Nonparametric Tests for Poolability in Panel Data Models with Cross Section Dependence

In this paper 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 asymp...

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Main Authors: JIN, Sainan, SU, Liangjun
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Language:English
Published: Institutional Knowledge at Singapore Management University 2010
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Online Access:https://ink.library.smu.edu.sg/soe_research/1258
https://ink.library.smu.edu.sg/context/soe_research/article/2257/viewcontent/poolability20100810.pdf
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spelling sg-smu-ink.soe_research-22572011-05-05T09:54:05Z Nonparametric Tests for Poolability in Panel Data Models with Cross Section Dependence JIN, Sainan SU, Liangjun In this paper 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 and justify its validity. A small set of Monte Carlo simulations indicate the test performs reasonably well in finite samples. 2010-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/1258 https://ink.library.smu.edu.sg/context/soe_research/article/2257/viewcontent/poolability20100810.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Common factor Cross-section dependence Poolability Semiparametric panel data model Sieve estimation Test Econometrics
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Common factor
Cross-section dependence
Poolability
Semiparametric panel data model
Sieve estimation
Test
Econometrics
spellingShingle Common factor
Cross-section dependence
Poolability
Semiparametric panel data model
Sieve estimation
Test
Econometrics
JIN, Sainan
SU, Liangjun
Nonparametric Tests for Poolability in Panel Data Models with Cross Section Dependence
description In this paper 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 and justify its validity. A small set of Monte Carlo simulations indicate the test performs reasonably well in finite samples.
format text
author JIN, Sainan
SU, Liangjun
author_facet JIN, Sainan
SU, Liangjun
author_sort JIN, Sainan
title Nonparametric Tests for Poolability in Panel Data Models with Cross Section Dependence
title_short Nonparametric Tests for Poolability in Panel Data Models with Cross Section Dependence
title_full Nonparametric Tests for Poolability in Panel Data Models with Cross Section Dependence
title_fullStr Nonparametric Tests for Poolability in Panel Data Models with Cross Section Dependence
title_full_unstemmed Nonparametric Tests for Poolability in Panel Data Models with Cross Section Dependence
title_sort nonparametric tests for poolability in panel data models with cross section dependence
publisher Institutional Knowledge at Singapore Management University
publishDate 2010
url https://ink.library.smu.edu.sg/soe_research/1258
https://ink.library.smu.edu.sg/context/soe_research/article/2257/viewcontent/poolability20100810.pdf
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