Publication Type
Journal Article
Version
submittedVersion
Publication Date
1-2004
Abstract
The null distribution of the overlapping variance-ratio (OVR) test of the random-walk hypothesis is known to be downward biased and skewed to the right in small samples. As shown by , the test under-rejects the null on the left tail seriously when the sample size is small. This property adversely affects the applicability of the OVR test to macroeconomic time series, which usually have rather small samples. In this paper, we propose a modified overlapping variance-ratio statistic and derive its exact mean under the normality assumption. We propose to approximate the small-sample distribution of the modified statistic using a beta distribution that matches the (exact) mean and the (asymptotic) variance. A Monte Carlo experiment shows that the beta approximation performs well in small samples.
Keywords
Beta distribution, Monte Carlo experiment, random-walk hypothesis, variance-ratio test
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Time Series Analysis
Volume
25
Issue
1
First Page
127
Last Page
135
ISSN
0143-9782
Identifier
10.1046/j.0143-9782.2003.01804.x
Publisher
Wiley
Citation
TSE, Yiu Kuen; NG, K. W.; and ZHANG, Xibin.
A Small-Sample Overlapping Variance-Ratio Test. (2004). Journal of Time Series Analysis. 25, (1), 127-135.
Available at: https://ink.library.smu.edu.sg/soe_research/149
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1046/j.0143-9782.2003.01804.x