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A Simple Omnibus Overidentification Specification Test For Time Series Econometric Models

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  • Domínguez, Manuel A.
  • Lobato, Ignacio N.

Abstract

Despite their theoretical advantages, Integrated Conditional Moment (ICM) specification tests are not commonly employed in the econometrics practice. An important reason is that the employed test statistics are nonpivotal, and so critical values are not readily available. This article proposes an omnibus test in the spirit of the ICM tests of Bierens and Ploberger (1997, Econometrica 65, 1129–1151) where the test statistic is based on the minimized value of a quadratic function of the residuals of time series econometric models. The proposed test falls under the category of overidentification restriction tests started by Sargan (1958, Econometrica 26, 393–415). The corresponding projection interpretation leads us to propose a straightforward wild bootstrap procedure that requires only linear regressions to estimate the critical values irrespective of the model functional form. Hence, contrary to other existing ICM tests, the critical values are easily calculated while the test preserves the admissibility property of ICM tests.

Suggested Citation

  • Domínguez, Manuel A. & Lobato, Ignacio N., 2015. "A Simple Omnibus Overidentification Specification Test For Time Series Econometric Models," Econometric Theory, Cambridge University Press, vol. 31(4), pages 891-910, August.
    • Handle: RePEc:cup:etheor:v:31:y:2015:i:04:p:891-910_00
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    Cited by:

    1. Manuel A. Domínguez & Ignacio N. Lobato, 2020. "Specification testing with estimated variables," Econometric Reviews, Taylor & Francis Journals, vol. 39(5), pages 476-494, May.
    2. Pedro H. C. Sant'Anna & Xiaojun Song & Qi Xu, 2022. "Covariate distribution balance via propensity scores," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1093-1120, September.
    3. Kimoto, Ryo & Otsu, Taisuke, 2022. "Inference on conditional moment restriction models with generated variables," Economics Letters, Elsevier, vol. 215(C).
    4. Kimoto, Ryo & Otsu, Taisuke, 2022. "Inference on conditional moment restriction models with generated variables," LSE Research Online Documents on Economics 114264, London School of Economics and Political Science, LSE Library.
    5. Wang, Xuexin, 2015. "A Note on Consistent Conditional Moment Tests," MPRA Paper 69005, University Library of Munich, Germany.

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