Home
About
Aims and Scope
Editorial Board
Submit
Archive
Search
|
Journal of Economic Theory and Econometrics
Journal of the Korean Econometric Society
Long-run Variance Estimation for Linear Processes Under Possible Degeneracy
Vol.21, No.1, March 2010, 1–22
|
|
Jin Lee
(Ewha Womans University)
|
|
|
|
Abstract
We analyze the asymptotic behavior of the long-run variance estimator for linear processes under degeneracy, where the spectral density function near the origin equals to zero. Given degeneracy which typically arises from over-differencing, standard results in the literature of heteroskedasticity and autocorrelation consistent (HAC) estimation are invalid. We provide asymptotic distribution of the long-run variance estimator from long term trends in linear processes. Further, we propose a test statistic to testing degeneracy, which achieves asymptotic normality. Our test is directly applied to testing for trend stationarity. Under the null of trend stationarity, the spectrum near the origin for the differenced process becomes zero. On the other hand, under the alternative of difference stationarity, the spectrum becomes strictly positive at the zero frequency. It is found that, depending on the signal-to-ratio, our test has significant power advantages over the KPSS test. Thus, the proposed test becomes an useful complement to the KPSS test.
|
Keywords
long-run variance, linear process, spectral density estimator, degeneracy, trend stationarity |
JEL classification codes
C12, C14, C22 |
|
Links
KCI
KES
SCOPUS
MathJax
|