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  • Hansen Test and Sargan Test

    Hello everyone.
    I hope you could assist me.
    I am using the two-step GMM model. Below the estimation table, Stata shows me the Sargan test and the Hansen test. I didn't understand exactly the difference between these two tests.
    What is their H0 and their alternative hypotheses H1 ?
    How can I validate my model using these two tests?
    Thank you for your time and assistance.

  • #2
    The null hypothesis is that all overidentifying restrictions are valid; the alternative hypothesis is that at least one of them is invalid. Not rejecting the null hypothesis - while desirable - is providing only limited information. It does not imply that your model is correctly specified, which still relies on untestable assumptions. A rejection of the null hypothesis - clearly undesirable - could indicate that there is some model misspecification, although it might not be specific about the nature of the misspecification. The Sargan test (for one-step GMM) makes stronger assumptions about the model's error term than the Hansen test. With two-step GMM, only the Hansen test is relevant.

    More on this topic:
    https://www.kripfganz.de/stata/

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    • #3
      Thank you so much for the response.
      If I understand the hansen test correctly, the H0 indicates that the instruments are valid. right ?

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      • #4
        Not precisely. Suppose you have K regressors and L>K instruments. You can think about the Hansen test as checking whether L-K instruments - the overidentifying restrictions - are valid, assuming that there are already K valid instruments. You can never test the joint validity of all instruments. Moreover, unless you have a very strong prior about which K instruments are valid by assumption, a rejection of the test would not even tell you which L-K instruments are invalid. In that regard, the test can never give you a definite answer but only an indication if there could be some concerns.
        https://www.kripfganz.de/stata/

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        • #5
          Thank you very much.

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