Retirement Transition Event-History Analysis

Comparing the share retired confounds the timing of retirement with how long people have been observed and ignores that many subjects are still at risk. A hazard model instead estimates the rate of retiring among those still working at each age or duration, so it isolates the timing process itself. Crucially, it uses right-censoring to include people who have not yet retired without assuming when they will, and it lets covariates such as health and pension status change over time. This yields a far more accurate picture of what speeds up or delays labor-force exit.

Both estimate the same underlying transition process and often give similar answers; the choice depends on the data. The Cox proportional-hazards model is natural when retirement timing is measured finely and ties are rare. The discrete-time approach, fitting a logistic or complementary log-log model on a person-period file, is convenient when timing is recorded in coarse units such as years, when many people retire in the same period, and when you want easy inclusion of time-varying covariates and a flexible baseline. Many retirement studies use the discrete-time form for exactly these reasons.

A single-event retirement hazard treats leaving work as a one-way, absorbing transition. In reality older workers may move into partial retirement, take bridge jobs, become disabled, or reenter employment, and they eventually die. Multistate and competing-risks models generalize the event-history framework to handle these multiple, possibly reversible transitions and to compute quantities like expected years of working life. The basic retirement hazard analyzed here is the building block; multistate life tables assemble several such transition rates into a fuller dynamic picture of the late-career life course.