Nutritional labeling has been of much interest to policy makers and health advocates due to rising obesity trends. So can nutritional label use really help reduce body weight outcomes? This study evaluates the impact of nutritional label use on body weight using the propensity score matching technique. We conducted a series of tests related to variable choice of the propensity score specificati...

With growing economic globalization, returnee managers who have obtained education or work experience overseas play a much more crucial role in corporations, especially in emerging economies. Using hand-collected managerial background data from a sample of firms listed on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2014, this paper investigates the impact of returnee managers on corp...

We offer an explanation to the simulation result of Austin (2009) regarding rate ratios, and argue that unmatched analysis of propensity score matched count data results in conservative statistical inferences on the rate ratios.

Two concerns in US education are shortages of qualified math and science teachers and the feminization of teaching. I draw on the National Education Longitudinal Study of 1988 to identify a common reason for the two phenomena. Controlling for self-selection by a propensity score matching estimator and the Heckit, I find that the rigid pay structure for teachers, rather than the pay level, appea...

The propensity score is the conditional probability of assignment to a particular treatment given a vector of observed covariates. Previous theoretical arguments have shown that subclassification on the propensity score will balance all observed covariates. Subclassification on an estimated propensity score is illustrated, using observational data on treatments for coronary artery disease. Five...

This paper re-examines the impact of a firm’s outward foreign direct investemnt on its R&D spending in the home country with propensity score matching method. Employing firm-level panel data on Taiwan’s manufacturing firms covering 1987-2003, this paper first demonstrates that firms with firm-specific and ownership advantages are more likely to undertake overseas inverstment. Controlling for ou...

Often it is infeasible or unethical to use random assignment in educational settings to study important constructs and questions. Hence, educational research often uses observational data, such as large-scale secondary data sets and state and school district data, and quasi-experimental designs. One method of reducing selection bias in estimations of treatment effects is propensity score analys...

Inverse probability of treatment weighting (IPTW) is a popular method for estimating causal effects in many disciplines. However, empirical studies show that the IPTW estimators can be sensitive to the misspecification of propensity score model. To address this problem, several researchers have proposed new methods to estimate propensity score by directly optimizing the balance of pre-treatment...

In recent years, propensity score matching (PSM) has gained attention as a potential method for estimating the impact of public policy programs in the absence of experimental evaluations. In this study, we evaluate the usefulness of PSM for estimating the impact of a program change in an educational context (Tennessee’s Student Teacher Achievement Ratio Project [Project STAR]). Because Tennesse...

The propensity score method is frequently used to deal with bias from standard regression in observational studies. The propensity score method involves calculating the conditional probability (propensity) of being in the treated group (of the exposure) given a set of covariates, weighting (or sampling) the data based on these propensity scores, and then analyzing the outcome using the weighted...