07. Maximum Entropy Mortality Forecasting for U.S. Females

The mortality experience in a population can be studied through the age-at-death distribution. This study investigates the mortality experience of a population by examining the age-at-death distribution, focusing on its first four statistical moments for calculating the mean, variance, skewness, and kurtosis. These moments are used to provide a good approximation of the shape of the probability density function of the underlying distribution of deaths. Using data from the Human Mortality Database for the U.S. female population, we apply the Maximum Entropy Mortality (MEM) model to reconstruct the full mortality density. We validate MEM by comparing observed and reconstructed densities, demonstrating its ability to capture shifting mortality patterns. Forecast accuracy is further evaluated using standard metrics and benchmarked against the Lee–Carter and some other models. Our analysis will highlight how the MEM model, leveraging moment information, provides a detailed characterization of age-specific mortality levels for the purpose of forecasting.

Maximum Entropy Mortality

Mortality Forecasting

Age-at-Death Distribution

Human Mortality Database

U.S. Female Mortality 

Mid-Level

Knowledge

Women in Statistics and Data Science 2025