gOPLP returns the second stage parameters estimates of both OP and LP models. It is part of both prodestOP() and prodestsLP() routines.
gOPLP(vtheta, mX, mlX, vphi, vlag.phi, vres, stol, Pr.hat, att)Vector of parameters to be estimated.
Matrix of regressors.
matrix of lagged regressors.
Vector of fitted polynomial.
Lagged vector of fitted polynomial.
Vector of residuals of the free variables.
Number setting the tolerance of the routine.
Vector of fitted exit probabilities.
Indicator for attrition in the data - i.e., if firms exit the market.
gOPLP() estimates the second stage of OP and LP routines. It accepts 7 inputs, generates and optimizes over the group of moment functions E(e_itX^k_it).