qlifetable: An R package for constructing quarterly life tables

Area of Science:

• Demography
• Actuarial Science
• Data Science

Background:

• The big data revolution has increased access to microdata on vital statistics.
• Existing demographic methods often lack the granularity to capture sub-annual variations.
• There is a need for advanced tools to analyze detailed demographic event data.

Purpose of the Study:

• To introduce a novel methodology and R package (qlifetable) for estimating sub-annual life tables.
• To demonstrate how to compute vital statistics and seasonal-ageing indexes from microdata.
• To highlight the impact of relative age observation for demographic analysis.

Main Methods:

• Utilized detailed individual records (microdata) on births, deaths, and migration.
• Developed an R package, qlifetable, implementing a novel sub-annual life table methodology.
• Computed summary statistics, including relative age, exposure times, and exact ages at events.

Main Results:

• The qlifetable package computes crude quarterly death rates and seasonal-ageing indexes (SAIs).
• Quarterly life tables can be constructed for general or insured populations.
• Relative observation of age is crucial for congruency between age and calendar time.

Conclusions:

• The qlifetable package provides a robust implementation for sub-annual life table estimation.
• This methodology offers new opportunities for the insurance industry, pension funds, and social security.
• The findings necessitate a shift towards relative time observation in actuarial science and demography.