Heteroskedasticity-Robust VCOV — vcov

Computes the heteroskedasticity-robust VCOV of fixest objects.

vcov_hetero(
  x,
  type = "hc1",
  exact = TRUE,
  boot.size = NULL,
  ssc = NULL,
  vcov_fix = TRUE
)

Arguments

x: A fixest object.
type: A string scalar. Either "HC1"/"HC2"/"HC3"
exact: Logical scalar, default is TRUE. Whether the diagonals of the projection matrix should be calculated exactly. If FALSE, then it will be approximated using a JLA algorithm. See details. Unless you have a very large number of observations, it is recommended to keep the default value.
boot.size: Integer scalar or NULL, default is 1000. This is only used when exact == FALSE. This determines the number of bootstrap samples used to estimate the projection matrix. If equal to NULL, it falls back to the default value of 1000.
ssc: An object returned by the function ssc. It specifies how to perform the small sample correction.
vcov_fix: Logical scalar, default is FALSE. If the VCOV ends up not being positive definite, whether to "fix" it using an eigenvalue decomposition (a la Cameron, Gelbach & Miller 2011). Since the VCOV should be PSD asymptotically, this might be a sign of a problem with using the asymptotic approximation (e.g. too few units in clusters). If a problem is detected, the function will print a message to inform you.

Value

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_hetero("HC3") is equivalent to vcov_hetero(type = "HC3") 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).

References

MacKinnon, J. G. (2012). "Thirty years of heteroscedasticity-robust inference." Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis, pp. 437–461. https://doi.org/10.1007/978-1-4614-1653-1_17

Author

Laurent Berge and Kyle Butts

Examples


base = iris
names(base) = c("y", "x1", "x2", "x3", "species")

est = feols(y ~ x1 | species, base)

vcov_hetero(est, "hc1")
#>            x1
#> x1 0.01127604
vcov_hetero(est, "hc2", ssc = ssc(K.adj = FALSE))
#>            x1
#> x1 0.01143592
vcov_hetero(est, "hc3", ssc = ssc(K.adj = FALSE))
#>            x1
#> x1 0.01192059

# Using approximate hatvalues
vcov_hetero(est, "hc3", exact = FALSE, boot.size = 500)
#>            x1
#> x1 0.01193672