Although the theoretical trade-off between the quantity and quality of children is well-established, empirical evidence supporting such a causal relationship - particularly on child health - is limited. We use two measures of child health to asses the quantity-quality trade-off across the entire...

We characterize the bias of propensity score based estimators of common average treatment effect parameters in the case of selection on unobservables. We then propose a new minimum biased estimator of the average treatment effect. We assess the finite sample performance of our estimator using...

Researchers in economics and other disciplines are often interested in the causal effect of a binary treatment on outcomes. Econometric methods used to estimate such effects are divided into one of two strands depending on whether they require the conditional independence assumption (i.e.,...

The empirical effects of place-based tax incentive schemes designed to aid low income communities are unclear. While a growing number of studies find beneficial effects on employment, there is little investigation into other behaviors of households affected by such programs. We analyze the...

Food security and obesity represent two of the most significant public health issues. However, little is known about how these issues are intertwined. Here, we assess the causal relationship between food security during early childhood and relatively long-run measures of child health....

Estimation of the causal effect of a binary treatment on outcomes often requires conditioning on covariates to address selection on observed variables. This is not straightforward when one or more of the covariates are measured with error. Here, we present a new semi-parametric estimator that...

We characterize the bias of propensity score based estimators of common average treatment effect parameters in the case of selection on unobservables. We then propose a new minimum biased estimator of the average treatment effect. We assess the finite sample performance of our estimator using...

Researchers in economics and other disciplines are often interested in the causal effect of a binary treatment on outcomes. Econometric methods used to estimate such effects are divided into one of two strands depending on whether they require the conditional independence assumption (i.e.,...