beta_hausman: Calculates a Hausman test on the difference between robust...

In robust2sls: Outlier Robust Two-Stage Least Squares Inference and Testing

Calculates a Hausman test on the difference between robust and full sample estimates

Description

Calculates a Hausman test on the difference between robust and full sample estimates

Usage

beta_hausman(robust2sls_object, iteration, subset = NULL, fp = FALSE)

Arguments

robust2sls_object	An object of class "robust2sls".
iteration	An integer > 0 specifying the iteration step for which parameters to calculate corrected standard errors.
subset	A vector of numeric indices or strings indicating which coefficients to include in the Hausman test. NULL uses the whole vector of coefficients.
fp	A logical value whether the fixed point asymptotic variance (TRUE) or the exact iteration asymptotic variance should be used (FALSE).

Details

Argument fp determines whether the fixed point asymptotic variance should be used. This argument is only respected if the specified iteration is one of the iterations after the algorithm converged.

Value

beta_hausman returns a matrix with the value of the Hausman test statistic and its corresponding p-value. The attribute "type of avar" records which asymptotic variance has been used (the specific iteration or the fixed point). The attribute "coefficients" stores the names of the coefficients that were included in the Hausman test.

robust2sls documentation built on Jan. 11, 2023, 5:13 p.m.