Motivated by an application to a longitudinal dataset regarding hospitals in Lombardy we propose a model to measure hospital efficiency which incorporates observed covariates and time-varying latent hospital effects. The distribution of the latter may be continuous-valued or discrete-valued. In the first case it is a mixture of auto-regressive AR(1) processes with specific mean values and correlation coefficients and common variances. In the second case it is based on a first order homogeneous Markov chain with a fixed number of states. Maximum likelihood estimation of the model parameters is performed by using the expectation-maximization algorithm and the Newton-Raphson algorithm. The effect of the different formulations is evaluated in terms of the estimated efficiency scores
Pennoni, F., Vittadini, G. (2013). Hospital efficiency under competing panel data models. In Cladag 2013. 9th Meeting of the Classification and Data Analysis Group. Book of Abstracts (pp.381-384). CLEUP.
Hospital efficiency under competing panel data models
PENNONI, FULVIA;VITTADINI, GIORGIO
2013
Abstract
Motivated by an application to a longitudinal dataset regarding hospitals in Lombardy we propose a model to measure hospital efficiency which incorporates observed covariates and time-varying latent hospital effects. The distribution of the latter may be continuous-valued or discrete-valued. In the first case it is a mixture of auto-regressive AR(1) processes with specific mean values and correlation coefficients and common variances. In the second case it is based on a first order homogeneous Markov chain with a fixed number of states. Maximum likelihood estimation of the model parameters is performed by using the expectation-maximization algorithm and the Newton-Raphson algorithm. The effect of the different formulations is evaluated in terms of the estimated efficiency scoresI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.