vcov_cluster function

Clustered VCOV

Computes the clustered VCOV of fixest objects.

vcov_cluster(x, cluster = NULL, ssc = NULL, vcov_fix = TRUE)

Arguments

• x: A fixest object.
• cluster: Either i) a character vector giving the names of the variables onto which to cluster, or ii) a formula giving those names, or iii) a vector/list/data.frame giving the hard values of the clusters. Note that in cases i) and ii) the variables are fetched directly in the data set used for the estimation.
• ssc: An object returned by the function ssc. It specifies how to perform the small sample correction.
• vcov_fix: Logical scalar, default is TRUE. If the VCOV ends up not being positive definite, whether to "fix" it using an eigenvalue decomposition (a la Cameron, Gelbach & Miller 2011).

Returns

If the first argument is a fixest object, then a VCOV is returned (i.e. a symmetric matrix).

If the first argument is not a fixest object, then a) implicitly the arguments are shifted to the left (i.e. vcov_cluster(~var1 + var2) is equivalent to vcov_cluster(cluster = ~var1 + var2)) and b) a VCOV-request is returned and NOT a VCOV. That VCOV-request can then be used in the argument vcov of various fixest

functions (e.g. vcov.fixest or even in the estimation calls).

Examples

base = iris
names(base) = c("y", "x1", "x2", "x3", "species")
base$clu = rep(1:5, 30)

est = feols(y ~ x1, base)

# VCOV: using a formula giving the name of the clusters
vcov_cluster(est, ~species + clu)

# works as well with a character vector
vcov_cluster(est, c("species", "clu"))

# you can also combine the two with '^'
vcov_cluster(est, ~species^clu)

#
# Using VCOV requests
#

# per se: pretty useless...
vcov_cluster(~species)

# ...but VCOV-requests can be used at estimation time:
# it may be more explicit than...
feols(y ~ x1, base, vcov = vcov_cluster("species"))

# ...the equivalent, built-in way:
feols(y ~ x1, base, vcov = ~species)

# The argument vcov does not accept hard values,
# so you can feed them with a VCOV-request:
feols(y ~ x1, base, vcov = vcov_cluster(rep(1:5, 30)))

References

Cameron AC, Gelbach JB, Miller DL (2011). "Robust Inference with Multiway Clustering." Journal of Business & Economic Statistics, 29(2), 238-249. doi:10.1198/jbes.2010.07136.

Author(s)

Laurent Berge