1 2007 (Bush 2008 Stimulus) Full States EV and EC of Two Checks
This is the example vignette for function: snw_evuvw19_jaeemk_foc from the PrjOptiSNW Package. 2008 integrated over VU and VW, given optimal savings choices, unemployment shocks and various expectations.
Given 2008 policy and value functions (given expectation of 2009 crisis unemployment shocks), call SNW_V08_JAEEMK to solve for value and consumption given stimulus checks. And then integrate over 08 JAEEMK states given 07 JAEEMK states (age, endogenous savings, education, income shock, marital status, kids count). The stimulus will be provisioned based on 07 JAEEMK states. Note that snw_evuvw19_jaeemk does not solve the 07/08 problem.
Despite the name, this function supports solving the 2019 looking into 2020 as well as the 2007 looking into 2008 problems. The idea is that the planner only has information from 2019 and from 2007, and must allocate using those information. Stimulus, however, is given in 2020 and in 2008. So the planner needs to consider expected values in consumption or welfare given the transition probabilities of states in 2007 to 2008 and in 2019 to 2020. The snw_evuvw19_jmky file then aggregates the full state-space results to just JMKY state-space, which is the extend of information available to the planner.
1.1 Test SNW_EVUVW19_JAEEMK Defaults for 2019
Call the function with defaults. First, set up some parameters.
clear all;
% Solution types
st_biden_or_trump = 'bushchck';
% Solve the VFI Problem and get Value Function
mp_controls = snw_mp_control('default_test');
% Solve for Unemployment Values
mp_controls('bl_print_a4chk') = false;
mp_controls('bl_print_a4chk_verbose') = false;
mp_controls('bl_print_vfi') = false;
mp_controls('bl_print_vfi_verbose') = false;
mp_controls('bl_print_ds') = false;
mp_controls('bl_print_ds_verbose') = false;
mp_controls('bl_print_precompute') = false;
mp_controls('bl_print_evuvw20_jaeemk') = false;
mp_controls('bl_print_evuvw20_jaeemk_verbose') = false;
mp_controls('bl_print_v08p08_jaeemk') = false;
mp_controls('bl_print_v08p08_jaeemk_verbose') = false;
mp_controls('bl_print_v08_jaeemk') = true;
mp_controls('bl_print_v08_jaeemk_verbose') = false;Second, run initializing functions.
% 1. generate MP_PARAMS specific to 2008 stimulus
% Use non-default values for Bush Stimulus
mp_more_inputs = containers.Map('KeyType','char', 'ValueType','any');
mp_more_inputs('fl_ss_non_college') = 0.225;
mp_more_inputs('fl_ss_college') = 0.271;
fl_p50_hh_income_07 = 54831;
mp_more_inputs('fl_scaleconvertor') = fl_p50_hh_income_07;
% st_param_group = 'default_small';
st_param_group = 'default_dense';
st_param_group = 'default_docdense';
mp_params = snw_mp_param(st_param_group, false, 'tauchen', false, 8, 8, mp_more_inputs);
mp_params('st_biden_or_trump') = st_biden_or_trump;
mp_params('beta') = 0.95;
% 2. Solve value steady state (2009 employed)
[V_ss, ap_ss, cons_ss, mp_valpol_more_ss] = snw_vfi_main_bisec_vec(mp_params, mp_controls);
Completed SNW_VFI_MAIN_BISEC_VEC;SNW_MP_PARAM=default_docdense;SNW_MP_CONTROL=default_test;time=495.65
V_emp_2009 = V_ss;
inc_ss = mp_valpol_more_ss('inc_VFI');
spouse_inc_ss = mp_valpol_more_ss('spouse_inc_VFI');
total_inc_ss = inc_ss + spouse_inc_ss;
% 3. Solve value unemployed 2009
mp_params('xi') = 0.532;
mp_params('b') = 0.37992;
mp_params('a2_covidyr') = mp_params('a2_greatrecession_2009');
mp_params('TR') = 100/fl_p50_hh_income_07;
[V_unemp_2009] = snw_vfi_main_bisec_vec(mp_params, mp_controls, V_ss);
Completed SNW_VFI_MAIN_BISEC_VEC 1 Period Unemp Shock;SNW_MP_PARAM=default_docdense;SNW_MP_CONTROL=default_test;time=304.5637
% 4. Value and Optimal choice in 2008
[V_2008, ap_2008, cons_2008, ev_empshk_2009] = ...
snw_v08p08_jaeemk(mp_params, mp_controls, V_emp_2009, V_unemp_2009);
Completed SNW_VFI_MAIN_BISEC_VEC 1 Period Unemp Shock;SNW_MP_PARAM=default_docdense;SNW_MP_CONTROL=default_test;time=491.5904
Completed SNW_V08P08_JAEEMK;SNW_MP_PARAM=default_docdense;SNW_MP_CONTROL=default_test;time=497.3876
% 5. matrixes to pre-compute
% Only using the SNW_A4CHK_WRK_BISEC_VEC function, no unemployment
% related matrixes needed Also don't need REF_EARN_WAGEIND_GRID,
% become unemployment not conditional on wage in 2009.
cl_st_precompute_list = {'a', ...
'inc', 'inc_unemp', 'spouse_inc',...
'ar_z_ctr_amz'};
% Shared: Steady-State distribution
[Phi_true] = snw_ds_main(mp_params, mp_controls, ap_ss, cons_ss, mp_valpol_more_ss);
Completed SNW_DS_MAIN;SNW_MP_PARAM=default_docdense;SNW_MP_CONTROL=default_test;time=1775.4241
% Shared: precompute, get Matrixes
% note, the mp_params inputs are based on unemployed in 2020 (MIT) or unemployed in 2009 (Expected)
% note, however, for the 2008/9 problem, only will use inc, inc_unemp, spouse_inc
mp_controls('bl_print_precompute_verbose') = false;
[mp_precompute_res] = snw_hh_precompute(mp_params, mp_controls, cl_st_precompute_list, ap_ss, Phi_true);
Wage quintile cutoffs=0.4645 0.71528 1.0335 1.5632
Completed SNW_HH_PRECOMPUTE;SNW_MP_PARAM=default_docdense;SNW_MP_CONTROL=default_test;time cost=254.74051.2 Solve for 2019 Evuvw With 0 and 2 Checks
Solve for 0 and 2 checks, by finding the increase to asset state-space that is equivalent to the check increase, so that the problem can be solved without increasing the state-space.
% Call Function
welf_checks = 0;
[ev07_jaeemk_check0, ec07_jaeemk_check0, ev08_jaeemk_check0, ec08_jaeemk_check0] = snw_evuvw19_jaeemk_foc(...
welf_checks, mp_params, mp_controls, ...
