fixest (version 0.8.0)

fitstat: Computes fit statistics of fixest objects

Description

Computes various fit statistics for fixest estimations.

Usage

fitstat(x, type, simplify = FALSE, verbose = TRUE, show_types = FALSE, ...)

Arguments

x

A fixest estimation.

type

Character vector. The type of fit statistic to be computed. The classic ones are: n, rmse, r2, pr2, f, wald, ivf, ivwald. You have the full list in the details section. Further, you can register your own types with fitstat_register.

simplify

Logical, default is FALSE. By default a list is returned whose names are the selected types. If simplify = TRUE and only one type is selected, then the element is directly returned (ie will not be nested in a list).

verbose

Logical, default is TRUE. If TRUE, an object of class fixest_fitstat is returned (so its associated print method will be triggerrd). If FALSE a simple list is returned instead.

show_types

Logical, default is FALSE. If TRUE, only prompts all available types.

...

Other elements to be passed to other methods and may be used to compute the statistics (for example you can pass on arguments to compute the VCOV when using type = "g" or type = "wald".).

Value

By default an object of class fixest_fitstat is returned. Using verbose = FALSE returns a simple a list. Finally, if only one type is selected, simplify = TRUE leads to the selected type to be returned.

Registering your own types

You can register custom fit statistics with the function fitstat_register.

Available types

The types are case sensitive, please use lower case only. The types available are:

• n, ll, aic, bic, rmseThe number of observations, the log-likelihood, the AIC, the BIC and the root mean squared error, respectively.

• gThe effective sample size. This is used only when the standard-errors are clustered and is used when computing the p-values of the coefficients.

• r2, ar2, wr2, awr2, pr2, apr2, wpr2, awpr2All r2 that can be obtained with the function r2. The a stands for 'adjusted', the w for 'within' and the p for 'pseudo'. Note that the order of the letters a, w and p does not matter.

• f, wfThe F-tests of nullity of the coefficients. The w stands for 'within'. These types return the following values: stat, p, df1 and df2. If you want to display only one of these, use their name after a dot: e.g. f.stat will give the statistic of the F-test, or wf.p will give the p-values of the F-test on the projected model (i.e. projected onto the fixed-effects).

• waldWald test of joint nullity of the coefficients. This test always excludes the intercept and the fixed-effects. These type returns the following values: stat, p, df1, df2 and vcov. The element vcov reports the way the VCOV matrix was computed since it directly influences this statistic.

• ivf, ivf1, ivf2, ivfallThese statistics are specific to IV estimations. They report either the IV F-test of the first stage (ivf or ivf1), of the second stage (ivf2) or of both (ivfall). The F-test of the first stage is commonly named weak instrument test. The value of ivfall is only useful in etable when both the 1st and 2nd stages are displayed (it leads to the 1st stage F-test(s) to be displayed on the 1st stage estimation(s), and the 2nd stage one on the 2nd stage estimation -- otherwise, ivf1 would also be displayed on the 2nd stage estimation). These types return the following values: stat, p, df1 and df2.

• ivwald, ivwald1, ivwald2, ivwaldallThese statistics are specific to IV estimations. They report either the IV Wald-test of the first stage (ivwald or ivwald1), of the second stage (ivwald2) or of both (ivwaldall). The Wald-test of the first stage is commonly named weak instrument test. The value of ivwaldall is only useful in etable when both the 1st and 2nd stages are displayed (it leads to the 1st stage Wald-test(s) to be displayed on the 1st stage estimation(s), and the 2nd stage one on the 2nd stage estimation -- otherwise, ivwald1 would also be displayed on the 2nd stage estimation). These types return the following values: stat, p, df1, df2, and vcov.

• whThis statistic is specific to IV estimations. Wu-Hausman endogeneity test. H0 is the absence of endogeneity of the instrumented variables. It returns the following values: stat, p, df1, df2.

• sarganSargan test of overidentifying restrictions. H0: the instruments are not correlated with the second stage residuals. It returns the following values: stat, p, df.

• lr, wlrLikelihood ratio and within likelihood ratio tests. It returns the following elements: stat, p, df. Concerning the within-LR test, note that, coutrary to estimations with femlm or feNmlm, estimations with feglm/fepois need to estimate the model with fixed-effects only which may prove time-consuming (depending on your model). Bottom line, if you really need the within-LR and estimate a Poisson model, use femlm instead of fepois (the former uses direct ML maximisation for which the only FEs model is a by product).

Examples

# NOT RUN {
data(trade)
gravity = feols(log(Euros) ~ log(dist_km) | Destination + Origin, trade)

# Extracting the 'working' number of observations used to compute the pvalues
fitstat(gravity, "g", simplify = TRUE)

# Some fit statistics
fitstat(gravity, ~ rmse + r2 + wald + wf)

# You can use them in etable
etable(gravity, fitstat = ~ rmse + r2 + wald + wf)

# For wald and wf, you could show the pvalue instead:
etable(gravity, fitstat = ~ rmse + r2 + wald.p + wf.p)

# Now let's display some statistics that are not built-in
# => we use fitstat_register to create them

# We need: a) type name, b) the function to be applied
#          c) (optional) an alias

fitstat_register("tstand", function(x) tstat(x, se = "stand")[1], "t-stat (regular)")
fitstat_register("thc", function(x) tstat(x, se = "heter")[1], "t-stat (HC1)")
fitstat_register("t1w", function(x) tstat(x, se = "clus")[1], "t-stat (clustered)")
fitstat_register("t2w", function(x) tstat(x, se = "twow")[1], "t-stat (2-way)")

# Now we can use these keywords in fitstat:
etable(gravity, fitstat = ~ . + tstand + thc + t1w + t2w)

# Note that the custom stats we created are can easily lead
# to errors, but that's another story!


# }