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Testing for Unit Roots With Missing Observations

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Abstract

This paper considers unit root testing of time-series data with missing observations. Three procedures for dealing with the gaps are discussed. These include: ignoring the gaps, replacing the gaps with the last available observation, and filling the gaps with a linear interpolation method. The tests for the first two procedures yield test statistics which have the same asymptotic distribution as that tabulated by Dickey and Fuller (1979) for the complete data situation. The remaining procedure yields a test statistic that has an asymptotic distribution that differs from Dickey and Fuller’s tabulated distribution by an adjustment factor. In addition, models that include an ARIMA (0,1,q) error and augmented Dickey-Fuller tests are also considered in this paper. A simulation experiment is performed for the above models using the A-B sampling scheme. The results show that ignoring gaps in time- series data with missing observations produces unit root tests that are more powerful than the other two approaches that are considered.

Suggested Citation

  • Kevin F. Ryan & David E. A. Giles, 1998. "Testing for Unit Roots With Missing Observations," Econometrics Working Papers 9802, Department of Economics, University of Victoria.
    • Handle: RePEc:vic:vicewp:9802
    Note: ISSN 1485-6441. This paper was presented at the CEFES98 Meetings, Cambridge, U.K., June 1998, & at the 3rd Meeting of the New Zealand Econometric Study Group, Auckland, July 1998.
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Unit Root Tests With Missing Observations
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2012-04-02 01:13:00

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    Cited by:

    1. Facchini, François & Melki, Mickaël, 2013. "Efficient government size: France in the 20th century," European Journal of Political Economy, Elsevier, vol. 31(C), pages 1-14.
    2. Chad Stroomer & David E.A. Giles, 2003. "Income Convergence and trade Openness: Fuzzy Clustering and Time Series Evidence," Econometrics Working Papers 0304, Department of Economics, University of Victoria.
    3. Mishra, Vinod & Smyth, Russell, 2010. "Female labor force participation and total fertility rates in the OECD: New evidence from panel cointegration and Granger causality testing," Journal of Economics and Business, Elsevier, vol. 62(1), pages 48-64, January.
    4. Francis Teal & Markus Eberhardt, 2010. "Productivity Analysis in Global Manufacturing Production," Economics Series Working Papers 515, University of Oxford, Department of Economics.
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    6. Robert N. Collender & Samantha Roberts & Valerie L. Smith, 2007. "Signals from the Markets for Fannie Mae and Freddie Mac Subordinated Debt," FHFA Staff Working Papers 07-04, Federal Housing Finance Agency.
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    10. Bishai, David & Opuni, Marjorie & Poon, Andrew, 2007. "Does the level of infant mortality affect the rate of decline?: Time series data from 21 countries," Economics & Human Biology, Elsevier, vol. 5(1), pages 74-81, March.
    11. Papana, Angeliki & Kyrtsou, Catherine & Kugiumtzis, Dimitris & Diks, Cees, 2017. "Financial networks based on Granger causality: A case study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 65-73.
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    13. J. C. H. Jones & J. A. Schofield & D. E. A. Giles, 2000. "Our fans in the north: the demand for British Rugby League," Applied Economics, Taylor & Francis Journals, vol. 32(14), pages 1877-1887.
    14. Facchini, François & Melki, Mickaël, 2013. "Efficient government size: France in the 20th century," European Journal of Political Economy, Elsevier, vol. 31(C), pages 1-14.
    15. Marvasti, Akbar & Smyth, David, 2008. "Barter and Business Cycles: A Comment and Further Empirical Evidence," MPRA Paper 18258, University Library of Munich, Germany.
    16. Mitchell, Karlyn & Pearce, Douglas K., 2007. "Professional forecasts of interest rates and exchange rates: Evidence from the Wall Street Journal's panel of economists," Journal of Macroeconomics, Elsevier, vol. 29(4), pages 840-854, December.

    More about this item

    Keywords

    Unit Roots; Dickey-Fuller Test; Missing Data;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: 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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