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Identifying Structural Breaks in Cointegrated Vector Autoregressive Models

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  • Håvard Hungnes

Abstract

This article suggests an alternative formulation of the cointegrated vector autoregressive (VAR) model such that the coefficients for the deterministic terms have straightforward interpretations. These coefficients can be interpreted as growth rates and cointegration mean level coefficients and express long-run properties of the model. For example, the growth rate coefficients tell us how much to expect (unconditionally) the variables in the system to grow from one period to the next, representing the underlying (steady state) growth in the variables. The estimation of the proposed formulation is made operationally in GRaM, which is a program for Ox Professional. GRaM can be used for analysing structural breaks when the deterministic terms include shift dummies and broken trends. By applying a formulation with interpretable deterministic components, different types of structural breaks can be identified. Shifts in both intercepts and growth rates, or combinations of these, can be tested for. The ability to distinguish between different types of structural breaks makes the procedure superior compared with alternative procedures. Furthermore, the procedure utilizes the information more efficiently than alternative procedures. Finally, interpretable coefficients of different types of structural breaks can be identified. Copyright (c) Blackwell Publishing Ltd and the Department of Economics, University of Oxford, 2010.

Suggested Citation

  • Håvard Hungnes, 2010. "Identifying Structural Breaks in Cointegrated Vector Autoregressive Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(4), pages 551-565, August.
  • Handle: RePEc:bla:obuest:v:72:y:2010:i:4:p:551-565
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    References listed on IDEAS

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    1. Hendry, David F. & Massmann, Michael, 2007. "Co-Breaking: Recent Advances and a Synopsis of the Literature," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 33-51, January.
    2. Saikkonen, Pentti & L tkepohl, Helmut, 2000. "Testing For The Cointegrating Rank Of A Var Process With An Intercept," Econometric Theory, Cambridge University Press, vol. 16(03), pages 373-406, June.
    3. Søren Johansen & Rocco Mosconi & Bent Nielsen, 2000. "Cointegration analysis in the presence of structural breaks in the deterministic trend," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 216-249.
    4. Doornik, Jurgen A, 1998. " Approximations to the Asymptotic Distributions of Cointegration Tests," Journal of Economic Surveys, Wiley Blackwell, vol. 12(5), pages 573-593, December.
    5. Peter Reinhard Hansen, 2005. "Granger's representation theorem: A closed-form expression for I(1) processes," Econometrics Journal, Royal Economic Society, vol. 8(1), pages 23-38, March.
    6. Lutkepohl, Helmut & Saikkonen, Pentti, 2000. "Testing for the cointegrating rank of a VAR process with a time trend," Journal of Econometrics, Elsevier, vol. 95(1), pages 177-198, March.
    7. Hansen, Peter Reinhard, 2003. "Structural changes in the cointegrated vector autoregressive model," Journal of Econometrics, Elsevier, vol. 114(2), pages 261-295, June.
    8. Saikkonen, Pentti & Lutkepohl, Helmut, 2000. "Testing for the Cointegrating Rank of a VAR Process with Structural Shifts," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(4), pages 451-464, October.
    9. Søren Johansen & Rocco Mosconi & Bent Nielsen, 2000. "Cointegration analysis in the presence of structural breaks in the deterministic trend," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 216-249.
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    Cited by:

    1. Esteban-Bravo, Mercedes & Vidal-Sanz, Jose M. & Yildirim, Gökhan, 2015. "Historical impact of technological change on the US mass media advertising expenditure," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 306-316.
    2. Thomas von Brasch, 2015. "Indentifying the sector bias of technical change," Discussion Papers 795, Statistics Norway, Research Department.
    3. repec:zbw:ifweej:20179 is not listed on IDEAS
    4. Pål Boug & Ådne Cappelen & Torbjørn Eika, 2013. "The importance of the distribution sector for exchange rate pass-through in a small open economy. A large scale macroeconometric modelling approach," Discussion Papers 731, Statistics Norway, Research Department.
    5. Thomas Brasch, 2016. "Identifying the sector bias of technical change," Empirical Economics, Springer, vol. 50(2), pages 595-621, March.
    6. Esteban-Bravo, Mercedes & Vidal-Sanz, Jose M. & Yildirim, Gökhan, 2012. "Expenditure trends in US advertising : long-term effects and structural changes with new media introductions," DEE - Working Papers. Business Economics. WB wb121506, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.

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