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(Consistently) testing strict exogeneity against the alternative of predeterminedness in linear time-series models

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  • Mayer, Alexander

Abstract

A portmanteau and a maximum statistic are proposed to discern strictly exogenous from predetermined regressors. Both test statistics rely on residual cross-correlations, pre-whitened via autoregressive sieves. Limiting normality of the portmanteau statistic and Gumbel-convergence of the maximum statistic are derived.

Suggested Citation

  • Mayer, Alexander, 2020. "(Consistently) testing strict exogeneity against the alternative of predeterminedness in linear time-series models," Economics Letters, Elsevier, vol. 193(C).
    • Handle: RePEc:eee:ecolet:v:193:y:2020:i:c:s0165176520302184
    DOI: 10.1016/j.econlet.2020.109335
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    References listed on IDEAS

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    Cited by:

    1. Mayer, Alexander, 2022. "On the local power of some tests of strict exogeneity in linear fixed effects models," Econometrics and Statistics, Elsevier, vol. 24(C), pages 49-74.
    2. Breitung, Jörg & Kripfganz, Sebastian & Hayakawa, Kazuhiko, 2022. "Bias-corrected method of moments estimators for dynamic panel data models," Econometrics and Statistics, Elsevier, vol. 24(C), pages 116-132.

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    More about this item

    Keywords

    Strict exogeneity; Long autoregressions; Kernel function; Extreme value theory; Many regressors/instruments;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • 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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