Files in this item



application/pdf8924813.pdf (5Mb)Restricted to U of Illinois
(no description provided)PDF


Title:Model selection: Consistency and robustness properties of the Schwarz Information Criterion for generalized M-estimation
Author(s):Machado, Jose Antonio Ferreira
Doctoral Committee Chair(s):Koenker, Roger W.
Department / Program:Economics
Degree Granting Institution:University of Illinois at Urbana-Champaign
Economics, Theory
Abstract: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.
Issue Date:1989
Rights Information:Copyright 1989 Machado, Jose Antonio Ferreira
Date Available in IDEALS:2011-05-07
Identifier in Online Catalog:AAI8924813
OCLC Identifier:(UMI)AAI8924813

This item appears in the following Collection(s)

Item Statistics

  • Total Downloads: 1
  • Downloads this Month: 0
  • Downloads Today: 0