IDEAS home Printed from https://ideas.repec.org/p/sgo/wpaper/2012.html
   My bibliography  Save this paper

Nonparametric Identification and Estimation of Panel Quantile Models with Sample Selection

Author

Listed:
  • Sungwon Lee

    (Department of Economics, Sogang University, Seoul)

Abstract

This paper develops nonparametric panel quantile regression models with sample selection. The class of models allows the unobserved heterogeneity to be correlated with time-varying regressors in a time-invariant manner. I adopt the correlated random effects approach proposed by Mundlak (1978) and Chamberlain (1980), and the control function approach to correct the sample selection bias. The class of models is general and flexible enough to incorporate many empirical issues, such as endogeneity of regressors and censoring. Identification of the model requires that T≥3, where T is the number of time periods, and that there is an excluded variable that affects the selection probability. Based on the identification result, this paper proposes sieve two-step estimation to estimate the model parameters. This paper also establishes the asymptotic theory for the sieve two-step estimators, including consistency, convergence rates, and asymptotic normality of functionals.

Suggested Citation

  • Sungwon Lee, 2020. "Nonparametric Identification and Estimation of Panel Quantile Models with Sample Selection," Working Papers 2012, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    • Handle: RePEc:sgo:wpaper:2012
    as

    Download full text from publisher

    File URL: https://tinyurl.com/ypwjjwt5
    File Function: First version, 2020
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Arthur Lewbel & Oliver Linton, 2007. "Nonparametric Matching and Efficient Estimators of Homothetically Separable Functions," Econometrica, Econometric Society, vol. 75(4), pages 1209-1227, July.
    2. Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
    3. Semykina, Anastasia & Wooldridge, Jeffrey M., 2010. "Estimating panel data models in the presence of endogeneity and selection," Journal of Econometrics, Elsevier, vol. 157(2), pages 375-380, August.
    4. Bryan S. Graham & James L. Powell, 2012. "Identification and Estimation of Average Partial Effects in “Irregular” Correlated Random Coefficient Panel Data Models," Econometrica, Econometric Society, vol. 80(5), pages 2105-2152, September.
    5. Whitney K. Newey & James L. Powell & Francis Vella, 1999. "Nonparametric Estimation of Triangular Simultaneous Equations Models," Econometrica, Econometric Society, vol. 67(3), pages 565-604, May.
    6. Donald, Stephen G., 1995. "Two-step estimation of heteroskedastic sample selection models," Journal of Econometrics, Elsevier, vol. 65(2), pages 347-380, February.
    7. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
    8. 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.
    9. Lee, Sokbae, 2007. "Endogeneity in quantile regression models: A control function approach," Journal of Econometrics, Elsevier, vol. 141(2), pages 1131-1158, December.
    10. Fernández-Val, Iván & van Vuuren, Aico & Vella, Francis, 2018. "Decomposing Real Wage Changes in the United States," IZA Discussion Papers 12044, Institute of Labor Economics (IZA).
    11. Joseph G. Altonji & Rosa L. Matzkin, 2005. "Cross Section and Panel Data Estimators for Nonseparable Models with Endogenous Regressors," Econometrica, Econometric Society, vol. 73(4), pages 1053-1102, July.
    12. Ahn, Hyungtaik & Powell, James L., 1993. "Semiparametric estimation of censored selection models with a nonparametric selection mechanism," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 3-29, July.
    13. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    14. Hahn, Jinyong & Liao, Zhipeng & Ridder, Geert, 2018. "Nonparametric Two-Step Sieve M Estimation And Inference," Econometric Theory, Cambridge University Press, vol. 34(6), pages 1281-1324, December.
    15. Christian Dustmann & María Engracia Rochina-Barrachina, 2007. "Selection correction in panel data models: An application to the estimation of females' wage equations," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 263-293, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Louise Laage, 2020. "A Correlated Random Coefficient Panel Model with Time-Varying Endogeneity," Papers 2003.09367, arXiv.org, revised Nov 2022.
