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neoclassical_Gaussian.mod
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neoclassical_Gaussian.mod
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%/////////////////////////////////////////////////////////////
%//// Model: Neolassical growth model ////
%//// Author: Willi Mutschler ////
%//// Email: willi@mutschler.eu ////
%//// Version: August 26, 2016 ////
%/////////////////////////////////////////////////////////////
%----------------------------------------------------------------
% 0. Specify options: User Settings (For other settings and defaults see updateOptions.m
%----------------------------------------------------------------
% Order of approximation
@#define orderApp = 3
% Which distribution: 0:for Gaussian, 1:for Student_t
@#define distrib = 0
% Do GMM estimation: 0 no or 1 yes
@#define GMMestimation = 0
@#if distrib == 1
opt.distrib = 'Student_t'; %multivariate student-t distribution ('Gaussian' is default)
@#endif
@#if GMMestimation == 1
opt.numSim = 250; % Number of observations of simulated data
opt.autoLagsIdx = [1]
opt.HOSThirdOrder = 1; % Use third-order statistics, 0: do not include or 1: include
opt.HOSFourthOrder = 0; % User fourth-order statistics, 0: do not include or 1: include
opt.AUXTEST = 0; % AUXILIARY TEST IF EMPIRICAL MOMENTS FIT TO THEORETICAL MOMENTS
opt.seed_nr = 10;
opt.transpar = 0;
@#else
opt.HOSThirdOrder = 1; % Use third-order statistics, 0: do not include or 1: include
opt.HOSFourthOrder = 1; % User fourth-order statistics, 0: do not include or 1: include
opt.MCruns = 1000; % Monte Carlo Runs for comparison
opt.numSim = 10000; % Number of observations of simulated data
opt.burnin = 1000; % Initial burnin periods, will be discarded from simulation
opt.antithetic = 1; % 1: Use antithetic shocks and quadratic resampling to reduce Monte Carlo variation
opt.simdata = 1; % compare theoretical statistics with simulated data, 0: no or 1: yes
@#endif