Measuring overfitting and mispecification in nonlinear models

Marcel Bilger and Willard Manning

Health, Econometrics and Data Group (HEDG) Working Papers from HEDG, c/o Department of Economics, University of York

Abstract: We start by proposing a new measure of overfitting expressed on the untransformed scale of the dependent variable, which is generally the scale of interest to the analyst.We then show that with nonlinear models shrinkage due to overfitting gets confounded by shrinkage—or expansion— arising from model misspecification. Out-of-sample predictive calibration can in fact be expressed as in-sample calibration times 1 minus this new measure of overfitting. We finally argue that re-calibration should be performed on the scale of interest and provide both a simulation study and a real-data illustration based on health care expenditure data.

Keywords: overfitting; shrinkage; misspecification; forecasting; health care expenditure (search for similar items in EconPapers)
Date: 2011-08
New Economics Papers: this item is included in nep-ecm, nep-for and nep-hea
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:yor:hectdg:11/25

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