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Indirect Inference Estimation of a First-Order Dynamic Panel Data Model

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  • Yong Bao

    (Purdue University)

Abstract

A new estimator is proposed in this paper that inverts a binding function that is based on the asymptotic bias of the within-groups (WG) estimator in a first-order dynamic panel model with fixed effects under the asymptotic regime of large N and finite T. The new estimator is in the spirit of indirect inference (II) and corrects the inconsistency of the WG estimator. It is simulation-free, does not rely on any distributional assumption on the idiosyncratic error term, and is asymptotically normally distributed. Monte Carlo results indicate its good finite-sample performance in comparison with other consistent estimators.

Suggested Citation

  • Yong Bao, 2021. "Indirect Inference Estimation of a First-Order Dynamic Panel Data Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 79-98, December.
    • Handle: RePEc:spr:jqecon:v:19:y:2021:i:1:d:10.1007_s40953-021-00264-w
    DOI: 10.1007/s40953-021-00264-w
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    Cited by:

    1. Chen, Weihao & Cizek, Pavel, 2023. "Bias-Corrected Instrumental Variable Estimation in Linear Dynamic Panel Data Models," Discussion Paper 2023-028, Tilburg University, Center for Economic Research.
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    3. Chen, Weihao & Cizek, Pavel, 2023. "Bias-Corrected Instrumental Variable Estimation in Linear Dynamic Panel Data Models," Other publications TiSEM 9bf2c16c-522f-4223-8037-c, Tilburg University, School of Economics and Management.

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    More about this item

    Keywords

    Dynamic panel; Indirect inference; Bias;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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