Long Run Variance Estimation and Robust Regression Testing Using Sharp Origin Kernels with No Truncation

Long Run Variance Estimation and Robust Regression Testing Using Sharp Origin Kernels with No Truncation

A new family of kernels is suggested for use in long run variance (LRV) estimation and robust regression testing. The kernels are constructed by taking powers of the Bartlett kernel and are intended to be used with no truncation (or bandwidth) parameter. As the power parameter ([rho]) increases, the...

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Bibliographic Details
Main Authors: PHILLIPS, Peter C. B., SUN, Yixiao, JIN, Sainan
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2007
Subjects:
Heteroscedasticity and autocorrelation consistent standard error; Data-determined kernel estimation; Long run variance; Power parameter; Sharp origin kernel
Econometrics
Online Access:https://ink.library.smu.edu.sg/soe_research/318
https://ink.library.smu.edu.sg/context/soe_research/article/1317/viewcontent/LongRunVarianceEstimation_sharpOriginKernels_2007.pdf
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Institution: Singapore Management University
Language: English

Internet

https://ink.library.smu.edu.sg/soe_research/318
https://ink.library.smu.edu.sg/context/soe_research/article/1317/viewcontent/LongRunVarianceEstimation_sharpOriginKernels_2007.pdf

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