title: Measurement of horizontal inequity in health care utilisation using European panel data.
abstract: Measurement of inequity in health care delivery has focused on the extent to which health care utilisation is or is not distributed according to need, irrespective of income. Studies using cross-sectional data have proposed various ways of measuring and standardizing for need, but inevitably much of the inter-individual variation in needs remains unobserved in cross-sections. This paper exploits panel data methods to improve the measurement by including the time-invariant part of unobserved heterogeneity into the need-standardization procedure. Using latent class hurdle models for GP and specialist visits estimated on 8 annual waves of the European Community Household Panel we compute indices of horizontal equity that partition total income-related variation in use into a need- and a non-need related part, not only for the observed but also for the unobserved but time-invariant component. We also propose and compare a more conservative index of horizontal inequity to the conventional statistic. We find that many of the cross-country comparative results appear fairly robust to the panel data test, although the panel-based methods lead to significantly higher estimates of horizontal inequity for most countries. This confirms that better estimation and control for need often reveals more pro-rich distributions of doctor utilisation.
authors.affiliation: Department of Applied Economics, Room H13-09, Erasmus School of Economics, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands. bagoduva@few.eur.nl
authors.forename: Teresa
authors.initials: T
authors.lastname: Bago d'Uva
authors.forename: Andrew M
authors.initials: AM
authors.lastname: Jones
authors.forename: Eddy
authors.initials: E
authors.lastname: van Doorslaer
mesh_terms: D000465:Algorithms; D003430:Cross-Sectional Studies; D019992:Databases as Topic; D005062:European Union; D006296:Health Services / Q000706:statistics & numerical data*; D054625:Healthcare Disparities / Q000706:statistics & numerical data; D006801:Humans