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...

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 ...

We explore the finite sample properties of several semiparametric estimators of average treatment effects, including propensity score reweighting, matching, double robust, and control function estimators. When there is good overlap in the distribution of propensity scores for treatment and control units, reweighting estimators are preferred on bias grounds and attain the semiparametric efficien...

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...

p eople’s business credit program (kur) has been launched to alleviate poverty through provision of micro financing to micro entrepreneurs in indonesia this study aims to estimate the impact of kur program using cross-sectional data and propensity score matching technique (psm). the survey was conducted on 332 household entrepreneurs, consisting of 155 kur receivers and 177 non-kur receivers. r...

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...