We exploit the size of the 2010 Ecuadorian Census to estimate the effect of remittances on secondary school enrollment across four key dimensions: gender, household wealth, rural vs. urban, and family migration status. Using a bivariate probit model that accounts for both endogeneity and non-linearity issues, we find both positive and negative effects of remittances on the likelihood of schooling. The strongest positive effects are for poorer, urban males, while the negative effects are for rural females. For children in wealthier households, the effects of remittances are either negative or non-significant. This suggests that the positive income effects of remittances may be offset by the negative effects of a missing parent due to migration, more visible in wealthier families where financial constraints may not be as binding. We find further support for this by estimating the effects of remittances conditional on migration status. Our results show positive effects on schooling for non-migrant households that receive remittances and no effects for children living in households where at least one parent has migrated. The sharp contrasts within and across groups, while using the same data and econometric specifications, help explain the lack of consensus in the literature.

We examine the impact of rural road construction on multidimensional poverty by using Nepal's Demographic and Health Survey and a difference‐in‐differences approach. We find reductions in deprivation, mainly driven by asset ownership and dwelling infrastructure, and small or non‐significant effects on health and education. Results are robust to different specifications and estimation methods, although we find heterogeneity across groups and dimensions. We argue that the heterogeneity might be driven by labour characteristics, infrastructure requirements, time considerations; and risk assessment and decision‐making practices. Our work highlights the importance of multidimensional measures to assess poverty and to evaluate infrastructure projects. Copyright © 2017 John Wiley & Sons, Ltd.

Smoking is the leading cause of avoidable death and is associated with type 2 diabetes (T2D) risk. Previous studies on the impact of passive smoking have not been applied to a Hispanic-majority population. We investigated the association between active smoking, exposure to environmental tobacco smoke (ETS), and pre-diabetes risk in a New Mexico population. We hypothesized that pre-diabetes risk increases with increasing smoking status after adjustment for important covariates. We screened 219 adults from an ongoing study who were categorized according to their smoking status (never smoker, current smoker, previous smoker) and their exposure to ETS (exposed or unexposed). Glucose homeostasis status was assigned using A1c: no diabetes (A1c <5.7%), pre-diabetes (A1c 5.7-6.4%), and T2D (A1c >6.4%). Among 160 patients with complete data, 51.6% had no diabetes and 48.4% had pre-diabetes. The mean age was 44.8±13.5 years. The study population was predominantly female (64.4%), and the ethnic composition was 44.4% Hispanic, 39.4% non-Hispanic White (NHW), 10.6% American Indian, 2.5% African-American, and 3.1% other. Using a logistic model with 2-way interactions, all predicted probabilities for being at risk for pre-diabetes were significant at the 0.001 level for smoking status and ETS exposure after adjusting for age, sex, ethnicity, family history of diabetes, alcohol consumption, BMI, and blood pressure. Active or passive smoking is independently associated with pre-diabetes risk.

No abstract