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Reconsideration of a simple approach to quantile regression for panel data

Author

Listed:
  • Galina Besstremyannaya

    (Centre for Economic and Financial Research at New Economic School)

  • Sergei Golovan

    (New Economic School)

Abstract

The note discusses a fallacy in the approach proposed by Ivan Canay (2011, The Econometrics Journal) for constructing a computationally simple two-step estimator in a quantile regression model with quantile-independent fixed effects. We formally prove that the estimator gives an incorrect inference for the constant term due to violation of the assumption about additive expansion of the first-step estimator, which requires the independence of its terms. Our simulations show that Canay's confidence intervals for the constant term are wrong. Finally, we focus on the fact that finding a sqrt(nT) consistent within estimator, as required by Canay's procedure, may be problematic. We provide an example of a model, for which we formally prove the non-existence of such an estimator.

Suggested Citation

  • Galina Besstremyannaya & Sergei Golovan, 2018. "Reconsideration of a simple approach to quantile regression for panel data," Working Papers w0248, New Economic School (NES).
    • Handle: RePEc:abo:neswpt:w0248
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    File URL: https://www.nes.ru/files/Preprints-resh/WP248.pdf
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    References listed on IDEAS

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    1. Ivan A. Canay, 2011. "A simple approach to quantile regression for panel data," Econometrics Journal, Royal Economic Society, vol. 14(3), pages 368-386, October.
    2. Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
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    3. Stelian STANCU & Eugenia GRECU & Mirela Ionela ACELEANU & Daniela Livia TRAŞCĂ & Claudiu Tiberiu ALBULESCU, 2021. "Does Firm Size Matters for Firm Growth? Evidence from the Romanian Health Sector," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 17-31, December.
    4. Tilov, Ivan & Weber, Sylvain, 2023. "Heterogeneity in price elasticity of vehicle kilometers traveled: Evidence from micro-level panel data," Energy Economics, Elsevier, vol. 127(PA).
    5. Liang Chen & Yulong Huo, 2019. "A Simple Estimator for Quantile Panel Data Models Using Smoothed Quantile Regressions," Papers 1911.04729, arXiv.org.
    6. Yoshibumi Makabe & Yoshihiko Norimasa, 2022. "The Term Structure of Inflation at Risk: A Panel Quantile Regression Approach," Bank of Japan Working Paper Series 22-E-4, Bank of Japan.
    7. Dimitrios Bakas & Theodore Panagiotidis & Gianluigi Pelloni, 2024. "Labour reallocation and unemployment fluctuations: A tale of two tails," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 3444-3468, July.
    8. Claudiu Tiberiu Albulescu & Matei Tămășilă & Ilie Mihai Tăucean, 2021. "The Nonlinear Relationship Between Firm Size and Growth in the Automotive Industry," Journal of Industry, Competition and Trade, Springer, vol. 21(3), pages 445-463, September.
    9. Yoshihiko Norimasa & Kazuki Ueda & Tomohiro Watanabe, 2021. "Emerging Economies' Vulnerability to Changes in Capital Flows: The Role of Global and Local Factors," Bank of Japan Working Paper Series 21-E-5, Bank of Japan.
    10. David Powell, 2022. "Quantile regression with nonadditive fixed effects," Empirical Economics, Springer, vol. 63(5), pages 2675-2691, November.
    11. Galina Besstremyannaya & Sergei Golovan, 2023. "Measuring heterogeneity in hospital productivity: a quantile regression approach," Journal of Productivity Analysis, Springer, vol. 59(1), pages 15-43, February.
    12. Fotié, Andrée Kenne & Mbratana, Taoufiki, 2024. "Informality and development: The nonlinear effect," Economics Letters, Elsevier, vol. 234(C).
    13. Lang, Jan Hannes & Rusnák, Marek & Greiwe, Moritz, 2023. "Medium-term growth-at-risk in the euro area," Working Paper Series 2808, European Central Bank.
    14. Battagliola, Maria Laura & Sørensen, Helle & Tolver, Anders & Staicu, Ana-Maria, 2022. "A bias-adjusted estimator in quantile regression for clustered data," Econometrics and Statistics, Elsevier, vol. 23(C), pages 165-186.
    15. Besstremyannaya, Galina & Golovan, Sergei, 2021. "Measuring heterogeneity with fixed effect quantile regression: Long panels and short panels," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 64, pages 70-82.

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    More about this item

    Keywords

    quantile regression; panel data; fixed effects; inference;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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