Class for prodest fitted objects.
A virtual Class: No objects may be created from it.
Model:Object of class list. Contains information about the model and the optimization procedure:
method: string The method used in estimation.
FSbetas: numeric First-stage estimated parameters.
boot.repetitions: numeric Number of bootstrap repetitions.
elapsed.time: numeric Time - in seconds - required for estimation.
theta0: numeric Vector of Second-stage optimization starting points.
opt: string Optimizer used for the Second-stage.
seed: numeric seed set.
opt.outcome: list Optimization outcome (depends on optimizer choice).
Data:Object of class list. Contains:
Y: numeric Dependent variable - Value added.
free: matrix Free variable(s).
state: matrix State variable(s).
proxy: matrix Proxy variable(s).
control: matrix Control variable(s).
idvar: numeric Panel identifiers.
timevar: numeric Time identifiers.
FSresiduals: numeric First-Stage residuals.
Estimates:Object of class list. Contains:
pars: numeric Estimated parameters for the variables of interest.
std.errors: numeric Estimated standard errors for the variables of interest.
show signature(object = 'prod'): Show table with the method, the estimated parameters and their standard errors.
summary signature(object = 'prod'): Show table with method, parameters, std.errors and auxiliary information on model and optimization.
FSres signature(object = 'prod'): Extract First-Stage residual vector.
omega signature(object = 'prod'): Extract estimated productivity vector.
coef signature(object = 'prod'): Extract estimated coefficients.