Bootstrap Methods for Median Regression Models

Joel L. Horowitz

Econometrica, 1998, vol. 66, issue 6, 1327-1352

Abstract: The least-absolute-deviations (LAD) estimator for a median-regression or censored median-regression model does not satisfy the standard conditions for obtaining asymptotic refinements through use of the bootstrap because the LAD objective function is not smooth. This paper overcomes this problem by smoothing the objective function. The smoothed estimator is asymptotically equivalent to the ordinary LAD estimator. With bootstrap critical values, the rejection probabilities of symmetrical t and chi-square tests based on the smoothed estimator are correct to nearly order 1/n under the null hypothesis. In contrast, first-order asymptotic approximations make errors of this size.

Date: 1998
References: Add references at CitEc
Citations: View citations in EconPapers (101)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Working Paper: Bootstrap Methods for Median Regression Models (1996)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ecm:emetrp:v:66:y:1998:i:6:p:1327-1352

Ordering information: This journal article can be ordered from
https://www.economet ... ordering-back-issues

Access Statistics for this article

Econometrica is currently edited by Guido Imbens

More articles in Econometrica from Econometric Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().