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Estimating Quantile Regressions with Multiple Fixed Effects through Method of Moments

Author

Listed:
  • Rios-Avila, Fernando

    (Levy Economics Institute)

  • Siles, Leonardo

    (Universidad de Chile)

  • Canavire Bacarreza, Gustavo J.

    (World Bank)

Abstract

This paper proposes a new method to estimate quantile regressions with multiple fixed effects. The method, which expands on the strategy proposed by Machado and Santos Silva (2019), allows for the inclusion of multiple fixed effects and provides various alternatives for estimating standard errors. We provide Monte Carlo simulations to show the finite sample properties of the proposed method in the presence of two sets of fixed effects. Finally, we apply the proposed method to two different examples using macroeconomic and microeconomic data and allowing for multiple fixed effects with robust results.

Suggested Citation

  • Rios-Avila, Fernando & Siles, Leonardo & Canavire Bacarreza, Gustavo J., 2024. "Estimating Quantile Regressions with Multiple Fixed Effects through Method of Moments," IZA Discussion Papers 17262, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp17262
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    References listed on IDEAS

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    1. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2011. "Robust Inference With Multiway Clustering," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 238-249, April.
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    5. Kaplan, David M. & Sun, Yixiao, 2017. "Smoothed Estimating Equations For Instrumental Variables Quantile Regression," Econometric Theory, Cambridge University Press, vol. 33(1), pages 105-157, February.
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    8. Ben Jann, 2020. "Influence functions continued. A framework for estimating standard errors in reweighting, matching, and regression adjustment," University of Bern Social Sciences Working Papers 35, University of Bern, Department of Social Sciences, revised 31 Aug 2020.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    fixed effects; linear heteroskedasticity; location-scale model;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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