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A modified Lee-Carter model for analysing short-base-period data.

Bojuan Barbara Zhao¹

¹Tianjin University of Finance and Economics.

Population Studies

|December 20, 2011

Summary

This study presents a modified Lee-Carter model to improve mortality data analysis, especially for short periods. The new model provides smoother, more reliable death rate predictions than the original, outperforming existing methods.

Area of Science:

Demography
Biostatistics
Actuarial Science

Background:

The original Lee-Carter model struggles with short-base-period mortality data, leading to unstable predictions.
Fluctuating age-specific mortality predictions hinder accurate demographic and actuarial analysis.

Purpose of the Study:

Introduce a modified Lee-Carter model for robust analysis of short-base-period mortality data.
Enhance the smoothness and reliability of predicted age-specific mortality rates.
Demonstrate the superiority of the modified model over existing methods.

Main Methods:

Developed a modified Lee-Carter model incorporating linearized cubic splines and additive functions.
Simplified the model into a logistic regression for binomial data fitting.

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Applied the model to analyze mortality data from China (2000-2008).

Main Results:

The modified model yields smooth expected death rates across ages and years.
Significantly reduced fluctuations in predicted age-specific mortality compared to the original model.
Empirical analysis confirmed the advantages of the new model.

Conclusions:

The modified Lee-Carter model offers a more stable and accurate approach for analyzing short-base-period mortality data.
Smoother mortality projections facilitate better demographic forecasting and risk assessment.
This enhanced model provides a valuable tool for researchers and practitioners in demography and actuarial science.