REVERSE MORTGAGES: A BIBLIOMETRIC APPROACH
DOI:
https://doi.org/10.55197/qjssh.v3i3.162Keywords:
reverse mortgages, bibliometric analysis, co-citation, VOSViewerAbstract
The present study performed a bibliometric analysis using 119 articles in the field of reverse mortgages from the Web of Sciences (WoS) database from 1978 to May 2022. To provide a comprehensive result, this study employs VOS Viewer software to construct the networks of co-citations of authors and sources of articles. The results show that the growth trend was recognized from the beginning year 2011 and it gained significant attention from researchers before and during the predicament period of the Global financial crisis 2007-8. It can be seen that the positive trend of interest in this field of study remained in the following years, particularly in the years 2020 and 2021. Using the co-citation analysis, the authors focus on fundamental issues in reverse mortgages such as knowledge (literacy) and demands of reverse mortgage products for elderly homeowners, risks associated with reverse mortgages such as default on their property taxes and insurance, potential growth of reverse mortgages as a financial tool, and fair valuations of reverse mortgages. The Journal of the American Real Estate and Urban Economics Association and Insurance Mathematics and Economics are found to be the most-cited journals in the field of study of reverse mortgages.
References
Baker, H.K., Kumar, S., Pandey, N. (2020): A bibliometric analysis of Managerial Finance: A retrospective. – Managerial Finance 46(11): 1495-1517.
Boj, E., Claramunt, M.M., Varea, X. (2022): Reverse mortgage and financial sustainability. – Technological and Economic Development of Economy 28(4): 872-892.
Chinloy, P., Megbolugbe, I.F. (1994): Reverse mortgages: contracting and crossover risk. – Real Estate Economics 22(2): 367-386.
Chen, K.S., Yang, J.J. (2020): Housing price dynamics, mortgage credit and reverse mortgage demand: theory and empirical evidence. – Real Estate Economics 48(2): 599-632.
Davidoff, T., Gerhard, P., Post, T. (2017): Reverse mortgages: what homeowners (don’t) know and how it matters. – Journal of Economic Behavior and Organization 133: 151-171.
Dillingh, R., Prast, H., Rossi, M., Brancati, C.U. (2017): Who wants to have their home and eat it too? Interest in reverse mortgages in the Netherlands. – Journal of Housing Economics 38: 25-37.
Donthu, N., Kumar, S., Pandey, N., Gupta, P. (2021): Forty years of the International Journal of Information Management: A bibliometric analysis. – International Journal of Information Management 57: 22p.
Fong, J.H., Mitchell, O.S., Koh, B.S. (2020): Asset-rich and cash-poor: which older adults value reverse mortgages? – Ageing & Society 18p.
Fornero, E., Rossi, M., Brancati, M.C.U. (2016): Explaining why, right or wrong (Italian) households do not like reverse mortgages. – Journal of Pension Economics & Finance 15(2): 180-202.
Han, W., Wang, P., Xu, H., Choi, J. S. (2017): Evaluation of the reverse mortgage option in Hong Kong. – Asian Economic Journal 31(2): 187-210.
Jefferson, T., Austen, S., Ong, R., Haffner, M.E., Wood, G.A. (2017): Housing equity withdrawal: Perceptions of obstacles among older Australian home owners and associated service providers. – Journal of Social Policy 46(3): 623-642.
Mitchell, O.S., Piggott, J. (2004): Unlocking housing equity in Japan. – Journal of the Japanese and International Economies 18(4): 466-505.
Nakajima, M., Telyukova, I.A. (2017): Reverse mortgage loans: A quantitative analysis. – The Journal of Finance 72(2): 911-950.
Phang, S.Y. (2015): Monetizing housing for retirement in Singapore. – Singapore Management University 4p.
Shan, H. (2011): Reversing the trend: The recent expansion of the reverse mortgage market. – Real Estate Economics 39(4): 743-768.
Szymanoski, E.J. (1994): Risk and the home equity conversion mortgage. – Real Estate Economics 22(2): 347-366.
Shi, T., Lee, Y.T. (2021): Prepayment risk in reverse mortgages: An intensity-governed surrender model. – Insurance: Mathematics and Economics 98: 68-82.
Shi, W., Lee, L.F. (2018): A spatial panel data model with time-varying endogenous weights matrices and common factors. – Regional Science and Urban Economics 72: 6-34.
