Abstract The Food for Education (FFE) program was introduced to Bangladesh in 1993. This paper evaluates the effect of this program on school participation and duration of schooling using household survey data collected in 2000. Using propensity score matching combined with differencein-differences methodologies, we find that the program is successful in that eligible children on average have 1...

This Monte Carlo simulation examined the effects of variable selection (combinations of confounders with four patterns of relationships to outcome and assignment to treatment) and number of strata (5, 10, or 20) in propensity score analyses. The focus was on how the variations affected the average effect size compared to quasi-assignment without adjustment for bias. Results indicate that if a p...

We apply propensity score matching estimators with multiple outcomes to evaluate the impacts of exchange rate regimes (fixed, intermediate, and flexible without inflation targeting) and inflation targeting on inflation rates in emerging and developing countries. An inflation-targeting regime does better than or at least as good work as a fixed regime in lowering inflation rates when compared wi...

Researchers are increasingly using complex population-based sample surveys to estimate the effects of treatments, exposures and interventions. In such analyses, statistical methods are essential to minimize the effect of confounding due to measured covariates, as treated subjects frequently differ from control subjects. Methods based on the propensity score are increasingly popular. Minimal res...

The purpose of this paper is to determine how much is the “bonus” or “prize” to the sales per worker of Internet-using firms compared to not Internet-using firms. The author employs matching techniques based on an Argentinean database. The author first presents a binary logit model, in which the dependent variable is a dichotomous variable equal to 1 if the firm adopted Internet and 0 otherwise...

The propensity score is defined as a subject's probability of treatment selection, conditional on observed baseline covariates. Weighting subjects by the inverse probability of treatment received creates a synthetic sample in which treatment assignment is independent of measured baseline covariates. Inverse probability of treatment weighting (IPTW) using the propensity score allows one to obtai...

The propensity score is defined as the probability of each individual study subject being assigned to a group of interest for comparison purposes. Propensity score adjustment is a method of ensuring an even distribution of confounders between groups, thereby increasing between group comparability. Propensity score analysis is therefore an increasingly applied statistical method in observational...

In this paper, we investigate regional differences in the gender pay gap both theoretically and empirically. Within a spatial oligopsony model, we show that more densely populated labour markets are more competitive and constrain employers’ ability to discriminate against women. Utilising a large administrative data set for western Germany and a flexible semi-parametric propensity score matchin...