- x
A fixest estimation.
- type
Character scalar, equal to "k", "resid", "t". If "k", then the number of
regressors is returned. If "resid", then it is the "residuals degree of freedom", i.e.
the number of observations minus the number of regressors. If "t", it is the degrees of
freedom used in the t-test. Note that these values are affected by how the VCOV of x
is computed, in particular when the VCOV is clustered.
- vars
A vector of variable names, of the regressors. This is optional. If provided,
then type is set to 1 by default and the number of regressors contained in vars
is returned. This is only useful in the presence of collinearity and we want a subset of
the regressors only. (Mostly for internal use.)
- vcov
Versatile argument to specify the VCOV. In general, it is either a character
scalar equal to a VCOV type, either a formula of the form: vcov_type ~ variables. The
VCOV types implemented are: "iid", "hetero" (or "HC1"), "cluster", "twoway",
"NW" (or "newey_west"), "DK" (or "driscoll_kraay"), and "conley". It also accepts
object from vcov_cluster, vcov_NW, NW,
vcov_DK, DK, vcov_conley and
conley. It also accepts covariance matrices computed externally.
Finally it accepts functions to compute the covariances. See the vcov documentation
in the vignette.
- se
Character scalar. Which kind of standard error should be computed:
“standard”, “hetero”, “cluster”, “twoway”, “threeway”
or “fourway”? By default if there are clusters in the estimation:
se = "cluster", otherwise se = "iid". Note that this argument is deprecated,
you should use vcov instead.
- cluster
Tells how to cluster the standard-errors (if clustering is requested).
Can be either a list of vectors, a character vector of variable names, a formula or
an integer vector. Assume we want to perform 2-way clustering over var1 and var2
contained in the data.frame base used for the estimation. All the following
cluster arguments are valid and do the same thing:
cluster = base[, c("var1", "var2")], cluster = c("var1", "var2"), cluster = ~var1+var2.
If the two variables were used as fixed-effects in the estimation, you can leave it
blank with vcov = "twoway" (assuming var1 [resp. var2] was
the 1st [resp. 2nd] fixed-effect). You can interact two variables using ^ with
the following syntax: cluster = ~var1^var2 or cluster = "var1^var2".
- ssc
An object of class ssc.type obtained with the function ssc. Represents
how the degree of freedom correction should be done.You must use the function ssc
for this argument. The arguments and defaults of the function ssc are:
adj = TRUE, fixef.K="nested", cluster.adj = TRUE, cluster.df = "min",
t.df = "min", fixef.force_exact=FALSE). See the help of the function ssc for details.
- stage
Either 1 or 2. Only concerns IV regressions, which stage to look at.
The type of VCOV can have an influence on the degrees of freedom. In particular, when the
VCOV is clustered, the DoF returned will be in accordance with the way the small
sample correction was performed when computing the VCOV. That type of value is in general
not what we have in mind when we think of "degrees of freedom". To obtain the ones that are
more intuitive, please use degrees_freedom_iid instead.