A consistent bootstrap procedure for the maximum score estimator

DOI10.1016/j.jeconom.2018.04.001zbMath1452.62254arXiv1105.1976OpenAlexW2962677564MaRDI QIDQ1644259

Bodhisattva Sen, Emilio Seijo, Rohit Kumar Patra

Publication date: 21 June 2018

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1105.1976

zbMATH Keywords

smoothed bootstrap(in)-consistency of bootstraplatent variable modelcube-root asymptoticsbinary choice model

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Nonparametric statistical resampling methods (62G09)

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Best subset binary prediction ⋮ Bootstrap confidence regions based on M-estimators under nonstandard conditions ⋮ Transformation-Invariant Learning of Optimal Individualized Decision Rules with Time-to-Event Outcomes ⋮ Isotonic regression discontinuity designs ⋮ INTEGRATED SCORE ESTIMATION ⋮ Efficient estimation in single index models through smoothing splines ⋮ Optimal linear discriminators for the discrete choice model in growing dimensions

Cites Work

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• Exact computation of max weighted score estimators
• Cube root asymptotics
• Inconsistency of bootstrap: the Grenander estimator
• Semiparametric analysis of discrete response. Asymptotic properties of the maximum score estimator
• Non-parametric analysis of a generalized regression model. The maximum rank correlation estimator
• Some asymptotic theory for the bootstrap
• On the asymptotic accuracy of Efron's bootstrap
• Maximum score estimation of the stochastic utility model of choice
• On the computation of semiparametric estimates in limited dependent variable models
• Asymptotics via empirical processes. With comments and a rejoinder by the author
• Optimal global rates of convergence for nonparametric regression
• Bootstrap critical values for tests based on the smoothed maximum score estimator
• The jackknife and bootstrap
• Weak convergence and empirical processes. With applications to statistics
• Rates of strong uniform consistency for local least squares kernel regression estimators
• Uniform in bandwidth consistency of kernel-type function estimators
• Distribution-Free Maximum Likelihood Estimator of the Binary Choice Model
• UNIFORM CONVERGENCE RATES FOR KERNEL ESTIMATION WITH DEPENDENT DATA
• A Smoothed Maximum Score Estimator for the Binary Response Model
• Direct Semiparametric Estimation of Single-Index Models with Discrete Covariates
• Semiparametric Estimation of Index Coefficients
• Robust Estimation in Binary Choice Models
• DYNAMIC TIME SERIES BINARY CHOICE
• The Limiting Distribution of the Maximum Rank Correlation Estimator
• On the Bootstrap of the Maximum Score Estimator
• Onmout ofnBootstrapping for Nonstandard M-Estimation With Nuisance Parameters
• Probability
• Set-valued analysis
• Subsampling inference in cube root asymptotics with an application to Manski's maximum score estimator.