ap_ss, V_2008, cons_2008, mp_precompute_res);
Solve for V_2008_check for 0 stimulus checks
Completed SNW_A4CHK_WRK_BISEC_VEC;SNW_MP_PARAM=bushchck;welf_checks=0;TR=0.0018238;SNW_MP_PARAM=default_docdense;SNW_MP_CONTROL=default_test;time cost=69.7671
Completed SNW_V08_JAEEMK;SNW_MP_PARAM=default_docdense;SNW_MP_CONTROL=default_test;timeEUEC=6.99e-05
Completed SNW_EVUVW19_JAEEMK_FOC;st_biden_or_trump=bushchck;SNW_MP_PARAM=default_docdense;SNW_MP_CONTROL=default_test;time=12.8037
----------------------------------------
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CONTAINER NAME: mp_outcomes ND Array (Matrix etc)
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
i idx ndim numel rowN colN sum mean std coefvari min max
_ ___ ____ __________ ____ _________ ___________ _______ ______ ________ ________ __________
ec07_jaeemk 1 1 6 4.3173e+07 82 5.265e+05 1.9685e+08 4.5597 5.3244 1.1677 0.039543 64.534
ec08_jaeemk 2 2 6 4.37e+07 83 5.265e+05 2.3277e+08 5.3267 8.4419 1.5848 0.036202 141.62
ev07_jaeemk 3 3 6 4.3173e+07 82 5.265e+05 -6.4618e+08 -14.967 21.06 -1.4071 -470.57 -0.015969
ev08_jaeemk 4 4 6 4.37e+07 83 5.265e+05 -6.6426e+08 -15.201 21.85 -1.4375 -508.1 -0.0071773
xxx TABLE:ec07_jaeemk xxxxxxxxxxxxxxxxxx
c1 c2 c3 c4 c5 c526496 c526497 c526498 c526499 c526500
________ ________ ________ ________ ________ _______ _______ _______ _______ _______
r1 0.039543 0.039543 0.039978 0.042271 0.04854 12.009 12.281 12.561 12.849 13.157
r2 0.039889 0.039889 0.040323 0.043305 0.049735 12.251 12.524 12.806 13.095 13.402
r3 0.041432 0.041432 0.041608 0.043991 0.050734 12.485 12.759 13.042 13.331 13.637
r4 0.042935 0.042935 0.043023 0.045459 0.052199 12.742 13.017 13.3 13.588 13.891
r5 0.044395 0.044395 0.044399 0.046895 0.053615 12.99 13.266 13.548 13.834 14.134
r78 0.2016 0.2016 0.2016 0.2016 0.20214 27.775 28.774 29.785 30.965 32.412
r79 0.2016 0.2016 0.2016 0.2016 0.2016 30.43 31.663 32.736 33.958 35.517
r80 0.2016 0.2016 0.2016 0.2016 0.2016 33.68 35.501 37.368 38.956 40.192
r81 0.2016 0.2016 0.2016 0.2016 0.2016 40.118 41.397 43.175 45.605 48.459
r82 0.2016 0.2016 0.2016 0.2016 0.2016 52.1 55.541 58.464 60.094 62.875
xxx TABLE:ec08_jaeemk xxxxxxxxxxxxxxxxxx
c1 c2 c3 c4 c5 c526496 c526497 c526498 c526499 c526500
________ ________ ________ ________ ________ _______ _______ _______ _______ _______
r1 0.036218 0.036736 0.038184 0.042735 0.048545 12.256 12.541 12.835 13.136 13.136
r2 0.036271 0.036736 0.038385 0.043404 0.049852 12.491 12.778 13.072 13.374 13.374
r3 0.036717 0.037251 0.039845 0.044907 0.051515 12.744 13.032 13.327 13.628 13.628
r4 0.038144 0.038678 0.041269 0.046371 0.053128 12.989 13.277 13.573 13.872 13.872
r5 0.039534 0.040068 0.042653 0.047793 0.054687 13.224 13.513 13.809 14.105 14.105
r79 0.2016 0.20214 0.20586 0.21598 0.23568 35.82 37.367 39.414 41.705 44.029
r80 0.2016 0.20214 0.20586 0.21598 0.23568 40.755 42.955 45.289 47.95 50.773
r81 0.2016 0.20214 0.20586 0.21598 0.23568 48.912 52.041 55.022 57.919 60.242
r82 0.2016 0.20214 0.20586 0.21598 0.23568 66.719 69.201 72.373 77.005 80.728
r83 0.2016 0.20214 0.20586 0.21598 0.23568 116.83 122.65 128.67 134.89 141.3
xxx TABLE:ev07_jaeemk xxxxxxxxxxxxxxxxxx
c1 c2 c3 c4 c5 c526496 c526497 c526498 c526499 c526500
_______ _______ _______ _______ _______ _________ _________ _________ _________ _________
r1 -282.59 -282.59 -282.23 -278.38 -270.8 -4.3833 -4.2888 -4.1954 -4.1032 -4.0073
r2 -272.49 -272.49 -272.13 -268.93 -261.76 -4.2754 -4.1844 -4.0945 -4.0056 -3.9131
r3 -262.36 -262.36 -262.23 -259.89 -253.05 -4.1651 -4.0777 -3.9913 -3.9057 -3.8166
r4 -253.22 -253.22 -253.16 -250.92 -244.6 -4.0512 -3.9675 -3.8846 -3.8025 -3.7165
r5 -244.95 -244.95 -244.95 -242.81 -236.93 -3.9436 -3.8633 -3.7837 -3.7047 -3.6215
r78 -13.362 -13.362 -13.362 -13.362 -13.349 -0.27313 -0.26104 -0.24971 -0.2389 -0.22855
r79 -12.032 -12.032 -12.032 -12.032 -12.032 -0.21855 -0.20781 -0.19875 -0.19057 -0.18272
r80 -10.388 -10.388 -10.388 -10.388 -10.388 -0.16126 -0.15407 -0.14734 -0.14134 -0.13574
r81 -8.1801 -8.1801 -8.1801 -8.1801 -8.1801 -0.10114 -0.097396 -0.093438 -0.089426 -0.084913
r82 -4.9651 -4.9651 -4.9651 -4.9651 -4.9651 -0.044201 -0.041462 -0.039412 -0.038348 -0.036626
xxx TABLE:ev08_jaeemk xxxxxxxxxxxxxxxxxx
c1 c2 c3 c4 c5 c526496 c526497 c526498 c526499 c526500
_______ _______ _______ _______ _______ _________ _________ _________ _________ _________
r1 -295.66 -295.26 -292.66 -286.62 -277.22 -4.3615 -4.2673 -4.1741 -4.0822 -3.9911
r2 -286.11 -285.71 -283.12 -277.16 -268.03 -4.2548 -4.1641 -4.0744 -3.9858 -3.8979
r3 -276.49 -276.09 -273.59 -267.84 -259.11 -4.1461 -4.0589 -3.9727 -3.8874 -3.8028
r4 -266.77 -266.41 -264.08 -258.7 -250.49 -4.0342 -3.9507 -3.868 -3.7862 -3.7045
r5 -257.99 -257.65 -255.48 -250.43 -242.69 -3.9287 -3.8485 -3.769 -3.6903 -3.6114
r79 -13.356 -13.343 -13.253 -13.025 -12.638 -0.22088 -0.21055 -0.20083 -0.1917 -0.18313
r80 -12.025 -12.012 -11.923 -11.695 -11.308 -0.16977 -0.1618 -0.15428 -0.14721 -0.14056
r81 -10.382 -10.369 -10.28 -10.052 -9.6651 -0.11711 -0.11162 -0.10645 -0.10156 -0.096943
r82 -8.1742 -8.1611 -8.0716 -7.844 -7.457 -0.065329 -0.062239 -0.059357 -0.056632 -0.054053
r83 -4.9602 -4.9471 -4.8576 -4.6301 -4.2431 -0.020966 -0.019971 -0.019037 -0.01816 -0.017335
% Call Function
welf_checks = 2;
[ev07_jaeemk_check2, ec07_jaeemk_check2, ev08_jaeemk_check2, ec08_jaeemk_check2] = snw_evuvw19_jaeemk_foc(...
welf_checks, mp_params, mp_controls, ...
ap_ss, V_2008, cons_2008, mp_precompute_res);
Solve for V_2008_check for 2 stimulus checks
Completed SNW_A4CHK_WRK_BISEC_VEC;SNW_MP_PARAM=bushchck;welf_checks=2;TR=0.0018238;SNW_MP_PARAM=default_docdense;SNW_MP_CONTROL=default_test;time cost=70.7648
Completed SNW_V08_JAEEMK;SNW_MP_PARAM=default_docdense;SNW_MP_CONTROL=default_test;timeEUEC=2.82e-05
Completed SNW_EVUVW19_JAEEMK_FOC;st_biden_or_trump=bushchck;SNW_MP_PARAM=default_docdense;SNW_MP_CONTROL=default_test;time=12.688
----------------------------------------
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CONTAINER NAME: mp_outcomes ND Array (Matrix etc)
