Publication:
Improved nonparametric confidence intervals in time series regressions

Simple item page
dc.affiliation.dptoUC3M. Departamento de Estadísticaes
dc.contributor.authorRomano, Joseph P.es
dc.contributor.authorWolf, Michaeles
dc.date.accessioned2006-11-08T15:55:51Z
dc.date.available2006-11-08T15:55:51Z
dc.date.issued2001-01es
dc.description.abstractConfidence intervals in time series regressions suffer from notorious coverage problems. This is especially true when the dependence in the data is noticeable and sample sizes are small to moderate, as is often the case in empirical studies. This paper proposes a method that combines prewhitening and the studentized bootstrap. While both prewhitening and the studentized bootstrap each provides improvement over standard normal theory intervals, one can achieve a further improvement by conjoining them in an appropriate way. As a side note, it is stressed that symmetric confidence intervals equal-tailed ones, since they exhibit improved coverage accuracy. We propose concrete ways to deal with the issues of block size, choice of kernel, and choice of bandwidth. The improvements in small sample performance are supported by a simulation study.es
dc.format.extent324440 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.repecws010201
dc.identifier.urihttps://hdl.handle.net/10016/148
dc.language.isoenges
dc.relation.ispartofseriesUC3M Working Papers. Statistics and Econometricses
dc.relation.ispartofseries2001-01es
dc.rights.accessRightsopen access
dc.subject.ecienciaEstadística
dc.titleImproved nonparametric confidence intervals in time series regressionses
dc.typeworking paper*
dspace.entity.typePublication
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
ws010201.pdf
Size:
316.84 KB
Format:
Adobe Portable Document Format
Download
Collections
DES - Working Papers. Statistics and Econometrics. WS