Quick vs Benchmark vs More Precise (Save + Borr Dynamic Programming Problem)

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Testing the ff_abz_vf_vecsv program for solving the savings and borrowing dynamic programming problem.

Computational speed is determined by the number of asset and shock grid points. Here we run the model with quick, benchmark and more precise simulations with increasing grid points for shocks and asset.

  1. quick: fast run
  2. benchmark: default as set in ffs_abz_set_default_param
  3. more precise: increase grid count for shocks and asset

@seealso

Contents

Quick Solution

it_param_set = 4;
[param_map, support_map] = ffs_abz_set_default_param(it_param_set);

% Simulation Accuracy
param_map('it_a_n') = 100;
param_map('it_z_n') = 11;

% Display Parameters
support_map('bl_display') = false;
support_map('bl_display_final') = false;
support_map('bl_time') = true;
support_map('bl_profile') = false;

% Call Program
ff_abz_vf_vecsv(param_map, support_map);

% Snap
snapnow;
close all;
Elapsed time is 0.134250 seconds.

Benchmark Solution

it_param_set = 4;
[param_map, support_map] = ffs_abz_set_default_param(it_param_set);

% Simulation Accuracy
param_map('it_a_n') = 750;
param_map('it_z_n') = 15;

% Display Parameters
support_map('bl_display') = false;
support_map('bl_display_final') = false;
support_map('bl_time') = true;
support_map('bl_profile') = false;

% Call Program
ff_abz_vf_vecsv(param_map, support_map);

% Snap
snapnow;
close all;
Elapsed time is 2.674076 seconds.

More Precise Solution

it_param_set = 4;
[param_map, support_map] = ffs_abz_set_default_param(it_param_set);

% Simulation Accuracy
param_map('it_a_n') = 2250;
param_map('it_z_n') = 27;

% Display Parameters
support_map('bl_display') = false;
support_map('bl_display_final') = false;
support_map('bl_time') = true;
support_map('bl_profile') = false;

% Call Program
ff_abz_vf_vecsv(param_map, support_map);

% Snap
snapnow;
close all;
clear all;
Elapsed time is 34.056837 seconds.