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자연과학대학
통계학전공
Journal papers
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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 B.G.
;
Shin D.W.
Ewha Authors
신동완
SCOPUS Author ID
신동완
Issue Date
2020
Journal Title
Economics Letters
ISSN
0165-1765
Citation
Economics Letters vol. 193
Keywords
Financial crisis
;
Recession
;
Self-normalization
;
Uncertainty index
;
Volatility spillover index
Publisher
Elsevier B.V.
Indexed
SSCI; 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. © 2019
DOI
10.1016/j.econlet.2019.01.007
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