Dynamic Estimation of Health Expenditure: A new approach for simulating individual expenditure

This study compares estimates of outpatient expenditure computed with different models. Our aim is to predict annual health expenditures. We use a French panel dataset over a six year period (2000-2006) for 7112 individuals. Our article is based on the estimations of five different models. The first model is a simple two part model estimated in cross section. The other models (models 2 to 5) are estimated with selection models (or generalized tobit models). Model 2 is a basic sample selection model in cross section. Model 3 is similar to model 2, but takes into account the panel dimension. It includes constant unobserved heterogeneity to deal with state dependency. Model 4 is a dynamic sample selection model (with lagged adjustement), while in model 5, we take into account the possible heteroskedasticity of residuals in the dynamic model. We find that all the models have the same properties in the cross section dimension (distribution, probability of health care use by gender and age, health expenditure by gender and age) but model 5 gives better results reflecting the temporal correlation with health expenditure. Indeed, the retransformation of predicted log transformed expenditures in homoscedastic models (models 1 to 4) generates very poor temporal correlation for " heavy consumers ", although the data show the contrary. Incorporation of heteroskedasticity gives better results in terms of temporal correlation.Health econometrics, expenditures, panel data, selection models

Does compulsory education lower mortality?

Recent studies have claimed to show a significant causal impact of education on health status. Their empirical strategy usually relied on changes in compulsory schooling laws. Using a French longitudinal dataset, we focus on the effect of school leaving age on mortality at later ages. The two identifying shocks are the Zay and Berthoin reforms, which respectively raised the minimum school leaving age to 14 and 16 years. We implement a non-parametric regression discontinuity design, comparing cohorts born immediately before or after the reforms, and a parametric two-stage approach using information from a larger part of our sample. None of these approaches reveals a significant causality of education on health. Despite the fact that these reforms increased education levels, and that subsequent declines in mortality are observed, none of these declines appears to be significant. We conclude with a discussion on possible limitations of these two reforms as identifying devices.Health Mortality Education Causality Regression discontinuity

Health expenditure models: A comparison using panel data

In this article, we focus on the estimation of outpatient expenditures with panel data. We model the logarithm of expenditures and consider five different models. The first two are two-part and sample selection cross-section models. Two-part panel data models turn out to be inappropriate for dealing with expenditures. We thus estimate sample selection models with panel data: one without a lagged dependent variable and two with a lagged dependent variable. These two latter models differ in their assumptions on the variance of the residuals. Modelling heteroscedasticity may indeed be important to avoid the bias due to the retransformation problem. We show that lagged dependent variables are important factors for heteroscedasticity. For the models with state dependence, we provide a new solution to the initial conditions problem by controlling for generalised residuals. We establish that panel data models highly improve the correlation explained by the model in the time-series dimension without damaging the fit in the cross-section dimension. For all indicators of fit, the model with state dependence and heteroscedasticity seems to dominate the others.Health econometrics Expenditures Panel data Selection models