IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2401.11422.html
   My bibliography  Save this paper

Local Identification in Instrumental Variable Multivariate Quantile Regression Models

Author

Listed:
  • Haruki Kono

Abstract

The instrumental variable (IV) quantile regression model introduced by Chernozhukov and Hansen (2005) is a useful tool for analyzing quantile treatment effects in the presence of endogeneity, but when outcome variables are multidimensional, it is silent on the joint distribution of different dimensions of each variable. To overcome this limitation, we propose an IV model built on the optimal-transport-based multivariate quantile that takes into account the correlation between the entries of the outcome variable. We then provide a local identification result for the model. Surprisingly, we find that the support size of the IV required for the identification is independent of the dimension of the outcome vector, as long as the IV is sufficiently informative. Our result follows from a general identification theorem that we establish, which has independent theoretical significance.

Suggested Citation

  • Haruki Kono, 2024. "Local Identification in Instrumental Variable Multivariate Quantile Regression Models," Papers 2401.11422, arXiv.org, revised Feb 2024.
    • Handle: RePEc:arx:papers:2401.11422
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2401.11422
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Richard Blundell & Dennis Kristensen & Rosa Matzkin, 2017. "Individual counterfactuals with multidimensional unobserved heterogeneity," CeMMAP working papers 60/17, Institute for Fiscal Studies.
    2. Victor Chernozhukov & Christian Hansen, 2005. "An IV Model of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 73(1), pages 245-261, January.
    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. Aguiar, Victor H. & Kashaev, Nail & Allen, Roy, 2023. "Prices, profits, proxies, and production," Journal of Econometrics, Elsevier, vol. 235(2), pages 666-693.
    2. Akosah, Nana Kwame & Alagidede, Imhotep Paul & Schaling, Eric, 2020. "Testing for asymmetry in monetary policy rule for small-open developing economies: Multiscale Bayesian quantile evidence from Ghana," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    3. Isaiah Andrews & Anna Mikusheva, 2016. "Conditional Inference With a Functional Nuisance Parameter," Econometrica, Econometric Society, vol. 84, pages 1571-1612, July.
    4. Ma, Lingjie & Koenker, Roger, 2006. "Quantile regression methods for recursive structural equation models," Journal of Econometrics, Elsevier, vol. 134(2), pages 471-506, October.
    5. Ron Diris, 2017. "Don't Hold Back? The Effect of Grade Retention on Student Achievement," Education Finance and Policy, MIT Press, vol. 12(3), pages 312-341, Summer.
    6. Muller, Christophe, 2018. "Heterogeneity and nonconstant effect in two-stage quantile regression," Econometrics and Statistics, Elsevier, vol. 8(C), pages 3-12.
    7. Xiaohong Chen & Demian Pouzo, 2012. "Estimation of Nonparametric Conditional Moment Models With Possibly Nonsmooth Generalized Residuals," Econometrica, Econometric Society, vol. 80(1), pages 277-321, January.
    8. Gernandt, Johannes & Maier, Michael & Pfeiffer, Friedhelm & Rat-Wirtzler, Julie, 2006. "Distributional effects of the high school degree in Germany," ZEW Discussion Papers 06-088, ZEW - Leibniz Centre for European Economic Research.
    9. Xiaohong Chen & Victor Chernozhukov & Sokbae Lee & Whitney K. Newey, 2014. "Local Identification of Nonparametric and Semiparametric Models," Econometrica, Econometric Society, vol. 82(2), pages 785-809, March.
    10. Arellano, Manuel & Blundell, Richard & Bonhomme, Stéphane & Light, Jack, 2024. "Heterogeneity of consumption responses to income shocks in the presence of nonlinear persistence," Journal of Econometrics, Elsevier, vol. 240(2).
    11. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    12. 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.
    13. Han, Sukjin, 2021. "Identification in nonparametric models for dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 132-147.
    14. Dima, Bogdan & Dincă, Marius Sorin & Spulbăr, Cristi, 2014. "Financial nexus: Efficiency and soundness in banking and capital markets," Journal of International Money and Finance, Elsevier, vol. 47(C), pages 100-124.
    15. Wehby, George L. & Castilla, Eduardo E. & Lopez-Camelo, Jorge, 2010. "The impact of altitude on infant health in South America," Economics & Human Biology, Elsevier, vol. 8(2), pages 197-211, July.
    16. Callaway, Brantly & Li, Tong & Oka, Tatsushi, 2018. "Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods," Journal of Econometrics, Elsevier, vol. 206(2), pages 395-413.
    17. Kang, Changhui, 2007. "Classroom peer effects and academic achievement: Quasi-randomization evidence from South Korea," Journal of Urban Economics, Elsevier, vol. 61(3), pages 458-495, May.
    18. Akosah, Nana & Alagidede, Imhotep & Schaling, Eric, 2019. "Unfolding the monetary policy rule in Ghana: quantile-based evidence within time-frequency framework," MPRA Paper 103260, University Library of Munich, Germany, revised 01 Oct 2020.
    19. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2008. "Nonparametric Tests for Treatment Effect Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 389-405, August.
    20. Victor Chernozhukov & Iván Fernández‐Val & Whitney Newey & Sami Stouli & Francis Vella, 2020. "Semiparametric estimation of structural functions in nonseparable triangular models," Quantitative Economics, Econometric Society, vol. 11(2), pages 503-533, May.

    More about this item

    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:arx:papers:2401.11422. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.