beta_inf_correction {robust2sls}

Calculates the correction factor for inference under H0 of no outliers

Description

Calculates the correction factor for inference under H0 of no outliers

Usage

beta_inf_correction(
  robust2sls_object,
  iteration = 1,
  exact = FALSE,
  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.

exact

A logical value indicating whether the actually detected share of outliers (TRUE) or the theoretical share (FALSE) should be used.

fp

A logical value whether the fixed point standard error correction (TRUE) or the exact iteration correction should be computed (FALSE).

Details

Argument iteration specifies which iteration of the robust structural parameter estimates should be calculated. Iteration 1 refers to the first robust estimate. Iteration 0 is not a valid argument since it is the baseline estimate, which is not robust.

The parameter exact does not matter much under the null hypothesis of no outliers since the detected share will converge to the theoretical share. Under the alternative, this function should not be used.

Argument fp determines whether the fixed point standard error correction should be computed. This argument is only respected if the specified iteration is one of the iterations after the algorithm converged.

Value

beta_inf_correction returns the numeric correction factor.