In this paper, we present a novel framework for automatically assessing facial attractiveness that considers four ratio feature sets as objective elements of facial attractiveness. In our framework, these feature sets are combined with three regression-based predictors to estimate a facial beauty score. To enhance the system’s performance to make it comparable with human scoring, we apply a sco...

Understanding the role of foreign aid in poverty alleviation is one of the central inquiries for development economics. To augment past crosscountry studies and randomized evaluations, this project estimates the first sub-national model of foreign aid allocation and impact. Newly geocoded aid project data from Malawi is used in combination with multiple rounds of living standards data to predic...

Doubly robust estimation combines a form of outcome regression with a model for the exposure (i.e., the propensity score) to estimate the causal effect of an exposure on an outcome. When used individually to estimate a causal effect, both outcome regression and propensity score methods are unbiased only if the statistical model is correctly specified. The doubly robust estimator combines these ...

Parents invest in their children’s human capital in several ways. We investigate the extent to which the levels and composition of parent-child time varies across countries with different welfare regimes: Finland, Germany and the United States. We test the hypothesis of parentchild time as a form of human capital investment in children using a propensity score treatment effects approach that ac...

In recent years many studies have reported significant empirical associations between fertility and marital dissolution. Whether this is a causal effect or only a correlation is not clear. We explore this issue by using the propensity score methods. First we explore the effect of the binary treatment ”having young children or not” on marital disruption. Then, we extend the method to the case of...

Because of the difficulty in multi-dimensional matching and missing variables, investigation of long-run stock performance after major corporate events has been plagued by the “bad model problem”. This study contributes to the literature by implementing the propensity score estimator which is able to match firms in multiple dimensions simultaneously, and illustrate this methodology in the conte...

This paper applies recently developed cross-sectional and longitudinal propensity score matching estimators to data from the National Supported Work Demonstration that have been previously analyzed by LaLonde (1986) and Dehejia and Wahba (1998,1999). We find little support for recent claims in the econometrics and statistics literatures that traditional, cross-sectional matching estimators gene...

Evidence-based management requires management scholars to draw causal inferences. Researchers generally rely on observational data sets and regression models where the independent variables have not been exogenously manipulated to estimate causal effects; however, using such models on observational data sets can produce a biased effect size of treatment intervention. This article introduces the...

When the treatment method was adjusted for propensity score in the propensity-score-matched pairs (n=100), we found that the hernia recurrence (32.0% vs 6.0%, p=0.002), overall complication (32.0% vs 6.0%, p=0.002), and freedom from hernia recurrence (68.2% vs 31.8%, p=0.001) rates were worse after bridged repair. We did not observe differences in wound healing and mesh complications between th...

In this paper, we give a short overview of some propensity score matching estimators suggested in the evaluation literature and we provide a set of Stata programs which we illustrate using the National Supported Work (NSW) demonstration widely known in labor economics.