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
i idx ndim numel rowN colN sum mean std coefvari min max
_ ___ ____ __________ ____ _________ ___________ _______ ______ ________ ________ __________
ec07_jaeemk 1 1 6 4.3173e+07 82 5.265e+05 1.9688e+08 4.5603 5.3245 1.1676 0.040827 64.538
ec08_jaeemk 2 2 6 4.37e+07 83 5.265e+05 2.328e+08 5.3273 8.442 1.5847 0.037917 141.63
ev07_jaeemk 3 3 6 4.3173e+07 82 5.265e+05 -6.4561e+08 -14.954 21.011 -1.4051 -465.69 -0.015968
ev08_jaeemk 4 4 6 4.37e+07 83 5.265e+05 -6.6365e+08 -15.187 21.798 -1.4353 -502.51 -0.0071771
xxx TABLE:ec07_jaeemk xxxxxxxxxxxxxxxxxx
c1 c2 c3 c4 c5 c526496 c526497 c526498 c526499 c526500
________ ________ ________ ________ ________ _______ _______ _______ _______ _______
r1 0.040827 0.040827 0.040972 0.04389 0.049551 12.009 12.281 12.561 12.849 13.157
r2 0.042096 0.042096 0.0424 0.045024 0.050802 12.251 12.524 12.806 13.095 13.402
r3 0.043624 0.043624 0.043746 0.045821 0.051869 12.485 12.76 13.042 13.331 13.637
r4 0.04511 0.04511 0.04517 0.047304 0.053361 12.742 13.017 13.3 13.588 13.891
r5 0.04655 0.04655 0.046553 0.048751 0.054802 12.99 13.266 13.549 13.834 14.134
r78 0.20525 0.20525 0.20525 0.20525 0.20579 27.775 28.775 29.786 30.966 32.413
r79 0.20525 0.20525 0.20525 0.20525 0.20525 30.431 31.664 32.737 33.96 35.519
r80 0.20525 0.20525 0.20525 0.20525 0.20525 33.681 35.503 37.369 38.957 40.193
r81 0.20525 0.20525 0.20525 0.20525 0.20525 40.119 41.4 43.178 45.607 48.46
r82 0.20525 0.20525 0.20525 0.20525 0.20525 52.103 55.545 58.468 60.098 62.879
xxx TABLE:ec08_jaeemk xxxxxxxxxxxxxxxxxx
c1 c2 c3 c4 c5 c526496 c526497 c526498 c526499 c526500
________ ________ ________ ________ ________ _______ _______ _______ _______ _______
r1 0.037941 0.038148 0.039819 0.043807 0.049244 12.256 12.541 12.835 13.136 13.136
r2 0.038108 0.038344 0.040188 0.044594 0.050571 12.492 12.778 13.073 13.374 13.374
r3 0.03941 0.039781 0.041664 0.046126 0.052244 12.745 13.032 13.327 13.628 13.628
r4 0.040834 0.041205 0.043102 0.047618 0.053867 12.989 13.278 13.573 13.872 13.872
r5 0.04222 0.042589 0.0445 0.049065 0.055435 13.224 13.513 13.809 14.105 14.105
r79 0.20525 0.20579 0.20951 0.21963 0.23776 35.821 37.368 39.415 41.707 44.03
r80 0.20525 0.20579 0.20951 0.21963 0.23776 40.756 42.957 45.29 47.952 50.774
r81 0.20525 0.20579 0.20951 0.21963 0.2378 48.914 52.043 55.024 57.92 60.244
r82 0.20525 0.20579 0.20951 0.21963 0.23814 66.72 69.203 72.375 77.007 80.731
r83 0.20525 0.20579 0.20951 0.21963 0.23933 116.84 122.66 128.68 134.89 141.31
xxx TABLE:ev07_jaeemk xxxxxxxxxxxxxxxxxx
c1 c2 c3 c4 c5 c526496 c526497 c526498 c526499 c526500
_______ _______ _______ _______ _______ _________ _________ _________ _________ _________
r1 -280.23 -280.23 -279.88 -276.5 -269.35 -4.3833 -4.2887 -4.1954 -4.1031 -4.0072
r2 -270.21 -270.21 -269.89 -267.08 -260.35 -4.2753 -4.1844 -4.0944 -4.0055 -3.913
r3 -260.26 -260.26 -260.13 -258.1 -251.71 -4.165 -4.0777 -3.9912 -3.9057 -3.8166
r4 -251.26 -251.26 -251.2 -249.25 -243.33 -4.0511 -3.9674 -3.8846 -3.8025 -3.7165
r5 -243.12 -243.12 -243.12 -241.24 -235.73 -3.9436 -3.8633 -3.7837 -3.7047 -3.6215
r78 -13.274 -13.274 -13.274 -13.274 -13.262 -0.27312 -0.26103 -0.2497 -0.23889 -0.22854
r79 -11.944 -11.944 -11.944 -11.944 -11.944 -0.21854 -0.2078 -0.19875 -0.19056 -0.18272
r80 -10.3 -10.3 -10.3 -10.3 -10.3 -0.16125 -0.15406 -0.14733 -0.14134 -0.13574
r81 -8.0921 -8.0921 -8.0921 -8.0921 -8.0921 -0.10113 -0.097391 -0.093433 -0.089423 -0.084909
r82 -4.8771 -4.8771 -4.8771 -4.8771 -4.8771 -0.044198 -0.04146 -0.03941 -0.038346 -0.036624
xxx TABLE:ev08_jaeemk xxxxxxxxxxxxxxxxxx
c1 c2 c3 c4 c5 c526496 c526497 c526498 c526499 c526500
_______ _______ _______ _______ _______ _________ _________ _________ _________ _________
r1 -293.09 -292.72 -290.49 -284.88 -275.86 -4.3615 -4.2672 -4.1741 -4.0821 -3.9911
r2 -283.55 -283.18 -280.98 -275.47 -266.73 -4.2548 -4.164 -4.0743 -3.9857 -3.8979
r3 -274.01 -273.65 -271.52 -266.23 -257.88 -4.146 -4.0589 -3.9726 -3.8874 -3.8028
r4 -264.47 -264.13 -262.14 -257.19 -249.33 -4.0341 -3.9506 -3.8679 -3.7861 -3.7045
r5 -255.84 -255.53 -253.66 -249 -241.59 -3.9286 -3.8484 -3.769 -3.6903 -3.6113
r79 -13.268 -13.255 -13.171 -12.954 -12.578 -0.22088 -0.21054 -0.20082 -0.1917 -0.18312
r80 -11.937 -11.924 -11.841 -11.623 -11.248 -0.16976 -0.16179 -0.15428 -0.1472 -0.14055
r81 -10.294 -10.281 -10.198 -9.9804 -9.6057 -0.11711 -0.11162 -0.10644 -0.10156 -0.096941
r82 -8.0862 -8.0735 -7.9895 -7.7724 -7.3981 -0.065327 -0.062237 -0.059355 -0.056631 -0.054052
r83 -4.8723 -4.8595 -4.7755 -4.5584 -4.1854 -0.020965 -0.01997 -0.019036 -0.018159 -0.017335Differences between Checks in Expected Value and Expected Consumption
mn_V_U_gain_check_07 = ev07_jaeemk_check2 - ev07_jaeemk_check0;
mn_MPC_U_gain_share_check_07 = (ec07_jaeemk_check2 - ec07_jaeemk_check0)./(welf_checks*mp_params('TR'));1.3 Param Results Define Frames
Define the matrix dimensions names and dimension vector values. Policy and Value Functions share the same ND dimensional structure.
% Grids:
age_grid = 18:99;
agrid = mp_params('agrid')';
eta_H_grid = mp_params('eta_H_grid')';
eta_S_grid = mp_params('eta_S_grid')';
ar_st_eta_HS_grid = string(cellstr([num2str(eta_H_grid', 'hz=%3.2f;'), num2str(eta_S_grid', 'wz=%3.2f')]));
edu_grid = [0,1];
marry_grid = [0,1];
kids_grid = (1:1:mp_params('n_kidsgrid'))';
% NaN(n_jgrid,n_agrid,n_etagrid,n_educgrid,n_marriedgrid,n_kidsgrid);
cl_mp_datasetdesc = {};
cl_mp_datasetdesc{1} = containers.Map({'name', 'labval'}, {'age', age_grid});
cl_mp_datasetdesc{2} = containers.Map({'name', 'labval'}, {'savings', agrid});
cl_mp_datasetdesc{3} = containers.Map({'name', 'labval'}, {'eta', 1:length(eta_H_grid)});
cl_mp_datasetdesc{4} = containers.Map({'name', 'labval'}, {'edu', edu_grid});
cl_mp_datasetdesc{5} = containers.Map({'name', 'labval'}, {'marry', marry_grid});
cl_mp_datasetdesc{6} = containers.Map({'name', 'labval'}, {'kids', kids_grid});1.4 Analyze Difference in V and C with Check
The difference between V and V with Check, marginal utility gain given the check.
