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Testing for Parameter Instability across Different Modeling Frameworks


  • Francesco Calvori
  • Drew Creal
  • Siem Jan Koopman
  • André Lucas


We develop a new parameter instability test that generalizes the seminal ARCH-Lagrange Multiplier test of Engle (1982) for a constant variance against the alternative of autoregressive conditional heteroskedasticity to settings with nonlinear time-varying parameters and non-Gaussian distributions. We investigate the performance of the new test relative to both classic and recently proposed parameter instability tests, including tests against structural breaks and parameter-driven dynamics. We find that the recent test of Müller and Petalas (2010) performs best across a wide range of alternatives, particularly if parameter instability is slow. For time-varying parameters that exhibit more mean reversion, our new test has higher power. We provide an application to a heavily unbalanced panel of losses given default for US corporations from 1982 to 2010 and provide evidence of significant parameter instability in the parameters of a static beta distributed model.

Suggested Citation

  • Francesco Calvori & Drew Creal & Siem Jan Koopman & André Lucas, 2017. "Testing for Parameter Instability across Different Modeling Frameworks," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 15(2), pages 223-246.
  • Handle: RePEc:oup:jfinec:v:15:y:2017:i:2:p:223-246.

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    References listed on IDEAS

    1. Shephard, Neil (ed.), 2005. "Stochastic Volatility: Selected Readings," OUP Catalogue, Oxford University Press, number 9780199257201.
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    Cited by:

    1. Harvey, Andrew & Thiele, Stephen, 2016. "Testing against changing correlation," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 575-589.

    More about this item


    credit risk; generalized autoregressive score model; observation-driven and parameter-driven models; regime switching; structural breaks; time-varying parameters;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • 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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