A conditional likelihood ratio test for structural models

Resumo

This paper develops a general method for constructing similar tests based on the conditional distribution of nonpivotal statistics in a simultaneous equations model with normal errors and known reducedform covariance matrix. The test based on the likelihood ratio statistic is particularly simple and has good power properties. When identification is strong, the power curve of this conditional likelihood ratio test is essentially equal to the power envelope for similar tests. Monte Carlo simulations also suggest that this test dominates the Anderson- Rubin test and the score test. Dropping the restrictive assumption of disturbances normally distributed with known covariance matrix, approximate conditional tests are found that behave well in small samples even when identification is weak.

Ficha do documento

Tipo

Estudo

Ano

2002

Instituição

Fundação Getulio Vargas. Escola de Pós-graduação em Economia

Fonte

Repositório da FGV

Idioma

Inglês

Acesso

Não informado

Identificador

oai:repositorio.fgv.br:10438/12955

Temas

EconomiaDados

Palavras-chave

Instrumental variablesSimilar testsWald testLikelihood ratio testPower envelopeConfidence regions2SLS estimatorLIML estimatorEconomiaVariáveis instrumentais (Estatística)