Semiparametrically Efficient Inference Based on Signs and Ranks for Median Restricted Models

M. Hallin, C. Vermandele, B.J.M. Werker

Research output: Working paperDiscussion paperOther research output

212 Downloads (Pure)

Abstract

Since the pioneering work of Koenker and Bassett (1978), econometric models involving median and quantile rather than the classical mean or conditional mean concepts have attracted much interest.Contrary to the traditional models where the noise is assumed to have mean zero, median-restricted models enjoy a rich group-invariance structure.In this paper, we exploit this invariance structure in order to obtain semiparametrically efficient inference procedures for these models.These procedures are based on residual signs and ranks, and therefore insensitive to possible misspecification of the underlying innovation density, yet semiparametrically efficient at correctly specified densities.This latter combination is a definite advantage of these procedures over classical quasi-likelihood methods.The techniques we propose can be applied, without additional technical difficulties, to both cross-sectional and time-series models.They do not require any explicit tangent space calculation nor any projections on these.
Original languageEnglish
Place of PublicationTilburg
PublisherFinance
Number of pages40
Volume2004-11
Publication statusPublished - 2004

Publication series

NameCentER Discussion Paper
Volume2004-11

Fingerprint

Invariance
Quasi-likelihood
Tangent Space
Misspecification
Likelihood Methods
Time Series Models
Econometrics
Quantile
Model
Projection
Zero
Innovation
Concepts

Keywords

  • models
  • regression analysis
  • econometrics

Cite this

Hallin, M., Vermandele, C., & Werker, B. J. M. (2004). Semiparametrically Efficient Inference Based on Signs and Ranks for Median Restricted Models. (CentER Discussion Paper; Vol. 2004-11). Tilburg: Finance.
Hallin, M. ; Vermandele, C. ; Werker, B.J.M. / Semiparametrically Efficient Inference Based on Signs and Ranks for Median Restricted Models. Tilburg : Finance, 2004. (CentER Discussion Paper).
@techreport{05757b2bad744583b012b417132f7675,
title = "Semiparametrically Efficient Inference Based on Signs and Ranks for Median Restricted Models",
abstract = "Since the pioneering work of Koenker and Bassett (1978), econometric models involving median and quantile rather than the classical mean or conditional mean concepts have attracted much interest.Contrary to the traditional models where the noise is assumed to have mean zero, median-restricted models enjoy a rich group-invariance structure.In this paper, we exploit this invariance structure in order to obtain semiparametrically efficient inference procedures for these models.These procedures are based on residual signs and ranks, and therefore insensitive to possible misspecification of the underlying innovation density, yet semiparametrically efficient at correctly specified densities.This latter combination is a definite advantage of these procedures over classical quasi-likelihood methods.The techniques we propose can be applied, without additional technical difficulties, to both cross-sectional and time-series models.They do not require any explicit tangent space calculation nor any projections on these.",
keywords = "models, regression analysis, econometrics",
author = "M. Hallin and C. Vermandele and B.J.M. Werker",
note = "Pagination: 40",
year = "2004",
language = "English",
volume = "2004-11",
series = "CentER Discussion Paper",
publisher = "Finance",
type = "WorkingPaper",
institution = "Finance",

}

Hallin, M, Vermandele, C & Werker, BJM 2004 'Semiparametrically Efficient Inference Based on Signs and Ranks for Median Restricted Models' CentER Discussion Paper, vol. 2004-11, Finance, Tilburg.

Semiparametrically Efficient Inference Based on Signs and Ranks for Median Restricted Models. / Hallin, M.; Vermandele, C.; Werker, B.J.M.

Tilburg : Finance, 2004. (CentER Discussion Paper; Vol. 2004-11).

Research output: Working paperDiscussion paperOther research output

TY - UNPB

T1 - Semiparametrically Efficient Inference Based on Signs and Ranks for Median Restricted Models

AU - Hallin, M.

AU - Vermandele, C.

AU - Werker, B.J.M.

N1 - Pagination: 40

PY - 2004

Y1 - 2004

N2 - Since the pioneering work of Koenker and Bassett (1978), econometric models involving median and quantile rather than the classical mean or conditional mean concepts have attracted much interest.Contrary to the traditional models where the noise is assumed to have mean zero, median-restricted models enjoy a rich group-invariance structure.In this paper, we exploit this invariance structure in order to obtain semiparametrically efficient inference procedures for these models.These procedures are based on residual signs and ranks, and therefore insensitive to possible misspecification of the underlying innovation density, yet semiparametrically efficient at correctly specified densities.This latter combination is a definite advantage of these procedures over classical quasi-likelihood methods.The techniques we propose can be applied, without additional technical difficulties, to both cross-sectional and time-series models.They do not require any explicit tangent space calculation nor any projections on these.

AB - Since the pioneering work of Koenker and Bassett (1978), econometric models involving median and quantile rather than the classical mean or conditional mean concepts have attracted much interest.Contrary to the traditional models where the noise is assumed to have mean zero, median-restricted models enjoy a rich group-invariance structure.In this paper, we exploit this invariance structure in order to obtain semiparametrically efficient inference procedures for these models.These procedures are based on residual signs and ranks, and therefore insensitive to possible misspecification of the underlying innovation density, yet semiparametrically efficient at correctly specified densities.This latter combination is a definite advantage of these procedures over classical quasi-likelihood methods.The techniques we propose can be applied, without additional technical difficulties, to both cross-sectional and time-series models.They do not require any explicit tangent space calculation nor any projections on these.

KW - models

KW - regression analysis

KW - econometrics

M3 - Discussion paper

VL - 2004-11

T3 - CentER Discussion Paper

BT - Semiparametrically Efficient Inference Based on Signs and Ranks for Median Restricted Models

PB - Finance

CY - Tilburg

ER -

Hallin M, Vermandele C, Werker BJM. Semiparametrically Efficient Inference Based on Signs and Ranks for Median Restricted Models. Tilburg: Finance. 2004. (CentER Discussion Paper).