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.
Common factor, Cross-section dependence, Poolability, Semiparametric panel data model, Sieve estimation, Test
JIN, Sainan and SU, Liangjun.
Nonparametric Tests for Poolability in Panel Data Models with Cross Section Dependence. (2010). Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/1258
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