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Smoothed LSDV estimation of functional-coefficient panel data models with two-way fixed effects

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  • Halder, Shaymal C.
  • Malikov, Emir

Abstract

The existing semiparametric estimators for varying-coefficient fixed-effects models exclusively assume one-way fixed effects, typically in the dimension of cross-sectional units. However, more often than not applied researchers wish to control for both the individual and time fixed effects in their panel regressions, with the latter included to account for common unobservable factors correlated with regressors. While rather trivial in a linear model, controlling for time effects by explicitly including time-period dummies as additional regressors does not provide a straight-forward estimation procedure in the case of a semiparametric model. We provide an alternative by extending the Sun et al. (2009) smoothed least-squares dummy variable (LSDV) estimator to the case of a functional-coefficient model with two-way fixed effects whereby we allow for unobservable heterogeneity in both dimensions of the data: cross-section and time. Both fixed effects are concentrated out of the model via locally smoothed two-dimensional within transformation. Simulations show that the estimator performs well in finite samples. We also showcase its practical usefulness by revisiting the role of management as a factor of production.

Suggested Citation

  • Halder, Shaymal C. & Malikov, Emir, 2020. "Smoothed LSDV estimation of functional-coefficient panel data models with two-way fixed effects," Economics Letters, Elsevier, vol. 192(C).
    • Handle: RePEc:eee:ecolet:v:192:y:2020:i:c:s0165176520301671
    DOI: 10.1016/j.econlet.2020.109239
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    References listed on IDEAS

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    1. Nicholas Bloom & John Van Reenen, 2007. "Measuring and Explaining Management Practices Across Firms and Countries," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(4), pages 1351-1408.
    2. Van Reenen, John & Bloom, Nicholas & Sadun, Raffaella, 2016. "Management as a Technology," CEPR Discussion Papers 11312, C.E.P.R. Discussion Papers.
    3. Malikov, Emir & Kumbhakar, Subal C. & Sun, Yiguo, 2016. "Varying coefficient panel data model in the presence of endogenous selectivity and fixed effects," Journal of Econometrics, Elsevier, vol. 190(2), pages 233-251.
    4. Qian, Junhui & Wang, Le, 2012. "Estimating semiparametric panel data models by marginal integration," Journal of Econometrics, Elsevier, vol. 167(2), pages 483-493.
    5. Henderson, Daniel J. & Carroll, Raymond J. & Li, Qi, 2008. "Nonparametric estimation and testing of fixed effects panel data models," Journal of Econometrics, Elsevier, vol. 144(1), pages 257-275, May.
    6. Su, Liangjun & Ullah, Aman, 2006. "Profile likelihood estimation of partially linear panel data models with fixed effects," Economics Letters, Elsevier, vol. 92(1), pages 75-81, July.
    7. Lin, Zhongjian & Li, Qi & Sun, Yiguo, 2014. "A consistent nonparametric test of parametric regression functional form in fixed effects panel data models," Journal of Econometrics, Elsevier, vol. 178(P1), pages 167-179.
    8. Rodriguez-Poo, Juan M. & Soberón, Alexandra, 2015. "Nonparametric estimation of fixed effects panel data varying coefficient models," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 95-122.
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    Cited by:

    1. Jinyu Chen & Dandan Zhu & Shijie Ding & Jingxiao Qu, 2024. "Government environmental concerns and corporate green innovation: Evidence from heavy‐polluting enterprises in China," Business Strategy and the Environment, Wiley Blackwell, vol. 33(3), pages 1920-1936, March.
    2. Sulaiman Ademola Oreshile & Nurul Shahnaz Mahdzan & Rozaimah Zainudin, 2025. "Enterprise risk management quality and firm value: Evidence from corporate reputation risk theory," Risk Management, Palgrave Macmillan, vol. 27(1), pages 1-31, February.

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    More about this item

    Keywords

    Fixed effect; Local linear; LSDV; Semiparametric; Smooth coefficient; Time effect;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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