Prepivoting to reduce level error of confidence sets

Beran, Rudolf

doi:10.1093/biomet/74.3.457

Cited by 263 publications

(118 citation statements)

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“…For the for the Fuller estimator and 2SLS (without covariates) values are bootstrapped, as this is likely to lead to more precise inference arising from asymptotic refinements. A nested bootstrap with 999 times 999 replications is used, see Hall (1986), Beran (1987), Loh (1987) and Cameron and Trivedi (2005, p. 374). Because of an excessive demand on computation time, this is not possible for the CIV estimator where inference is based on 499 replications only.…”

Section: Results Of the Instrumental Variable Estimatorsmentioning

confidence: 99%

Exploiting regional treatment intensity for the evaluation of labour market policies

Frölich

Lechner

2006

Working Paper Series

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Exploiting Regional Treatment Intensity for the Evaluation of Labour Market Policies *We estimate the effects of active labour market policies (ALMP) on subsequent employment by nonparametric instrumental variables and matching estimators. Very informative administrative Swiss data with detailed regional information are combined with exogenous regional variation in programme participation probabilities, which generate an instrument within well-defined local labour markets. This allows pursuing instrumental variable as well as matching estimation strategies. A specific combination of those methods identifies a new type of effect heterogeneity. We find that ALMP increases individual employment probabilities by about 15% in the short term for unemployed that may be called 'marginal' participants. The effects seem to be considerably smaller for those unemployed not marginal to the participation decision. JEL Classification:J68, C14, C21

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Section: Results Of the Instrumental Variable Estimatorsmentioning

confidence: 99%

Exploiting regional treatment intensity for the evaluation of labour market policies

Frölich

Lechner

2006

Working Paper Series

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“…The double bootstrap was introduced by Beran in two papers, Beran (1987) and Beran (1988), in which he refers to "pre-pivoting", meaning making some quantity more close to being pivotal for a model by bootstrapping it, and then bootstrapping the result. This interpretation clearly applies to higher orders of bootstrap iteration.…”

Section: Discussionmentioning

confidence: 99%

A discrete model for bootstrap iteration

Davidson

2017

Journal of Econometrics

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractIn an attempt to free bootstrap theory from the shackles of asymptotic considerations, this paper studies the possibility of justifying, or validating, the bootstrap, not by letting the sample size tend to infinity, but by considering the sequence of bootstrap P values obtained by iterating the bootstrap. The main idea of the paper is that, if this sequence converges to a random variable that follows the uniform U(0, 1) distribution, then the bootstrap is valid. The idea is studied by making the model under test discrete and finite, so that it is characterised by a finite three-dimensional array of probabilities. This device, when available, renders bootstrap iteration to any desired order feasible. It is used for studying a unit-root test for a process driven by a stationary MA(1) process, where it is known that the unit-root test, even when bootstrapped, becomes quite unreliable when the MA(1) parameter is in the vicinity of -1. Iteration of the bootstrap P value to convergence achieves reliable inference except for a parameter value very close to -1. The paper then endeavours to see these specific results in a wider context, and tries to cast new light on where bootstrap theory may be going.

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“…Usually, the bootstrap can only be corrected by resorting to a more computer-intensive methods such as bootstrap iteration, e.g. Hall (1986) and Beran (1987). In one of Peter's latest papers, Chang and Hall (2015) showed that a single double bootstrap resampling is enough for achieving bias reduction in estimating such defined θ 0 , but not so for converge accuracy improvement of the confidence regions of θ 0 .…”

Section: El Is Bartlett-correctablementioning

confidence: 99%

Peter Hall's Contribution to Empirical Likelihood

Chang¹,

Guo²,

Tang³

2018

STAT SINICA

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We deeply mourn the loss of Peter Hall. Peter was the premier mathematical statistician of his era. His work illuminated many aspects of statistical thought. While his body of work on bootstrap and nonparametric smoothing is widely known and appreciated, less well known is his work in many other areas. In this article, we review Peter's contribution to empirical likelihood (EL). Peter has done fundamental work on studying the coverage accuracy of confidence regions constructed with EL.

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Prepivoting to reduce level error of confidence sets

Cited by 263 publications

References 15 publications

Exploiting regional treatment intensity for the evaluation of labour market policies

Exploiting regional treatment intensity for the evaluation of labour market policies

A discrete model for bootstrap iteration

Peter Hall's Contribution to Empirical Likelihood

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