prod {prodest}

Class for Prodest Fitted object

Description

Class for prodest fitted objects.

Objects from the Class

A virtual Class: No objects may be created from it.

Slots

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.

Methods

• 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.

Author(s)

Gabriele Rovigatti