I am working with counterfactual command (https://sites.google.com/site/blaise...-distributions) to estimate counterfactual distribution. Estimation runs without problems, but I do not understand how could I put estimated counterfactual distribution on the graph. I know that it is saved in the matrix.
Saved results
counterfactual saves the following in e():
Scalars
e(N) number of observations
e(obs0) number of observations in the reference group
e(obsc) number of observations in the counterfactual group
e(nreg) number of regressions estimated
Macros
e(cmd) counterfactual
e(properties) b V
Matrices
e(b) QEs vector
e(V) variance-covariance matrix of the estimated QES
e(fit) matrix containing the differences between the observed quantiles and the fitted quantiles. It can be used to assess the quality of the fit of the parametric model
e(distributions)
matrix containing the observed, fitted and counterfactual distributions
e(quantiles) vector of the quantiles at which the QEs have been estimated
e(qe) matrix containing the QEs, their standard errors and uniform confidence bands.
Functions
e(sample) marks estimation sample
I am using Stata15.
Saved results
counterfactual saves the following in e():
Scalars
e(N) number of observations
e(obs0) number of observations in the reference group
e(obsc) number of observations in the counterfactual group
e(nreg) number of regressions estimated
Macros
e(cmd) counterfactual
e(properties) b V
Matrices
e(b) QEs vector
e(V) variance-covariance matrix of the estimated QES
e(fit) matrix containing the differences between the observed quantiles and the fitted quantiles. It can be used to assess the quality of the fit of the parametric model
e(distributions)
matrix containing the observed, fitted and counterfactual distributions
e(quantiles) vector of the quantiles at which the QEs have been estimated
e(qe) matrix containing the QEs, their standard errors and uniform confidence bands.
Functions
e(sample) marks estimation sample
I am using Stata15.
