Lowering Child Mortality in Poor Countries: The Power of Knowledgeable Parents

Why do over 20% of children die in some poor countries, while in others only 2% die? We examine this question using survey data covering 278,000 children in 45 low-income countries. We find that parents' education and a mother's propensity to seek out modern healthcare are empirically important when explaining child survival, while the prevalence of common diseases, along with infrastructure such as improved water and sanitation, are not. Using a GINI coefficient we construct for treatment services, we find that public and private health systems are "equally unequal", that is, both tend to favor children in relatively well-off households, and neither appears superior at improving outcomes in very poor communities. These facts contrast with a common view that a much-expanded public health sector is necessary to reduce child mortality. Instead, we believe the empirical evidence points to the essential role of parents as advocates for their child's health. If we can provide better health knowledge and general education to parents, a private healthcare sector can arise to meet demand. We provide evidence that this alternative route to low mortality is indeed a reason behind the current success of many countries with low child mortality, including Vietnam, Indonesia, Egypt, and the Indian state of Kerala. Finally, we calculate a realistic package of interventions that target education, health knowledge and treatment seeking could reduce child mortality by 32%.

Local Composite Quantile Regression for Regression Discontinuity

We introduce the local composite quantile regression (LCQR) to causal inference in regression discontinuity (RD) designs. Kai et al. (2010) study the efficiency property of LCQR, while we show that its nice boundary performance translates to accurate estimation of treatment effects in RD under a variety of data generating processes. Moreover, we propose a bias-corrected and standard error-adjusted t-test for inference, which leads to confidence intervals with good coverage probabilities. A bandwidth selector is also discussed. For illustration, we conduct a simulation study and revisit a classic example from Lee (2008). A companion R package rdcqr is developed

Does Extending Unemployment Benefits Improve Job Quality? Comment

In contrast with a large body of existing literature, Nekoei and Weber (2017, NW henceforth) find a positive effect of unemployment insurance on job quality. This comment shows that NW's finding is driven by unnecessarily large bandwidths used in their regression discontinuity analysis. When the focus is on the data near the cutoff of the regression discontinuity design, the significantly positive effect documented in NW vanishes. Thus, re-examining NW's empirical analysis leads to results that are consistent with, rather than contrary to, many past studies. Our findings indicate the importance of using a range of bandwidths in future studies

Does Extending Unemployment Benefits Improve Job Quality? Comment

In contrast with a large body of existing literature, Nekoei and Weber (2017, NW henceforth) find a positive effect of unemployment insurance on job quality. This comment shows that NW's finding is driven by unnecessarily large bandwidths used in their regression discontinuity analysis. When the focus is on the data near the cutoff of the regression discontinuity design, the significantly positive effect documented in NW vanishes. Thus, re-examining NW's empirical analysis leads to results that are consistent with, rather than contrary to, many past studies. Our findings indicate the importance of using a range of bandwidths in future studies

The Impact of Rural Pensions in China on Labor Migration

We study the impact of China’s new rural pension program on promoting migration of labor by applying a regression discontinuity analysis to this new pension program. The results reveal a perceptible difference in labor migration among adult children whose parents are just above and below the age of pension eligibility: The adult children with a parent just attaining the pension-eligible age are more likely to be labor migrants compared with those with a parent just below the pension-eligible age. We also find that with a pension-eligible parent, the adult children are more likely to have off-farm jobs. These abrupt changes in household behavior at the cutoff suggest that these households are credit constrained. In addition, we find that the pension’s effect on migration is greater among adult children with a parent in poor health; pension-eligible elderly report that they are more likely to use inpatient services when needed and less likely to rely on adult children for care when they are ill. These results suggest that (expectations regarding) providing care for elderly parents has constrained labor migration from China\u27s rural areas to some extent, and that the new rural pension program has helped to relax this constraint

Lowering child mortality in poor countries: the power of knowledgeable parents

Why do over 20% of children die in some poor countries, while in others only 2% die? We examine this question using survey data covering 278,000 children in 45 low-income countries. We find that parents’ education and a mother’s propensity to seek out modern healthcare are empirically important when explaining child survival, while the prevalence of common diseases, along with infrastructure such as improved water and sanitation, are not. Using a GINI coefficient we construct for treatment services, we find that public and private health systems are “equally unequal”, that is, both tend to favor children in relatively well-off households, and neither appears superior at improving outcomes in very poor communities. These facts contrast with a common view that a much-expanded public health sector is necessary to reduce child mortality. Instead, we believe the empirical evidence points to the essential role of parents as advocates for their child’s health. If we can provide better health knowledge and general education to parents, a private healthcare sector can arise to meet demand. We provide evidence that this alternative route to low mortality is indeed a reason behind the current success of many countries with low child mortality, including Vietnam, Indonesia, Egypt, and the Indian state of Kerala. Finally, we calculate a realistic package of interventions that target education, health knowledge and treatment seeking could reduce child mortality by 32%

A medal share model for Olympic performance

A sizable empirical literature relates a nation\u27s Olympic performance to socioeconomic factors by adopting linear regression or a Tobit approach suggested by Bernard and Busse (2004). We propose an alternative model where a nation\u27s medal share depends on its competitiveness relative to other nations and the model is logically consistent. Empirical evidence shows that our model fits data better than the existing linear regression and Tobit model. Besides Olympic Games, the proposed model and its estimation method could also be similarly applied to other settings with competitions

Identification Robust Testing of Risk Premia in Finite Samples

The reliability of tests on the risk premia in linear factor models is threatened by limited sample sizes and weak identification of risk premia frequently encountered in applied work. We, therefore, propose novel tests on the risk premia that are robust to both limited sample sizes and the identification strength of the risk premia as reflected by the quality of the risk factors. These tests are appealing for empirically relevant settings, and lead to confidence sets of risk premia that can substantially differ from conventional ones. To show the latter, we revisit two high-profile empirical applications

Robust inference in structural VARs with long-run restrictions

Long-run restrictions are a very popular method for identifying structural vector autoregressions, but they suffer from weak identification when the data is very persistent, i.e., when the highest autoregressive roots are near unity. Near unit roots introduce additional nuisance parameters and make standard weak-instrument-robust methods of inference inapplicable. We develop a method of inference that is robust to both weak identification and strong persistence. The method is based on a combination of the Anderson-Rubin test with instruments derived by filtering potentially non-stationary variables to make them near stationary. We apply our method to obtain robust confidence bands on impulse responses in two leading applications in the literature