pmpp (version 0.1.1)

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

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