IDEAS home Printed from https://ideas.repec.org/p/cte/werepe/we1017.html
   My bibliography  Save this paper

Testing conditional monotonicity in the absence of smoothness

Author

Listed:
  • Delgado, Miguel A.
  • Escanciano, Juan Carlos

Abstract

This article proposes an omnibus test for monotonicity of nonparametric conditional distributions and its moments. Unlike previous proposals, our method does not require smooth estimation of the derivatives of nonparametric curves and it can be implemented even when the probability densities do not exist. In fact, we only require continuity of the marginal distributions. Distinguishing features of our approach are that the test statistic is pivotal under the null and invariant to any monotonic continuous transformation of the explanatory variable in finite samples. The test statistic is the sup-norm of the difference between the empirical copula function and its least concave majorant with respect to the explanatory variable coordinate. The resulting test is able to detect local alternatives converging to the null at the parametric rate n-1/2; like the classical goodness-of-.t tests. The article also discusses restricted estimation procedures under monotonicity and extensions of the basic framework to general conditional moments, estimated parameters and multivariate explanatory variables. The finite sample performance of the test is examined by means of a Monte Carlo experiment.

Suggested Citation

  • Delgado, Miguel A. & Escanciano, Juan Carlos, 2010. "Testing conditional monotonicity in the absence of smoothness," UC3M Working papers. Economics we1017, Universidad Carlos III de Madrid. Departamento de Economía.
  • Handle: RePEc:cte:werepe:we1017
    as

    Download full text from publisher

    File URL: https://e-archivo.uc3m.es/bitstream/handle/10016/9136/we1017.pdf?sequence=1
    Download Restriction: no

    Citations

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


    Cited by:

    1. Denis Chetverikov, 2012. "Testing regression monotonicity in econometric models," CeMMAP working papers CWP35/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    More about this item

    Keywords

    Stochastic monotonicity;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

    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:cte:werepe:we1017. 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: (Ana Poveda). General contact details of provider: http://www.eco.uc3m.es/ .

    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.

    We have no references for this item. You can help adding them by using 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.