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: | , |
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| Format: | text |
| Language: | English |
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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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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | 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. |
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