Testing Homogeneity in Panel Data Models with Interactive Fixed Effects
This paper proposes a residual-based LM test for slope homogeneity in large dimensional panel data models with interactive fixed effects. We first run the panel regression under the null to obtain the restricted residuals, and then use them to construct our LM test statistic. We show that after bein...
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sg-smu-ink.soe_research-24332018-03-20T08:37:16Z Testing Homogeneity in Panel Data Models with Interactive Fixed Effects SU, Liangjun CHEN, Qihui This paper proposes a residual-based LM test for slope homogeneity in large dimensional panel data models with interactive fixed effects. We first run the panel regression under the null to obtain the restricted residuals, and then use them to construct our LM test statistic. We show that after being appropriately centered and scaled, our test statistic is asymptotically normally distributed under the null and a sequence of Pitman local alternatives. The asymptotic distributional theories are established under fairly general conditions which allow for both lagged dependent variables and conditional heteroskedasticity of unknown form by relying on the concept of conditional strong mixing. To improve the finite sample performance of the test, we also propose a bootstrap procedure to obtain the bootstrap p-values and justify its validity. Monte Carlo simulations suggest that the test has correct size and satisfactory power. We apply our test to study the OECD economic growth model. 2013-12-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/1434 info:doi/10.1017/S0266466613000017 https://ink.library.smu.edu.sg/context/soe_research/article/2433/viewcontent/homogeneity_main_20130111.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Conditional strong mixing Cross-sectional dependence Heterogeneity Interactive fixed effects Large panels LM test Principal component analysis Econometrics |
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Conditional strong mixing Cross-sectional dependence Heterogeneity Interactive fixed effects Large panels LM test Principal component analysis Econometrics SU, Liangjun CHEN, Qihui Testing Homogeneity in Panel Data Models with Interactive Fixed Effects |
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This paper proposes a residual-based LM test for slope homogeneity in large dimensional panel data models with interactive fixed effects. We first run the panel regression under the null to obtain the restricted residuals, and then use them to construct our LM test statistic. We show that after being appropriately centered and scaled, our test statistic is asymptotically normally distributed under the null and a sequence of Pitman local alternatives. The asymptotic distributional theories are established under fairly general conditions which allow for both lagged dependent variables and conditional heteroskedasticity of unknown form by relying on the concept of conditional strong mixing. To improve the finite sample performance of the test, we also propose a bootstrap procedure to obtain the bootstrap p-values and justify its validity. Monte Carlo simulations suggest that the test has correct size and satisfactory power. We apply our test to study the OECD economic growth model. |
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SU, Liangjun CHEN, Qihui |
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SU, Liangjun CHEN, Qihui |
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SU, Liangjun |
title |
Testing Homogeneity in Panel Data Models with Interactive Fixed Effects |
title_short |
Testing Homogeneity in Panel Data Models with Interactive Fixed Effects |
title_full |
Testing Homogeneity in Panel Data Models with Interactive Fixed Effects |
title_fullStr |
Testing Homogeneity in Panel Data Models with Interactive Fixed Effects |
title_full_unstemmed |
Testing Homogeneity in Panel Data Models with Interactive Fixed Effects |
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testing homogeneity in panel data models with interactive fixed effects |
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Institutional Knowledge at Singapore Management University |
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2013 |
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https://ink.library.smu.edu.sg/soe_research/1434 https://ink.library.smu.edu.sg/context/soe_research/article/2433/viewcontent/homogeneity_main_20130111.pdf |
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