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...

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

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 paper we characterise the selection into parenthood for men and women separately and estimate effects of motherhood and fatherhood on wages. We apply propensity score matching exploiting an extensive high-quality register-based data set augmented with family background information. We estimate net effects of parenthood and find that mothers receive 7.4% lower average wages compared to n...

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 ...

This article provides an assessment of the causal effect of customer relationship management (CRM) applications on one-to-one marketing effectiveness. We use a potential outcomes based propensity score approach to assess this causal effect. We find that firms using CRM systems have greater levels of one-to-one marketing effectiveness. We discuss the strengths and challenges of using the propens...