A Fixed-bandwidth View of the Pre-asymptotic Inference for Kernel Smoothing with Time Series Data

Min Seong Kim (), Yixiao Sun and Jingjing Yang ()
Additional contact information
Min Seong Kim: Department of Economics, Ryerson University, Toronto, Canada

No 49, Working Papers from Toronto Metropolitan University, Department of Economics

Abstract: This paper develops robust testing procedures for nonparametric kernel methods in the presence of temporal dependence of unknown forms. Based on the ?fixed-bandwidth asymptotic variance and the pre-asymptotic variance, we propose a heteroskedasticity and autocorrelation robust (HAR) variance estimator that achieves double robustness ? it is asymptotically valid regardless of whether the temporal dependence is present or not, and whether the kernel smoothing bandwidth is held constant or allowed to decay with the sample size. Using the HAR variance estimator, we construct the studentized test statistic and examine its asymptotic properties under both the fi?xed-smoothing and increasing-smoothing asymptotics. The ?fixed-smoothing approximation and the associated convenient t-approximation achieve extra robustness ? it is asymptotically valid regardless of whether the truncation lag parameter governing the covariance weighting grows at the same rate as or a slower rate than the sample size. Finally, we suggest a simulation-based calibration approach to choose smoothing parameters that optimize testing oriented criteria. Simulation shows that the proposed procedures work very well in ?finite samples.

Keywords: heteroskedasticity and autocorrelation robust variance; calibration; fi?xed-smoothing asymptotics; ?fixed-bandwidth asymptotics; kernel density estimator; local polynomial estimator; t-approximation; testing-optimal smoothing-parameters choice; temporal dependence (search for similar items in EconPapers)
JEL-codes: C12 C14 C22 (search for similar items in EconPapers)
Pages: 50 pages
Date: 2015-09
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.arts.ryerson.ca/economics/repec/pdfs/wp049.pdf (application/pdf)

Related works:
Journal Article: A fixed-bandwidth view of the pre-asymptotic inference for kernel smoothing with time series data (2017)
Working Paper: A Fixed-bandwidth View of the Pre-asymptotic Inference for Kernel Smoothing with Time Series Data (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rye:wpaper:wp049

Access Statistics for this paper

More papers in Working Papers from Toronto Metropolitan University, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Doosoo Kim ().