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030 Department Bulletin Papers = 本学紀要論文
*Hitotsubashi journal of economics
Vol. 64, no. 2(Dec. 2023)
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Identifier to cite or link to this item: https://doi.org/10.15057/26018
Identifier to cite or link to this item: https://hdl.handle.net/10086/26018
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cover_26018
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Title
ESTIMATION AND INFERENCE IN PREDICTIVE REGRESSIONS
Creator
Creator Name
KUROZUMI, EIJI
KUROZUMI, EIJI
Affiliation
Affiliation Name
Hitotsubashi University
Creator Name
AONO, KOHEI
AONO, KOHEI
Affiliation
Affiliation Name
Kyoto Sangyo University
Key Word
near unit root
bias
stock return
jackknife
JEL
C13
C22
C58
G17
Abstract
In this paper, we analyze feasible bias-reduced versions of point estimates for predictive regressions: The plug-in estimates, which are based on the augmented regressions proposed by Amihud and Hurvich (2004) and Amihud, Hurvich and Wang (2010), and the grouped jackknife estimate by Quenouille (1949, 1956).We also derive the correct standard errors associated with these point estimates.The methods thus allow for a unified inferential framework, where point estimates and statistical inference are based on the same methods. Using the new estimates, we investigate U.S. stock returns and find that some variables are able to predict stock returns.
Publisher
Hitotsubashi University
Issued Date
2013-12
Language
English(eng)
Resource Type
departmental bulletin paper
Version Type
VoR
selfDOI
10.15057/26018
ISSN
0018-280x
NCID
AA00207547
Source Title
Hitotsubashi Journal of Economics
Volume Number
54
Issue Number
2
Page Start
231
Page End
250
Appears in Collections
Vol. 54, no. 2 (Dec. 2013)
URL
https://hdl.handle.net/10086/26018
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