compute.cfa2: compute.cfa2

In WeigeHuangEcon/cfa: Continuous Counterfactual Analysis

Description

an update of compute.cfa that allows one to use other other estimators such as quantile regression or nonparametric methods (not yet implemented) as the first step estimator of the conditional distribution

Usage

compute.cfa2(
  tvals,
  yvals,
  data,
  yname,
  tname,
  xnames = NULL,
  method = "dr",
  link = "logit",
  tau = seq(0.1, 0.99, 0.01),
  condDistobj = NULL
)

Arguments

tvals	the values of the "treatment" to compute parameters of interest for
yvals	the values to compute the counterfactual distribution for
data	the data.frame where y, t, and x are
method	either "dr" or "qr" for distribution regression or quantile regression
link	if using distribution regression, any link function that works with the binomial family (e.g. logit (the default), probit, cloglog)
tau	if using quantile regression, which values of tau to estimate the conditional quantiles
condDistobj	optional conditional distribution object that has been previously computed
condDist	optional pre-estimated conditional distribution function

Value

CFA.OBJ

WeigeHuangEcon/cfa documentation built on Dec. 20, 2020, 4:39 p.m.