Sargan–Hansen test

The Sargan–Hansen test or Sargan's ${\displaystyle J}$test is a statistical test used for testing over-identifying restrictions in a statistical model. It was proposed by John Denis Sargan in 1958, and several variants were derived by him in 1975. Lars Peter Hansen re-worked through the derivations and showed that it can be extended to general non-linear GMM in a time series context.

The Sargan test is based on the assumption that model parameters are identified via a priori restrictions on the coefficients, and tests the validity of over-identifying restrictions. The test statistic can be computed from residuals from instrumental variables regression by constructing a quadratic form based on the cross-product of the residuals and exogenous variables. Under the null hypothesis that the over-identifying restrictions are valid, the statistic is asymptotically distributed as a chi-square variable with ${\displaystyle (m-k)}$degrees of freedom (where ${\displaystyle m}$is the number of instruments and ${\displaystyle k}$is the number of endogenous variables).

• Durbin–Wu–Hausman test

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