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A Generalized Portmanteau Goodness-Of-Fit Test For Time Series Models

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  • Chen, Willa W.
  • Deo, Rohit S.

Abstract

We present a goodness-of-fit test for time series models based on the discrete spectral average estimator. Unlike current tests of goodness of fit, the asymptotic distribution of our test statistic allows the null hypothesis to be either a short- or long-range dependence model. Our test is in the frequency domain, is easy to compute, and does not require the calculation of residuals from the fitted model. This is especially advantageous when the fitted model is not a finite-order autoregressive model. The test statistic is a frequency domain analogue of the test by Hong (1996, Econometrica 64, 837–864), which is a generalization of the Box and Pierce (1970, Journal of the American Statistical Association 65, 1509–1526) test statistic. A simulation study shows that our test has power comparable to that of Hong's test and superior to that of another frequency domain test by Milhoj (1981, Biometrika 68, 177–187).

Suggested Citation

  • Chen, Willa W. & Deo, Rohit S., 2004. "A Generalized Portmanteau Goodness-Of-Fit Test For Time Series Models," Econometric Theory, Cambridge University Press, vol. 20(2), pages 382-416, April.
    • Handle: RePEc:cup:etheor:v:20:y:2004:i:02:p:382-416_20
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    Cited by:

    1. Filip Žikeš & Jozef Baruník & Nikhil Shenai, 2017. "Modeling and forecasting persistent financial durations," Econometric Reviews, Taylor & Francis Journals, vol. 36(10), pages 1081-1110, November.
    2. Proietti, Tommaso & Luati, Alessandra, 2015. "The generalised autocovariance function," Journal of Econometrics, Elsevier, vol. 186(1), pages 245-257.
    3. Chen, Willa W. & Deo, Rohit S., 2006. "Estimation of mis-specified long memory models," Journal of Econometrics, Elsevier, vol. 134(1), pages 257-281, September.
    4. McElroy, Tucker & Holan, Scott, 2009. "A local spectral approach for assessing time series model misspecification," Journal of Multivariate Analysis, Elsevier, vol. 100(4), pages 604-621, April.
    5. repec:wyi:journl:002087 is not listed on IDEAS
    6. Deo, Rohit S. & Chen, Willa W., 2003. "Estimation of Mis-Specified Long Memory Models," Papers 2004,03, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    7. T. S. McElroy, 2016. "Nonnested model comparisons for time series," Biometrika, Biometrika Trust, vol. 103(4), pages 905-914.
    8. Davidson, James & Sibbertsen, Philipp, 2009. "Tests of bias in log-periodogram regression," Economics Letters, Elsevier, vol. 102(2), pages 83-86, February.
    9. Terence Tai-Leung Chong, 2007. "Estimating the Fractionally Integrated Model with a Break in the Differencing Parameter," Economics Bulletin, AccessEcon, vol. 3(67), pages 1-10.
    10. Poulin, Jennifer & Duchesne, Pierre, 2008. "On the power transformation of kernel-based tests for serial correlation in vector time series: Some finite sample results and a comparison with the bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4432-4457, May.
    11. Tucker S. McElroy & Anindya Roy, 2022. "Model identification via total Frobenius norm of multivariate spectra," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(2), pages 473-495, April.
    12. Laura Mayoral, 2007. "Minimum distance estimation of stationary and non-stationary ARFIMA processes," Econometrics Journal, Royal Economic Society, vol. 10(1), pages 124-148, March.
    13. Li, Meiyu & Gençay, Ramazan, 2017. "Tests for serial correlation of unknown form in dynamic least squares regression with wavelets," Economics Letters, Elsevier, vol. 155(C), pages 104-110.
    14. Nankervis, John C. & Savin, N. E., 2010. "Testing for Serial Correlation: Generalized Andrews–Ploberger Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 246-255.
    15. John K. Dagsvik & Mariachiara Fortuna & Sigmund Hov Moen, 2020. "How does temperature vary over time?: evidence on the stationary and fractal nature of temperature fluctuations," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 883-908, June.
    16. repec:ebl:ecbull:v:3:y:2007:i:67:p:1-10 is not listed on IDEAS

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