% Generate some Data
mp_support_graph = containers.Map('KeyType', 'char', 'ValueType', 'any');
mp_support_graph('cl_st_xtitle') = {'Savings States, a'};
mp_support_graph('st_legend_loc') = 'eastoutside';
mp_support_graph('bl_graph_logy') = true; % do not log
mp_support_graph('it_legend_select') = 21; % how many shock legends to show
mp_support_graph('cl_colors') = 'jet';MEAN(MN_V_GAIN_CHECK(A,Z))
Tabulate value and policies along savings and shocks:
% Set
ar_permute = [1,4,5,6,3,2];
% Value Function
st_title = ['MEAN(MN_V_U_GAIN_CHECK(A,Z)), welf_checks=' num2str(welf_checks) ', TR=' num2str(mp_params('TR'))];
tb_az_v = ff_summ_nd_array(st_title, mn_V_U_gain_check_07, true, ["mean"], 4, 1, cl_mp_datasetdesc, ar_permute);
xxx MEAN(MN_V_U_GAIN_CHECK(A,Z)), welf_checks=2, TR=0.0018238 xxxxxxxxxxxxxxxxxxxxxxxxxxx
group savings mean_eta_1 mean_eta_2 mean_eta_3 mean_eta_4 mean_eta_5 mean_eta_6 mean_eta_7 mean_eta_8 mean_eta_9 mean_eta_10 mean_eta_11 mean_eta_12 mean_eta_13 mean_eta_14 mean_eta_15 mean_eta_16 mean_eta_17 mean_eta_18 mean_eta_19 mean_eta_20 mean_eta_21 mean_eta_22 mean_eta_23 mean_eta_24 mean_eta_25 mean_eta_26 mean_eta_27 mean_eta_28 mean_eta_29 mean_eta_30 mean_eta_31 mean_eta_32 mean_eta_33 mean_eta_34 mean_eta_35 mean_eta_36 mean_eta_37 mean_eta_38 mean_eta_39 mean_eta_40 mean_eta_41 mean_eta_42 mean_eta_43 mean_eta_44 mean_eta_45 mean_eta_46 mean_eta_47 mean_eta_48 mean_eta_49 mean_eta_50 mean_eta_51 mean_eta_52 mean_eta_53 mean_eta_54 mean_eta_55 mean_eta_56 mean_eta_57 mean_eta_58 mean_eta_59 mean_eta_60 mean_eta_61 mean_eta_62 mean_eta_63 mean_eta_64 mean_eta_65 mean_eta_66 mean_eta_67 mean_eta_68 mean_eta_69 mean_eta_70 mean_eta_71 mean_eta_72 mean_eta_73 mean_eta_74 mean_eta_75 mean_eta_76 mean_eta_77 mean_eta_78 mean_eta_79 mean_eta_80 mean_eta_81 mean_eta_82 mean_eta_83 mean_eta_84 mean_eta_85 mean_eta_86 mean_eta_87 mean_eta_88 mean_eta_89 mean_eta_90 mean_eta_91 mean_eta_92 mean_eta_93 mean_eta_94 mean_eta_95 mean_eta_96 mean_eta_97 mean_eta_98 mean_eta_99 mean_eta_100 mean_eta_101 mean_eta_102 mean_eta_103 mean_eta_104 mean_eta_105 mean_eta_106 mean_eta_107 mean_eta_108 mean_eta_109 mean_eta_110 mean_eta_111 mean_eta_112 mean_eta_113 mean_eta_114 mean_eta_115 mean_eta_116 mean_eta_117 mean_eta_118 mean_eta_119 mean_eta_120 mean_eta_121 mean_eta_122 mean_eta_123 mean_eta_124 mean_eta_125 mean_eta_126 mean_eta_127 mean_eta_128 mean_eta_129 mean_eta_130 mean_eta_131 mean_eta_132 mean_eta_133 mean_eta_134 mean_eta_135 mean_eta_136 mean_eta_137 mean_eta_138 mean_eta_139 mean_eta_140 mean_eta_141 mean_eta_142 mean_eta_143 mean_eta_144 mean_eta_145 mean_eta_146 mean_eta_147 mean_eta_148 mean_eta_149 mean_eta_150 mean_eta_151 mean_eta_152 mean_eta_153 mean_eta_154 mean_eta_155 mean_eta_156 mean_eta_157 mean_eta_158 mean_eta_159 mean_eta_160 mean_eta_161 mean_eta_162 mean_eta_163 mean_eta_164 mean_eta_165 mean_eta_166 mean_eta_167 mean_eta_168 mean_eta_169 mean_eta_170 mean_eta_171 mean_eta_172 mean_eta_173 mean_eta_174 mean_eta_175 mean_eta_176 mean_eta_177 mean_eta_178 mean_eta_179 mean_eta_180 mean_eta_181 mean_eta_182 mean_eta_183 mean_eta_184 mean_eta_185 mean_eta_186 mean_eta_187 mean_eta_188 mean_eta_189 mean_eta_190 mean_eta_191 mean_eta_192 mean_eta_193 mean_eta_194 mean_eta_195 mean_eta_196 mean_eta_197 mean_eta_198 mean_eta_199 mean_eta_200 mean_eta_201 mean_eta_202 mean_eta_203 mean_eta_204 mean_eta_205 mean_eta_206 mean_eta_207 mean_eta_208 mean_eta_209 mean_eta_210 mean_eta_211 mean_eta_212 mean_eta_213 mean_eta_214 mean_eta_215 mean_eta_216 mean_eta_217 mean_eta_218 mean_eta_219 mean_eta_220 mean_eta_221 mean_eta_222 mean_eta_223 mean_eta_224 mean_eta_225 mean_eta_226 mean_eta_227 mean_eta_228 mean_eta_229 mean_eta_230 mean_eta_231 mean_eta_232 mean_eta_233 mean_eta_234 mean_eta_235 mean_eta_236 mean_eta_237 mean_eta_238 mean_eta_239 mean_eta_240 mean_eta_241 mean_eta_242 mean_eta_243 mean_eta_244 mean_eta_245 mean_eta_246 mean_eta_247 mean_eta_248 mean_eta_249 mean_eta_250 mean_eta_251 mean_eta_252 mean_eta_253 mean_eta_254 mean_eta_255 mean_eta_256 mean_eta_257 mean_eta_258 mean_eta_259 mean_eta_260 mean_eta_261 mean_eta_262 mean_eta_263 mean_eta_264 mean_eta_265 mean_eta_266 mean_eta_267 mean_eta_268 mean_eta_269 mean_eta_270 mean_eta_271 mean_eta_272 mean_eta_273 mean_eta_274 mean_eta_275 mean_eta_276 mean_eta_277 mean_eta_278 mean_eta_279 mean_eta_280 mean_eta_281 mean_eta_282 mean_eta_283 mean_eta_284 mean_eta_285 mean_eta_286 mean_eta_287 mean_eta_288 mean_eta_289 mean_eta_290 mean_eta_291 mean_eta_292 mean_eta_293 mean_eta_294 mean_eta_295 mean_eta_296 mean_eta_297 mean_eta_298 mean_eta_299 mean_eta_300 mean_eta_301 mean_eta_302 mean_eta_303 mean_eta_304 mean_eta_305 mean_eta_306 mean_eta_307 mean_eta_308 mean_eta_309 mean_eta_310 mean_eta_311 mean_eta_312 mean_eta_313 mean_eta_314 mean_eta_315 mean_eta_316 mean_eta_317 mean_eta_318 mean_eta_319 mean_eta_320 mean_eta_321 mean_eta_322 mean_eta_323 mean_eta_324 mean_eta_325 mean_eta_326 mean_eta_327 mean_eta_328 mean_eta_329 mean_eta_330 mean_eta_331 mean_eta_332 mean_eta_333 mean_eta_334 mean_eta_335 mean_eta_336 mean_eta_337 mean_eta_338 mean_eta_339 mean_eta_340 mean_eta_341 mean_eta_342 mean_eta_343 mean_eta_344 mean_eta_345 mean_eta_346 mean_eta_347 mean_eta_348 mean_eta_349 mean_eta_350 mean_eta_351 mean_eta_352 mean_eta_353 mean_eta_354 mean_eta_355 mean_eta_356 mean_eta_357 mean_eta_358 mean_eta_359 mean_eta_360 mean_eta_361 mean_eta_362 mean_eta_363 mean_eta_364 mean_eta_365 mean_eta_366 mean_eta_367 mean_eta_368 mean_eta_369 mean_eta_370 mean_eta_371 mean_eta_372 mean_eta_373 mean_eta_374 mean_eta_375 mean_eta_376 mean_eta_377 mean_eta_378 mean_eta_379 mean_eta_380 mean_eta_381 mean_eta_382 mean_eta_383 mean_eta_384 mean_eta_385 mean_eta_386 mean_eta_387 mean_eta_388 mean_eta_389 mean_eta_390 mean_eta_391 mean_eta_392 mean_eta_393 mean_eta_394 mean_eta_395 mean_eta_396 mean_eta_397 mean_eta_398 mean_eta_399 mean_eta_400 mean_eta_401 mean_eta_402 mean_eta_403 mean_eta_404 mean_eta_405
