How useful is yet another data-driven bandwidth in long-run variance estimation? A simulation study on cointegrating regressions
type: Item
instance of: scholarly article
title: How useful is yet another data-driven bandwidth in long-run variance estimation? A simulation study on cointegrating regressions
zbMATH Open document ID: 1216.62142
author: Masayuki Hirukawa
published in: Economics Letters
publication date: 2011-06-30T00:00:00Z
Mathematics Subject Classification ID: 62M10
Mathematics Subject Classification ID: 62P20
Mathematics Subject Classification ID: 65C05
Mathematics Subject Classification ID: 91B84
zbMATH DE Number: 5916280
zbMATH Keywords: cointegration
zbMATH Keywords: kernel
MaRDI profile type: Publication
full work available at URL: j.econlet.2011.02.006
OpenAlex ID: W2154538336
cites work: Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
cites work: A TWO-STAGE PLUG-IN BANDWIDTH SELECTION AND ITS IMPLEMENTATION FOR COVARIANCE ESTIMATION
cites work: Asymptotic properties of the efficient estimators for cointegrating regression models with serially dependent errors
cites work: Automatic Lag Selection in Covariance Matrix Estimation
cites work: Canonical Cointegrating Regressions
cites work: Statistical Inference in Instrumental Variables Regression with I(1) Processes
cites work: Q4272483
DOI: 10.1016/J.ECONLET.2011.02.006
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description: scientific article; zbMATH DE number 5916280