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Approaches for the Joint Evaluation of Hypothesis Tests: Classical Testing, Bayes Testing, and Joint Confirmation

  • Kunst, Robert M.

    (Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria and Department of Economics, University of Vienna)

The occurrence of decision problems with changing roles of null and alternative hypotheses has increased interest in extending the classical hypothesis testing setup. Particularly, confirmation analysis has been in the focus of some recent contributions in econometrics. We emphasize that confirmation analysis is grounded in classical testing and should be contrasted with the Bayesian approach. Differences across the three approaches – traditional classical testing, Bayes testing, joint confirmation – are highlighted for a popular testing problem. A decision is searched for the existence of a unit root in a time-series process on the basis of two tests. One of them has the existence of a unit root as its null hypothesis and its non-existence as its alternative, while the roles of null and alternative are reversed for the other hypothesis test.

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File URL: http://www.ihs.ac.at/publications/eco/es-177.pdf
File Function: First version, 2005
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Paper provided by Institute for Advanced Studies in its series Economics Series with number 177.

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Length: 25 pages
Date of creation: Sep 2005
Date of revision:
Handle: RePEc:ihs:ihsesp:177
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  1. Kwiatkowski, D. & Phillips, P.C.B. & Schmidt, P., 1990. "Testing the Null Hypothesis of Stationarity Against the Alternative of Unit Root : How Sure are we that Economic Time Series have a Unit Root?," Papers 8905, Michigan State - Econometrics and Economic Theory.
  2. Pantula, Sastry G., 1989. "Testing for Unit Roots in Time Series Data," Econometric Theory, Cambridge University Press, vol. 5(02), pages 256-271, August.
  3. Hatanaka, Michio, 1996. "Time-Series-Based Econometrics: Unit Roots and Co-integrations," OUP Catalogue, Oxford University Press, number 9780198773535.
  4. Leybourne, S J, 1995. "Testing for Unit Roots Using Forward and Reverse Dickey-Fuller Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 57(4), pages 559-71, November.
  5. Stephen Leybourne & Tae-Hwan Kim & Paul Newbold, 2005. "Examination of Some More Powerful Modifications of the Dickey-Fuller Test," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(3), pages 355-369, 05.
  6. Kunst, Robert M., 2002. "Decision Maps for Bivariate Time Series with Potential Thrshold Cointegration," Economics Series 121, Institute for Advanced Studies.
  7. Stock, James H., 1994. "Deciding between I(1) and I(0)," Journal of Econometrics, Elsevier, vol. 63(1), pages 105-131, July.
  8. Keblowski, Piotr & Welfe, Aleksander, 2004. "The ADF-KPSS test of the joint confirmation hypothesis of unit autoregressive root," Economics Letters, Elsevier, vol. 85(2), pages 257-263, November.
  9. Robert M. Kunst & Michael Reutter, 2000. "Decisions on Seasonal Unit Roots," CESifo Working Paper Series 286, CESifo Group Munich.
  10. Charemza, Wojciech W. & Syczewska, Ewa M., 1998. "Joint application of the Dickey-Fuller and KPSS tests," Economics Letters, Elsevier, vol. 61(1), pages 17-21, October.
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