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...

Title of Thesis: TO DETAIN OR NOT TO DETAIN? USING PROPENSITY SCORES TO EXAMINE THE RELATIONSHIP BETWEEN PRETRIAL DETENTION AND CONVICTION Jacqueline Lee, Master of Arts, 2014 Thesis directed by: Associate Professor Brian Johnson, Department of Criminology and Criminal Justice Scholars have long known that individuals who are detained prior to their sentencing fare worse in the criminal justice...

The investigation of job insecurity has been a growing field of research. However, little is known about the strategies employees adopt to reduce job insecurity. Former research has shown that employees who perceive high job insecurity tend to engage in voluntary turnover. Yet, we do not know whether such a strategy is successful in reducing perceived job insecurity. Based on the Swiss Househol...

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...

In this article we develop the theoretical properties of the propensity function, which is a generalization of the propensity score of Rosenbaum and Rubin. Methods based on the propensity score have long been used for causal inference in observational studies; they are easy to use and can effectively reduce the bias caused by nonrandom treatment assignment. Although treatment regimes need not b...

The use of propensity score methods for program evaluation with nonexperimental data typically requires that the propensity score be estimated, often with a model whose specification is unknown. Although theoretical results suggest that estimators using more flexible propensity score specifications perform better, this has not filtered into applied research. Here we provide Monte Carlo evidence...

counterfactual propensity score matching to examine repression of health service utilization and expenditure of the elderly in China. The results showed that whether the poor elderly in China visited a doctor when suffering an illness was not affected by income, but that their expenditures on medical treatment were significantly suppressed by income. The subgroup analysis further indicated that...

In the online supplement we present details of additional simulations and results that have been referred to in the main text of the paper. In Appendix 1 we present results of the treatment effect estimates from the Across and Within methods in the simulations of Section 3 when matching is performed with replacement. In Appendix 2 we investigate different applications of propensity scores to es...

This paper evaluates the effects of a property tax bonus to promote the installation of solar–thermal energy systems in buildings in Andalusia (southern Spain). The propensity score matching methodology is used. The treatment group consists of municipalities of Andalusia that established property tax bonuses in their municipalities in 2010. The control group consists of municipalities that did ...