Application of the Lee-Carter Model to Uruguay
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Resumen
The Lee-Carter Model is one of the most popular methodologies for forecasting mortality rates. The model is widely known to be simple and has been used very successfully in U.S. and several countries. This model uses principal component analysis to decompose the age-time matrix of mortality rates into a bilinear combination of age and period parameters, with the latter being treated as time series to produce mortality projections. This paper describes the application of the Lee-Carter model to age-specific death rates by gender in Uruguay. These rates are available for the period that goes from 1974 to 2020. We concluded by forecasting the mortality rates for the time period that goes from 2021 to 2050 in order to project life expectancy at birth using life tables.
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Citas
Brouhns N, Denuit M, Vermunt J (2002). “A Poisson Log-Bilinear Regression Approach to the Construction of Projected Lifetables.” Insurance: Mathematics and Economics, 31(3),373–393.
Cairns A, Blake D, Dowd K (2006). “A Two-Factor Model for Stochastic Mortality with Parameter Uncertainty: Theory and Calibration.” Journal of Risk and Insurance, 73(4), 687–718.
Cairns A, Blake D, Dowd K, Coughlan G, Epstein D, Ong A, Balevich I (2009). “A Quantitative Comparison of Stochastic Mortality Models Using Data from England and Wales and the United States.” North American Actuarial Journal, 13(1), 1–35.
Coale, A., Guo, G. (1989). “Revised Regional Model Life Tables at Very Low Levels of Mortality,” Population Index, 55, 613-643.
Coale, A., Kisker, E, (1990). “Defects in data on old age mortality in the United States: New procedures for calculating approximately accurate mortality schedules and life tables at the highest ages”. Asian and Pacific Population Forum, vol. 4. pp. 1–31.
Currie I (2016). “On Fitting Generalized Linear and non-linear Models of Mortality.” Scandinavian Actuarial Journal, (4), 356–383.
Hyndman RJ, Ullah S (2007). “Robust Forecasting of Mortality and Fertility Rates: A Functional Data Approach.” Computational Statistics & Data Analysis, 51(10), 4942–4956.
Gompertz, B., (1825). “On the nature of the function expressive of the law of human mortality and on the mode of determining the value of life contingencies”. Phil. Trans. R. Soc. A 115, 513–585.
Lee R, Carter L (1992). “Modeling and Forecasting U.S. Mortality.” Journal of the American Statistical Association, 87(419), 659–671.
Lee R, Miller T (2001). “Evaluating the Performance of the Lee-Carter Method for Forecasting Mortality.” Demography, 38(4), 537–549.
Makeham, W. (1860). “On the law of mortality and construction of annuity tables”. J. Inst. Actuar. 8 (6), 301–310.
Renshaw A, Haberman S (2003). “Lee-Carter Mortality Forecasting with Age-specific Enhancement.” Insurance: Mathematics and Economics, 33(2), 255–272.
Renshaw A, Haberman S (2006). “A Cohort-Based Extension to the Lee-Carter Model for Mortality Reduction Factors.” Insurance: Mathematics and Economics, 38(3), 556–570.
Villegas, A., Kaishev, V., Pietro, M. (2018). “An R Package for Stochastic Mortality Modeling”. Journal of Statistical Software, 84 (3), pp 1-38.