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DF-IV Unit Root Tests Using Stationary Instrument Variables

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  • Kyung So Im
  • Junsoo Lee
  • Vladimir Arcabic
  • Mansik Hur

Abstract

We propose new unit root tests using stationary instrumental variables in the framework of the Dickey-Fuller (DF) regression. The most noteworthy feature of the suggested tests is that they are free of nuisance parameters. Under the null hypothesis, the proposed test statistic converges to the standard normal distribution regardless of various types of linear deterministic trends or structural breaks in the time series.Mathematics Subject Classification: 91B84; 62M10Keywords: Unit Root Tests; Dickey Fuller; Instrumental Variables; Standard Normal Distributions; t-test

Suggested Citation

  • Kyung So Im & Junsoo Lee & Vladimir Arcabic & Mansik Hur, 2018. "DF-IV Unit Root Tests Using Stationary Instrument Variables," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 7(1), pages 1-1.
    • Handle: RePEc:spt:stecon:v:7:y:2018:i:1:f:7_1_1
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    References listed on IDEAS

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    1. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
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    3. Phillips, Peter C. B. & Park, Joon Y. & Chang, Yoosoon, 2004. "Nonlinear instrumental variable estimation of an autoregression," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 219-246.
    4. Junsoo Lee & Mark C. Strazicich, 2001. "Break Point Estimation and Spurious Rejections With Endogenous Unit Root Tests," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 63(5), pages 535-558, December.
    5. Harris, David & McCabe, Brendan & Leybourne, Stephen, 2003. "Some Limit Theory For Autocovariances Whose Order Depends On Sample Size," Econometric Theory, Cambridge University Press, vol. 19(5), pages 829-864, October.
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    7. So, Beong Soo & Shin, Dong Wan, 1999. "Cauchy Estimators For Autoregressive Processes With Applications To Unit Root Tests And Confidence Intervals," Econometric Theory, Cambridge University Press, vol. 15(2), pages 165-176, April.
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