@article{ART002998748},
author={Cho, Seong Eun and Won, Hye Jin and Chang-Moo Lee},
title={Home-Ownership Rate Analysis Based on Bayesian Nonlinear Model},
journal={Korea Real Estate Review},
issn={2092-5395},
year={2023},
volume={33},
number={3},
pages={59-79},
doi={10.35136/krer.33.3.3}

TY - JOUR
AU - Cho, Seong Eun
AU - Won, Hye Jin
AU - Chang-Moo Lee
TI - Home-Ownership Rate Analysis Based on Bayesian Nonlinear Model
JO - Korea Real Estate Review
PY - 2023
VL - 33
IS - 3
PB - korea real estate research institute
SP - 59
EP - 79
SN - 2092-5395
AB - 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.
KW - APC Effects;Home-Ownership Rate;Bayesian Nonlinear Model;MCMC Sampling
DO - 10.35136/krer.33.3.3
ER -

Cho, Seong Eun, Won, Hye Jin and Chang-Moo Lee. (2023). Home-Ownership Rate Analysis Based on Bayesian Nonlinear Model. Korea Real Estate Review, 33(3), 59-79.

Cho, Seong Eun, Won, Hye Jin and Chang-Moo Lee. 2023, "Home-Ownership Rate Analysis Based on Bayesian Nonlinear Model", Korea Real Estate Review, vol.33, no.3 pp.59-79. Available from: doi:10.35136/krer.33.3.3

Cho, Seong Eun, Won, Hye Jin, Chang-Moo Lee "Home-Ownership Rate Analysis Based on Bayesian Nonlinear Model" Korea Real Estate Review 33.3 pp.59-79 (2023) : 59.

Cho, Seong Eun, Won, Hye Jin, Chang-Moo Lee. Home-Ownership Rate Analysis Based on Bayesian Nonlinear Model. 2023; 33(3), 59-79. Available from: doi:10.35136/krer.33.3.3

Cho, Seong Eun, Won, Hye Jin and Chang-Moo Lee. "Home-Ownership Rate Analysis Based on Bayesian Nonlinear Model" Korea Real Estate Review 33, no.3 (2023) : 59-79.doi: 10.35136/krer.33.3.3

Cho, Seong Eun; Won, Hye Jin; Chang-Moo Lee. Home-Ownership Rate Analysis Based on Bayesian Nonlinear Model. Korea Real Estate Review, 33(3), 59-79. doi: 10.35136/krer.33.3.3

Cho, Seong Eun; Won, Hye Jin; Chang-Moo Lee. Home-Ownership Rate Analysis Based on Bayesian Nonlinear Model. Korea Real Estate Review. 2023; 33(3) 59-79. doi: 10.35136/krer.33.3.3

Cho, Seong Eun, Won, Hye Jin, Chang-Moo Lee. Home-Ownership Rate Analysis Based on Bayesian Nonlinear Model. 2023; 33(3), 59-79. Available from: doi:10.35136/krer.33.3.3

Cho, Seong Eun, Won, Hye Jin and Chang-Moo Lee. "Home-Ownership Rate Analysis Based on Bayesian Nonlinear Model" Korea Real Estate Review 33, no.3 (2023) : 59-79.doi: 10.35136/krer.33.3.3