A panel vector autoregression analysis for the dynamics of medical and long-term care expenditures.

Although medical and long-term care expenditures for older adults are closely related, providing rigorous statistical analysis for their dynamic relationship is challenging. In this research, we propose a novel approach using the panel vector autoregression model to reveal the realized patterns of the interdependence. As an empirical application, we analyze monthly panel data on individuals in a city of Japan, where social insurance covers many formal services for long-term care. Our estimation results indicate the existence of intertemporal transition from expensive acute medical care to reasonable at-home medical care, then to at-home long-term care. Under this context, the enhancement of formal long-term care sector in Japan might have played an important role in the suppression of the total care cost in spite for its rapid aging over the past 2 decades. Additionally, we find that daycare plays multiple roles in Japanese long-term care, such as respite and rehabilitation, but there is no considerable transition from outpatient rehabilitation to daycare in the long-term care sector.

Long-term care at home and female work during the COVID-19 pandemic.

This study analyzes the impacts of COVID-19 on two elements: long-term care at home, which is available for care recipients who live in their own home, and working status in Japan. A regression analysis of municipality data reveals that the number of users of adult daycare is negatively correlated to COVID-19, both nationally and regionally. This finding is intuitive because people avoid daycare due to the increased risk of exposure to infection. However, the number of users of home care is positively correlated to users of daycare, which implies that home care has not functioned as a replacement for daycare, despite government encouragement. Furthermore, a regression analysis using prefecture data shows that working hours for both females and males were negatively correlated to the national status of the pandemic, while the regional status of the pandemic was negatively correlated only to female working hours. This implies that female labor status is more vulnerable to such outbreaks in Japan. Also, we find consistent results with a situation in which informal care compensated for the decline in daycare use; and this care has been provided primarily by especially females who have reduced their working hours by COVID-19.

A basket two-part model to analyze medical expenditure on interdependent multiple sectors.

This study proposes a novel statistical methodology to analyze expenditure on multiple medical sectors using consumer data. Conventionally, medical expenditure has been analyzed by two-part models, which separately consider purchase decision and amount of expenditure. We extend the traditional two-part models by adding the step of basket analysis for dimension reduction. This new step enables us to analyze complicated interdependence between multiple sectors without an identification problem. As an empirical application for the proposed method, we analyze data of 13 medical sectors from the Medical Expenditure Panel Survey. In comparison with the results of previous studies that analyzed the multiple sector independently, our method provides more detailed implications of the impacts of individual socioeconomic status on the composition of joint purchases from multiple medical sectors; our method has a better prediction performance.