IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v95y2000i2p347-374.html
   My bibliography  Save this article

Galton, Edgeworth, Frisch, and prospects for quantile regression in econometrics

Author

Listed:
  • Koenker, Roger

Abstract

No abstract is available for this item.

Suggested Citation

  • Koenker, Roger, 2000. "Galton, Edgeworth, Frisch, and prospects for quantile regression in econometrics," Journal of Econometrics, Elsevier, vol. 95(2), pages 347-374, April.
  • Handle: RePEc:eee:econom:v:95:y:2000:i:2:p:347-374
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304-4076(99)00043-3
    Download Restriction: Full text for ScienceDirect subscribers only

    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(03), pages 295-317, September.
    2. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    3. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
    4. Manski, Charles F., 1985. "Semiparametric analysis of discrete response : Asymptotic properties of the maximum score estimator," Journal of Econometrics, Elsevier, vol. 27(3), pages 313-333, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Giorgio Canarella & Stephen Pollard, 2004. "Parameter Heterogeneity In The Neoclassical Growth Model: A Quantile Regression Approach," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 29(1), pages 1-31, June.
    2. Heski Bar-Isaac & Ian Jewitt & Clare Leaver, 2007. "Information and Human Capital Managment," Working Papers 07-28, New York University, Leonard N. Stern School of Business, Department of Economics.
    3. Bera, Anil K. & Bilias, Yannis, 2002. "The MM, ME, ML, EL, EF and GMM approaches to estimation: a synthesis," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 51-86, March.
    4. Hallin, M. & Vermandele, C. & Werker, B.J.M., 2003. "Serial and Nonserial Sign-and-Rank Statistics : Asymptotic Representation and Asymptotic Normality," Discussion Paper 2003-23, Tilburg University, Center for Economic Research.
    5. Giloni, Avi & Simonoff, Jeffrey S. & Sengupta, Bhaskar, 2006. "Robust weighted LAD regression," Computational Statistics & Data Analysis, Elsevier, vol. 50(11), pages 3124-3140, July.
    6. Hiau Joo Kee, 2005. "Glass Ceiling or Sticky Floor? Exploring the Australian Gender Pay Gap using Quantile Regression and Counterfactual Decomposition Methods," CEPR Discussion Papers 487, Centre for Economic Policy Research, Research School of Economics, Australian National University.
    7. Koutsomanoli-Filippaki, Anastasia I. & Mamatzakis, Emmanuel C., 2011. "Efficiency under quantile regression: What is the relationship with risk in the EU banking industry?," Review of Financial Economics, Elsevier, vol. 20(2), pages 84-95, May.
    8. Laurens CHERCHYE & Timo KUOSMANEN & Thierry POST, 2000. "New Tools for Dealing with Errors-in-Variables in DEA," Working Papers Department of Economics ces0006, KU Leuven, Faculty of Economics and Business, Department of Economics.
    9. Cathy Chen & Richard Gerlach, 2013. "Semi-parametric quantile estimation for double threshold autoregressive models with heteroskedasticity," Computational Statistics, Springer, vol. 28(3), pages 1103-1131, June.
    10. Drescher, Larissa S. & Goddard, Ellen W., 2011. "Heterogeneous Demand for Food Diversity: A Quantile Regression Analysis," 51st Annual Conference, Halle, Germany, September 28-30, 2011 114484, German Association of Agricultural Economists (GEWISOLA).
    11. Pereira, Pedro Telhado & Martins, Pedro Silva, 2000. "Does Education Reduce Wage Inequality? Quantile Regressions Evidence from Fifteen European Countries," FEUNL Working Paper Series wp379, Universidade Nova de Lisboa, Faculdade de Economia.
    12. Landajo, Manuel & de Andres, Javier & Lorca, Pedro, 2007. "Robust neural modeling for the cross-sectional analysis of accounting information," European Journal of Operational Research, Elsevier, vol. 177(2), pages 1232-1252, March.
    13. Basu, Sudipta & Markov, Stanimir, 2004. "Loss function assumptions in rational expectations tests on financial analysts' earnings forecasts," Journal of Accounting and Economics, Elsevier, vol. 38(1), pages 171-203, December.
    14. Li, Ming-Yuan Leon, 2009. "Value or volume strategy?," Finance Research Letters, Elsevier, vol. 6(4), pages 210-218, December.
    15. Jungsik Noh & Sangyeol Lee, 2016. "Quantile Regression for Location-Scale Time Series Models with Conditional Heteroscedasticity," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(3), pages 700-720, September.
    16. Manuel Landajo & Javier de Andrés & Pedro Lorca, 2008. "Measuring firm performance by using linear and non-parametric quantile regressions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(2), pages 227-250.
    17. Omid Ranjbar & Chien-Chiang Lee & Tsangyao Chang & Mei-Ping Chen, 2014. "Income Convergence in African Countries: Evidence from a Stationary Test With Multiple Structural Breaks," South African Journal of Economics, Economic Society of South Africa, vol. 82(3), pages 371-391, September.
    18. Ming-Yuan Leon Li, 2009. "Reexamining asymmetric effects of monetary and government spending policies on economic growth using quantile regression," Journal of Developing Areas, Tennessee State University, College of Business, vol. 43(1), pages 137-154, September.
    19. Marcio Laurini, 2007. "A note on the use of quantile regression in beta convergence analysis," Economics Bulletin, AccessEcon, vol. 3(52), pages 1-8.
    20. repec:eee:ecofin:v:42:y:2017:i:c:p:285-299 is not listed on IDEAS
    21. Warren Gilchrist, 2008. "Regression Revisited," International Statistical Review, International Statistical Institute, vol. 76(3), pages 401-418, December.
    22. Simila, Timo, 2006. "Self-organizing map visualizing conditional quantile functions with multidimensional covariates," Computational Statistics & Data Analysis, Elsevier, vol. 50(8), pages 2097-2110, April.
    23. Shahidur Rahman, 2005. "An Alternative Estimation to Spurious Regression Model," Economic Growth Centre Working Paper Series 0507, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.

    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:eee:econom:v:95:y:2000:i:2:p:347-374. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/jeconom .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.