testsuite: add integration test for model_diagnostics with block
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@ -268,6 +268,7 @@ MODFILES = \
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identification/correlated_errors/fs2000_corr.mod \
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identification/correlated_errors/fs2000_corr.mod \
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identification/forward_looking/forward_looking_empty_ghx.mod \
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identification/forward_looking/forward_looking_empty_ghx.mod \
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identification/forward_looking/forward_looking_varobs_x.mod \
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identification/forward_looking/forward_looking_varobs_x.mod \
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model_diagnostics/example2_block_model_diag.mod \
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simul/example1.mod \
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simul/example1.mod \
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simul/ramst_vec.mod \
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simul/ramst_vec.mod \
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simul/Solow_no_varexo.mod \
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simul/Solow_no_varexo.mod \
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@ -0,0 +1,63 @@
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//test singular Jacobian check with block decomposition
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/*
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* Example 2 from F. Collard (2001): "Stochastic simulations with DYNARE:
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* A practical guide" (see "guide.pdf" in the documentation directory).
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*/
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/*
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* Copyright (C) 2001-2010 Dynare Team
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*
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* This file is part of Dynare.
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*
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* Dynare is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* Dynare is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with Dynare. If not, see <https://www.gnu.org/licenses/>.
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*/
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var y, c, k, a, h, b;
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varexo e, u;
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parameters beta, rho, alpha, delta, theta, psi, tau;
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alpha = 0.36;
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rho = 1;
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tau = 0;
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beta = 0.99;
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delta = 0.025;
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psi = 0;
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theta = 2.95;
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model(block);
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exp(c)*theta*exp(h)^(1+psi)=(1-alpha)*exp(y);
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exp(k) = beta*(((exp(b)*exp(c))/(exp(b(+1))*exp(c(+1))))
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*(exp(b(+1))*alpha*exp(y(+1))+(1-delta)*exp(k)));
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exp(y) = exp(a)*(exp(k(-1))^alpha)*(exp(h)^(1-alpha));
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exp(k) = exp(b)*(exp(y)-exp(c))+(1-delta)*exp(k(-1));
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a = rho*a(-1)+tau*b(-1) + e;
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b = tau*a(-1)+rho*b(-1) + u;
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end;
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initval;
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y = 0.1;
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c = -0.2;
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h = -1.2;
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k = 2.4;
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a = 0;
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b = 0;
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e = 0;
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u = 0;
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end;
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steady;
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model_diagnostics;
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