The Maximum Number of Parameters for the Hausman Test When the Estimators are from Different Sets of Equations
Hausman (1978) developed a widely-used model specification test that has passed the test of time. The test is based on two estimators, one being consistent under the null hypothesis but inconsistent under the alternative, and the other being consistent under both the null and alternative hypotheses....
| Autores: | , |
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| Tipo de recurso: | informe técnico |
| Fecha de publicación: | 2013 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/41534 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/41534 |
| Access Level: | acceso abierto |
| Palabra clave: | Hausman test Specification test Number of parameters Instrumental variable (IV) model Box-Cox model Sample selection bias. Econometría (Economía) 5302 Econometría |
| Sumario: | Hausman (1978) developed a widely-used model specification test that has passed the test of time. The test is based on two estimators, one being consistent under the null hypothesis but inconsistent under the alternative, and the other being consistent under both the null and alternative hypotheses. In this paper, we show that the asymptotic variance of the difference of the two estimators can be a singular matrix. Moreover, in calculating the Hausman test there is a maximum number of parameters which is the number of different equations that are used to obtain the two estimators. Three illustrative examples are used, namely an exogeneity test for the linear regression model, a test for the Box-Cox transformation, and a test for sample selection bias. |
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