity especially in young children

• Even small wage increases could have major impact on household finances of families living in poverty and economic hardship

• Increasing awareness of/interest in role of wage policies and health outcomes in LMIC, but we don’t know the effect

*Public Sector Health

Expenditures

**Minimum Wage Policies

*Gross National Income

Child Nutritional

Status

Access to Health Services

Child Characteristics

Links**MACHEquity & World Policy Analyisis Center; *World Bank WDI Database

Demographic & Health Surveys

Minimum Wage: Important Policy Lever, but Unknown Direction of Effect, If Any

• Employment impact– Exacerbates unemployment and thus eventually

exacerbates poverty?

• Impact on informal sector– Minimum wage not meaningful for the lowest-

wage workers in informal sector– However, Spillover from minimum wage to

informal sector has been observed in some LMIC (e.g. Latin America

• Worker displacement– Displaces workers, pushing them into the informal

sector where wages are lower

Only a Few Recent Studies on Minimum Wage Impact on Health

• Behavioral Risk Factor Surveillance System (BRFSS) from 1984-2006. – Gradual reductions over time in inflation-adjusted

minimum wages across states explain about 10% of the increases in average body mass since 1970.

• Panel Study of Income Dynamics (PSID) data used to examine wage and adult health outcomes.– Low wages predicted increases in the prevalence of

obesity and hypertension.

• Lack of studies in LMIC setting

Our Study: Examining link between Minimum Wage & Child Outcomes

• 2003-2012, a recent period spanning from before, through, and after the global economic crisis

• Minimum wage data from McGill’s MACHEquity, UCLA’s WORLD Policy Analysis Center: cross-national information on minimum wage levels, as set by policy, for all LMICs

• 23 LMIC for which at least two rounds of DHS data (between 2003-2012) on child anthropometrics were available

Malnutrition Prevalence in Children Under 523 LMIC countries

STUNTING FAILURE

WASTINGUNDERWEIGHT

Analysis• Primary Regressor: hourly minimum wage rates in purchasing

power parity (PPP) dollars—lagged 1y

• Primary Outcomes: anthropometric measures of stunting, underweight, wasting and a composite measure of anthropometric failure

• Covariates: variables from the child (age, gender, birth order), parent/household (education, relationship status, wealth index, employment, urban/rural), and country levels (GDP per capita, public sector health spending per capita, year of DHS survey)

• (3 level) LPM random intercept models: children nested in households nested in countries.

Findings• With a $1 dollar PPP increase in MW, on average,

all else equal, and accounting for random effects:– Stunting decreases by 1.36 percentage points from

the mean stunting rate of 33%. (arc elasticity =-.084)

– Failure decreases by 1.24 percentage points from the mean failure rate of 38%. (arc elasticity =-.072)

• Minimum wage’s protective effects against stunting and failure were also significant for children in the poorest quintile households. (arc elasticity =-.06 for stunting and -.05 for failure)

• For the full sample and for the poorest quintile, we observed no significant effect of previous year’s minimum wage policies on wasting, and underweight.

Inference• Modest effects compared to household income

elasticity of stunting (e=-.6 ; Alderman in Sahn 2015); GNI growth & stunting ( e= -.2 ; Heltberg PAHO).

• Though elasticities are smaller for poorest quintile that surely comprise most of the informal sector in LMICs, MW laws do have a favorable (not penalizing) effect.

• Effects are for 2 important nutritional outcome measures: stunting—chronic malnutrition and failure---a composite indicator of the malnutrition.

• This work highlights the potential contribution of income policies such as minimum wage legislation on improving population health, especially among poor children.

Study Limitations• Not able to obtain data on the

informal work sector

• Not able to collect information on other potential institutional confounders, such as which jobs are covered by the minimum wage or how well the minimum wage policy is enforced.

• We do not know whether the prevailing market wage is above the minimum wage and we cannot parse out the impact of gender.

This unobserved heterogeneity is partially addressed by specifying a set of model covariates that may explain these unmeasured labor market characteristics at the parent/household and country levels as well as by partitioning the variance at multiple levels.