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Nonlinear panel data estimation via quantile regressions

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  • Manuel Arellano
  • Stéphane Bonhomme

Abstract

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 birthweight completes the paper.

Suggested Citation

  • Manuel Arellano & Stéphane Bonhomme, 2016. "Nonlinear panel data estimation via quantile regressions," Econometrics Journal, Royal Economic Society, vol. 19(3), pages 61-94, October.
  • Handle: RePEc:wly:emjrnl:v:19:y:2016:i:3:p:c61-c94
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    File URL: http://hdl.handle.net/10.1111/ectj.12062
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Jiaying Gu & Stanislav Volgushev, 2018. "Panel Data Quantile Regression with Grouped Fixed Effects," Papers 1801.05041, arXiv.org, revised Aug 2018.
    2. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    3. repec:eee:econom:v:206:y:2018:i:2:p:395-413 is not listed on IDEAS
    4. repec:eee:econom:v:206:y:2018:i:2:p:305-335 is not listed on IDEAS
    5. 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.
    6. 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.
    7. Victor Chernozhukov & Ivan Fernandez-Val & Martin Weidner, 2018. "Network and panel quantile effects via distribution regression," CeMMAP working papers CWP21/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. repec:eee:finsta:v:33:y:2017:i:c:p:331-345 is not listed on IDEAS

    More about this item

    JEL classification:

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

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