_____ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________
1 0 0.52526 0.48873 0.44813 0.40715 0.3683 0.33276 0.30078 0.27223 0.24678 0.22413 0.20396 0.18601 0.17002 0.15577 0.14307 0.13175 0.12166 0.11267 0.10465 0.09751 0.091135 0.085453 0.080374 0.075853 0.071836 0.068264 0.06509 0.062263 0.059754 0.057504 0.05549 0.05369 0.052071 0.050614 0.049312 0.048142 0.04708 0.046138 0.045281 0.044511 0.043819 0.043192 0.042626 0.042113 0.04165 0.041228 0.040845 0.040499 0.040184 0.039897 0.039636 0.039397 0.03918 0.038982 0.038802 0.038635 0.038485 0.038347 0.03822 0.038105 0.037999 0.037902 0.037813 0.037731 0.037657 0.037588 0.037525 0.037468 0.037415 0.037366 0.037322 0.037281 0.037244 0.03721 0.037179 0.037151 0.037125 0.037102 0.037081 0.037063 0.037048 0.52526 0.48873 0.44813 0.40715 0.3683 0.33276 0.30078 0.27223 0.24678 0.22413 0.20396 0.18601 0.17002 0.15577 0.14307 0.13175 0.12166 0.11267 0.10465 0.09751 0.091135 0.085453 0.080374 0.075853 0.071836 0.068263 0.065088 0.062255 0.059738 0.057481 0.055465 0.05367 0.052051 0.050596 0.049302 0.048125 0.04707 0.046125 0.045269 0.044501 0.043808 0.043184 0.042618 0.042105 0.041643 0.041221 0.040839 0.040494 0.040178 0.039892 0.039632 0.039393 0.039176 0.038979 0.038798 0.038633 0.038482 0.038344 0.038218 0.038103 0.037997 0.0379 0.037811 0.037729 0.037655 0.037587 0.037524 0.037467 0.037414 0.037366 0.037321 0.037281 0.037243 0.037209 0.037178 0.03715 0.037124 0.037101 0.037081 0.037063 0.037048 0.50045 0.46535 0.42651 0.38741 0.35042 0.31663 0.2863 0.25924 0.23517 0.21377 0.19474 0.17782 0.16276 0.14934 0.13739 0.12673 0.11722 0.10875 0.1012 0.094463 0.088442 0.083061 0.07824 0.073944 0.070121 0.066724 0.063694 0.060994 0.058593 0.056438 0.054512 0.05279 0.051236 0.049838 0.048583 0.047445 0.046421 0.045502 0.04467 0.043919 0.043243 0.042632 0.042077 0.041574 0.04112 0.040706 0.040331 0.039991 0.03968 0.039397 0.03914 0.038905 0.038691 0.038496 0.038318 0.038154 0.038006 0.03787 0.037744 0.037631 0.037526 0.037431 0.037343 0.037262 0.037189 0.037121 0.037059 0.037002 0.03695 0.036902 0.036858 0.036818 0.036781 0.036748 0.036717 0.036689 0.036664 0.036641 0.03662 0.036603 0.036588 0.46769 0.43375 0.39612 0.35824 0.32245 0.28983 0.26062 0.23466 0.21163 0.19124 0.17318 0.15719 0.14302 0.13046 0.11933 0.10947 0.10072 0.092964 0.086091 0.08 0.074591 0.069793 0.065523 0.061742 0.058399 0.055441 0.052827 0.050507 0.04846 0.046632 0.045005 0.043561 0.042259 0.041092 0.04005 0.039105 0.038253 0.037491 0.0368 0.036176 0.035613 0.035104 0.034639 0.034217 0.033834 0.033483 0.033164 0.032873 0.032605 0.032361 0.032138 0.031932 0.031744 0.031571 0.031413 0.031267 0.031133 0.03101 0.030896 0.030793 0.030696 0.030609 0.030527 0.030452 0.030384 0.03032 0.030263 0.030209 0.03016 0.030115 0.030073 0.030035 0.03 0.029968 0.029938 0.029912 0.029887 0.029865 0.029845 0.029828 0.029814 0.45639 0.42267 0.38527 0.34763 0.3121 0.27975 0.2508 0.22508 0.20231 0.18216 0.16434 0.14858 0.13464 0.12231 0.1114 0.10174 0.093193 0.085634 0.078951 0.073044 0.067812 0.063183 0.059078 0.055454 0.052262 0.049448 0.046971 0.044781 0.042859 0.04115 0.039637 0.038299 0.0371 0.036028 0.035075 0.034215 0.033443 0.032756 0.032135 0.031577 0.031076 0.030624 0.030213 0.029841 0.029504 0.029196 0.028916 0.028662 0.028429 0.028216 0.028022 0.027843 0.02768 0.02753 0.027393 0.027266 0.027151 0.027044 0.026945 0.026856 0.026772 0.026696 0.026625 0.02656 0.026501 0.026445 0.026395 0.026348 0.026305 0.026265 0.026229 0.026195 0.026165 0.026136 0.02611 0.026087 0.026065 0.026046 0.026029 0.026013 0.026001
2 0.00051498 0.52526 0.48873 0.44813 0.40715 0.3683 0.33276 0.30078 0.27223 0.24678 0.22413 0.20396 0.18601 0.17002 0.15577 0.14307 0.13174 0.12165 0.11266 0.10465 0.097509 0.091134 0.085449 0.080371 0.075849 0.071832 0.06826 0.065086 0.062259 0.059751 0.057501 0.055488 0.053687 0.052069 0.050612 0.049311 0.04814 0.047079 0.046136 0.045279 0.044509 0.043818 0.043191 0.042625 0.042112 0.041649 0.041228 0.040845 0.040499 0.040183 0.039896 0.039636 0.039397 0.039179 0.038982 0.038801 0.038635 0.038485 0.038347 0.03822 0.038105 0.037999 0.037902 0.037813 0.037731 0.037657 0.037588 0.037525 0.037468 0.037415 0.037366 0.037322 0.037281 0.037244 0.03721 0.037179 0.037151 0.037125 0.037102 0.037081 0.037063 0.037048 0.52526 0.48873 0.44813 0.40715 0.3683 0.33276 0.30078 0.27223 0.24678 0.22413 0.20396 0.18601 0.17002 0.15577 0.14307 0.13174 0.12165 0.11266 0.10465 0.097509 0.091134 0.085449 0.080371 0.075849 0.071832 0.068259 0.065084 0.062251 0.059734 0.057478 0.055463 0.053668 0.052049 0.050595 0.049301 0.048123 0.047068 0.046123 0.045268 0.0445 0.043807 0.043183 0.042617 0.042104 0.041642 0.041221 0.040839 0.040494 0.040178 0.039891 0.039631 0.039393 0.039176 0.038979 0.038798 0.038633 0.038482 0.038344 0.038218 0.038103 0.037997 0.0379 0.037811 0.037729 0.037655 0.037587 0.037524 0.037467 0.037414 0.037366 0.037321 0.037281 0.037243 0.037209 0.037178 0.03715 0.037124 0.037101 0.037081 0.037063 0.037048 0.50033 0.46524 0.42641 0.38731 0.35033 0.31655 0.28622 0.25916 0.23509 0.2137 0.19468 0.17776 0.1627 0.14929 0.13734 0.12668 0.11718 0.10871 0.10117 0.094431 0.088414 0.083034 0.078216 0.073919 0.070097 0.066701 0.063672 0.060973 0.058574 0.056421 0.054497 0.052775 0.051222 0.049825 0.04857 0.047433 0.046409 0.045491 0.044659 0.043909 0.043233 0.042622 0.042067 0.041565 0.041111 0.040697 0.040322 0.039982 0.039671 0.039388 0.039132 0.038896 0.038682 0.038488 0.03831 0.038146 0.037997 0.037861 0.037736 0.037623 0.037518 0.037422 0.037335 0.037253 0.03718 0.037112 0.037051 0.036994 0.036942 0.036894 0.03685 0.03681 0.036773 0.03674 0.036709 0.036681 0.036656 0.036633 0.036612 0.036594 0.03658 0.46768 0.43374 0.39611 0.35823 0.32244 0.28983 0.26062 0.23465 0.21162 0.19123 0.17317 0.15718 0.14301 0.13045 0.11932 0.10946 0.10071 0.092955 0.086084 0.079994 0.074584 0.069784 0.065515 0.061733 0.05839 0.055433 0.052818 0.050499 0.048452 0.046625 0.044999 0.043554 0.042254 0.041086 0.040044 0.039099 0.038248 0.037486 0.036795 0.036171 0.035609 0.035099 0.034635 0.034213 0.03383 0.033479 0.03316 0.032869 0.032601 0.032357 0.032134 0.031928 0.03174 0.031568 0.031409 0.031263 0.03113 0.031007 0.030893 0.030789 0.030693 0.030605 0.030524 0.030449 0.030381 0.030317 0.030259 0.030205 0.030156 0.030111 0.030069 0.030031 0.029996 0.029964 0.029935 0.029908 0.029884 0.029862 0.029842 0.029825 0.029811 0.45639 0.42267 0.38527 0.34763 0.3121 0.27975 0.2508 0.22508 0.20231 0.18216 0.16434 0.14858 0.13464 0.1223 0.11139 0.10173 0.093187 0.08563 0.07895 0.073043 0.067809 0.06318 0.059074 0.055449 0.052257 0.049444 0.046966 0.044777 0.042855 0.041147 0.039634 0.038297 0.037098 0.036025 0.035073 0.034213 0.033441 0.032754 0.032134 0.031575 0.031075 0.030623 0.030211 0.02984 0.029503 0.029195 0.028915 0.028662 0.028428 0.028215 0.028021 0.027843 0.027679 0.02753 0.027393 0.027266 0.02715 0.027044 0.026945 0.026856 0.026772 0.026696 0.026625 0.02656 0.0265 0.026445 0.026395 0.026347 0.026305 0.026265 0.026229 0.026195 0.026164 0.026136 0.02611 0.026087 0.026065 0.026046 0.026028 0.026013 0.026001
