Structural analysis of reverse mortgages in Taiwan

Hong-Ming Chen and Jing-Yi Chen ()
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Hong-Ming Chen: Tunghai University. No. 1727, Sanhe 1st Ln.
Jing-Yi Chen: National Kaohsiung University of Science and Technology, No.1, University Road

Palgrave Communications, 2024, vol. 11, issue 1, 1-11

Abstract: Abstract This study investigated the framework of reverse mortgage (RM) programs in Taiwan, with a particular emphasis on the perspectives of both debtors and creditors. Employing the Lee–Carter model, the research estimated mortality rates in Taiwan while utilizing the theoretical framework to analyze various aspects of RM. House prices were assessed using the house price index as a foundational metric for estimating prices, along with lump-sum loanable amounts and RM considerations. Empirical analysis was conducted on debtors’ loans and incomes and financial institutions’ perspectives. The study delved into parameters such as maximum loanable amounts and income replacement ratios for debtors based on demographic factors such as sex, age, and occupation. Furthermore, the structure of RM programs was scrutinized from the viewpoint of financial institutions, considering factors such as rental income, remaining house value, creditor insurance protection, premium expenses, and creditor profitability. A series of simulations were performed to gauge the effects of different variables on the outcomes. The normal distribution of the house price index (HPI), as verified through the Anderson-Darling (AD) test and Kolmogorov–Smirnov (KS) test, bolstered the theoretical findings. This study’s primary contribution lies in its comprehensive exploration of the structure and advantages of RMs from the dual perspectives of debtors and creditors, a departure from insights from previous research predominantly focused on financial institutions. This research can aid debtors and creditors in evaluating RM programs and making informed decisions regarding asset allocation, thereby facilitating the selection of more suitable programs tailored to debtor characteristics.

Date: 2024
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DOI: 10.1057/s41599-024-03641-x

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