Please use this identifier to cite or link to this item:
Title: The Lee-Carter model under Bayesian analysis : Markov Chain Monte Carlo simulation with WinBUGS.
Authors: Tan, Chong It.
Lu, Xin.
Chong, Zi Kent.
Keywords: DRNTU::Business
Issue Date: 2010
Abstract: Mortality improvement has become a significant concern in mortality projections because it directly affects the risk in life insurance business. As such, the Lee-Carter model that uses a stochastic framework is preferred against other deterministic models because of its allowance for the associated uncertainty. Various estimation methods have been proposed to estimate its parameters. In this paper, we consider the Lee-Carter model under the context of Bayesian analysis, which is able to furnish a posterior distribution for each parameter or variable of interest. We propose using a method called Markov Chain Monte Carlo (MCMC) simulation to estimate the parameters in the Lee-Carter model. Specifically, we use WinBUGS software to carry out the parameter estimation.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:NBS Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
  Restricted Access
1.4 MBAdobe PDFView/Open

Page view(s) 50

checked on Oct 28, 2020

Download(s) 50

checked on Oct 28, 2020

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.