The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Least Squares Model Averaging
Abstract
This paper considers the problem of selection of weights for averaging across leastsquares estimates obtained from a set of models. Existing model average methods are based on exponential AIC and BIC weights. In distinction, this paper proposes selecting the weights by minimizing a Mallows ’ criterion, the latter an estimate of the average squared error from the model average fit. We show that our new Mallows ’ Model Average (MMA) estimator is asymptotically optimal in the sense of achieving the lowest possible squared error in a class of discrete model average estimators. In a simulation experiment we show that the MMA estimator compares favorably with those based on AIC and BIC weights. The proof of the main result is an application of Li (1987). Research supported by the National Science Foundation. I gratefully thank the Co-Editor (Whitney Newey), three referees, and Benedickt Potscher for helpful comments.
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Cites
Estimating the Dimension of a Model
Schwarz, G. (1978) · The Annals of Statistics · doi:10.1214/aos/1176344136 · Cited by 47,033
Model selection and multimodel inference: a practical information-theoretic approach.
Guthery, F. S., Burnham, K. P., & Anderson, D. R. (2003) · The Journal of Wildlife Management · doi:10.2307/3802723 · Cited by 41,495
Information Theory and an Extension of the Maximum Likelihood Principle
Akaike, H. (1998) · Springer Series in Statistics · doi:10.1007/978-1-4612-1694-0_15 · Cited by 17,781
Cross validatory choice and assessment of statistical predictions
Stone, M. (1974) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1974.tb00994.x · Cited by 10,881
Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
Fan, J., & Li, R. (2001) · Journal of the American Statistical Association · doi:10.1198/016214501753382273 · Cited by 8,900
Hoeting, J. A., Madigan, D., Raftery, A. E., & Volinsky, C. T. (1999) · Statistical Science · doi:10.1214/ss/1009212519 · Cited by 4,118
Craven, P., & Wahba, G. (1978) · Numerische Mathematik · doi:10.1007/bf01404567 · Cited by 3,388
Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach
Sala-i-Martin, X., Doppelhofer, G., & Miller, R. I. (2004) · American Economic Review · doi:10.1257/0002828042002570 · Cited by 2,112
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Cited by
Should Macroeconomic Forecasters Use Daily Financial Data and How?
Andreou, E., Ghysels, E., & Kourtellos, A. (2013) · Journal of Business & Economic Statistics · doi:10.1080/07350015.2013.767199 · Cited by 331
Model Averaging and Its Use in Economics
Steel, M. F. J. (2020) · Journal of Economic Literature · doi:10.1257/jel.20191385 · Cited by 321
Estimating the Armington elasticity: The importance of study design and publication bias
Bajzik, J., Havranek, T., Irsova, Z., & Schwarz, J. (2020) · Journal of International Economics · doi:10.1016/j.jinteco.2020.103383 · Cited by 150
How puzzling is the forward premium puzzle? A meta-analysis
Zigraiova, D., Havranek, T., Irsova, Z., & Novak, J. (2021) · European Economic Review · doi:10.1016/j.euroecorev.2021.103714 · Cited by 71
Metadata
- Authors
- Hansen, B. E.
- Venue
- Econometrica
- Publisher
- The Econometric Society
- Published
- 2007-07
- Volume
- 75
- Issue
- 4
- Pages
- 1175-1189
- ISSN
- 0012-9682 (ISSN-L)
- 1468-0262
- OpenAlex
- W2122196572
- Cited by
- 837
- References
- 49
- FWCI
- 14.72
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
