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# Copyright (C) 2003,2004 Michael Creel michael.creel@uab.es
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
# GMM example file, shows initial consistent estimator,
# estimation of efficient weight, and second round
# efficient estimator
# This also shows how do use data scaling - WHICH YOU SHOULD DO!
1;
# the form a user-written moment function should take
function m = mymoments(theta, data, momentargs)
k = momentargs{1}; # use this so that data can hold dep, indeps, and instr
y = data(:,1);
x = data(:,2:k+1);
w = data(:, k+2:columns(data));
lambda = exp(x*theta);
e = y ./ lambda - 1;
m = dmult(e, w);
endfunction
n = 1000;
k = 5;
x = [ones(n,1) rand(n,k-1)];
w = [x, rand(n,1)];
theta = ones(k,1);
lambda = exp(x*theta);
y = randp(lambda);
[xs, scalecoef] = scale_data(x);
# The arguments for gmm_estimate
theta = zeros(k,1);
data = [y xs w];
weight = eye(columns(w));
moments = "mymoments";
momentargs = {k}; # needed to know where x ends and w starts
# additional args for gmm_results
names = str2mat("theta1", "theta2", "theta3", "theta4", "theta5");
title = "Poisson GMM trial";
control = {100,0,1,1};
# initial consistent estimate: only used to get efficient weight matrix, no screen output
[theta, obj_value, convergence] = gmm_estimate(theta, data, weight, moments, momentargs);
# efficient weight matrix
# this method is valid when moments are not autocorrelated
# the user is reponsible to properly estimate the efficient weight
m = feval(moments, theta, data, momentargs);
weight = inverse(cov(m));
# second round efficient estimator
gmm_results(theta, data, weight, moments, momentargs, names, title, scalecoef, control);

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