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The Effect of the Estimation on Goodness‐of‐Fit Tests in Time Series Models

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  • Yue Fang

Abstract

. We analyze, by simulation, the finite‐sample properties of goodness‐of‐fit tests based on residual autocorrelation coefficients (simple and partial) obtained using different estimators frequently used in the analysis of autoregressive moving‐average time‐series models. The estimators considered are unconditional least squares, maximum likelihood and conditional least squares. The results suggest that although the tests based on these estimators are asymptotically equivalent for particular models and parameter values, their sampling properties for samples of the size commonly found in economic applications can differ substantially, because of differences in both finite‐sample estimation efficiencies and residual regeneration methods.

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  • Yue Fang, 2005. "The Effect of the Estimation on Goodness‐of‐Fit Tests in Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(4), pages 527-541, July.
    • Handle: RePEc:bla:jtsera:v:26:y:2005:i:4:p:527-541
    DOI: 10.1111/j.1467-9892.2005.00418.x
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    1. Aigner, Dennis J, 1971. "A Compendium on Estimation of the Autoregressive-Moving Average Model from Time Series Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 12(3), pages 348-371, October.
    2. Ansley, Craig F. & Newbold, Paul, 1980. "Finite sample properties of estimators for autoregressive moving average models," Journal of Econometrics, Elsevier, vol. 13(2), pages 159-183, June.
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