Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Benoit Perron"'
Publikováno v:
Econometrics, Vol 9, Iss 3, p 29 (2021)
Peter Phillips has had a tremendous impact on econometric theory and practice [...]
Externí odkaz:
https://doaj.org/article/36259733d5f741cb81d303bd2ec3fd31
Publikováno v:
Quantitative Economics. 14:511-569
In this paper, we introduce a method of generating bootstrap samples with unknown patterns of cross‐ sectional/spatial dependence, which we call the spatial dependent wild bootstrap. This method is a spatial counterpart to the wild dependent bootst
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a73fd8229602e8854f2bec7f7fb94b47
https://doi.org/10.3982/qe1626
https://doi.org/10.3982/qe1626
Publikováno v:
Journal of Econometrics. 218:243-246
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c74078e6a73f4baf24d1d5470d7173a6
https://doi.org/10.1016/j.jeconom.2020.07.040
https://doi.org/10.1016/j.jeconom.2020.07.040
Autor:
Benoit Perron, Sílvia Gonçalves
Publikováno v:
Journal of Econometrics. 218:476-495
We consider bootstrap methods for factor-augmented regressions with cross sectional dependence among idiosyncratic errors. This is important to capture the bias of the OLS estimator derived recently by Goncalves and Perron (2014). We first show that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::49a9b92347949bd23df07f47ad252edc
https://doi.org/10.1016/j.jeconom.2020.04.026
https://doi.org/10.1016/j.jeconom.2020.04.026
Le but du présent travail est d'évaluer l'apport que pourrait avoir l’imposition de règles budgétaires sur le retour au déficit 0 annoncé pour 2027-28 dans le budget 2021-22. Notre approche simule de nombreux scénarios économiques futurs, c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4bbdcd797205403ef49168569a2b00be
https://doi.org/10.54932/nesj4065
https://doi.org/10.54932/nesj4065
Publikováno v:
Journal of Business & Economic Statistics. 35:53-69
We propose bootstrap prediction intervals for an observation h periods into the future and its conditional mean. We assume that these forecasts are made using a set of factors extracted from a large panel of variables. Because we treat these factors
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::41e7ef1545613603b91c964e218b815e
https://doi.org/10.1080/07350015.2015.1054492
https://doi.org/10.1080/07350015.2015.1054492
Autor:
Sílvia Gonçalves, Benoit Perron
Publikováno v:
Journal of Statistical Planning and Inference. 177:31-34
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6050275e01212b5c1cd750b85b0dafb3
https://doi.org/10.1016/j.jspi.2015.10.013
https://doi.org/10.1016/j.jspi.2015.10.013
We introduce a new stylized fact: the hump-shaped behavior of slopes and coefficients of determination as a function of the aggregation horizon when running (forward/backward) predictive regressions of future excess market returns onto past economic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e855790aa74bd1c8363752ed66ed396b
http://eprints.lse.ac.uk/85646/
http://eprints.lse.ac.uk/85646/
Publikováno v:
Journal of Time Series Analysis. 36:481-502
This article considers bootstrap inference in a factor-augmented regression context where the errors could potentially be serially correlated. This generalizes results in Goncalves & Perron (2014) and makes the bootstrap applicable to forecasting con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::05b599ecd99d903ad5c97ce34e95cbb5
https://doi.org/10.1111/jtsa.12118
https://doi.org/10.1111/jtsa.12118
Publikováno v:
The Econometrics Journal. 17:338-372
Summary Generalizations of the point-optimal panel unit root tests of Moon, Perron and Phillips (MPP) are developed to cover cases of serially correlated errors. The resulting statistics involve two modifications relative to those of MPP: (a) the err
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0cc9f722b6b1663636b3a8598dcc63d4
https://doi.org/10.1111/ectj.12030
https://doi.org/10.1111/ectj.12030