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Asymptotics for panel quantile regression models with individual effects

Author

Listed:
  • Kato, Kengo
  • F. Galvao, Antonio
  • Montes-Rojas, Gabriel V.

Abstract

This paper studies panel quantile regression models with individual fixed effects. We formally establish sufficient conditions for consistency and asymptotic normality of the quantile regression estimator when the number of individuals, n, and the number of time periods, T, jointly go to infinity. The estimator is shown to be consistent under similar conditions to those found in the nonlinear panel data literature. Nevertheless, due to the non-smoothness of the objective function, we had to impose a more restrictive condition on T to prove asymptotic normality than that usually found in the literature. The finite sample performance of the estimator is evaluated by Monte Carlo simulations.

Suggested Citation

  • Kato, Kengo & F. Galvao, Antonio & Montes-Rojas, Gabriel V., 2012. "Asymptotics for panel quantile regression models with individual effects," Journal of Econometrics, Elsevier, vol. 170(1), pages 76-91.
  • Handle: RePEc:eee:econom:v:170:y:2012:i:1:p:76-91
    DOI: 10.1016/j.jeconom.2012.02.007
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Fernández-Val, Iván & Weidner, Martin, 2016. "Individual and time effects in nonlinear panel models with large N, T," Journal of Econometrics, Elsevier, vol. 192(1), pages 291-312.
    2. Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear Panel Data Estimation via Quantile Regression," Working Papers wp2015_1505, CEMFI.
    3. Jiaying Gu & Stanislav Volgushev, 2018. "Panel Data Quantile Regression with Grouped Fixed Effects," Papers 1801.05041, arXiv.org, revised Aug 2018.
    4. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    5. Firpo, Sergio & Galvao, Antonio F. & Song, Suyong, 2017. "Measurement errors in quantile regression models," Journal of Econometrics, Elsevier, vol. 198(1), pages 146-164.
    6. Riccardo Crescenzi & Mara Giua, 2016. "The EU Cohesion Policy in context: Does a bottom-up approach work in all regions?," Environment and Planning A, , vol. 48(11), pages 2340-2357, November.
    7. Gonzalo, Jesús & Dolado Lobregad, Juan José & Chen, Liang, 2017. "Quantile Factor Models," UC3M Working papers. Economics 25299, Universidad Carlos III de Madrid. Departamento de Economía.
    8. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers CWP34/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Frantisek Cech & Jozef Barunik, 2017. "Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns," Papers 1708.08622, arXiv.org.
    10. Antonio F. Galvao & Gabriel Montes-Rojas, 2015. "On Bootstrap Inference for Quantile Regression Panel Data: A Monte Carlo Study," Econometrics, MDPI, Open Access Journal, vol. 3(3), pages 1-13, September.
    11. Galvao, Antonio F. & Wang, Liang, 2015. "Efficient minimum distance estimator for quantile regression fixed effects panel data," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 1-26.
    12. 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.
    13. Mingli Chen & Iv'an Fern'andez-Val & Martin Weidner, 2014. "Nonlinear Factor Models for Network and Panel Data," Papers 1412.5647, arXiv.org, revised Jun 2018.
    14. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile Regression with Panel Data," NBER Working Papers 21034, National Bureau of Economic Research, Inc.
    15. Denis Chetverikov & Bradley Larsen & Christopher Palmer, 2016. "IV Quantile Regression for Group‐Level Treatments, With an Application to the Distributional Effects of Trade," Econometrica, Econometric Society, vol. 84, pages 809-833, March.
    16. Riccardo Crescenzi & Mara Giua, 2016. "Eu Cohesion Policy In Context: Does A Bottom-Up Approach Work In All Regions?," Departmental Working Papers of Economics - University 'Roma Tre' 0206, Department of Economics - University Roma Tre.
    17. Yuzhu Tian & Er’qian Li & Maozai Tian, 2016. "Bayesian joint quantile regression for mixed effects models with censoring and errors in covariates," Computational Statistics, Springer, vol. 31(3), pages 1031-1057, September.
    18. Su, Liangjun & Hoshino, Tadao, 2016. "Sieve instrumental variable quantile regression estimation of functional coefficient models," Journal of Econometrics, Elsevier, vol. 191(1), pages 231-254.
    19. repec:bla:jorssa:v:180:y:2017:i:3:p:907-922 is not listed on IDEAS
    20. Harding, Matthew & Lamarche, Carlos, 2013. "Penalized Quantile Regression with Semiparametric Correlated Effects: Applications with Heterogeneous Preferences," IZA Discussion Papers 7741, Institute for the Study of Labor (IZA).
    21. Erik Figueiredo & Luiz Lima & Georg Schaur, 2016. "The effect of the Euro on the bilateral trade distribution," Empirical Economics, Springer, vol. 50(1), pages 17-29, February.
    22. repec:eee:riibaf:v:42:y:2017:i:c:p:1455-1466 is not listed on IDEAS
    23. Yu-Yen Ku & Tze-Yu Yen, 2016. "Heterogeneous Effect of Financial Leverage on Corporate Performance: A Quantile Regression Analysis of Taiwanese Companies," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 1-33, September.
    24. Li, Tong & Oka, Tatsushi, 2015. "Set identification of the censored quantile regression model for short panels with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 363-377.
    25. Riccardo Crescenzi & Mara Giua, 2014. "The EU Cohesion policy in context: regional growth and the influence of agricultural and rural development policies," LEQS – LSE 'Europe in Question' Discussion Paper Series 85, European Institute, LSE.

    More about this item

    Keywords

    Asymptotics; Fixed effects; Panel data; Quantile regression;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • 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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