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Testing for a change in persistence in the presence of non-stationary volatility

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  • Cavaliere, Giuseppe
  • Taylor, A.M. Robert

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 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 USÂ price inflation data is provided.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 147 (2008)
Issue (Month): 1 (November)
Pages: 84-98

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Handle: RePEc:eee:econom:v:147:y:2008:i:1:p:84-98

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Web page: http://www.elsevier.com/locate/jeconom

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Keywords: Persistence change Non-stationary volatility Wild bootstrap;

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Citations

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Cited by:
  1. Chen, Zhanshou & Jin, Zi & Tian, Zheng & Qi, Peiyan, 2012. "Bootstrap testing multiple changes in persistence for a heavy-tailed sequence," Computational Statistics & Data Analysis, Elsevier, vol. 56(7), pages 2303-2316.
  2. Taipalus , Katja, 2012. "Signaling asset price bubbles with time-series methods," Research Discussion Papers 7/2012, Bank of Finland.
  3. Heinen, Florian & Sibbertsen, Philipp & Kruse, Robinson, 2009. "Forecasting long memory time series under a break in persistence," Hannover Economic Papers (HEP) dp-433, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  4. Aleksandar Zaklan & Jan Abrell & Anne Neumann, 2011. "Stationarity Changes in Long-Run Fossil Resource Prices: Evidence from Persistence Break Testing," Discussion Papers of DIW Berlin 1152, DIW Berlin, German Institute for Economic Research.
  5. Cavaliere, Giuseppe & Taylor, A.M. Robert, 2008. "Testing for a change in persistence in the presence of non-stationary volatility," Journal of Econometrics, Elsevier, vol. 147(1), pages 84-98, November.
  6. Chen, Zhanshou & Tian, Zheng & Wei, Yuesong, 2010. "Monitoring change in persistence in linear time series," Statistics & Probability Letters, Elsevier, vol. 80(19-20), pages 1520-1527, October.
  7. Taipalus, Katja, 2012. "Detecting asset price bubbles with time-series methods," Scientific Monographs E:47/2012, Bank of Finland.
  8. Heinen, Florian & Willert, Juliane, 2011. "Monitoring a change in persistence of a long range dependent time series," Hannover Economic Papers (HEP) dp-479, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

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