qte: A package for computating quantile treatment effects

Main class of objects. A QTE object is returned by all of the methods that compute the QTE or QTET.

QTE(
  qte,
  ate = NULL,
  qte.se = NULL,
  qte.lower = NULL,
  qte.upper = NULL,
  ate.se = NULL,
  ate.lower = NULL,
  ate.upper = NULL,
  c = NULL,
  alp = 0.05,
  pscore.reg = NULL,
  probs,
  type = "On the Treated",
  F.treated.t = NULL,
  F.untreated.t = NULL,
  F.treated.t.cf = NULL,
  F.treated.tmin1 = NULL,
  F.treated.tmin2 = NULL,
  F.treated.change.tmin1 = NULL,
  F.untreated.change.t = NULL,
  F.untreated.change.tmin1 = NULL,
  F.untreated.tmin1 = NULL,
  F.untreated.tmin2 = NULL,
  condQ.treated.t = NULL,
  condQ.treated.t.cf = NULL,
  eachIterList = NULL,
  inffunct = NULL,
  inffuncu = NULL
)

Arguments

qte

The Quantile Treatment Effect at each value of probs

ate

The Average Treatment Effect (or Average Treatment Effect on the Treated)

qte.se

A vector of standard errors for each qte

qte.lower

A vector of lower confidence intervals for each qte (it is based on the bootstrap confidence interval -- not the se -- so it may not be symmyetric about the qte

qte.upper

A vector of upper confidence intervals for each qte (it is based on the bootstrap confidence interval -- not the se -- so it may not be symmetric about the qte

ate.se

The standard error for the ATE

ate.lower

Lower confidence interval for the ATE (it is based on the bootstrap confidence intervall -- not the se -- so it may not be symmetric about the ATE

ate.upper

Upper confidence interval for the ATE (it is based on the bootstrap confidence interval -- not the se -- so it may not be symmetric about the ATE

c

The critical value from a KS-type statistic used for creating uniform confidence bands

alp

The significance level

pscore.reg

The results of propensity score regression, if specified

probs

The values for which the qte is computed

type

Takes the values "On the Treated" or "Population" to indicate whether the estimated QTE is for the treated group or for the entire population

F.treated.t

Distribution of treated outcomes for the treated group at period t

F.untreated.t

Distribution of untreated potential outcomes for the untreated group at period t

F.treated.t.cf

Counterfactual distribution of untreated potential outcomes for the treated group at period t

F.treated.tmin1

Distribution of treated outcomes for the treated group at period tmin1

F.treated.tmin2

Distribution of treated outcomes for the treated group at period tmin2

F.treated.change.tmin1

Distribution of the change in outcomes for the treated group between periods tmin1 and tmin2

F.untreated.change.t

Distribution of the change in outcomes for the untreated group between periods t and tmin1

F.untreated.change.tmin1

Distribution of the change in outcomes for the untreated group between periods tmin1 and tmin2

F.untreated.tmin1

Distribution of outcomes for the untreated group in period tmin1

F.untreated.tmin2

Distribution of outcomes for the untreated group in period tmin2

condQ.treated.t

Conditional quantiles for the treated group in period t

condQ.treated.t.cf

Counterfactual conditional quantiles for the treated group in period t

eachIterList

An optional list of the outcome of each bootstrap iteration

inffunct

The influence function for the treated group; used for inference when there are multiple periods and in the case with panel data. It is needed for computing covariance terms in the variance-covariance matrix.

inffuncu

The influence function for the untreated group