Publication Type

Journal Article

Version

Preprint

Publication Date

5-2013

Abstract

In this article we propose a nonparametric test for poolability in large dimensional semiparametric panel data models with cross-section dependence based on the sieve estimation technique. To construct the test statistic, we only need to estimate the model under the alternative. We establish the asymptotic normal distributions of our test statistic under the null hypothesis of poolability and a sequence of local alternatives, and prove the consistency of our test. We also suggest a bootstrap method as an alternative way to obtain the critical values. A small set of Monte Carlo simulations indicate the test performs reasonably well in finite samples.

Keywords

Common factor, Cross-section dependence, Poolability, Semiparametric panel data model, Sieve estimation, Test

Discipline

Econometrics

Research Areas

Econometrics

Publication

Econometric Reviews

Volume

32

Issue

4

First Page

469

Last Page

512

ISSN

0747-4938

Identifier

10.1080/07474938.2012.690669

Publisher

Taylor and Francis

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1080/07474938.2012.690669

Included in

Econometrics Commons

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