Add a useful package (from Source forge) for octave

[CreaPhase.git] / octave_packages / econometrics-1.0.8 / gmm_results.m

diff --git a/octave_packages/econometrics-1.0.8/gmm_results.m b/octave_packages/econometrics-1.0.8/gmm_results.m
new file mode 100644 (file)
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+++ b/octave_packages/econometrics-1.0.8/gmm_results.m
@@ -0,0 +1,105 @@
+# Copyright (C) 2003,2004,2005  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, see <http://www.gnu.org/licenses/>.
+
+# usage: [theta, V, obj_value] =
+#  gmm_results(theta, data, weight, moments, momentargs, names, title, unscale, control, nslaves)
+#
+# inputs:
+#      theta: column vector initial parameters
+#       data: data matrix
+#     weight: the GMM weight matrix
+#    moments: name of function computes the moments
+#             (should return nXg matrix of contributions)
+# momentargs: (cell) additional inputs needed to compute moments.
+#             May be empty ("")
+#      names: vector of parameter names
+#             e.g., names = char("param1", "param2");
+#      title: string, describes model estimated
+#    unscale: (optional) cell that holds means and std. dev. of data
+#             (see scale_data)
+#    control: (optional) BFGS or SA controls (see bfgsmin and samin). May be empty ("").
+#    nslaves: (optional) number of slaves if executed in parallel
+#             (requires MPITB)
+#
+# outputs:
+# theta: GMM estimated parameters
+# V: estimate of covariance of parameters. Assumes the weight matrix
+#    is optimal (inverse of covariance of moments)
+# obj_value: the value of the GMM objective function
+#
+# please type "gmm_example" while in octave to see an example
+
+
+function [theta, V, obj_value] = gmm_results(theta, data, weight, moments, momentargs, names, title, unscale, control, nslaves)
+
+  if nargin < 10 nslaves = 0; endif # serial by default
+
+       if nargin < 9
+               [theta, obj_value, convergence] = gmm_estimate(theta, data, weight, moments, momentargs, "", nslaves);
+       else
+               [theta, obj_value, convergence] = gmm_estimate(theta, data, weight, moments, momentargs, control, nslaves);
+       endif
+
+
+       m = feval(moments, theta, data, momentargs); # find out how many obsns. we have
+       n = rows(m);
+
+       if convergence == 1
+               convergence="Normal convergence";
+       else
+               convergence="No convergence";
+       endif
+
+       V = gmm_variance(theta, data, weight, moments, momentargs);
+
+       # unscale results if argument has been passed
+       # this puts coefficients into scale corresponding to the original data
+       if nargin > 7
+               if iscell(unscale)
+                       [theta, V] = unscale_parameters(theta, V, unscale);
+               endif
+       endif
+
+       [theta, V] = delta_method("parameterize", theta, {data, moments, momentargs}, V);
+
+       k = rows(theta);
+       se = sqrt(diag(V));
+
+       printf("\n\n******************************************************\n");
+       disp(title);
+       printf("\nGMM Estimation Results\n");
+       printf("BFGS convergence: %s\n", convergence);
+       printf("\nObjective function value: %f\n", obj_value);
+       printf("Observations: %d\n", n);
+
+       junk = "X^2 test";
+       df = n - k;
+       if df > 0
+               clabels = char("Value","df","p-value");
+               a = [n*obj_value, df, 1 - chi2cdf(n*obj_value, df)];
+               printf("\n");
+               prettyprint(a, junk, clabels);
+       else
+               disp("\nExactly identified, no spec. test");
+       end;
+
+       # results for parameters
+       a =[theta, se, theta./se, 2 - 2*normcdf(abs(theta ./ se))];
+       clabels = char("estimate", "st. err", "t-stat", "p-value");
+       printf("\n");
+       prettyprint(a, names, clabels);
+
+       printf("******************************************************\n");
+endfunction