GMM_parametric: Produce posterior means of lambda's for the parametric GMM...

In pmpp: Posterior Mean Panel Predictor

Description

Produce posterior means of lambda's for the parametric GMM implementation given autoregressive coefficient (rho)

Usage

GMM_parametric(rho, alpha = 0, optim_method, init, n_lambda, n_alpha,
  X_mat, Y_mat, Z_mat, W, T, N, aux_Y0, common_par_method, X_star, Y_star,
  Z_star)

Arguments

rho	lagged dependent variable coefficients
alpha	external variables coefficients
optim_method	optimization method
init	initial values for the optimization routine
n_lambda	number of columns in W; currently always set to 1
n_alpha	number of external variables
X_mat	lagged dependent variable matrix
Y_mat	dependent variable matrix
Z_mat	external variable matrix
W	cross-sectionally invariant variables - not used now
T	time dimension of the data
N	cross-sectional dimension of the data
aux_Y0	auxiliary matrix with initial observations of the dependent variable
common_par_method	method for estimating common parameters
X_star	auxiliary matrix for OFD transformation
Y_star	auxiliary matrix for OFD transformation
Z_star	auxiliary matrix for OFD transformation

pmpp documentation built on Oct. 30, 2019, 11:35 a.m.