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Three-dimensional panel data models with interactive effects: Estimation and simulation

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  • Ye, Xiaoqing
  • Wu, Xiangjun

Abstract

This paper considers three-dimensional panel data models with unobservable multiple interactive effects, which are potentially correlated with the covariates. We propose an iterated OLS (IOLS) approach for the estimation of the static model and an iterated GMM (IGMM) method for the dynamic model. Monte Carlo simulations illustrate that our methods perform well in finite samples.

Suggested Citation

  • Ye, Xiaoqing & Wu, Xiangjun, 2014. "Three-dimensional panel data models with interactive effects: Estimation and simulation," Economics Letters, Elsevier, vol. 123(1), pages 62-65.
    • Handle: RePEc:eee:ecolet:v:123:y:2014:i:1:p:62-65
    DOI: 10.1016/j.econlet.2014.01.017
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    References listed on IDEAS

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    5. Davis, Peter, 2002. "Estimating multi-way error components models with unbalanced data structures," Journal of Econometrics, Elsevier, vol. 106(1), pages 67-95, January.
    6. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
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    Cited by:

    1. Xiaoqing Ye & Xiangjun Wu, 2017. "Estimating three-dimensional nonlinear panel data models with interactive effects," Applied Economics Letters, Taylor & Francis Journals, vol. 24(10), pages 708-712, June.

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    More about this item

    Keywords

    Three-dimensional panel data models; Interactive effects; Iterated OLS; Iterated GMM;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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