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Estimation and Inference in Econometrics

Bibliographic Data

ID9725157
AuthorsJames Davidson (Queen's University, corresponding author), Russell Davidson (0000-0003-4214-5198), James G MacKinnon (0000-0002-5457-294X, Queen's University, corresponding author)
Year1995
Volume62
Issue245
Pages133
Publication date1995-02-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueEconomica (JOURNAL)
Journal identifiersISSN: 0013-0427 • E-ISSN: 1468-0335
PublisherJSTOR (PUBLISHER)
DOI10.2307/2554780
OpenAlexW4230682695
LanguageEN
Citations received5
References cited16

The astonishing increase in computer performance over the past two decades has made it possible for economists to base many statistical inferences on simulated, or bootstrap, distributions rather than on distributions obtained from asymptotic theory. In this paper, I review some of the basic ideas of bootstrap inference. The paper discusses Monte Carlo tests, several types of bootstrap test, and bootstrap confidence intervals. Although bootstrapping often works well, it does not do so in every case

Econometrics · Economics · Estimation · Inference · Advanced Statistical Methods and Models · Artificial Intelligence · Computer Science · Forecasting Techniques and Applications

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Unique citing works5
Citations per year0,19
Citation span1999 - 2006 (8)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 5

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