Implements a Fortran routine `k_order_moment` to compute the k-order unconditional moment of the vector of endogenous variables using simulation
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mex_PROGRAMS = k_order_mean
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k_order_mean_FCFLAGS = $(AM_FCFLAGS) -I../libkordersim
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nodist_k_order_mean_SOURCES = \
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mexFunction.f08
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k_order_mean_LDADD = ../libkordersim/libkordersim.a
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BUILT_SOURCES = $(nodist_k_order_mean_SOURCES)
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CLEANFILES = $(nodist_k_order_mean_SOURCES)
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%.f08: $(top_srcdir)/../../sources/k_order_mean/%.f08
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$(LN_S) -f $< $@
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@ -4,7 +4,7 @@ SUBDIRS = mjdgges kronecker bytecode block_kalman_filter sobol perfect_foresight
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# libdynare++ must come before gensylv, k_order_perturbation, dynare_simul_
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# libdynare++ must come before gensylv, k_order_perturbation, dynare_simul_
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if ENABLE_MEX_DYNAREPLUSPLUS
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if ENABLE_MEX_DYNAREPLUSPLUS
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SUBDIRS += libdynare++ gensylv libkorder dynare_simul_ k_order_perturbation k_order_welfare local_state_space_iterations libkordersim folded_to_unfolded_dr local_state_space_iteration_fortran k_order_simul
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SUBDIRS += libdynare++ gensylv libkorder dynare_simul_ k_order_perturbation k_order_welfare local_state_space_iterations libkordersim folded_to_unfolded_dr local_state_space_iteration_fortran k_order_simul k_order_mean
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endif
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endif
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if ENABLE_MEX_MS_SBVAR
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if ENABLE_MEX_MS_SBVAR
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@ -165,6 +165,7 @@ AC_CONFIG_FILES([Makefile
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folded_to_unfolded_dr/Makefile
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folded_to_unfolded_dr/Makefile
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local_state_space_iteration_fortran/Makefile
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local_state_space_iteration_fortran/Makefile
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k_order_simul/Makefile
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k_order_simul/Makefile
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k_order_mean/Makefile
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perfect_foresight_problem/Makefile
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perfect_foresight_problem/Makefile
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num_procs/Makefile
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num_procs/Makefile
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block_trust_region/Makefile
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block_trust_region/Makefile
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@ -0,0 +1,2 @@
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include ../mex.am
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include ../../k_order_mean.am
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@ -20,6 +20,7 @@ EXTRA_DIST = \
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folded_to_unfolded_dr \
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folded_to_unfolded_dr \
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local_state_space_iteration_fortran \
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local_state_space_iteration_fortran \
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k_order_simul \
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k_order_simul \
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k_order_mean \
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gensylv \
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gensylv \
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dynare_simul_ \
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dynare_simul_ \
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perfect_foresight_problem \
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perfect_foresight_problem \
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@ -0,0 +1,200 @@
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! Copyright © 2021 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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! input:
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! order the order of approximation, needs order+1 derivatives
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! nstat
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! npred
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! nboth
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! nforw
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! nexog
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! order_moment order of the moment we need to compute
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! nburn number of burn-in periods
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! yhat_start starting value for the full vector of endogenous variables minus its steady-state value
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! shocks matrix of shocks (number of exogenous variables x number of periods)
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! ysteady steady-state value for the full vector of endogenous variables
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! dr structure containing the matrices for the decision rule (g_0, g_1,…)
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! output:
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! mean estimated `order_moment`-order moment for the full vector of e
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subroutine mexFunction(nlhs, plhs, nrhs, prhs) bind(c, name='mexFunction')
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use iso_fortran_env
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use iso_c_binding
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use struct
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use matlab_mex
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use partitions
