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On the Bootstrap of the Maximum Score Estimator
Author(s) -
Abrevaya Jason,
Huang Jian
Publication year - 2005
Publication title -
econometrica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 16.7
H-Index - 199
eISSN - 1468-0262
pISSN - 0012-9682
DOI - 10.1111/j.1468-0262.2005.00613.x
Subject(s) - estimator , mathematics , cube root , inference , statistics , class (philosophy) , extremum estimator , asymptotic distribution , convergence (economics) , weak convergence , bootstrapping (finance) , m estimator , econometrics , computer science , economics , artificial intelligence , geometry , computer security , asset (computer security) , economic growth
This paper shows that the bootstrap does not consistently estimate the asymptotic distribution of the maximum score estimator. The theory developed also applies to other estimators within a cube‐root convergence class. For some single‐parameter estimators in this class, the results suggest a simple method for inference based upon the bootstrap.