Easy bootstrap-like estimation of asymptotic variances

Bo E. Honoré; Luojia Hu

doi:10.1016/j.econlet.2018.07.002

Easy bootstrap-like estimation of asymptotic variances

Bo E. Honoré, Luojia Hu

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the bootstrap can be very time-consuming. In a recent paper, Honoré and Hu (2017), we propose a “Poor (Wo)man's Bootstrap” based on one-dimensional estimators. In this paper, we propose a modified, simpler method and illustrate its potential for estimating asymptotic variances.

Original language	English (US)
Pages (from-to)	46-50
Number of pages	5
Journal	Economics Letters
Volume	171
DOIs	https://doi.org/10.1016/j.econlet.2018.07.002
State	Published - Oct 2018

All Science Journal Classification (ASJC) codes

Finance
Economics and Econometrics

Keywords

Bootstrap
Censored regression
Inference
Standard error
Two-step estimation

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10.1016/j.econlet.2018.07.002

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title = "Easy bootstrap-like estimation of asymptotic variances",

abstract = "The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the bootstrap can be very time-consuming. In a recent paper, Honor{\'e} and Hu (2017), we propose a “Poor (Wo)man's Bootstrap” based on one-dimensional estimators. In this paper, we propose a modified, simpler method and illustrate its potential for estimating asymptotic variances.",

keywords = "Bootstrap, Censored regression, Inference, Standard error, Two-step estimation",

author = "Honor{\'e}, \{Bo E.\} and Luojia Hu",

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year = "2018",

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doi = "10.1016/j.econlet.2018.07.002",

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AU - Honoré, Bo E.

AU - Hu, Luojia

PY - 2018/10

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N2 - The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the bootstrap can be very time-consuming. In a recent paper, Honoré and Hu (2017), we propose a “Poor (Wo)man's Bootstrap” based on one-dimensional estimators. In this paper, we propose a modified, simpler method and illustrate its potential for estimating asymptotic variances.

AB - The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the bootstrap can be very time-consuming. In a recent paper, Honoré and Hu (2017), we propose a “Poor (Wo)man's Bootstrap” based on one-dimensional estimators. In this paper, we propose a modified, simpler method and illustrate its potential for estimating asymptotic variances.

KW - Bootstrap

KW - Censored regression

KW - Inference

KW - Standard error

KW - Two-step estimation

UR - https://www.scopus.com/pages/publications/85049791311

UR - https://www.scopus.com/inward/citedby.url?scp=85049791311&partnerID=8YFLogxK

U2 - 10.1016/j.econlet.2018.07.002

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M3 - Article

AN - SCOPUS:85049791311

SN - 0165-1765

VL - 171

SP - 46

EP - 50

JO - Economics Letters

JF - Economics Letters

ER -

Easy bootstrap-like estimation of asymptotic variances

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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