This function retrieves the fixed effects from a fixest estimation. It is useful only when there are one or more fixed-effect dimensions.

# S3 method for fixest
fixef(
object,
notes = getFixest_notes(),
sorted = TRUE,
fixef.tol = 1e-05,
fixef.iter = 10000,
...
)

## Arguments

object

A fixest estimation (e.g. obtained using feols or feglm).

notes

Logical. Whether to display a note when the fixed-effects coefficients are not regular.

sorted

Logical, default is TRUE. Whether to order the fixed-effects by their names. If FALSE, then the order used in the demeaning algorithm is used.

The number of threads. Can be: a) an integer lower than, or equal to, the maximum number of threads; b) 0: meaning all available threads will be used; c) a number strictly between 0 and 1 which represents the fraction of all threads to use. The default is to use 50% of all threads. You can set permanently the number of threads used within this package using the function setFixest_nthreads.

fixef.tol

Precision used to obtain the fixed-effects. Defaults to 1e-5. It corresponds to the maximum absolute difference allowed between two coefficients of successive iterations. Argument fixef.tol cannot be lower than 10000*.Machine$double.eps. Note that this parameter is dynamically controlled by the algorithm. fixef.iter Maximum number of iterations in fixed-effects algorithm (only in use for 2+ fixed-effects). Default is 10000. ... Not currently used. ## Value A list containing the vectors of the fixed effects. If there is more than 1 fixed-effect, then the attribute “references” is created. This is a vector of length the number of fixed-effects, each element contains the number of coefficients set as references. By construction, the elements of the first fixed-effect dimension are never set as references. In the presence of regular fixed-effects, there should be Q-1 references (with Q the number of fixed-effects). ## Details If the fixed-effect coefficients not regular, then several reference points need to be set, leading to the coefficients to be NOT interpretable. If this is the case, then a warning is raised. ## See also plot.fixest.fixef. See also the main estimation functions femlm, feols or feglm. Use summary.fixest to see the results with the appropriate standard-errors, fixef.fixest to extract the fixed-effect coefficients, and the function etable to visualize the results of multiple estimations. ## Author Laurent Berge ## Examples  data(trade) # We estimate the effect of distance on trade => we account for 3 fixed-effects est_pois = femlm(Euros ~ log(dist_km)|Origin+Destination+Product, trade) # Obtaining the fixed-effects coefficients: fe_trade = fixef(est_pois) # The fixed-effects of the first fixed-effect dimension: head(fe_trade$Origin)
#>       AT       BE       DE       DK       ES       FI
#> 22.67038 23.72304 24.86999 23.60329 25.12917 21.80906

# Summary information:
#> Fixed_effects coefficients
#>                         Origin Destination Product
#> Number of fixed-effects     15          15      20
#> Number of references         0           1       1
#> Mean                      23.5        3.09  0.0127
#> Standard-deviation        1.28        1.11    1.36
#>
#> COEFFICIENTS:
#>   Origin:    AT    BE    DE   DK    ES
#>           22.67 23.72 24.87 23.6 25.13 ... 10 remaining
#> -----
#>   Destination:    AT    BE    DE    DK    ES
#>                2.436 2.696 4.323 2.451 4.043 ... 10 remaining
#> -----
#>   Product: 1     2     3     4      5
#>            0 1.414 0.656 1.449 -1.521 ... 15 remaining

# Plotting them: