Updates a fixest estimation

Updates and re-estimates a fixest model (estimated with femlm, feols or feglm). This function updates the formulas and use previous starting values to estimate a new fixest model. The data is obtained from the original call.

Usage

# S3 method for fixest
update(object, fml.update, nframes = 1, evaluate = TRUE, ...)

# S3 method for fixest_multi
update(object, fml.update, nframes = 1, evaluate = TRUE, ...)

Arguments

object

A fixest or fixest_multi object. These are obtained from feols, or feglm estimations, for example.

fml.update

Changes to be made to the original argument fml. See more information on update.formula. You can add/withdraw both variables and fixed-effects. E.g. . ~ . + x2 | . + z2 would add the variable x2 and the fixed-effect z2 to the former estimation.

nframes

(Advanced users.) Defaults to 1. Number of frames up the stack where to perform the evaluation of the updated call. By default, this is the parent frame.

evaluate

Logical, default is TRUE. If FALSE, only the updated call is returned.

...

Other arguments to be passed to the functions femlm, feols or feglm.

Value

It returns a fixest object (see details in femlm, feols or feglm).

See also

See also the main estimation functions femlm, feols or feglm. predict.fixest, summary.fixest, vcov.fixest, fixef.fixest.

Author

Laurent Berge

Examples

# Example using trade data
data(trade)

# main estimation
est_pois = fepois(Euros ~ log(dist_km) | Origin + Destination, trade)

# we add the variable log(Year)
est_2 = update(est_pois, . ~ . + log(Year))

# we add another fixed-effect: "Product"
est_3 = update(est_2, . ~ . | . + Product)

# we remove the fixed-effect "Origin" and the variable log(dist_km)
est_4 = update(est_3, . ~ . - log(dist_km) | . - Origin)

# Quick look at the 4 estimations
etable(est_pois, est_2, est_3, est_4)
#>                           est_pois              est_2              est_3
#> Dependent Var.:              Euros              Euros              Euros
#>                                                                         
#> log(dist_km)    -1.517*** (0.1131) -1.518*** (0.1132) -1.528*** (0.1157)
#> log(Year)                            72.37*** (6.900)   72.62*** (6.983)
#> Fixed-Effects:  ------------------ ------------------ ------------------
#> Origin                         Yes                Yes                Yes
#> Destination                    Yes                Yes                Yes
#> Product                         No                 No                Yes
#> _______________ __________________ __________________ __________________
#> S.E.: Clustered         by: Origin         by: Origin         by: Origin
#> Observations                38,325             38,325             38,325
#> Squared Cor.               0.37832            0.38444            0.61155
#> Pseudo R2                  0.58950            0.59290            0.76381
#> BIC                       2.44e+12           2.42e+12           1.41e+12
#> 
#>                            est_4
#> Dependent Var.:            Euros
#>                                 
#> log(dist_km)                    
#> log(Year)       70.82*** (5.989)
#> Fixed-Effects:  ----------------
#> Origin                        No
#> Destination                  Yes
#> Product                      Yes
#> _______________ ________________
#> S.E.: Clustered  by: Destination
#> Observations              38,325
#> Squared Cor.             0.17893
#> Pseudo R2                0.35377
#> BIC                     3.85e+12
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1