    2. Ming Li, 2021. "Identification and Estimation in a Time-Varying Endogenous Random Coefficient Panel Data Model," Papers 2110.00982, arXiv.org, revised Nov 2024.
    3. Laage, Louise, 2024. "A Correlated Random Coefficient panel model with time-varying endogeneity," Journal of Econometrics, Elsevier, vol. 242(2).
    4. 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.
    5. Alyssa Carlson & Riju Joshi, 2024. "Sample selection in linear panel data models with heterogeneous coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 237-255, March.
    6. Huber, Martin & Melly, Blaise, 2011. "Quantile Regression in the Presence of Sample Selection," Economics Working Paper Series 1109, University of St. Gallen, School of Economics and Political Science.
    7. Woutersen, Tiemen & Khandker, Shahidur R., 2013. "Estimating the effects of credit constraints on productivity of Peruvian agriculture," Policy Research Working Paper Series 6658, The World Bank.
    8. Schwiebert, Jörg, 2012. "Semiparametric Estimation of a Sample Selection Model in the Presence of Endogeneity," Hannover Economic Papers (HEP) dp-504, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    9. Martin Huber & Blaise Melly, 2012. "A test of the conditional independence assumption in sample selection models," Working Papers 2012-11, Brown University, Department of Economics.
    10. Manuel Arellano & Stéphane Bonhomme, 2017. "Quantile Selection Models With an Application to Understanding Changes in Wage Inequality," Econometrica, Econometric Society, vol. 85, pages 1-28, January.
    11. 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.
    12. Chernozhukov, Victor & Fernández-Val, Iván & Kowalski, Amanda E., 2015. "Quantile regression with censoring and endogeneity," Journal of Econometrics, Elsevier, vol. 186(1), pages 201-221.
    13. Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
    14. Moro, D. & Guastella, G. & Sckokai, P. & Veneziani, M., 2013. "The Capitalization of Area Payment into Land Rental Prices: Micro-evidence from Italy," 2013 Second Congress, June 6-7, 2013, Parma, Italy 149746, Italian Association of Agricultural and Applied Economics (AIEAA).
    15. Gianni Guastella & Daniele Moro & Paolo Sckokai & Mario Veneziani, 2018. "The Capitalisation of CAP Payments into Land Rental Prices: A Panel Sample Selection Approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(3), pages 688-704, September.
    16. Meghir, Costas & Rivkin, Steven, 2011. "Econometric Methods for Research in Education," Handbook of the Economics of Education, in: Erik Hanushek & Stephen Machin & Ludger Woessmann (ed.), Handbook of the Economics of Education, edition 1, volume 3, chapter 1, pages 1-87, Elsevier.
    17. Georges Bresson & Guy Lacroix & Mohammad Arshad Rahman, 2021. "Bayesian panel quantile regression for binary outcomes with correlated random effects: an application on crime recidivism in Canada," Empirical Economics, Springer, vol. 60(1), pages 227-259, January.
    18. Malikov, Emir & Kumbhakar, Subal C., 2014. "A generalized panel data switching regression model," Economics Letters, Elsevier, vol. 124(3), pages 353-357.
    19. Genya Kobayashi & Hideo Kozumi, 2012. "Bayesian analysis of quantile regression for censored dynamic panel data," Computational Statistics, Springer, vol. 27(2), pages 359-380, June.
    20. John Bailey Jones & Minhee Kim & Byoung G. Park, 2020. "The Wage Penalty for Married Women of Career Interruptions: Evidence from the 1970s and the 1990s," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 783-807, August.

    More about this item

    Keywords

    Sample selection; panel data; quantile regression; nonseparable models; correlated random effects; control function approach; nonparametric identification; sieve two-step estimation;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: 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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sgo:wpaper:2012. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Jung Hur (email available below). General contact details of provider: https://edirc.repec.org/data/risogkr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.