Stochastic Volatility: Selected Readings
In: The economic journal: the journal of the Royal Economic Society, Band 116, Heft 512, S. F326-F327
ISSN: 1468-0297
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In: The economic journal: the journal of the Royal Economic Society, Band 116, Heft 512, S. F326-F327
ISSN: 1468-0297
In: Journal of Econometrics, Band 147, Heft 1, S. 84-98
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.
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In: Journal of Time Series Analysis, Band 39, Heft 6, S. 920-941
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In: Journal of Time Series Analysis, Band 38, Heft 4, S. 513-534
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In: Tinbergen Institute Discussion Paper 2019-083/III
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In: Univ. of Copenhagen Dept. of Economics Discussion Paper No. 13-13
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