Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/74852
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Type: | Journal article |
Title: | A new diagnostic test for cross-section uncorrelatedness in non parametric panel data models |
Author: | Chen, Jia Gao, Jiti Li, Degui |
Citation: | Econometric Theory, 2012; 28(5):1144-1163 |
Publisher: | Cambridge University Press |
Issue Date: | 2012 |
ISSN: | 0266-4666 |
School/Discipline: | School of Economics |
Statement of Responsibility: | Jia Chen And Jiti Gao And Degui Li |
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. |
Rights: | © Cambridge University Press 2012 |
DOI: | 10.1017/S0266466612000072 |
Appears in Collections: | Economics publications |
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