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Nonlinear panel data estimation via quantile regressions


  • Manuel Arellano

    () (Institute for Fiscal Studies and CEMFI)

  • Stéphane Bonhomme

    () (Institute for Fiscal Studies and University of Chicago)


We introduce a class of quantile regression estimators for short panels. Our framework covers static and dynamic autoregressive models, models with general predetermined regressors, and models with multiple individual effects. We use quantile regression as a flexible tool to model the relationships between outcomes, covariates, and heterogeneity. We develop an iterative simulation-based approach for estimation, which exploits the computational simplicity of ordinary quantile regression in each iteration step. Finally, an application to measure the effect of smoking during pregnancy on children’s birthweights completes the paper.

Suggested Citation

  • Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear panel data estimation via quantile regressions," CeMMAP working papers CWP40/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:cemmap:40/15

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    References listed on IDEAS

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    Cited by:

    1. Victor Chernozhukov & Iv'an Fern'andez-Val & Martin Weidner, 2018. "Network and Panel Quantile Effects Via Distribution Regression," Papers 1803.08154,, revised Dec 2018.
    2. Jiaying Gu & Stanislav Volgushev, 2018. "Panel Data Quantile Regression with Grouped Fixed Effects," Papers 1801.05041,, revised Aug 2018.
    3. repec:eee:finsta:v:33:y:2017:i:c:p:331-345 is not listed on IDEAS
    4. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    5. repec:eee:econom:v:206:y:2018:i:2:p:395-413 is not listed on IDEAS
    6. repec:eee:econom:v:206:y:2018:i:2:p:305-335 is not listed on IDEAS
    7. Graham, Bryan S. & Hahn, Jinyong & Poirier, Alexandre & Powell, James L., 2018. "A quantile correlated random coefficients panel data model," Journal of Econometrics, Elsevier, vol. 206(2), pages 305-335.
    8. Schorr, A. & Lips, M., 2018. "Influence of milk yield on profitability a quantile regression analysis," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277000, International Association of Agricultural Economists.

    More about this item


    Panel data; dynamic models; non-separable heterogeneity; quantile regression; expectation-maximization;

    JEL classification:

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

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