베이지안 비선형 모형에 기반한 자가율 분석

Abstract

Age-period-cohort (APC) analysis is well known for its suitability in the life cycle, aging, and long-term trend studies, with the cohort effect explaining social phenomena as the influx of new generations. The analysis can be divided into two components: the cohort effect and the period effect. In this study, a Bayesian nonlinear model was introduced to estimate the home-ownership rate of the baby boomer generation based on APC analysis. Three types of data were used to ensure the robustness of the results, taking into account the APC linear relationship and findings from previous studies. In some models, age dummies were included to capture the home-ownership rate intuitively. Additionally, a nonlinear model was applied to the finance and labor panels, which maintained the same sample over time, to isolate each effect of APC. This novel approach demonstrated the potential for improving the identification problem of APC in comparison to traditional linear analysis. The study found distinct differences in the housing consumption pattern of the baby boomer generation compared with previous generations. The baby boomers now constitute a significant portion of the elderly population, implying a shift in the implications for housing stability. By addressing the identification issues, the Bayesian nonlinear model enhances the utility of APC analysis and contributes to a great understanding of the differences in housing preference systems among generations.