View : 16 Download: 0

Tests for asymmetry in possibly nonstationary time series data

Title
Tests for asymmetry in possibly nonstationary time series data
Authors
Shin D.W.Lee O.
Ewha Authors
이외숙신동완
SCOPUS Author ID
이외숙scopus; 신동완scopus
Issue Date
2001
Journal Title
Journal of Business and Economic Statistics
ISSN
0735-0015JCR Link
Citation
vol. 19, no. 2, pp. 233 - 244
Indexed
SCIE; SSCI; SCOPUS scopus
Abstract
Tests for asymmetric adjustment in possibly nonstationary, nearly nonstationary, or stationary time series data are developed. The asymmetry is modeled by the momentum threshold autoregressive model of Enders and Granger and an extension of it. The tests are t-type tests and Wald tests based on instrumental-variable estimators and are asymptotically normal or chi-squared regardless of stationarity/nonstationarity of data-generating processes. This is in contrast to the fact that the t tests and the Wald tests based on the ordinary least squares estimator (OLSE) are asymptotically normal and chi-squared, respectively, only under stationarity and are thus statistically invalid under nonstationarity. A Monte Carlo simulation shows that the proposed tests have stable sizes. Powers of the proposed tests against stationary alternatives are comparable to those of the OLSE-based tests. The Monte Carlo study also shows that the new estimators are less biased than the OLSE when data-generating processes are random walks. The proposed tests are applied to a monthly U.K. interest-rate dataset to find evidences for asymmetry in directions of adjustments as well as in amounts of adjustments.
DOI
10.1198/073500101316970458
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE