Sébastien Villemot
parent
7d3ab36743
commit
3b4ef0df49
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@ -124,7 +124,9 @@ not recommended as it already denotes the inverse operator. Commands
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for declaring variables and parameters are described below.
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.. command:: var VAR_NAME [$TEX_NAME$] [(long_name=QUOTED_STRING|NAME=QUOTED_STRING)]...;
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var(log) VAR_NAME [$TEX_NAME$] [(long_name=QUOTED_STRING|NAME=QUOTED_STRING)]...;
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var(deflator=MODEL_EXPR) VAR_NAME (... same options apply)
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var(log, deflator=MODEL_EXPR) VAR_NAME (... same options apply)
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var(log_deflator=MODEL_EXPR) VAR_NAME (... same options apply)
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|br| This required command declares the endogenous variables in
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@ -138,14 +140,28 @@ for declaring variables and parameters are described below.
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in the order of declaration, in a column cell array
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``M_.endo_names``.
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*Options*
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If the model is nonstationary and is to be written as such in the
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``model`` block, Dynare will need the trend deflator for the
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appropriate endogenous variables in order to stationarize the
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model. The trend deflator must be provided alongside the variables
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that follow this trend.
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*Options*
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.. option:: log
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In addition to the endogenous variable(s) thus declared, this option
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also triggers the creation of auxiliary variable(s) equal to the log of
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the corresponding endogenous variable(s). For example, given a
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``var(log) y`` statement, two endogenous will be created (``y`` and
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``LOG_y``), and an auxiliary equation linking the two will also be
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added (equal to ``LOG_y = log(y)``). Moreover, every occurence of ``y``
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in the model will be replaced by ``exp(LOG_y)``. This option is for
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example useful when one wants to perform a loglinear approximation of
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some variable(s) in the context of a first-order stochastic
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approximation; or when one wants to ensure the variable(s) stay(s) in
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the definition domain of the function defining the steady state or the
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dynamic residuals when the nonlinear solver is used.
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.. option:: deflator = MODEL_EXPR
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@ -155,6 +171,8 @@ for declaring variables and parameters are described below.
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the ``trend_var, log_trend_var, var`` and ``parameters``
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commands. The deflator is assumed to be multiplicative; for an
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additive deflator, use ``log_deflator``.
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This option can be used together with the ``log`` option (the latter
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must come first).
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.. option:: log_deflator = MODEL_EXPR
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@ -162,6 +180,10 @@ for declaring variables and parameters are described below.
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be additive instead of multiplicative (or, to put it
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otherwise, the declared variable is equal to the log of a
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variable with a multiplicative trend).
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This option cannot be used together with the ``log`` option, because it
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would not make much sense from an economic point of view (the
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corresponding auxiliary variable would correspond to the log taken
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two times on a variable with a multiplicative trend).
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.. _long-name:
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@ -11,7 +11,7 @@ function str = subst_auxvar(var_index, aux_lead_lag, M_)
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% OUTPUTS
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% - str [string] name of auxiliary
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% Copyright (C) 2001-2021 Dynare Team
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% Copyright (C) 2001-2022 Dynare Team
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%
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% This file is part of Dynare.
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%
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@ -61,8 +61,9 @@ if ~isempty(aux_index)
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end
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return
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case 7
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% currently unused
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error('This type of auxiliary variable should not occur, please contact the developers.')
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% Log-transformation of a variable
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str = sprintf('log(%s(%d))', M_.endo_names{M_.aux_vars(aux_index).orig_index}, aux_lead_lag);
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return;
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case 8
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% Diff operator
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str = sprintf('diff(%s)', M_.endo_names{M_.aux_vars(aux_index).orig_index});
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@ -1 +1 @@
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Subproject commit 46cc47266bac728eeb0758d3b7cff18f841437bb
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Subproject commit 71edfd05e4cc28cb3e36e217aaa0e0cbdc030fd2
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@ -461,7 +461,11 @@ MODFILES = \
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bgp/solow-1/solow.mod \
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bgp/nk-1/nk.mod \
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bgp/ramsey-1/ramsey.mod \
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dynare-command-options/ramst.mod
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dynare-command-options/ramst.mod \
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log_transform/example1.mod \
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log_transform/ramst.mod \
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log_transform/fs2000_nonstationary.mod \
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log_transform/nk_ramsey.mod
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ECB_MODFILES = \
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var-expectations/1/example1.mod \
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@ -938,6 +942,10 @@ pruning/AS_pruned_state_space_red_shock.o.trs: pruning/AnSchorfheide_pruned_stat
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ramst_model_edit.m.trs: ramst.m.trs
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ramst_model_edit.o.trs: ramst.o.trs
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log_transform/ramst.m.trs: ramst.m.trs
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log_transform/ramst.o.trs: ramst.o.trs
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observation_trends_and_prefiltering/MCMC: m/observation_trends_and_prefiltering/MCMC o/observation_trends_and_prefiltering/MCMC
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m/observation_trends_and_prefiltering/MCMC: $(patsubst %.mod, %.m.trs, $(filter observation_trends_and_prefiltering/MCMC/%.mod, $(MODFILES)))
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o/observation_trends_and_prefiltering/MCMC: $(patsubst %.mod, %.o.trs, $(filter observation_trends_and_prefiltering/MCMC/%.mod, $(MODFILES)))
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@ -0,0 +1,50 @@
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// Test for var(log) in a stochastic context
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var(log) c, y, k;
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var 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 = 0.95;
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tau = 0.025;
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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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phi = 0.1;
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model;
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c*theta*h^(1+psi)=(1-alpha)*y;
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k = beta*(((exp(b)*c)/(exp(b(+1))*c(+1)))
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*(exp(b(+1))*alpha*y(+1)+(1-delta)*k));
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y = exp(a)*(k(-1)^alpha)*(h^(1-alpha));
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k = exp(b)*(y-c)+(1-delta)*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 = 1.08068253095672;
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c = 0.80359242014163;
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h = 0.29175631001732;
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k = 11.08360443260358;
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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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shocks;
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var e; stderr 0.009;
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var u; stderr 0.009;
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var e, u = phi*0.009*0.009;
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end;
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stoch_simul;
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if isempty(strmatch('LOG_y', M_.endo_names))
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error('Log-transformed variable not created')
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end
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@ -0,0 +1,78 @@
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// Test for var(log, deflator=…)
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/*
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* Copyright (C) 2004-2022 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 gM gA;
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trend_var(growth_factor=gA) A;
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trend_var(growth_factor=gM) M;
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var(log, deflator=A) k c y;
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var(deflator=M(-1)/A) P;
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var(deflator=M(-1)) W l d;
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var R n;
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varexo e_a e_m;
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parameters alp bet gam mst rho psi del;
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alp = 0.33;
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bet = 0.99;
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gam = 0.003;
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mst = 1.011;
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rho = 0.7;
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psi = 0.787;
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del = 0.02;
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model;
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gA = exp(gam+e_a);
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log(gM) = (1-rho)*log(mst) + rho*log(gM(-1))+e_m;
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c+k = k(-1)^alp*(A*n)^(1-alp)+(1-del)*k(-1);
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P*c = M;
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P/(c(+1)*P(+1))=bet*P(+1)*(alp*k^(alp-1)*(A(+1)*n(+1))^(1-alp)+(1-del))/(c(+2)*P(+2));
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(psi/(1-psi))*(c*P/(1-n))=W;
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R = P*(1-alp)*k(-1)^alp*A^(1-alp)*n^(-alp)/W;
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W = l/n;
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M-M(-1)+d = l;
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1/(c*P)=bet*R/(c(+1)*P(+1));
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y = k(-1)^alp*(A*n)^(1-alp);
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end;
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initval;
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k = 6;
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gM = mst;
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P = 2.25;
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c = 0.45;
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W = 4;
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R = 1.02;
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d = 0.85;
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n = 0.19;
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l = 0.86;
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y = 0.6;
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gA = exp(gam);
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end;
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shocks;
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var e_a; stderr 0.014;
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var e_m; stderr 0.005;
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end;
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steady;
