IDEAS home Printed from https://ideas.repec.org/a/bla/istatr/v84y2016i3p367-370.html
   My bibliography  Save this article

Rejoinder

Author

Listed:
  • Yunwen Yang
  • Huixia Judy Wang
  • Xuming He

Abstract

No abstract is available for this item.

Suggested Citation

  • Yunwen Yang & Huixia Judy Wang & Xuming He, 2016. "Rejoinder," International Statistical Review, International Statistical Institute, vol. 84(3), pages 367-370, December.
    • Handle: RePEc:bla:istatr:v:84:y:2016:i:3:p:367-370
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/insr.12181
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Newey, Whitney K. & Powell, James L., 1990. "Efficient Estimation of Linear and Type I Censored Regression Models Under Conditional Quantile Restrictions," Econometric Theory, Cambridge University Press, vol. 6(3), pages 295-317, September.
    2. Kim, Jae-Young, 2014. "An alternative quasi likelihood approach, Bayesian analysis and data-based inference for model specification," Journal of Econometrics, Elsevier, vol. 178(P1), pages 132-145.
    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. Ma, Lingjie & Koenker, Roger, 2006. "Quantile regression methods for recursive structural equation models," Journal of Econometrics, Elsevier, vol. 134(2), pages 471-506, October.
    2. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    3. Kaplan, David M. & Sun, Yixiao, 2017. "Smoothed Estimating Equations For Instrumental Variables Quantile Regression," Econometric Theory, Cambridge University Press, vol. 33(1), pages 105-157, February.
    4. Yasufumi Gemma & Takushi Kurozumi & Mototsugu Shintani, 2023. "Trend Inflation and Evolving Inflation Dynamics:A Bayesian GMM Analysis," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 506-520, December.
    5. Wu Wang & Zhongyi Zhu, 2017. "Conditional empirical likelihood for quantile regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(1), pages 1-16, January.
    6. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
    7. Sun, Yiguo, 2006. "A Consistent Nonparametric Equality Test Of Conditional Quantile Functions," Econometric Theory, Cambridge University Press, vol. 22(4), pages 614-632, August.
    8. Robert F. Engle & Simone Manganelli, 1999. "CAViaR: Conditional Value at Risk by Quantile Regression," NBER Working Papers 7341, National Bureau of Economic Research, Inc.
    9. Chen, Xiaohong & Linton, Oliver & Jacho-Chávez, David T., 2009. "An alternative way of computing efficient instrumental variable estimators," LSE Research Online Documents on Economics 58016, London School of Economics and Political Science, LSE Library.
    10. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    11. Golan, Amos & Judge, George & Perloff, Jeffrey, 1997. "Estimation and inference with censored and ordered multinomial response data," Journal of Econometrics, Elsevier, vol. 79(1), pages 23-51, July.
    12. Oberhofer, Walter & Haupt, Harry, 2005. "Consistency of nonlinear regression quantiles under Type I censoring weak dependence and general covariate design," University of Regensburg Working Papers in Business, Economics and Management Information Systems 406, University of Regensburg, Department of Economics.
    13. Heejung Bang & Anastasios A. Tsiatis, 2002. "Median Regression with Censored Cost Data," Biometrics, The International Biometric Society, vol. 58(3), pages 643-649, September.
    14. de Castro, Luciano & Galvao, Antonio F. & Kaplan, David M. & Liu, Xin, 2019. "Smoothed GMM for quantile models," Journal of Econometrics, Elsevier, vol. 213(1), pages 121-144.
    15. Lingjie Ma & Roger Koenker, 2004. "Quantile regression methods for recursive structural equation models," CeMMAP working papers 01/04, Institute for Fiscal Studies.
    16. Manganelli, Simone & White, Halbert & Kim, Tae-Hwan, 2008. "Modeling autoregressive conditional skewness and kurtosis with multi-quantile CAViaR," Working Paper Series 957, European Central Bank.
    17. Andrew Chesher, 2001. "Exogenous impact and conditional quantile functions," Econometrics 0108001, University Library of Munich, Germany.
    18. Chesher, Andrew, 2007. "Instrumental values," Journal of Econometrics, Elsevier, vol. 139(1), pages 15-34, July.
    19. Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
    20. Myoung-jae Lee & Maria Karlsson, 2015. "Trimmed and winsorized semiparametric estimator for left-truncated and right-censored regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(4), pages 485-495, May.

    More about this item

    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:bla:istatr:v:84:y:2016:i:3:p:367-370. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/isiiinl.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.