options are none, diagonal, and block_diagonal (default) MAP transform operation options are kaczmarz, cimmino, and symmetric kaczmarz (default) MAP acceleration method options are conjugate_gradient ( cg, default), steep_descent ( sd), and aitken Variation of Spielman et al's graph-theoretical (GT) approach (using spectral sparsification of graphs) currently disabled Partial out variables using the 'method of alternating projections' (MAP) in any of its variants (default) Unique identifier for the first mobility group note: the postestimation command ' predict, d' requires this optionĪllows selecting the desired adjustments for degrees of freedom rarely used but changing it can speed-up execution Vcetype may be unadjusted (default), robust or cluster fvvarlist (allowing two- and multi-way clustering) note: mean and sum are equivalent if all groups are of equal size (eg: 11 starting players in a football/soccer team) How are the individual FEs aggregated within a group. note: the individual() option requires the group() note: using group() without individual() is equivalent to running the regression on 1 observation per groupĬategorical variable representing each individual whose fixed effect will be absorbed(eg: inventor_id) note: regression variables (depvar, indepvars) must be constant within each group (eg: patent_citations must be constant within a patent_id)

Save all fixed effect estimates with the _hdfe* prefixĬategorical variable representing each group (eg: patent_id) Reghdfe depvar, absorb( absvars indvar) group( groupvar) individual( indvar) OptionsĬategorical variables representing the fixed effects to be absorbed

Reghdfe depvar, absorb( absvars) įixed effects regressions with group-level outcomes and individual FEs: Least-square regressions (no fixed effects): Also supports individual FEs with group-level outcomes Linear regression with multiple fixed effects.

Stata regress by group