James E. Prieger

a flexible parametric selection model for non-normal data with application to health care usage (replication data)

I examine the effects of insurance status and managed care on hospitalization spells, and develop a new approach for sample selection problems in parametric duration models. MLE of the Flexible Parametric Selection (FPS) model does not require numerical integration or simulation techniques. I discuss application to the exponential, Weibull, log-logistic and gamma duration models. Applying the model to the hospitalization data indicates that the FPS model may be preferred even in cases in which other parametric approaches are available.

Data and Resources

Suggested Citation

Prieger, James E. (2002): A flexible parametric selection model for non-normal data with application to health care usage (replication data). Version: 1. Journal of Applied Econometrics. Dataset. https://jda-test.zbw.eu/dataset/a-flexible-parametric-selection-model-for-nonnormal-data-with-application-to-health-care-usage