“Hodges-Lehmann Sign-based Estimators and Generalized Confidence Distributions in Linear Median Regressions with Moment-free Heterogenous Errors and Dependence of Unknown Form”
AbstractThis paper develops sign-based estimation methods for the parameters of a median regression in finite samples.We introduce p-value functions that give the confidence one may have in a certain value of the parameter giventhe realization of the sample and sign-based estimators that are the values associated with the highest confidence(p-value). The sign-based estimators are thus obtained using the Hodges-Lehmann principle of test inversion.They are expected to present the same robustness properties than the test statistics they come from and canstraightly be associated with the finite-sample-based inference procedure described in Coudin and Dufour (2007).We also show they are median unbiased (under symmetry and estimator unicity) and present equivariancefeatures similar to the LAD estimator. Consistency under point identification and asymptotic normality areprovided and hold under weaker assumptions than the LAD estimator. However, small sample behavior is ourfirst interest. By a Monte Carlo study of bias and RMSE, we show sign-based estimators perform better than theLAD in very heteroskedastic settings.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Centre de Recherche en Economie et Statistique in its series Working Papers with number 2008-33.
Date of creation: 2008
Date of revision:
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral 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: (Florian Sallaberry).
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 references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link 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 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.