A NEW DIAGNOSTIC TEST FOR CROSS-SECTION UNCORRELATEDNESS IN NON PARAMETRIC PANEL DATA MODELS

Jia Chen; Jiti Gao; Degui Li

doi:10.1017/S0266466612000072

A NEW DIAGNOSTIC TEST FOR CROSS-SECTION UNCORRELATEDNESS IN NON PARAMETRIC PANEL DATA MODELS

Jia Chen^*, Jiti Gao, Degui Li

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper, we propose a new diagnostic test for residual cross-section uncorrelatedness (CU) in a nonparametric panel data model. The proposed nonparametric CU test is a nonparametric counterpart of an existing parametric cross-section dependence test proposed in Pesaran (2004, Cambridge Working paper in Economics 0435). Without assuming cross-section independence, we establish asymptotic distribution for the proposed test statistic for the case. where both the cross-section dimension and the time dimension go to infinity simultaneously, and then analyze the power function of the proposed test under a sequence of local alternatives that involve a nonlinear multifactor model. The simulation results and real data analysis show that the nonparametric CU test associated with an asymptotic critical value works well.

Original language	English
Pages (from-to)	1144-1163
Number of pages	20
Journal	Econometric Theory
Volume	28
Issue number	5
DOIs	https://doi.org/10.1017/S0266466612000072
Publication status	Published - Oct 2012

Keywords

INDEPENDENCE

Access to Document

10.1017/S0266466612000072

http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=8697967

Cite this

@article{38cb12fe301643df8de49a328b0a4438,

title = "A NEW DIAGNOSTIC TEST FOR CROSS-SECTION UNCORRELATEDNESS IN NON PARAMETRIC PANEL DATA MODELS",

abstract = "In this paper, we propose a new diagnostic test for residual cross-section uncorrelatedness (CU) in a nonparametric panel data model. The proposed nonparametric CU test is a nonparametric counterpart of an existing parametric cross-section dependence test proposed in Pesaran (2004, Cambridge Working paper in Economics 0435). Without assuming cross-section independence, we establish asymptotic distribution for the proposed test statistic for the case. where both the cross-section dimension and the time dimension go to infinity simultaneously, and then analyze the power function of the proposed test under a sequence of local alternatives that involve a nonlinear multifactor model. The simulation results and real data analysis show that the nonparametric CU test associated with an asymptotic critical value works well.",

keywords = "INDEPENDENCE",

author = "Jia Chen and Jiti Gao and Degui Li",

year = "2012",

month = oct,

doi = "10.1017/S0266466612000072",

language = "English",

volume = "28",

pages = "1144--1163",

journal = "Econometric Theory",

issn = "0266-4666",

publisher = "Cambridge University Press",

number = "5",

}

TY - JOUR

T1 - A NEW DIAGNOSTIC TEST FOR CROSS-SECTION UNCORRELATEDNESS IN NON PARAMETRIC PANEL DATA MODELS

AU - Chen, Jia

AU - Gao, Jiti

AU - Li, Degui

PY - 2012/10

Y1 - 2012/10

N2 - In this paper, we propose a new diagnostic test for residual cross-section uncorrelatedness (CU) in a nonparametric panel data model. The proposed nonparametric CU test is a nonparametric counterpart of an existing parametric cross-section dependence test proposed in Pesaran (2004, Cambridge Working paper in Economics 0435). Without assuming cross-section independence, we establish asymptotic distribution for the proposed test statistic for the case. where both the cross-section dimension and the time dimension go to infinity simultaneously, and then analyze the power function of the proposed test under a sequence of local alternatives that involve a nonlinear multifactor model. The simulation results and real data analysis show that the nonparametric CU test associated with an asymptotic critical value works well.

AB - In this paper, we propose a new diagnostic test for residual cross-section uncorrelatedness (CU) in a nonparametric panel data model. The proposed nonparametric CU test is a nonparametric counterpart of an existing parametric cross-section dependence test proposed in Pesaran (2004, Cambridge Working paper in Economics 0435). Without assuming cross-section independence, we establish asymptotic distribution for the proposed test statistic for the case. where both the cross-section dimension and the time dimension go to infinity simultaneously, and then analyze the power function of the proposed test under a sequence of local alternatives that involve a nonlinear multifactor model. The simulation results and real data analysis show that the nonparametric CU test associated with an asymptotic critical value works well.

KW - INDEPENDENCE

UR - http://www.scopus.com/inward/record.url?scp=84865774441&partnerID=8YFLogxK

U2 - 10.1017/S0266466612000072

DO - 10.1017/S0266466612000072

M3 - Article

SN - 0266-4666

VL - 28

SP - 1144

EP - 1163

JO - Econometric Theory

JF - Econometric Theory

IS - 5

ER -

A NEW DIAGNOSTIC TEST FOR CROSS-SECTION UNCORRELATEDNESS IN NON PARAMETRIC PANEL DATA MODELS

Abstract

Keywords

Access to Document

Other files and links

Cite this