Measuring overfitting and mispecification in nonlinear models
Marcel Bilger and
Health, Econometrics and Data Group (HEDG) Working Papers from HEDG, c/o Department of Economics, University of York
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)
New Economics Papers: this item is included in nep-ecm, nep-for and nep-hea
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
https://www.york.ac.uk/media/economics/documents/herc/wp/11_25.pdf Main text (application/pdf)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:yor:hectdg:11/25
Access Statistics for this paper
More papers in Health, Econometrics and Data Group (HEDG) Working Papers from HEDG, c/o Department of Economics, University of York HEDG/HERC, Department of Economics and Related Studies, University of York, York, YO10 5DD, United Kingdom. Contact information at EDIRC.
Bibliographic data for series maintained by Jane Rawlings ().