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Specification Sensitivities in Right-Tailed Unit Root Testing for Financial Bubbles

Author

Listed:
  • Shu-Ping Shi

    (The Australian National University)

  • Peter C. B. Phillips

    (Yale University, University of Auckland, University of Southampton and Singapore Management University)

  • Jun Yu

    (Singapore Management University and Hong Kong Institute for Monetary Research)

Abstract

Right-tailed unit root tests have proved promising for detecting exuberance in economic and financial activities. Like left-tailed tests, the limit theory and test performance are sensitive to the null hypothesis and the model specification used in parameter estimation. This paper aims to provide some empirical guidelines for the practical implementation of right-tailed unit root tests, focusing on the sup ADF test of Phillips, Wu and Yu (2011), which implements a right-tailed ADF test repeatedly on a sequence of forward sample recursions. We analyze and compare the limit theory of the sup ADF test under different hypotheses and model specifications. The size and power properties of the test under various scenarios are examined in simulations and some recommendations for empirical practice are given. An empirical application to Nasdaq data reveals the practical importance of model specification on test outcomes.

Suggested Citation

  • Shu-Ping Shi & Peter C. B. Phillips & Jun Yu, 2011. "Specification Sensitivities in Right-Tailed Unit Root Testing for Financial Bubbles," Working Papers 172011, Hong Kong Institute for Monetary Research.
    • Handle: RePEc:hkm:wpaper:172011
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    References listed on IDEAS

    as
    1. Peter C. B. Phillips & Yangru Wu & Jun Yu, 2011. "EXPLOSIVE BEHAVIOR IN THE 1990s NASDAQ: WHEN DID EXUBERANCE ESCALATE ASSET VALUES?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(1), pages 201-226, February.
    2. Diba, Behzad T & Grossman, Herschel I, 1988. "Explosive Rational Bubbles in Stock Prices?," American Economic Review, American Economic Association, vol. 78(3), pages 520-530, June.
    3. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    4. Peter C.B. Phillips & Chin Chin Lee, 1996. "Efficiency Gains from Quasi-Differencing Under Nonstationarity," Cowles Foundation Discussion Papers 1134, Cowles Foundation for Research in Economics, Yale University.
    5. Evans, George W, 1991. "Pitfalls in Testing for Explosive Bubbles in Asset Prices," American Economic Review, American Economic Association, vol. 81(4), pages 922-930, September.
    6. Phillips, Peter C.B. & Magdalinos, Tassos, 2007. "Limit theory for moderate deviations from a unit root," Journal of Econometrics, Elsevier, vol. 136(1), pages 115-130, January.
    7. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    8. Schmidt, Peter & Phillips, C B Peter, 1992. "LM Tests for a Unit Root in the Presence of Deterministic Trends," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 257-287, August.
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    Cited by:

    1. Peter C.B. Phillips & Shu-Ping Shi, 2014. "Financial Bubble Implosion," Cowles Foundation Discussion Papers 1967, Cowles Foundation for Research in Economics, Yale University.
    2. Xi-Xi Zhang & Lu Liu & Chi-Wei Su & Ran Tao & Oana-Ramona Lobonţ & Nicoleta-Claudia Moldovan, 2019. "Bubbles in Agricultural Commodity Markets of China," Complexity, Hindawi, vol. 2019, pages 1-7, December.
    3. Yoon, Gawon, 2012. "Explosive U.S. budget deficit," Economic Modelling, Elsevier, vol. 29(4), pages 1076-1080.

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    More about this item

    Keywords

    Unit Root Test; Mildly Explosive Process; Recursive Regression; Size and Power;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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