Estimating Prison Stays Among Current Prison Populations

Reporting estimates of length of stay in prison populations is a common objective in corrections research. Researchers and prison administrators use these estimates for many different purposes. These include projecting future prison operational and capacity needs, describing levels of punitiveness among states, and explaining the drivers of prison growth or decline. Because of their critical importance to so many dimensions of corrections and criminal justice, researchers have compared the merits of various methods to estimate prison length of stay. This article revisits a survival-based approach for estimating length of stay originally described in Patterson and Preston and uses historical prison data from the Bureau of Justice Statistics National Corrections Reporting Program to compare this method to alternatives. It also describes and tests the merits of extending this method to parametric frameworks. Using 20 years of data in nine states, we model estimates of (1) average length of stay for the 1995 prison admission cohort and (2) length of stay distributions for the 1995 prison stock and compare estimates to true values for these samples over a 20-year period. We compare results derived from adjusted and unadjusted stock-flow calculations, release cohorts, and nonparametric and parametric survival models. We demonstrate that estimates of length of stay using survival-based estimators consistently perform much better than other estimators and that there are advantages to using parametric estimation techniques over nonparametric ones. Parametric-based estimates are less variable and more reliable on average. We conclude that in the future, stay length estimates should be estimated using survival models like the ones we describe and that data exist which provide the means to do so effectively