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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.

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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?__no_cache__=True