Krishna, A., Mejía-Guevara, I., McGovern, M., Aguayo, V. M., & Subramanian, S. V. (2018).
Trends in Inequalities in Child Stunting in South Asia.
Maternal & Child Nutrition ,
S4 (14), e12517.
Publisher's VersionAbstractWe analysed socio-economic inequalities in stunting in South Asia and investigated disparities associated with factors at the individual, caregiver, and household levels (poor dietary diversity, low maternal education, and household poverty). We used time-series analysis of data from 55,459 children ages 6–23 months from Demographic and Health Surveys in Bangladesh, India, Nepal, and Pakistan (1991–2014). Logistic regression models, adjusted for age, sex, birth order, and place of residency, examined associations between stunting and multiple types of socio-economic disadvantage. All countries had high stunting rates. Bangladesh and Nepal recorded the largest reductions—2.9 and 4.1 percentage points per year, respectively—compared to 1.3 and 0.6 percentage points in India and Pakistan, respectively. Socio-economic adversity was associated with increased risk of stunting, regardless of disadvantage type. Poor children with inadequate diets and with poorly educated mothers experienced greater risk of stunting. Although stunting rates declined in the most deprived groups, socio-economic differences were largely preserved over time and in some cases worsened, namely, between wealth quintiles. The disproportionate burden of stunting experienced by the most disadvantaged children and the worsening inequalities between socio-economic groups are of concern in countries with substantial stunting burdens. Closing the gap between best and worst performing countries, and between most and least disadvantaged groups within countries, would yield substantial improvements in stunting rates in South Asia. To do so, greater attention needs to be paid to addressing the social, economic, and political drivers of stunting with targeted efforts towards the populations experiencing the greatest disadvantage and child growth faltering.
McGovern_2018_Maternal_Child_Nutrition.pdf McGovern, M., Canning, D., & Bärnighausen, T. (2018).
Accounting for non-response bias using participation incentives and survey design: An application using gift vouchers.
Economics Letters ,
171, 239-244.
Publisher's VersionAbstractStandard corrections for missing data rely on the strong and generally untestable assumption of missing at random. Heckman-type selection models relax this assumption, but have been criticized because they typically require a selection variable which predicts non-response but not the outcome of interest, and can impose bivariate normality. In this paper we illustrate an application using a copula methodology which does not rely on bivariate normality. We implement this approach in data on HIV testing at a demographic surveillance site in rural South Africa which are affected by non-response. Randomized incentives are the ideal selection variable, particularly when implemented ex ante to deal with potential missing data. However, elements of survey design may also provide a credible method of correcting for non-response bias ex post. For example, although not explicitly randomized, allocation of food gift vouchers during our survey was plausibly exogenous and substantially raised participation, as did effective survey interviewers. Based on models with receipt of a voucher and interviewer identity as selection variables, our results imply that 37% of women in the population under study are HIV positive, compared to imputation-based estimates of 28%. For men, confidence intervals are too wide to reject the absence of non-response bias. Consistent results obtained when comparing different selection variables and error structures strengthen these conclusions. Our application illustrates the feasibility of the selection model approach when combined with survey metadata.
McGovern_EL_2018.pdf Bloom, D., Chen, S., & McGovern, M. (2018).
The Economic Burden of Non-Communicable Diseases and Mental Health Conditions: Results for Costa Rica, Jamaica, and Peru.
Pan American Journal of Public Health ,
42 (e18).
Publisher's VersionAbstractObjectives
We extend the World Health Organization’s (WHO) EPIC model and apply it to analyze the macroeconomic impact of non-communicable diseases (NCDs) and mental health conditions in Costa Rica, Jamaica, and Peru.
Methods
The EPIC model quantifies the impact of NCDs and mental health conditions on aggregate output solely through the effect of chronic conditions on labor supply due to mortality. In contrast, the expanded EPIC-H Plus framework also incorporates reductions in effective labor supply due to morbidity and negative effects of health expenditure on output via the diversion of productive savings and reduced capital accumulation. We apply this methodology to Costa Rica, Jamaica, and Peru, and estimate the economic burden of all NCDs and mental health conditions in these countries.
Results
Overall, our results show total losses associated with these NCDs and mental health conditions over the period 2015–2030 of $81.96 billion 2015 USD for Costa Rica, $18.45 billion for Jamaica, and $477.33 billion for Peru. The costliest condition varies by country.
Conclusions
These results indicate that the economic impact of NCDs and mental health conditions is substantial and that interventions to reduce the prevalence of chronic conditions in Latin American countries are likely to be highly cost beneficial.
mcgovern_pajph.pdf