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A mean-difference test based on self-normalization for alternating regime index data sets

Title
A mean-difference test based on self-normalization for alternating regime index data sets
Authors
Kim, Bo GyeongShin, Dong Wan
Ewha Authors
신동완
SCOPUS Author ID
신동완scopus
Issue Date
2020
Journal Title
ECONOMICS LETTERS
ISSN
0165-1765JCR Link

1873-7374JCR Link
Citation
ECONOMICS LETTERS vol. 193
Keywords
Financial crisisRecessionSelf-normalizationUncertainty indexVolatility spillover index
Publisher
ELSEVIER SCIENCE SA
Indexed
SSCI; SCOPUS WOS scopus
Document Type
Article
Abstract
We are interested in testing regime mean difference in some recently developed indexes which try to characterize alternating regimes: uncertainty indexes for economic expansion and recession and volatility spillover indexes for financial crisis and non-crisis. To account for strong serial correlation and conditional heteroskedasticity apparent in the index data sets, we consider the Kiefer-Vogelsang-Bunzell (KVB) self-normalization method for normalization of the estimated mean difference to construct a t-test. The limiting null distribution of the proposed test is shown to be different from the distribution derived by Kiefer-Vogelsang-Bunzel for a standard regression model. The proposed test is shown to have better finite sample size than the conventional t-test based on the Newey-West HAC standard error. Using the proposed test, we show a statistically significant counter-cyclical feature of uncertainty index and sensitivity of volatility spillover index to financial crisis. (C) 2019 Published by Elsevier B.V.
DOI
10.1016/j.econlet.2019.01.007
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
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