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Mild-explosive and Local-to-mild-explosive Autoregressions with Serially Correlated Errors

Author

Listed:
  • Lui, Yiu Lim

    (School of Economics, Singapore Management University)

  • Xiao, Weilin

    (School of Management, Zhejiang University)

  • Yu, Jun

    (School of Economics, Singapore Management University)

Abstract

This paper firstly extends the results of Phillips and Magdalinos (2007a) by allowing for anti-persistent errors in mildly explosive autoregressive models. It is shown that the Cauchy asymptotic theory remains valid for the least squares (LS) estimator. The paper then extends the results of Phillips, Magdalinos and Giraitis (2010) by allowing for serially correlated errors of various forms in local-to mild-explosive autoregressive models. It is shown that the result of smooth transition in the limit theory between local-to-unity and mild-explosiveness remains valid for the LS estimator. Finally, the limit theory for autoregression with intercept is developed.

Suggested Citation

  • Lui, Yiu Lim & Xiao, Weilin & Yu, Jun, 2018. "Mild-explosive and Local-to-mild-explosive Autoregressions with Serially Correlated Errors," Economics and Statistics Working Papers 22-2018, Singapore Management University, School of Economics.
    • Handle: RePEc:ris:smuesw:2018_022
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    More about this item

    Keywords

    Anti-persistent; unit root; mildly explosive; limit theory; bubble; fractional integration; Young integral;
    All these keywords.

    JEL classification:

    • 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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