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use simulation
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implicit none
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type(c_ptr), dimension(*), intent(in), target :: prhs
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type(c_ptr), dimension(*), intent(out) :: plhs
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integer(c_int), intent(in), value :: nlhs, nrhs
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type(c_ptr) :: order_mx, nstatic_mx, npred_mx, nboth_mx, nfwrd_mx, nexog_mx, order_moment_mx, nburn_mx, &
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yhat_start_mx, shocks_mx, ysteady_mx, dr_mx, tmp
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type(pol), dimension(:), allocatable, target :: fdr, udr
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integer :: order, nstatic, npred, nboth, nfwrd, exo_nbr, endo_nbr, nys, nvar, nper, nburn, order_moment
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real(real64), dimension(:,:), allocatable :: shocks, sim
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real(real64), dimension(:), allocatable :: dyu, mean
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real(real64), dimension(:), pointer, contiguous :: ysteady, yhat_start
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type(pascal_triangle) :: p
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type(horner), dimension(:), allocatable :: h
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integer :: i, t, d, m, n
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character(kind=c_char, len=10) :: fieldname
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order_mx = prhs(1)
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nstatic_mx = prhs(2)
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npred_mx = prhs(3)
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nboth_mx = prhs(4)
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nfwrd_mx = prhs(5)
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nexog_mx = prhs(6)
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order_moment_mx = prhs(7)
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nburn_mx = prhs(8)
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yhat_start_mx = prhs(9)
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shocks_mx = prhs(10)
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ysteady_mx = prhs(11)
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dr_mx = prhs(12)
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! Checking the consistence and validity of input arguments
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if (nrhs /= 12) then
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call mexErrMsgTxt("Must have exactly 12 inputs")
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end if
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if (.not. (mxIsScalar(order_mx)) .and. mxIsNumeric(order_mx)) then
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call mexErrMsgTxt("1st argument (order) should be a numeric scalar")
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end if
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if (.not. (mxIsScalar(nstatic_mx)) .and. mxIsNumeric(nstatic_mx)) then
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call mexErrMsgTxt("2nd argument (nstat) should be a numeric scalar")
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end if
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if (.not. (mxIsScalar(npred_mx)) .and. mxIsNumeric(npred_mx)) then
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call mexErrMsgTxt("3rd argument (npred) should be a numeric scalar")
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end if
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if (.not. (mxIsScalar(nboth_mx)) .and. mxIsNumeric(nboth_mx)) then
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call mexErrMsgTxt("4th argument (nboth) should be a numeric scalar")
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end if
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if (.not. (mxIsScalar(nfwrd_mx)) .and. mxIsNumeric(nfwrd_mx)) then
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call mexErrMsgTxt("5th argument (nforw) should be a numeric scalar")
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end if
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if (.not. (mxIsScalar(nexog_mx)) .and. mxIsNumeric(nexog_mx)) then
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call mexErrMsgTxt("6th argument (nexog) should be a numeric scalar")
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end if
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if (.not. (mxIsScalar(order_moment_mx)) .and. mxIsNumeric(order_moment_mx)) then
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call mexErrMsgTxt("7th argument (order_moment) should be a numeric scalar")
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end if
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if (.not. (mxIsScalar(nburn_mx)) .and. mxIsNumeric(nburn_mx)) then
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call mexErrMsgTxt("8th argument (nburn) should be a numeric scalar")
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end if
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if (.not. (mxIsDouble(yhat_start_mx) .and. (mxGetM(yhat_start_mx) == 1 .or. mxGetN(yhat_start_mx) == 1))) then
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call mexErrMsgTxt("9th argument (yhat_start) should be a real vector")
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end if
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if (.not. (mxIsDouble(shocks_mx))) then
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call mexErrMsgTxt("10th argument (shocks) should be a real matrix")
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end if
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if (.not. (mxIsDouble(ysteady_mx) .and. (mxGetM(ysteady_mx) == 1 .or. mxGetN(ysteady_mx) == 1))) then
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call mexErrMsgTxt("11th argument (ysteady) should be a real vector")
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end if
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if (.not. mxIsStruct(dr_mx)) then
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call mexErrMsgTxt("12th argument (dr) should be a struct")
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end if
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! Converting inputs in Fortran format
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order = int(mxGetScalar(order_mx))
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nstatic = int(mxGetScalar(nstatic_mx))
