ccrm_est_2: GMM Estimator of distributional parameters of a K = 2 random...

In zhan-gao/ccrm: Package for estimation of categorical coefficient regression models (Gao and Pesaran, 2023).

GMM Estimator of distributional parameters of a K = 2 random coefficient model

Description

This function estimates the distribution of beta_i using GMM. The moment conditions are listed in Section 3 of Gao and Pesaran (2023)

Usage

ccrm_est_2(
  x,
  y,
  z = NULL,
  theta_init = NULL,
  s_max = 4,
  remove_intercept = TRUE,
  iter_gmm = TRUE,
  seed = 2023
)

Arguments

x	regressor (N-by-1)
y	dependent variable (N-by-p_x)
z	control variables (N-by-p_z)
theta_init	Initial estimates of distributional parameters
s_max	Maximum order of moments used in estimation
remove_intercept	whether subtract estimated intercept term in calculation of y_tilde
iter_gmm	Whether to use iterative GMM (If FALSE, use OW-GMM with initial estimates)
seed	seed for random number generator

Value

A list contains estimated coefficients and inferential statistics

theta_b	Estimated distributional parameter p, b_L, b_H
theta_b_se	s.e. of Estimated distributional parameter p, b_L, b_H
theta_m
theta_m_se	s.e. of estimated moments of beta_i
theta_m_gmm	Estimated moments of beta_i from gmm
theta_m_gmm_se	s.e. estimated moments of beta_i from gmm
gamma	estimated coefficients of control varibles, including intercept
gamma_se	s.e. estimated coefficients of control varibles, including intercept
V_theta	variance
gmm_res	GMM estimation of moments output object

zhan-gao/ccrm documentation built on Oct. 22, 2023, 3:24 p.m.