3 0.0041199 0.52469 0.48792 0.44711 0.40616 0.36748 0.3321 0.30026 0.2718 0.24642 0.22382 0.2037 0.18578 0.16982 0.1556 0.14292 0.13162 0.12155 0.11257 0.10457 0.097435 0.09106 0.085389 0.08031 0.075795 0.071783 0.068222 0.065049 0.06223 0.059723 0.057476 0.055464 0.053664 0.052048 0.050592 0.049294 0.048124 0.047064 0.046124 0.045268 0.0445 0.043809 0.043183 0.042618 0.042106 0.041643 0.041223 0.04084 0.040495 0.040179 0.039893 0.039632 0.039394 0.039177 0.03898 0.038799 0.038633 0.038483 0.038345 0.038218 0.038103 0.037997 0.037901 0.037811 0.03773 0.037655 0.037587 0.037524 0.037466 0.037414 0.037365 0.037321 0.03728 0.037243 0.037209 0.037178 0.03715 0.037124 0.037101 0.03708 0.037062 0.037047 0.52469 0.48792 0.44711 0.40616 0.36748 0.3321 0.30026 0.2718 0.24642 0.22382 0.2037 0.18578 0.16982 0.1556 0.14292 0.13162 0.12155 0.11257 0.10457 0.097435 0.09106 0.085389 0.08031 0.075795 0.071783 0.06822 0.065047 0.06222 0.059706 0.057453 0.055439 0.053645 0.052026 0.050577 0.049282 0.048107 0.047055 0.046111 0.045257 0.04449 0.043798 0.043175 0.04261 0.042098 0.041637 0.041216 0.040834 0.04049 0.040174 0.039888 0.039628 0.03939 0.039173 0.038976 0.038796 0.03863 0.03848 0.038342 0.038216 0.038101 0.037995 0.037899 0.03781 0.037728 0.037654 0.037585 0.037523 0.037465 0.037413 0.037364 0.03732 0.037279 0.037242 0.037208 0.037177 0.037149 0.037123 0.0371 0.03708 0.037062 0.037047 0.49901 0.46373 0.42473 0.3857 0.34892 0.31534 0.28516 0.25821 0.23424 0.21292 0.19396 0.17711 0.16211 0.14875 0.13686 0.12626 0.11682 0.10839 0.10086 0.094149 0.088151 0.082802 0.078001 0.073722 0.069915 0.066529 0.063507 0.060824 0.058435 0.056293 0.05438 0.052664 0.051116 0.049724 0.048475 0.047344 0.046323 0.045409 0.04458 0.043833 0.043159 0.04255 0.041997 0.041496 0.041043 0.04063 0.040255 0.039916 0.039606 0.039324 0.039067 0.038833 0.038619 0.038425 0.038247 0.038083 0.037935 0.037799 0.037674 0.037561 0.037456 0.037361 0.037273 0.037192 0.037119 0.037051 0.036989 0.036932 0.036881 0.036833 0.036789 0.036749 0.036712 0.036678 0.036648 0.03662 0.036594 0.036571 0.036551 0.036533 0.036519 0.46704 0.43286 0.39502 0.35718 0.32156 0.28912 0.26004 0.23416 0.21121 0.19087 0.17286 0.1569 0.14277 0.13024 0.11914 0.10929 0.10056 0.092825 0.085966 0.079884 0.074475 0.069689 0.06542 0.061646 0.058309 0.055363 0.052751 0.05044 0.048397 0.046572 0.04495 0.043505 0.042207 0.041042 0.040001 0.039058 0.038208 0.037449 0.036759 0.036137 0.035576 0.035067 0.034603 0.034182 0.033801 0.03345 0.033131 0.032841 0.032574 0.03233 0.032107 0.031902 0.031713 0.031541 0.031383 0.031237 0.031104 0.030981 0.030867 0.030764 0.030668 0.03058 0.030499 0.030423 0.030355 0.030292 0.030234 0.03018 0.030132 0.030086 0.030045 0.030007 0.029972 0.029939 0.02991 0.029883 0.029859 0.029837 0.029817 0.0298 0.029786 0.45582 0.42185 0.38423 0.34664 0.31128 0.27909 0.25027 0.22465 0.20194 0.18185 0.16407 0.14835 0.13444 0.12213 0.11124 0.1016 0.093078 0.085536 0.078865 0.072966 0.067733 0.063116 0.05901 0.055392 0.052205 0.049402 0.046927 0.044745 0.042826 0.04112 0.03961 0.038273 0.037076 0.036005 0.035054 0.034196 0.033425 0.032741 0.032121 0.031564 0.031065 0.030613 0.030203 0.029832 0.029496 0.029188 0.028909 0.028656 0.028423 0.02821 0.028016 0.027838 0.027674 0.027526 0.027389 0.027262 0.027146 0.02704 0.026941 0.026852 0.026768 0.026692 0.026622 0.026556 0.026497 0.026441 0.026391 0.026344 0.026301 0.026262 0.026225 0.026192 0.026161 0.026133 0.026107 0.026083 0.026062 0.026042 0.026025 0.02601 0.025997
4 0.013905 0.47091 0.43897 0.40471 0.37007 0.337 0.30644 0.27869 0.25369 0.2313 0.21125 0.19328 0.17717 0.16273 0.14978 0.13818 0.12778 0.11843 0.11004 0.10253 0.095784 0.089752 0.08434 0.079485 0.075147 0.071261 0.067796 0.064692 0.061927 0.059447 0.057226 0.055238 0.05345 0.051852 0.050408 0.049122 0.047958 0.04691 0.045974 0.045124 0.044362 0.043674 0.04305 0.042488 0.041978 0.041517 0.041098 0.040717 0.040373 0.040058 0.039772 0.039513 0.039276 0.039059 0.038862 0.038682 0.038517 0.038367 0.038229 0.038103 0.037988 0.037882 0.037786 0.037697 0.037615 0.037541 0.037472 0.03741 0.037352 0.0373 0.037251 0.037207 0.037166 0.037129 0.037095 0.037064 0.037036 0.03701 0.036987 0.036966 0.036949 0.036934 0.47091 0.43897 0.40471 0.37007 0.337 0.30644 0.27869 0.25369 0.2313 0.21125 0.19328 0.17717 0.16273 0.14978 0.13818 0.12778 0.11843 0.11004 0.10253 0.095784 0.089752 0.08434 0.079485 0.075147 0.07126 0.067794 0.064686 0.061914 0.059425 0.057201 0.055215 0.053434 0.051826 0.050398 0.049107 0.047942 0.0469 0.045961 0.045114 0.044351 0.043664 0.043043 0.042479 0.04197 0.041511 0.04109 0.040711 0.040368 0.040053 0.039768 0.039509 0.039272 0.039055 0.038859 0.038679 0.038514 0.038364 0.038227 0.038101 0.037986 0.03788 0.037784 0.037695 0.037614 0.03754 0.037471 0.037409 0.037351 0.037299 0.03725 0.037206 0.037166 0.037129 0.037095 0.037064 0.037036 0.03701 0.036987 0.036966 0.036948 0.036933 0.44343 0.41307 0.38073 0.34812 0.31704 0.28836 0.26236 0.23897 0.21804 0.19933 0.18258 0.16756 0.15412 0.14208 0.1313 0.12162 0.11294 0.10515 0.098166 0.091906 0.086295 0.08125 0.076717 0.072652 0.069009 0.065747 0.06282 0.060204 0.057855 0.055754 0.053876 0.052182 0.050663 0.0493 0.048067 0.046954 0.04595 0.045047 0.044229 0.04349 0.042825 0.042221 0.041672 0.041176 0.040727 0.040317 0.039945 0.039607 0.039299 0.039018 0.038763 0.038531 0.038317 0.038124 0.037947 0.037784 0.037636 0.037501 0.037376 0.037263 0.037158 0.037063 0.036976 0.036895 0.036822 0.036754 0.036693 0.036636 0.036584 0.036536 0.036493 0.036453 0.036416 0.036382 0.036352 0.036324 0.036298 0.036276 0.036255 0.036237 0.036223 0.41308 0.38374 0.35246 0.32093 0.29092 0.2633 0.23832 0.21592 0.19595 0.17817 0.16232 0.14817 0.13555 0.12431 0.11429 0.10534 0.097342 0.090196 0.083824 0.078137 0.073074 0.06855 0.064507 0.060912 0.057703 0.054856 0.052313 0.050059 0.048046 0.046251 0.044657 0.043223 0.04194 0.040793 0.039759 0.038827 0.037987 0.037233 0.03655 0.035932 0.035377 0.03487 0.034409 0.03399 0.03361 0.033262 0.032944 0.032655 0.032389 0.032146 0.031924 0.031721 0.031533 0.031361 0.031204 0.031058 0.030925 0.030803 0.030689 0.030586 0.03049 0.030403 0.030322 0.030247 0.030179 0.030115 0.030058 0.030004 0.029955 0.02991 0.029869 0.02983 0.029795 0.029763 0.029734 0.029707 0.029683 0.029661 0.029641 0.029624 0.02961 0.40202 0.37288 0.34183 0.31054 0.28078 0.25341 0.22868 0.20653 0.18681 0.16927 0.15365 0.13973 0.12733 0.11631 0.10649 0.097751 0.089953 0.082999 0.076813 0.071305 0.066416 0.062059 0.058177 0.054735 0.051675 0.048969 0.046561 0.044435 0.042545 0.040868 0.039385 0.038058 0.036875 0.035822 0.034876 0.034028 0.033267 0.032588 0.031974 0.031421 0.030926 0.030476 0.030068 0.029699 0.029365 0.029059 0.028781 0.028528 0.028296 0.028085 0.027892 0.027715 0.027551 0.027403 0.027267 0.02714 0.027025 0.026919 0.026821 0.026731 0.026648 0.026572 0.026501 0.026436 0.026377 0.026322 0.026272 0.026225 0.026182 0.026142 0.026106 0.026072 0.026042 0.026014 0.025988 0.025964 0.025943 0.025923 0.025906 0.025891 0.025878
