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Koenker, Roger W. Machado, Jose Antonio Ferreira 2011-05-07T13:08:30Z 2011-05-07T13:08:30Z 10000-01-01 1989 This thesis main focus are the robustness properties of the Schwarz Information Criterion (SIC) based on sample objective functions defining (Bias) robust M-estimators. The Bayesian underpinnings of such a criterion are established by extending Schwarz's original framework to densities not belonging to the exponential family. A definition of qualitative robustness appropriate for model selection is provided and it is shown that the crucial restriction needed to achieve robustness is the uniform boundedness of the objective function defining Bias robust M-estimators. In this process, the asymptotic performance of the SIC for generalized M-estimators is also studied. The finite sample behavior of the SIC for different types of M-estimators is analyzed by means of Monte Carlo experiments. Made available in DSpace on 2011-05-07T13:08:30Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 8924813.pdf: 4836418 bytes, checksum: ff9911359d999ca6f43e8197310f04c0 (MD5) Previous issue date: 1989 Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T14:50:45Z Item is restricted indefinitely. Restriction data tranferred 2014-07-01T11:23:13-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission ETDs are only available to UIUC Users without author permission U of I Only AAI8924813 (UMI)AAI8924813 http://hdl.handle.net/2142/21433 eng Copyright 1989 Machado, Jose Antonio Ferreira Statistics Economics, Theory Model selection: Consistency and robustness properties of the Schwarz Information Criterion for generalized M-estimation text Economics Economics University of Illinois at Urbana-Champaign Dissertation Ph.D.