One-sided tests for linear panel data models
This paper proposes simple tests for the error component model for the joint null hypothesis of absence of random effects and positive first order serial correlation. These tests explicitely exploit the one-sided nature of the alternative hypotheses, which yields a power gain compared to existing pr...
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2001
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| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/173776 |
| Aporte de: |
| Sumario: | This paper proposes simple tests for the error component model for the joint null hypothesis of absence of random effects and positive first order serial correlation. These tests explicitely exploit the one-sided nature of the alternative hypotheses, which yields a power gain compared to existing procedures based on two-sided alternatives. The test statistics are, by construction, asymptotically optimal. A Monte Carlo experiment shows that the proposed statistics have good size and power performance in very small samples like those typically used in applied work in panel data. |
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