5 0.032959 0.39774 0.3737 0.34722 0.32037 0.29449 0.27025 0.24791 0.22748 0.20889 0.19201 0.17669 0.16282 0.15026 0.13891 0.12867 0.11944 0.11113 0.10364 0.096872 0.090771 0.085279 0.080345 0.075916 0.071934 0.068366 0.065156 0.062284 0.059695 0.057365 0.055267 0.053379 0.051684 0.05015 0.048781 0.047545 0.046421 0.04542 0.044505 0.043678 0.042932 0.042256 0.041644 0.04109 0.040588 0.040133 0.039719 0.039343 0.039003 0.038692 0.038408 0.038151 0.037916 0.037701 0.037505 0.037326 0.037162 0.037013 0.036876 0.036751 0.036636 0.03653 0.036435 0.036346 0.036264 0.03619 0.036122 0.03606 0.036002 0.03595 0.035902 0.035857 0.035817 0.03578 0.035746 0.035715 0.035687 0.035661 0.035638 0.035617 0.0356 0.035585 0.39774 0.3737 0.34722 0.32037 0.29449 0.27025 0.24791 0.22748 0.20889 0.19201 0.17669 0.16282 0.15026 0.13891 0.12867 0.11944 0.11113 0.10364 0.096872 0.090771 0.085279 0.080345 0.075916 0.071934 0.068365 0.065152 0.062272 0.059673 0.057338 0.055242 0.053362 0.051661 0.050134 0.048769 0.047527 0.046411 0.045406 0.044492 0.043668 0.042921 0.042246 0.041636 0.041081 0.040581 0.040126 0.039712 0.039337 0.038997 0.038687 0.038404 0.038147 0.037912 0.037697 0.037502 0.037323 0.037159 0.03701 0.036873 0.036748 0.036634 0.036528 0.036433 0.036344 0.036263 0.036189 0.036121 0.036059 0.036001 0.035949 0.035901 0.035857 0.035816 0.035779 0.035745 0.035714 0.035686 0.035661 0.035638 0.035617 0.035599 0.035584 0.36681 0.34452 0.32012 0.29547 0.27174 0.24954 0.22909 0.21041 0.19343 0.17802 0.16406 0.15143 0.14 0.12967 0.12035 0.11195 0.10438 0.09756 0.091399 0.085828 0.080807 0.076287 0.072219 0.068559 0.06527 0.06231 0.059656 0.057262 0.055106 0.053168 0.051416 0.049836 0.048408 0.047124 0.045958 0.044901 0.043948 0.043081 0.042293 0.041579 0.040933 0.040345 0.039811 0.039328 0.038888 0.038487 0.038122 0.037791 0.037487 0.037211 0.036959 0.03673 0.036518 0.036327 0.036151 0.03599 0.035844 0.035709 0.035585 0.035473 0.035369 0.035275 0.035187 0.035107 0.035035 0.034967 0.034906 0.034849 0.034798 0.03475 0.034706 0.034666 0.03463 0.034596 0.034566 0.034538 0.034512 0.03449 0.034469 0.034452 0.034437 0.33958 0.31814 0.29465 0.27093 0.24812 0.22683 0.20727 0.18944 0.17329 0.15868 0.14549 0.13359 0.12287 0.11322 0.10456 0.096797 0.089839 0.083597 0.077985 0.072944 0.068425 0.064384 0.060771 0.057536 0.054649 0.05206 0.049754 0.047681 0.045822 0.044161 0.042667 0.041324 0.040116 0.039035 0.038055 0.037167 0.036369 0.035641 0.03498 0.03438 0.033837 0.033341 0.032889 0.032481 0.032106 0.031764 0.031451 0.031166 0.030904 0.030663 0.030444 0.030242 0.030056 0.029886 0.02973 0.029585 0.029453 0.029331 0.029219 0.029116 0.029021 0.028934 0.028853 0.028778 0.028711 0.028647 0.02859 0.028536 0.028488 0.028443 0.028402 0.028363 0.028329 0.028297 0.028267 0.028241 0.028216 0.028194 0.028175 0.028158 0.028143 0.32883 0.30759 0.28431 0.26082 0.23825 0.2172 0.19788 0.1803 0.16438 0.15 0.13703 0.12536 0.11485 0.10541 0.096958 0.089393 0.082628 0.076572 0.071141 0.066275 0.061924 0.058046 0.054591 0.051506 0.048764 0.046313 0.044138 0.042192 0.040455 0.038908 0.037524 0.036285 0.035174 0.034185 0.033292 0.032487 0.031767 0.031112 0.030519 0.029983 0.0295 0.02906 0.028661 0.028301 0.027971 0.027671 0.027398 0.027148 0.02692 0.026711 0.02652 0.026345 0.026183 0.026036 0.0259 0.025775 0.02566 0.025554 0.025457 0.025368 0.025285 0.02521 0.025139 0.025074 0.025016 0.02496 0.02491 0.024864 0.024821 0.024781 0.024745 0.024712 0.024681 0.024653 0.024627 0.024604 0.024582 0.024563 0.024546 0.024531 0.024518
6 0.064373 0.32479 0.30724 0.28795 0.26815 0.24878 0.23037 0.21312 0.19716 0.18244 0.16891 0.1565 0.14515 0.13478 0.12531 0.11669 0.10882 0.10165 0.09514 0.089224 0.083887 0.079041 0.074664 0.070705 0.067117 0.06388 0.06096 0.058314 0.055918 0.053759 0.051803 0.050043 0.048442 0.047005 0.045706 0.044522 0.043462 0.042496 0.04162 0.040829 0.040113 0.03946 0.03887 0.038332 0.037845 0.037401 0.036996 0.036629 0.036294 0.035988 0.03571 0.035456 0.035224 0.035012 0.034818 0.034641 0.034479 0.034331 0.034195 0.034071 0.033957 0.033852 0.033757 0.033669 0.033588 0.033514 0.033446 0.033384 0.033327 0.033275 0.033227 0.033183 0.033143 0.033106 0.033072 0.033041 0.033013 0.032987 0.032964 0.032944 0.032926 0.032911 0.32234 0.30499 0.28598 0.26649 ...
% Consumption
st_title = ['MEAN(MN_MPC_U_GAIN_CHECK(A,Z)), welf_checks=' num2str(welf_checks) ', TR=' num2str(mp_params('TR'))];
tb_az_c = ff_summ_nd_array(st_title, mn_MPC_U_gain_share_check_07, true, ["mean"], 4, 1, cl_mp_datasetdesc, ar_permute);
xxx MEAN(MN_MPC_U_GAIN_CHECK(A,Z)), welf_checks=2, TR=0.0018238 xxxxxxxxxxxxxxxxxxxxxxxxxxx
group savings mean_eta_1 mean_eta_2 mean_eta_3 mean_eta_4 mean_eta_5 mean_eta_6 mean_eta_7 mean_eta_8 mean_eta_9 mean_eta_10 mean_eta_11 mean_eta_12 mean_eta_13 mean_eta_14 mean_eta_15 mean_eta_16 mean_eta_17 mean_eta_18 mean_eta_19 mean_eta_20 mean_eta_21 mean_eta_22 mean_eta_23 mean_eta_24 mean_eta_25 mean_eta_26 mean_eta_27 mean_eta_28 mean_eta_29 mean_eta_30 mean_eta_31 mean_eta_32 mean_eta_33 mean_eta_34 mean_eta_35 mean_eta_36 mean_eta_37 mean_eta_38 mean_eta_39 mean_eta_40 mean_eta_41 mean_eta_42 mean_eta_43 mean_eta_44 mean_eta_45 mean_eta_46 mean_eta_47 mean_eta_48 mean_eta_49 mean_eta_50 mean_eta_51 mean_eta_52 mean_eta_53 mean_eta_54 mean_eta_55 mean_eta_56 mean_eta_57 mean_eta_58 mean_eta_59 mean_eta_60 mean_eta_61 mean_eta_62 mean_eta_63 mean_eta_64 mean_eta_65 mean_eta_66 mean_eta_67 mean_eta_68 mean_eta_69 mean_eta_70 mean_eta_71 mean_eta_72 mean_eta_73 mean_eta_74 mean_eta_75 mean_eta_76 mean_eta_77 mean_eta_78 mean_eta_79 mean_eta_80 mean_eta_81 mean_eta_82 mean_eta_83 mean_eta_84 mean_eta_85 mean_eta_86 