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Testing for co-non-linearity




This article introduces the concept of co-non-linearity. Co-non-linearity is an example of a common feature in time series (Engle and Koziciki, 1993, J. Bus. Econ. Statist.) and an extension of the concept of common nonlinear components (Anderson and Vahid, 1998, J. Econometrics). If some time series follow a non-linear process but there exists a linear relationship between the levels of these series that removes the non-linearity, then this relationship is said to be a co-non-linear relationship. In this article I show how to determine the number of such co-non-linear relationships. Furthermore, I show how to formulate hypothesis tests on the co-non-linear relationships in a full maximum likelihood framework.

Suggested Citation

  • Håvard Hungnes, 2012. "Testing for co-non-linearity," Discussion Papers 699, Statistics Norway, Research Department.
  • Handle: RePEc:ssb:dispap:699

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    References listed on IDEAS

    1. González Andrés & Teräsvirta Timo, 2008. "Modelling Autoregressive Processes with a Shifting Mean," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(1), pages 1-28, March.
    2. Vahid, F & Engle, Robert F, 1993. "Common Trends and Common Cycles," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(4), pages 341-360, Oct.-Dec..
    3. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    4. Anderson, Heather M. & Victor Issler, Joao & Vahid, Farshid, 2006. "Common features," Journal of Econometrics, Elsevier, vol. 132(1), pages 1-5, May.
    5. Terasvirta, Timo & Tjostheim, Dag & Granger, Clive W. J., 2010. "Modelling Nonlinear Economic Time Series," OUP Catalogue, Oxford University Press, number 9780199587155, June.
    6. Ericsson, Neil R, 1993. "Testing for Common Features: Comment," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 380-383, October.
    7. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    8. Robert B. Davies, 2002. "Hypothesis testing when a nuisance parameter is present only under the alternative: Linear model case," Biometrika, Biometrika Trust, vol. 89(2), pages 484-489, June.
    9. Doornik, Jurgen A, 1999. " Erratum [Approximations to the Asymptotic Distribution of Cointegration Tests]," Journal of Economic Surveys, Wiley Blackwell, vol. 13(2), April.
    10. Anderson, Heather M. & Vahid, Farshid, 1998. "Testing multiple equation systems for common nonlinear components," Journal of Econometrics, Elsevier, vol. 84(1), pages 1-36, May.
    11. H. Peter Boswijk & Jurgen A. Doornik, 2004. "Identifying, estimating and testing restricted cointegrated systems: An overview," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(4), pages 440-465.


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      Cited by:

      1. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.

    More about this item


    Common features; non-linearity; reduced rank regression;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects

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