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Lee-Carter Mortality Model

The Lee-Carter model is the benchmark method for forecasting human mortality. Introduced by Ronald Lee and Lawrence Carter in 1992 for U.S. data, it captures the entire schedule of age-specific death rates with a remarkably parsimonious structure: the logarithm of the death rate at each age is a fixed average age profile, plus an age-specific sensitivity multiplied by a single time index that summarizes the overall level of mortality in each year. Because mortality has fallen steadily across the twentieth century, this single index trends downward over time, and forecasting it as a simple time-series process, typically a random walk with drift, propagates the historical pace of improvement into the future for every age at once. Brouhns, Denuit, and Vermunt later recast the fitting step as a Poisson regression on observed death counts, giving the model a proper statistical likelihood and more reliable uncertainty, and the approach now anchors official population and pension projections worldwide.

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Sources

  1. Lee, R. D., & Carter, L. R. (1992). Modeling and Forecasting U.S. Mortality. Journal of the American Statistical Association, 87(419), 659-671. DOI: 10.1080/01621459.1992.10475265
  2. Brouhns, N., Denuit, M., & Vermunt, J. K. (2002). A Poisson log-bilinear regression approach to the construction of projected lifetables. Insurance: Mathematics and Economics, 31(3), 373-393. DOI: 10.1016/S0167-6687(02)00185-3

How to cite this page

ScholarGate. (2026, June 23). Lee-Carter Model for Mortality Forecasting. ScholarGate. https://scholargate.app/en/demography/lee-carter-mortality-model

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ScholarGateLee-Carter Mortality Model (Lee-Carter Model for Mortality Forecasting). Retrieved 2026-06-24 from https://scholargate.app/en/demography/lee-carter-mortality-model · Dataset: https://doi.org/10.5281/zenodo.20539026