A flexible two-dimensional mortality model for use in indirect estimation

• Published in: Population studies Vol. 66; no. 1; pp. 1 - 28
• Main Authors: Wilmoth, John, Zureick, Sarah, Canudas-Romo, Vladimir, Inoue, Mie, Sawyer, Cheryl
• Format: Journal Article
• Language: English
• Published: England Taylor & Francis Group 01-03-2012; Taylor & Francis; Population Investigation Committee, London School of Economics and Political Science
• Subjects: Accuracy; Adolescent; Adult; Adults; Age; Age Factors; Age groups; age patterns of mortality; Aged; Aged, 80 and over; Child; Child Mortality; Child, Preschool; Children; Databases, Factual; death rates; Demography; Estimate reliability; Estimating techniques; Estimation methods; Female; Humans; indirect methods; Infant; Infant, Newborn; Information; International cooperation; Life Expectancy; Life Tables; Logistic Models; Male; Mathematical models; Methodology; Middle Aged; model life tables; Modeling; Models, Statistical; Mortality; Mortality - trends; mortality estimation; mortality models; Mortality Rates; Parametric models; Probability; relational logit model; Risk Assessment; Statistics; Statistics as Topic - methods; United Nations; Young Adult
• ISSN: 0032-4728; 1477-4747
• DOI: 10.1080/00324728.2011.611411

Mortality estimates for many populations are derived using model life tables, which describe typical age patterns of human mortality. We propose a new system of model life tables as a means of improving the quality and transparency of such estimates. A flexible two-dimensional model was fitted to a collection of life tables from the Human Mortality Database. The model can be used to estimate full life tables given one or two pieces of information: child mortality only, or child and adult mortality. Using life tables from a variety of sources, we have compared the performance of new and old methods. The new model outperforms the Coale-Demeny and UN model life tables. Estimation errors are similar to those produced by the modified Brass logit procedure. The proposed model is better suited to the practical needs of mortality estimation, since both input parameters are continuous yet the second one is optional.