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To pool or not to pool: What is a good strategy for parameter estimation and forecasting in panel regressions?

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  • Wendun Wang
  • Xinyu Zhang
  • Richard Paap

Abstract

This paper considers estimating the slope parameters and forecasting in potentially heterogeneous panel data regressions with a long time dimension. We propose a novel optimal pooling averaging estimator that makes an explicit trade‐off between efficiency gains from pooling and bias due to heterogeneity. By theoretically and numerically comparing various estimators, we find that a uniformly best estimator does not exist and that our new estimator is superior in nonextreme cases and robust in extreme cases. Our results provide practical guidance for the best estimator and forecast depending on features of data and models. We apply our method to examine the determinants of sovereign credit default swap spreads and forecast future spreads.

Suggested Citation

  • Wendun Wang & Xinyu Zhang & Richard Paap, 2019. "To pool or not to pool: What is a good strategy for parameter estimation and forecasting in panel regressions?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(5), pages 724-745, August.
    • Handle: RePEc:wly:japmet:v:34:y:2019:i:5:p:724-745
    DOI: 10.1002/jae.2696
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    Cited by:

    1. Yifan Chen & Jianhua Gang & Zongxin Qian & Jinfan Zhang, 2023. "Rationality test in the housing market: Project‐level evidence from China," Journal of Regional Science, Wiley Blackwell, vol. 63(3), pages 583-616, June.
    2. Pesaran, M. Hashem & Pick, Andreas & Timmermann, Allan, 2022. "Forecasting with panel data: estimation uncertainty versus parameter heterogeneity," CEPR Discussion Papers 17123, C.E.P.R. Discussion Papers.
    3. Jack Fosten & Shaoni Nandi, 2023. "Nowcasting from cross‐sectionally dependent panels," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 898-919, September.
    4. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    5. Tobias Keller & Martin Glaum & Andreas Bausch & Thorsten Bunz, 2023. "The “CEO in context” technique revisited: A replication and extension of Hambrick and Quigley (2014)," Strategic Management Journal, Wiley Blackwell, vol. 44(4), pages 1111-1138, April.
    6. Didier Nibbering & Richard Paap, 2024. "Forecasting carbon emissions using asymmetric grouping," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2228-2256, September.
    7. Christian Brownlees & Vladislav Morozov, 2022. "Unit Averaging for Heterogeneous Panels," Papers 2210.14205, arXiv.org, revised May 2024.
    8. Greenaway-McGrevy, Ryan, 2022. "Forecast combination for VARs in large N and T panels," International Journal of Forecasting, Elsevier, vol. 38(1), pages 142-164.

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