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In instrumental variables regression always check the joint significance of your instruments. The Staiger-Stock rule of thumb says that an F-statistic of less than 10 is worrisome and indicates that your instruments might be weak, i.e. they are not sufficiently correlated with the endogenous variable. However, this does not automatically imply that an F above 10 guarantees strong instruments. Staiger and Stock (1997)Staiger and Stock (1997) have shown that instrumental variables techniques like 2SLS can be badly biased in "small" samples if the instruments are only weakly correlated with the endogenous variable. Their example was the study by Angrist and Krueger (1991) who had more than 300,000 observations - a disturbing fact about the notion of "small" samples.

In instrumental variables regression always check the joint significance of your instruments. The Staiger-Stock rule of thumb says that an F-statistic of less than 10 is worrisome and indicates that your instruments might be weak, i.e. they are not sufficiently correlated with the endogenous variable. However, this does not automatically imply that an F above 10 guarantees strong instruments. Staiger and Stock (1997) have shown that instrumental variables techniques like 2SLS can be badly biased in "small" samples if the instruments are only weakly correlated with the endogenous variable. Their example was the study by Angrist and Krueger (1991) who had more than 300,000 observations - a disturbing fact about the notion of "small" samples.

In instrumental variables regression always check the joint significance of your instruments. The Staiger-Stock rule of thumb says that an F-statistic of less than 10 is worrisome and indicates that your instruments might be weak, i.e. they are not sufficiently correlated with the endogenous variable. However, this does not automatically imply that an F above 10 guarantees strong instruments. Staiger and Stock (1997) have shown that instrumental variables techniques like 2SLS can be badly biased in "small" samples if the instruments are only weakly correlated with the endogenous variable. Their example was the study by Angrist and Krueger (1991) who had more than 300,000 observations - a disturbing fact about the notion of "small" samples.

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In instrumental variables regression always check the joint significance of your instruments. The Staiger-Stock rule of thumb says that an F-statistic of less than 10 is worrisome and indicates that your instruments might be weak, i.e. they are not sufficiently correlated with the endogenous variable. However, this does not automatically imply that an F above 10 guarantees strong instruments. Staiger and Stock (1997) have shown that instrumental variables techniques like 2SLS can be badly biased in "small" samples if the instruments are only weakly correlated with the endogenous variable. Their example was the study by Angrist and Krueger (1991) who had more than 300,000 observations - a disturbing fact about the notion of "small" samples.

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