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check;
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stoch_simul;
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@ -0,0 +1,85 @@
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// Tests var(log) in combination with ramsey_model
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//------------------------------------------------------------------------------------------------------------------------
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//1. Variable declaration
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//------------------------------------------------------------------------------------------------------------------------
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var pai, n, r, a;
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var(log) c;
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//4 variables + 1 shock
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varexo u;
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//------------------------------------------------------------------------------------------------------------------------
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// 2. Parameter declaration and calibration
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//-------------------------------------------------------------------------------------------------------------------------
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parameters beta, rho, epsilon, omega, phi, gamma;
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beta=0.99;
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gamma=3; //Frish elasticity
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omega=17; //price stickyness
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epsilon=8; //elasticity for each variety of consumption
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phi=1; //coefficient associated to labor effort disutility
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rho=0.95; //coefficient associated to productivity shock
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//-----------------------------------------------------------------------------------------------------------------------
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// 3. The model
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//-----------------------------------------------------------------------------------------------------------------------
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model;
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a=rho*(a(-1))+u;
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1/c=beta*(1/(c(+1)))*(r/(pai(+1))); //euler
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omega*pai*(pai-1)=beta*omega*(c/(c(+1)))*(pai(+1))*(pai(+1)-1)+epsilon*exp(a)*n*(c/exp(a)*phi*n^gamma-(epsilon-1)/epsilon); //NK pc
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//pai*(pai-1)/c = beta*pai(+1)*(pai(+1)-1)/c(+1)+epsilon*phi*n^(gamma+1)/omega-exp(a)*n*(epsilon-1)/(omega*c); //NK pc
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(exp(a))*n=c+(omega/2)*((pai-1)^2);
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end;
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//--------------------------------------------------------------------------------------------------------------------------
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// 4. Steady state
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//---------------------------------------------------------------------------------------------------------------------------
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initval;
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pai=1;
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r=1/beta;
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c=0.9671684882;
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n=0.9671684882;
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a=0;
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end;
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//---------------------------------------------------------------------------------------------------------------------------
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// 5. shocks
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//---------------------------------------------------------------------------------------------------------------------------
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shocks;
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var u; stderr 0.008;
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end;
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//--------------------------------------------------------------------------------------------------------------------------
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// 6. Ramsey problem
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//--------------------------------------------------------------------------------------------------------------------------
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planner_objective(ln(c)-phi*((n^(1+gamma))/(1+gamma)));
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ramsey_model(planner_discount=0.99, planner_discount_latex_name = $\delta$);
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stoch_simul(order=1,irf=20);
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evaluate_planner_objective;
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@ -0,0 +1,51 @@
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// Test for var(log) in a deterministic context
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var(log) c k;
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varexo x;
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parameters alph gam delt bet aa;
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alph=0.5;
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gam=0.5;
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delt=0.02;
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bet=0.05;
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aa=0.5;
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model;
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c + k - aa*x*k(-1)^alph - (1-delt)*k(-1);
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c^(-gam) - (1+bet)^(-1)*(aa*alph*x(+1)*k^(alph-1) + 1 - delt)*c(+1)^(-gam);
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end;
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initval;
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x = 1;
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k = ((delt+bet)/(1.0*aa*alph))^(1/(alph-1));
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c = aa*k^alph-delt*k;
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end;
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steady;
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check;
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shocks;
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var x;
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periods 1;
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values 1.2;
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end;
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perfect_foresight_setup(periods=200);
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perfect_foresight_solver;
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idx_c = strmatch('c', M_.endo_names);
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idx_log_c = strmatch('LOG_c', M_.endo_names);
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if isempty(idx_log_c)
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error('Log-transformed variable not created')
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end
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if max(abs(oo_.endo_simul(idx_log_c, :) - log(oo_.endo_simul(idx_c, :)))) > 1e-7
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error('Transformation not correctly performed')
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end
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S = load('../ramst/Output/ramst_results.mat');
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if max(abs(oo_.endo_simul(idx_c, :) - S.oo_.endo_simul(idx_c, :))) > 1e-7
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error('Result differs from non-transformed model')
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end
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Reference in New Issue