A New Fourier Approach under the Lee-Carter Model for Incorporating Time-Varying Age Patterns of Structural Changes
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Inoue, Atsushi & Jin, Lu & Rossi, Barbara, 2017.
"Rolling window selection for out-of-sample forecasting with time-varying parameters,"
Journal of Econometrics, Elsevier, vol. 196(1), pages 55-67.
- Atsushi Inoue & Lu Jin & Barbara Rossi, 2014. "Rolling Window Selection for Out-of-Sample Forecasting with Time-Varying Parameters," Working Papers 768, Barcelona School of Economics.
- Atsushi Inoue & Lu Jin & Barbara Rossi, 2014. "Rolling window selection for out-of-sample forecasting with time-varying parameters," Economics Working Papers 1435, Department of Economics and Business, Universitat Pompeu Fabra, revised Apr 2016.
- Yaser Awad & Shaul K. Bar-Lev & Udi Makov, 2022. "A New Class of Counting Distributions Embedded in the Lee–Carter Model for Mortality Projections: A Bayesian Approach," Risks, MDPI, vol. 10(6), pages 1-17, May.
- Amit Goyal & Ivo Welch, 2003.
"Predicting the Equity Premium with Dividend Ratios,"
Management Science, INFORMS, vol. 49(5), pages 639-654, May.
- Amit Goyal & Ivo Welch, 1999. "Predicting the Equity Premium with Dividend Ratios," Yale School of Management Working Papers amz2437, Yale School of Management, revised 01 Nov 2002.
- Amit Goyal & Ivo Welch, 2002. "Predicting the Equity Premium With Dividend Ratios," NBER Working Papers 8788, National Bureau of Economic Research, Inc.
- Kevin Dowd & Andrew Cairns & David Blake & Guy Coughlan & David Epstein & Marwa Khalaf-Allah, 2010. "Backtesting Stochastic Mortality Models," North American Actuarial Journal, Taylor & Francis Journals, vol. 14(3), pages 281-298.
- Jackie Li, 2013. "A Poisson common factor model for projecting mortality and life expectancy jointly for females and males," Population Studies, Taylor & Francis Journals, vol. 67(1), pages 111-126, March.
- Edviges Coelho & Luis C. Nunes, 2011. "Forecasting mortality in the event of a structural change," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(3), pages 713-736, July.
- Wong, Jackie S.T. & Forster, Jonathan J. & Smith, Peter W.F., 2018. "Bayesian mortality forecasting with overdispersion," Insurance: Mathematics and Economics, Elsevier, vol. 83(C), pages 206-221.
- Juha Alho, 2000. "“The Lee-Carter Method for Forecasting Mortality, with Various Extensions and Applications“, Ronald Lee, January 2000," North American Actuarial Journal, Taylor & Francis Journals, vol. 4(1), pages 91-93.
- Carter, Lawrence R. & Lee, Ronald D., 1992. "Modeling and forecasting US sex differentials in mortality," International Journal of Forecasting, Elsevier, vol. 8(3), pages 393-411, November.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Blake, David & Cairns, Andrew J.G., 2021. "Longevity risk and capital markets: The 2019-20 update," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 395-439.
- Schinzinger, Edo & Denuit, Michel M. & Christiansen, Marcus C., 2016. "A multivariate evolutionary credibility model for mortality improvement rates," Insurance: Mathematics and Economics, Elsevier, vol. 69(C), pages 70-81.
- Li, Johnny Siu-Hang & Liu, Yanxin, 2021. "Recent declines in life expectancy: Implication on longevity risk hedging," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 376-394.
- Blake, David & El Karoui, Nicole & Loisel, Stéphane & MacMinn, Richard, 2018.
"Longevity risk and capital markets: The 2015–16 update,"
Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 157-173.
- David Blake & Nicole El Karoui & Stéphane Loisel & Richard Macminn, 2018. "Longevity risk and capital markets: The 2015–16 update," Post-Print hal-01995778, HAL.
- Wang, Pengjie & Pantelous, Athanasios A. & Vahid, Farshid, 2023. "Multi-population mortality projection: The augmented common factor model with structural breaks," International Journal of Forecasting, Elsevier, vol. 39(1), pages 450-469.
- de Jong, Piet & Tickle, Leonie & Xu, Jianhui, 2020. "A more meaningful parameterization of the Lee–Carter model," Insurance: Mathematics and Economics, Elsevier, vol. 94(C), pages 1-8.
