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Testing for a change in persistence in the presence of non-stationary volatility
[Zeitschriftenartikel]
Abstract
In this paper we consider tests for the null of (trend-) stationarity against the alternative of a change in persistence at some (known or unknown) point in the observed sample, either from I(0) to I(1) behaviour or vice versa, of, inter alia, (Kim, J., 2000. Detection of change in persistence of a ... mehr
In this paper we consider tests for the null of (trend-) stationarity against the alternative of a change in persistence at some (known or unknown) point in the observed sample, either from I(0) to I(1) behaviour or vice versa, of, inter alia, (Kim, J., 2000. Detection of change in persistence of a linear time series. Journal of Econometrics 95, 97–116). We show that in circumstances where the innovation process displays non-stationary unconditional volatility of a very general form, which includes single and multiple volatility breaks as special cases, the ratio-based statistics used to test for persistence change do not have pivotal limiting null distributions. Numerical evidence suggests that this can cause severe over-sizing in the tests. In practice it may therefore be hard to discriminate between persistence change processes and processes with constant persistence but which display time-varying unconditional volatility. We solve the identified inference problem by proposing wild bootstrap-based implementations of the tests. Monte Carlo evidence suggests that the bootstrap tests perform well in finite samples. An empirical illustration using US price inflation data is provided.... weniger
Klassifikation
Wirtschaftswissenschaften
Freie Schlagwörter
persistence change; non-stationary volatility; wild bootstrap
Sprache Dokument
Englisch
Publikationsjahr
2008
Seitenangabe
S. 84-98
Zeitschriftentitel
Journal of Econometrics, 147 (2008) 1
DOI
https://doi.org/10.1016/j.jeconom.2008.09.004
Status
Postprint; begutachtet (peer reviewed)
Lizenz
PEER Licence Agreement (applicable only to documents from PEER project)