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Finite Sample Behaviour of the Level Shift Model using Quasi-Differenced Data

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  • Gabriel Rodriguez

    ()
    (Department of Economics, University of Ottawa)

Abstract

When using quasi-differenced data in a model where a break in the intercept is allowed, asymptotic distributions of the M, ADF, and PT statistics are the same as those in the model where only an intercept and a time trend are included. However, the finite sample behaviour for common sample sizes used in empirical applications, is very different. I calculate finite-sample critical values using two different methods to select the break point and the lag length. Comparison with asymptotic and finite-sample distributions of a model where only a constant and a time trend are included in the set of deterministic components show strong differences. In particular these differences are more clear for the M and PT statistics, while the ADF statistics is not affected too much. An empirical application is performed to show the pitfalls of using asymptotic or finite-sample critical values for a model where a break in the intercept has not been taken into account.

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Bibliographic Info

Paper provided by University of Ottawa, Department of Economics in its series Working Papers with number 0604E.

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Length: 25 pages
Date of creation: 2006
Date of revision:
Handle: RePEc:ott:wpaper:0604e

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Related research

Keywords: Unit root test; GLS detrending; structural change; truncation lag; information criteria;

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References

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  1. Poyago-Theotoky, Joanna, 1998. "R&D Competition in a Mixed Duopoly under Uncertainty and Easy Imitation," Journal of Comparative Economics, Elsevier, vol. 26(3), pages 415-428, September.
  2. Stephen Martin & John T. Scott, 1999. "The Nature of Innovation Market Failure and the Design of Public Support for Private Innovation," CIE Discussion Papers 1999-02, University of Copenhagen. Department of Economics. Centre for Industrial Economics.
  3. Minoru Kitahara & Toshihiro Matsumura, 2006. "Realized Cost-Based Subsidies For Strategic R&D Investments With "Ex Ante" And "Ex Post" Asymmetries," The Japanese Economic Review, Japanese Economic Association, vol. 57(3), pages 438-448.
  4. Karolina Ekholm & Johan Torstensson, 1997. "High-Technology Subsidies in General Equilibrium: A Sector-Specific Approach," Canadian Journal of Economics, Canadian Economics Association, vol. 30(4), pages 1184-1203, November.
  5. Klette, T.J. & Moen, J. & Griliches, Z., 1999. "Do Subsidies to Commercial R&D Reduce Market Failures? Microeconometric Evaluation Studies," Papers 16/99, Norwegian School of Economics and Business Administration-.
  6. Isabel Busom, 2000. "An Empirical Evaluation of The Effects of R&D Subsidies," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 9(2), pages 111-148.
  7. Petrakis, Emmanuel & Poyago-Theotoky, Joanna, 2002. "R&D Subsidies versus R&D Cooperation in a Duopoly with Spillovers and Pollution," Australian Economic Papers, Wiley Blackwell, vol. 41(1), pages 37-52, March.
  8. Miyagiwa, Kaz & Ohno, Yuka, 2002. "Uncertainty, spillovers, and cooperative R&D," International Journal of Industrial Organization, Elsevier, vol. 20(6), pages 855-876, June.
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Cited by:
  1. Fossati, Sebastian, 2011. "Unit Root Testing with Stationary Covariates and a Structural Break in the Trend Function," Working Papers 2011-10, University of Alberta, Department of Economics.

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