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• W3121553376 abstract "This paper establishes consistency and non‐standard rates of convergence for set estimators based on contour sets of criterion functions for a semi‐parametric binary response model under a conditional median restriction. The model can be partially identified due to potentially limited‐support regressors and an unknown distribution of errors. A set estimator analogous to the maximum score estimator is essentially cube‐root consistent for the identified set when a continuous but possibly bounded regressor is present. Arbitrarily fast convergence occurs when all regressors are discrete. We also establish the validity of a subsampling procedure for constructing confidence sets for the identified set. As a technical contribution, we provide more convenient sufficient conditions on the underlying empirical processes for cube‐root convergence and a sufficient condition for arbitrarily fast convergence, both of which can be applied to other models. Finally, we carry out a series of Monte Carlo experiments, which verify our theoretical findings and shed light on the finite‐sample performance of the proposed procedures." @default.
• W3121553376 created "2021-02-01" @default.
• W3121553376 creator A5011461802 @default.
• W3121553376 date "2015-06-01" @default.
• W3121553376 modified "2023-09-27" @default.
• W3121553376 title "Non‐standard rates of convergence of criterion‐function‐based set estimators for binary response models" @default.
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• W3121553376 doi "https://doi.org/10.1111/ectj.12048" @default.
• W3121553376 hasPublicationYear "2015" @default.
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