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npred = int(mxGetScalar(npred_mx))
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nboth = int(mxGetScalar(nboth_mx))
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nfwrd = int(mxGetScalar(nfwrd_mx))
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exo_nbr = int(mxGetScalar(nexog_mx))
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endo_nbr = nstatic+npred+nboth+nfwrd
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nys = npred+nboth
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nvar = nys+exo_nbr
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nburn = int(mxGetScalar(nburn_mx))
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order_moment = int(mxGetScalar(order_moment_mx))
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if (endo_nbr /= int(mxGetM(yhat_start_mx))) then
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call mexErrMsgTxt("yhat_start should have nstat+npred+nboth+nforw rows")
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end if
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yhat_start => mxGetPr(yhat_start_mx)
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if (exo_nbr /= int(mxGetM(shocks_mx))) then
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call mexErrMsgTxt("shocks should have nexog rows")
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end if
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nper = int(mxGetN(shocks_mx))
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allocate(shocks(exo_nbr,nper))
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shocks = reshape(mxGetPr(shocks_mx),[exo_nbr,nper])
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if (.not. (int(mxGetM(ysteady_mx)) == endo_nbr)) then
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call mexErrMsgTxt("ysteady should have nstat+npred+nboth+nforw rows")
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end if
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ysteady => mxGetPr(ysteady_mx)
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allocate(h(0:order), fdr(0:order), udr(0:order))
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do i = 0, order
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write (fieldname, '(a2, i1)') "g_", i
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tmp = mxGetField(dr_mx, 1_mwIndex, trim(fieldname))
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if (.not. (c_associated(tmp) .and. mxIsDouble(tmp))) then
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call mexErrMsgTxt(trim(fieldname)//" is not allocated in dr")
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end if
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m = int(mxGetM(tmp))
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n = int(mxGetN(tmp))
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allocate(fdr(i)%g(m,n), udr(i)%g(endo_nbr, nvar**i), h(i)%c(endo_nbr, nvar**i))
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fdr(i)%g(1:m,1:n) = reshape(mxGetPr(tmp), [m,n])
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end do
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udr(0)%g = fdr(0)%g
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udr(1)%g = fdr(1)%g
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if (order > 1) then
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! Compute the useful binomial coefficients from Pascal's triangle
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p = pascal_triangle(nvar+order-1)
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block
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type(uf_matching), dimension(2:order) :: matching
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! Pinpointing the corresponding offsets between folded and unfolded tensors
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do d=2,order
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allocate(matching(d)%folded(nvar**d))
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call fill_folded_indices(matching(d)%folded, nvar, d, p)
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udr(d)%g = fdr(d)%g(:,matching(d)%folded)
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end do
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end block
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end if
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allocate(dyu(nvar), mean(endo_nbr), sim(endo_nbr,nper))
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! Getting the predetermined part of the endogenous variable vector
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dyu(1:nys) = yhat_start(nstatic+1:nstatic+nys)
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dyu(nys+1:) = shocks(:,1)
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! Using the Horner algorithm to evaluate the decision rule at the chosen dyu
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call eval(h, dyu, udr, endo_nbr, nvar, order)
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sim(:,1) = h(0)%c(:,1) + ysteady
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mean = 0.
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! Carrying out the simulation
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do t=2,nper
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dyu(1:nys) = h(0)%c(nstatic+1:nstatic+nys,1)
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dyu(nys+1:) = shocks(:,t)
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call eval(h, dyu, udr, endo_nbr, nvar, order)
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sim(:,t) = h(0)%c(:,1) + ysteady
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if (t > nburn) then
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mean = mean + sim(:,t)**order_moment
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end if
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end do
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! scaling the mean with the number of non-burn-in periods
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mean = mean/(nper-nburn)
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! Generating output
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plhs(1) = mxCreateDoubleMatrix(int(endo_nbr, mwSize), 1_mwSize, mxREAL)
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mxGetPr(plhs(1)) = mean
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plhs(2) = mxCreateDoubleMatrix(int(endo_nbr, mwSize), int(nper, mwSize), mxREAL)
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mxGetPr(plhs(2)) = reshape(sim, [size(sim)])
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end subroutine mexFunction
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