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A Comparison of Alternative Models for the Demand for Medical Care
Authors:Naihua Duan  Willard G Manning  Carl N Morris  Joseph P Newhouse
Institution:1. Economics Department , The Rand Corporation , 1700 Main Street, Santa Monica , CA , 90406;2. Department of Statistics , University of Texas , Austin , TX , 78712
Abstract:We have tested alternative models of the demand for medical care using experimental data. The estimated response of demand to insurance plan is sensitive to the model used. We therefore use a split-sample analysis and find that a model that more closely approximates distributional assumptions and uses a nonparametric retransformation factor performs better in terms of mean squared forecast error. Simpler models are inferior either because they are not robust to outliers (e.g., ANOVA, ANOCOVA), or because they are inconsistent when strong distributional assumptions are violated (e.g., a two-parameter Box-Cox transformation).
Keywords:Health insurance  Cost sharing  Transformation  Forecast  Smearing estimate  Intrafamily correlation  Cross validation  Mean forecast squared error
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