Currently available asymptotic results in the literature suggest that matching estimators have higher variance than reweighting estimators. The extant literature comparing the finite sample properties of matching to specific reweighting estimators, however, has concluded that reweighting performs far worse than even the simplest matching estimator. We resolve these puzzling conclusions. Specifi...

Spending on big-time college athletics is often justified on the grounds that athletic success attracts students and raises donations. We exploit data on bookmaker spreads to estimate the probability of winning each game for college football teams. We then condition on these probabilities using a propensity score design to estimate the effects of winning on donations, applications, and enrollme...

Propensity score methods are increasingly being used to reduce or minimize the effects of confounding when estimating the effects of treatments, exposures, or interventions when using observational or non-randomized data. Under the assumption of no unmeasured confounders, previous research has shown that propensity score methods allow for unbiased estimation of linear treatment effects (e.g., d...

In medical research logistic regression and Cox proportional hazards regression analysis, in which all the confounders are included as covariates, are often used to estimate an adjusted treatment effect in observational studies. In the last decade the method of propensity scores has been developed as an alternative adjustment method and many examples of applications can be found in the literatu...

More than 124 governmental entities concerned about suburban sprawl and farmland loss have implemented farmland preservation programs preserving 1.67 million acres at a cost of $3.723 billion. Yet little analysis on these programs’ effectiveness in slowing farmland loss has been conducted. Using a unique 50-year 269 county panel data set on preservation programs and farmland loss for six Mid-At...

We use propensity scores to evaluate the effect of Food Stamps on food insecurity, a measure of inadequate food supply. Data come from the Early Childhood Longitudinal Study–Kindergarten Cohort. Propensity scores offer an advantage over traditional linear regression methods because they address omitted variable bias associated with Food Stamp use by matching similarly situated treatment and con...

Skills shortages and skill mismatch are a pressing concern for policymakers in several developing countries, and in East Asia specifically. Providing on-the-job training can be an effective policy tool to shape the skills of the existent workforce to the specific needs of the firms. This paper explores a unique data set of matched employer-employee data for Malaysia and Thailand to estimate the...

The internal validity of an observational study is enhanced by only comparing sets of treated and control subjects which have sufficient overlap in their covariate distributions. Methods have been developed for defining the study population using propensity scores to ensure sufficient overlap. However, a study population defined by propensity scores is difficult for other investigators to under...

Marital dissolution is commonly assumed to cause increased depression among adults, but causality can be questioned based on directionality and third variable concerns. The present study improves upon past research by using a propensity score matching algorithm to identify a sub-sample of continuously married participants equivalent in divorce risk to participants who actually experienced separ...

Recent researches in econometrics and statistics have gained considerable insights into the use of instrumental variables (IVs) for causal inference. A basic idea is that IVs serve as an experimental handle, the turning of which may change each individual’s treatment status and, through and only through this effect, also change observed outcome. The average difference in observed outcome relati...