boot_ssc: boot_ssc() handles the small sample correction factor applied...

In s3alfisc/wildboottestjlr: Fast Wild Cluster Bootstrap Inference in R via WildBootTests.jl and JuliaConnectoR

boot_ssc() handles the small sample correction factor applied in boottest() in analogy to fixest::ssc()

Description

boot_ssc() handles the small sample correction factor applied in boottest() in analogy to fixest::ssc()

Usage

boot_ssc(
  adj = TRUE,
  fixef.K = "none",
  cluster.adj = TRUE,
  cluster.df = "conventional"
)

Arguments

cluster.adj	Logical scalar, defaults to TRUE. If TRUE, a cluster correction G/(G-1) is performed, with G the number of clusters.
cluster.df	Either "conventional" or "min" default. Controls how "G" is computed for multiway clustering if cluster.adj = TRUE. Note that the covariance matrix in the multiway clustering case is of the form V = V_1 + V_2 - V_12. If "conventional", then each summand G_i is multiplied with a small sample adjustment G_i / (G_i - 1). If "min", all summands are multiplied with the same value, min(G) / (min(G) - 1)
adj.	Logical scalar, defaults to TRUE. If TRUE, applies a small sample correction of (N-1) / (N-k) where N is the number of observations and k is the number of estimated coefficients excluding any fixed effects projected out in either fixest::feols() or lfe::felm().
fixef.k	Character scalar, equal to 'none': the fixed effects parameters are discarded when calculating k in (N-1) / (N-k).

s3alfisc/wildboottestjlr documentation built on June 16, 2022, 7:40 a.m.