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An empirical study on the influence of product portfolio and interest rate on the lapse rate in the life insurance industry  

Jung, Se-Chang (Department of Banking and Insurance, Hongik University)
Ouh, Seung-Cheol (Korea Insurance Development Institute)
Kang, Jung-Chul (Department of Banking and Insurance, Dong-eui University)
Publication Information
Journal of the Korean Data and Information Science Society / v.22, no.1, 2011 , pp. 73-80 More about this Journal
Abstract
The purpose of this study is to analyse the influence of product portfolio and interest rate on the lapse ratio. This issue is very important because of the recent introduction of IFRS and CFP. The fixed-effect model and the random-effect model are estimated with using panel data and the Hausman test is employed in order to select a model. The results of this study is summarized as follows. Firstly, the random effect model is selected. According to the model, the lapse rate increases as the portfolio of savings plan, sickness, and death increases and the interest rate is high. Secondly, health insurance and variable insurance product show a negative relationship with the lapse rate.
Keywords
Fixed-effect model; lapse rate; life insurance; random-effect model;
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1 Outreville, J. F. (1990). Whole-life insurance lapse rates and the emergency fund hypothesis, Insurance. Mathematics and Economics, 9, 249-255.   DOI   ScienceOn
2 Granger, C. W. J. (1969). Investigating causal relation by econometric and cross-sectional method. Econometrica, 37, 424-438.   DOI   ScienceOn
3 Kim, Changki (2005). Modeling surrender and lapse rate with economic variables. North American Actuarial Journal, 9-4, 56-70.
4 Kuo, W., Tsai, C. and Chen, W. (2003). An empirical study on the lapse rate : The cointegration approach. Journal of Risk and Insurance, 70 , 489-508.   DOI   ScienceOn
5 MacKinnon, J. G. (1996). Numerical distribution functions for unit root and cointegration tests. Journal of Applied Econometrics, 11, 601-618.   DOI
6 Nelson, C. R. and Plosser, C. I. (1982). Trends and random walks in macroeconomic time series: Some evidence and implications. Journal of Monetary Economics, 10, 139-162.   DOI   ScienceOn
7 Otero, J. and Smith, J. (2000). Testing for cointegration: Power versus frequency of observation-further monte carlo results. Economics Letters, 67, 5-9.   DOI   ScienceOn
8 정세창, 오승철 (2009). 생명보험회사의 해약률에 관한 연구, <보험학회지>, 82, 158-161.
9 최영목, 최원 (2008). 경제변수가 생명보험 해약률에 미치는 영향, <보험개발연구>, 55, 3-34.
10 황진태, 이경희 (2010). <생명보험 상품별 해지율 추정 및 예측모형> , 연구보고서 2010-2, 22-39, 보험연구원, 서울.
11 황진태, 서대교 (2010). 거시경제변수가 변액보험 초회보험료에 미치는 영향에 관한 분석, <보험금융연구> 21, 3-32.
12 유동헌 (2005), <에너지절약투입자금에 대한 경제적 성과 분석>, 연구보고서 2005-04, 에너지경제연구원, 경기도
13 Burnett, J. J. and Palmer, B. A. (1984). Examining life insurance ownership through demographic and psychographic characteristics. Journal of Risk and Insurance, 51, 453-467.   DOI   ScienceOn
14 Engle, R. F. and Granger, C. W. J. (1987). Cointegration and error correction representation, estimation, and testing. Econometrica, 55 , 1057-1072.   DOI   ScienceOn
15 강중철, 장강봉 (1999). <생존분석기법을 이용한 생명보험 실효.해약 분석>, 연구보고서 99-5, 보험개발원, 서울.
16 김헌수 (1996). 생보사의 양적경영전략 선택과 해약률에 관한 연구, <리스크관리연구>, 6, 83-107.
17 이영민 (2001). <생명보험 계약 유지율 개선을 위한 실증연구>, 석사학위논문, 서강대학교, 서울.