*! version 1.0.0 15December2015
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Title

edfreg -- Corrections for statistical inference with robust and clustered covariance matrices.

Syntax

edfreg depvar indepvars [if] [in] [weight] [, options]

Options

robust Robust estimate of covariance.
cluster(varname) Clustered estimate of covariance.
select(varlist) Calculates corrections only for the specified subset of regressors, reducing execution time.
absorb(varname) Fixed effects for the categories defined by varname (must be subsets of cluster if used with that option).
noconstant Suppress constant term.

Either robust or cluster must be specified. Supports aweights and pweights.

Description

edfreg computes bias adjusted standard errors and effective degrees of freedom corrections for robust and clustered covariance matrices.
Depending upon the interaction between the hypothesis test and regression leverage these covariance estimates may place weight on a subset of residuals.
edfreg calculates the bias and variance of the covariance estimate in the case of iid normal errors and uses these to adjust the standard error and degrees of freedom for each estimated coefficient.
This has been found to improve the accuracy of statistical inference in cases with normal iid and non-normal non-iid errors. See:

Young, Alwyn.
Improved, Nearly Exact, Statistical Inference with Robust and Clustered Covariance Matrices using Effective Degrees of Freedom Corrections.

edfreg first reports the robust or clustered regression and then calculates and reports corrections.

Stored results

edfreg stores the following in e():

Matrices

e(edf) coefficient, bias adjusted standard error, effective degrees of freedom, t-stat, p-value, 95% confidence interval.

Author

Alwyn Young, London School of Economics, a.young@lse.ac.uk.