This paper investigates how effective safety education reduces workforce risks by using an establishment-level dataset in South Korea. We focus on identification and estimation of causal effects. Since provision of safety education depends on establishment’s decision, the main variable of interest is endogenous. We adopt a partial identification approach to identifying and estimating the causal effects. The empirical results indicate that we cannot rule out the possibility that safety education may not be effective in most cases. We then discuss potential reasons that safety education would not help reduce workforce risks. Our findings are expected to be helpful to develop an effective policy to reduce workforce risks and improve work environments.

Medical services are closely related to individual health and welfare, and health status in childhood or adolescence is widely recognized to be related to many socioeconomic outcomes. Therefore, providing appropriate medical services in childhood and adolescence is important. We aimed to investigate the determinants of traditional Korean medical services (TKMS) usage by children aged < 19 years. The focus was on the role of their parents' experiences with TKMS in determining TKMS use by children. Methods: Using a representative sample in South Korea, we conducted a regression analysis to assess how parents' experience with TKMS affects the probability of their children using TKMS. Results: We found parents' experience with TKMS to have a significantly positive effect on the probability of TKMS use by children and parents' biological information, such as age and sex, to affect the probability of TKMS use. Specifically, parents' experiences with TKMS generally increased the probability of children using TKMS by approximately 20%. Conclusion: This study's results suggest that considering parents' opinions and providing them the opportunity to participate in programs that enhance young children's use of TKMS may be effective.

We consider the impacts of a new information and communications technology, referred to as the Fourth Industrial Revolution (4IR) technology, on firm productivity by using a Korean dataset. We estimate the total factor productivity (TFP) of each firm using the control function approach for estimating the production functions, and then estimate the impacts of 4IR technology on TFP. We consider quantile regression models to account for the potential heterogeneity in the effects across TFP distribution. Overall, 4IR technology is beneficial to firms with a high level of productivity, suggesting that there is substantial heterogeneity in the effects that cannot be captured by the conditional mean regression. Our results contribute to the literature by investigating the distributional effects (quantile treatment effects) of the use of new technology on productivity, and these findings are expected to have rich implications for policies regarding support on the use of 4IR technology and R&D.

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