- Stephen G. Hall & George S. Tavlas & Yongli Wang, 2023.
"Forecasting inflation: The use of dynamic factor analysis and nonlinear combinations,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 514-529, April.
- Stephen G. Hall & George S. Tavlas & Yongli Wang, 2022. "Forecasting Inflation: The Use of Dynamic Factor Analysis and Nonlinear Combinations," Discussion Papers 22-12, Department of Economics, University of Birmingham.
- Stephen G. Hall & George S. Tavlas & Yongli Wang, 2023. "Forecasting inflation: the use of dynamic factor analysis and nonlinear combinations," Working Papers 314, Bank of Greece.
- Hunt, Andrew & Villegas, Andrés M., 2015. "Robustness and convergence in the Lee–Carter model with cohort effects," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 186-202.
- Katrien Antonio & Anastasios Bardoutsos & Wilbert Ouburg, 2015.
"Bayesian Poisson log-bilinear models for mortality projections with multiple populations,"
BAFFI CAREFIN Working Papers
1505, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
- Katrien Antonio & Anastasios Bardoutsos & Wilbert Ouburg, 2015. "Bayesian Poisson log-bilinear models for mortality projections with multiple populations," Working Papers Department of Accountancy, Finance and Insurance (AFI), Leuven 485564, KU Leuven, Faculty of Economics and Business (FEB), Department of Accountancy, Finance and Insurance (AFI), Leuven.
- de Jong, Piet & Tickle, Leonie & Xu, Jianhui, 2016. "Coherent modeling of male and female mortality using Lee–Carter in a complex number framework," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 130-137.
- Jens Robben & Katrien Antonio & Sander Devriendt, 2022.
"Assessing the Impact of the COVID-19 Shock on a Stochastic Multi-Population Mortality Model,"
Risks, MDPI, vol. 10(2), pages 1-33, January.
- Jens Robben & Katrien Antonio & Sander Devriendt, 2021. "Assessing the impact of the COVID-19 shock on a stochastic multi-population mortality model," Papers 2111.10164, arXiv.org.
- Colin O’hare & Youwei Li, 2017.
"Modelling mortality: are we heading in the right direction?,"
Applied Economics, Taylor & Francis Journals, vol. 49(2), pages 170-187, January.
- O'Hare, Colin & Li, Youwei, 2016. "Modelling mortality: Are we heading in the right direction?," MPRA Paper 71392, University Library of Munich, Germany.
- Barigou, Karim & Goffard, Pierre-Olivier & Loisel, Stéphane & Salhi, Yahia, 2023. "Bayesian model averaging for mortality forecasting using leave-future-out validation," International Journal of Forecasting, Elsevier, vol. 39(2), pages 674-690.
- Colin O’hare & Youwei Li, 2017.
"Models of mortality rates – analysing the residuals,"
Applied Economics, Taylor & Francis Journals, vol. 49(52), pages 5309-5323, November.
- O'Hare, Colin & Li, Youwei, 2016. "Models of Mortality rates - analysing the residuals," MPRA Paper 71394, University Library of Munich, Germany.
- Yanlin Shi & Sixian Tang & Jackie Li, 2020. "A Two-Population Extension of the Exponential Smoothing State Space Model with a Smoothing Penalisation Scheme," Risks, MDPI, vol. 8(3), pages 1-18, June.
- Börger, Matthias & Schupp, Johannes, 2018. "Modeling trend processes in parametric mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 369-380.
- Stephen G. Hall & George S. Tavlas & Yongli Wang & Deborah Gefang, 2024. "Inflation forecasting with rolling windows: An appraisal," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 827-851, July.
- Börger, Matthias & Russ, Jochen & Schupp, Johannes, 2021. "It takes two: Why mortality trend modeling is more than modeling one mortality trend," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 222-232.
- Yousuf, Kashif & Ng, Serena, 2021.
"Boosting high dimensional predictive regressions with time varying parameters,"
Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
- Kashif Yousuf & Serena Ng, 2019. "Boosting High Dimensional Predictive Regressions with Time Varying Parameters," Papers 1910.03109, arXiv.org.
- Li, Johnny Siu-Hang & Zhou, Rui & Hardy, Mary, 2015. "A step-by-step guide to building two-population stochastic mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 63(C), pages 121-134.
More about this item
Keywords
mortality forecasting; structural changes; age effects; Fourier series; life expectancy;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jrisks:v:10:y:2022:i:8:p:147-:d:870761. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.