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Bootstrap Improved Inference for Factor-Augmented Regressions with CCE

Author

Listed:
  • De Vos, Ignace

    (Department of Economics, Lund University)

  • Stauskas, Ovidijus

    (Department of Economics, Lund University)

Abstract

The Common Correlated Effects (CCE) methodology is now well established for the analysis of factor-augmented panel models. Yet, it is often neglected that the pooled variant is biased unless the cross-section dimension (N) of the dataset dominates the time series length (T). This is problematic for inference with typical macroeconomic datasets where T often equal or larger than N. Given that an analytical correction is also generally infeasible, the issue remains without a solution. In response, we provide in this paper the theoretical foundation for the cross-section, or pairs bootstrap in large N and T panels with T/N finite. We show that the scheme replicates the distribution of the CCE estimators, under both constant and heterogeneous slopes, such that bias can be eliminated and asymptotically correct inference can ensue even when N does not dominate. Monte Carlo experiments illustrate that the asymptotic properties also translate well to finite samples.

Suggested Citation

  • De Vos, Ignace & Stauskas, Ovidijus, 2021. "Bootstrap Improved Inference for Factor-Augmented Regressions with CCE," Working Papers 2021:16, Lund University, Department of Economics.
    • Handle: RePEc:hhs:lunewp:2021_016
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    References listed on IDEAS

    as
    1. Chatterjee, Snigdhansu, 1998. "Another look at the jackknife: further examples of generalized bootstrap," Statistics & Probability Letters, Elsevier, vol. 40(4), pages 307-319, November.
    2. Antonio F. Galvao & Kengo Kato, 2014. "Estimation and Inference for Linear Panel Data Models Under Misspecification When Both n and T are Large," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 285-309, April.
    3. Karabiyik, Hande & Reese, Simon & Westerlund, Joakim, 2017. "On the role of the rank condition in CCE estimation of factor-augmented panel regressions," Journal of Econometrics, Elsevier, vol. 197(1), pages 60-64.
    4. Gonçalves, Sílvia & Kaffo, Maximilien, 2015. "Bootstrap inference for linear dynamic panel data models with individual fixed effects," Journal of Econometrics, Elsevier, vol. 186(2), pages 407-426.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Artūras Juodis, 2022. "A regularization approach to common correlated effects estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 788-810, June.
    2. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    3. Stauskas, Ovidijus, 2021. "Uniform Theory for CCE under Heterogeneous Slopes and General Unknown Factors," Working Papers 2021:9, Lund University, Department of Economics.

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    More about this item

    Keywords

    Panel data; CCE; Bootstrap; Pairs; Factors; Bias Correction;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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