mean_eta_87 mean_eta_88 mean_eta_89 mean_eta_90 mean_eta_91 mean_eta_92 mean_eta_93 mean_eta_94 mean_eta_95 mean_eta_96 mean_eta_97 mean_eta_98 mean_eta_99 mean_eta_100 mean_eta_101 mean_eta_102 mean_eta_103 mean_eta_104 mean_eta_105 mean_eta_106 mean_eta_107 mean_eta_108 mean_eta_109 mean_eta_110 mean_eta_111 mean_eta_112 mean_eta_113 mean_eta_114 mean_eta_115 mean_eta_116 mean_eta_117 mean_eta_118 mean_eta_119 mean_eta_120 mean_eta_121 mean_eta_122 mean_eta_123 mean_eta_124 mean_eta_125 mean_eta_126 mean_eta_127 mean_eta_128 mean_eta_129 mean_eta_130 mean_eta_131 mean_eta_132 mean_eta_133 mean_eta_134 mean_eta_135 mean_eta_136 mean_eta_137 mean_eta_138 mean_eta_139 mean_eta_140 mean_eta_141 mean_eta_142 mean_eta_143 mean_eta_144 mean_eta_145 mean_eta_146 mean_eta_147 mean_eta_148 mean_eta_149 mean_eta_150 mean_eta_151 mean_eta_152 mean_eta_153 mean_eta_154 mean_eta_155 mean_eta_156 mean_eta_157 mean_eta_158 mean_eta_159 mean_eta_160 mean_eta_161 mean_eta_162 mean_eta_163 mean_eta_164 mean_eta_165 mean_eta_166 mean_eta_167 mean_eta_168 mean_eta_169 mean_eta_170 mean_eta_171 mean_eta_172 mean_eta_173 mean_eta_174 mean_eta_175 mean_eta_176 mean_eta_177 mean_eta_178 mean_eta_179 mean_eta_180 mean_eta_181 mean_eta_182 mean_eta_183 mean_eta_184 mean_eta_185 mean_eta_186 mean_eta_187 mean_eta_188 mean_eta_189 mean_eta_190 mean_eta_191 mean_eta_192 mean_eta_193 mean_eta_194 mean_eta_195 mean_eta_196 mean_eta_197 mean_eta_198 mean_eta_199 mean_eta_200 mean_eta_201 mean_eta_202 mean_eta_203 mean_eta_204 mean_eta_205 mean_eta_206 mean_eta_207 mean_eta_208 mean_eta_209 mean_eta_210 mean_eta_211 mean_eta_212 mean_eta_213 mean_eta_214 mean_eta_215 mean_eta_216 mean_eta_217 mean_eta_218 mean_eta_219 mean_eta_220 mean_eta_221 mean_eta_222 mean_eta_223 mean_eta_224 mean_eta_225 mean_eta_226 mean_eta_227 mean_eta_228 mean_eta_229 mean_eta_230 mean_eta_231 mean_eta_232 mean_eta_233 mean_eta_234 mean_eta_235 mean_eta_236 mean_eta_237 mean_eta_238 mean_eta_239 mean_eta_240 mean_eta_241 mean_eta_242 mean_eta_243 mean_eta_244 mean_eta_245 mean_eta_246 mean_eta_247 mean_eta_248 mean_eta_249 mean_eta_250 mean_eta_251 mean_eta_252 mean_eta_253 mean_eta_254 mean_eta_255 mean_eta_256 mean_eta_257 mean_eta_258 mean_eta_259 mean_eta_260 mean_eta_261 mean_eta_262 mean_eta_263 mean_eta_264 mean_eta_265 mean_eta_266 mean_eta_267 mean_eta_268 mean_eta_269 mean_eta_270 mean_eta_271 mean_eta_272 mean_eta_273 mean_eta_274 mean_eta_275 mean_eta_276 mean_eta_277 mean_eta_278 mean_eta_279 mean_eta_280 mean_eta_281 mean_eta_282 mean_eta_283 mean_eta_284 mean_eta_285 mean_eta_286 mean_eta_287 mean_eta_288 mean_eta_289 mean_eta_290 mean_eta_291 mean_eta_292 mean_eta_293 mean_eta_294 mean_eta_295 mean_eta_296 mean_eta_297 mean_eta_298 mean_eta_299 mean_eta_300 mean_eta_301 mean_eta_302 mean_eta_303 mean_eta_304 mean_eta_305 mean_eta_306 mean_eta_307 mean_eta_308 mean_eta_309 mean_eta_310 mean_eta_311 mean_eta_312 mean_eta_313 mean_eta_314 mean_eta_315 mean_eta_316 mean_eta_317 mean_eta_318 mean_eta_319 mean_eta_320 mean_eta_321 mean_eta_322 mean_eta_323 mean_eta_324 mean_eta_325 mean_eta_326 mean_eta_327 mean_eta_328 mean_eta_329 mean_eta_330 mean_eta_331 mean_eta_332 mean_eta_333 mean_eta_334 mean_eta_335 mean_eta_336 mean_eta_337 mean_eta_338 mean_eta_339 mean_eta_340 mean_eta_341 mean_eta_342 mean_eta_343 mean_eta_344 mean_eta_345 mean_eta_346 mean_eta_347 mean_eta_348 mean_eta_349 mean_eta_350 mean_eta_351 mean_eta_352 mean_eta_353 mean_eta_354 mean_eta_355 mean_eta_356 mean_eta_357 mean_eta_358 mean_eta_359 mean_eta_360 mean_eta_361 mean_eta_362 mean_eta_363 mean_eta_364 mean_eta_365 mean_eta_366 mean_eta_367 mean_eta_368 mean_eta_369 mean_eta_370 mean_eta_371 mean_eta_372 mean_eta_373 mean_eta_374 mean_eta_375 mean_eta_376 mean_eta_377 mean_eta_378 mean_eta_379 mean_eta_380 mean_eta_381 mean_eta_382 mean_eta_383 mean_eta_384 mean_eta_385 mean_eta_386 mean_eta_387 mean_eta_388 mean_eta_389 mean_eta_390 mean_eta_391 mean_eta_392 mean_eta_393 mean_eta_394 mean_eta_395 mean_eta_396 mean_eta_397 mean_eta_398 mean_eta_399 mean_eta_400 mean_eta_401 mean_eta_402 mean_eta_403 mean_eta_404 mean_eta_405
_____ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________ ____________
1 0 0.74182 0.72635 0.71164 0.69952 0.69052 0.68421 0.67981 0.67678 0.67481 0.67381 0.6737 0.67437 0.67552 0.67678 0.67777 0.67831 0.67853 0.6789 0.67999 0.68191 0.68445 0.68625 0.68682 0.68371 0.67769 0.66661 0.65135 0.63314 0.61533 0.60068 0.5923 0.58952 0.59341 0.59965 0.60503 0.60664 0.60362 0.59667 0.58773 0.57862 0.57118 0.56561 0.56154 0.55773 0.55356 0.54879 0.5437 0.53864 0.5336 0.5284 0.52334 0.51762 0.51177 0.50563 0.49945 0.49396 0.48755 0.48116 0.47514 0.4689 0.46331 0.45754 0.45174 0.44632 0.44082 0.4361 0.4321 0.42817 0.4244 0.42098 0.41806 0.41545 0.41305 0.41049 0.40844 0.40645 0.40473 0.40327 0.40162 0.40058 0.39907 0.74182 0.72635 0.71164 0.69952 0.69052 0.68421 0.67981 0.67678 0.67481 0.67381 0.6737 0.67437 0.67552 0.67678 0.67777 0.67831 0.67853 0.6789 0.67999 0.68191 0.68445 0.68625 0.68682 0.68371 0.67769 0.66675 0.65147 0.63328 0.61587 0.60104 0.59152 0.58953 0.59298 0.59939 0.60481 0.60627 0.6035 0.59641 0.58747 0.57853 0.57111 0.56552 0.56148 0.55762 0.55346 0.54871 0.54357 0.53838 0.53346 0.5284 0.52316 0.51746 0.51162 0.5051 0.4994 0.4934 0.48718 0.48089 0.4747 0.46872 0.46288 0.45744 0.45136 0.44604 0.44062 0.43594 0.43166 0.42785 0.42429 0.42105 0.41794 0.41502 0.41283 0.41043 0.40833 0.40637 0.40468 0.40309 0.40154 0.40037 0.39895 0.73312 0.71841 0.70435 0.69283 0.6844 0.67866 0.67484 0.6724 0.67129 0.67083 0.6712 0.6726 0.67479 0.67728 0.67986 0.68184 0.68332 0.68448 0.68599 0.68807 0.69038 0.6918 0.69162 0.68764 0.68076 0.66872 0.65201 0.63205 0.61216 0.59569 0.58505 0.58068 0.58067 0.58433 0.5896 0.5925 0.59155 0.5869 0.58031 0.57318 0.5672 0.56208 0.55792 0.55387 0.54963 0.54431 0.53853 0.53279 0.52711 0.5211 0.51538 0.50912 0.50256 0.49594 0.48955 0.48369 0.47796 0.47201 0.46601 0.45998 0.45446 0.44941 0.44456 0.43998 0.43519 0.43122 0.42757 0.42463 0.42164 0.41865 0.41584 0.41327 0.41128 0.40887 0.40707 0.40553 0.40389 0.40244 0.40102 0.40018 0.39889 0.55826 0.54295 0.52839 0.51631 0.50725 0.50082 0.49636 0.49328 0.49129 0.49033 0.49037 0.49134 0.49301 0.49503 0.49701 0.49871 0.50021 0.50191 0.50427 0.50732 0.5108 0.51331 0.51438 0.51172 0.50629 0.49609 0.48199 0.46507 0.4482 0.43435 0.42589 0.42396 0.42754 0.43427 0.44031 0.4429 0.44094 0.43467 0.42621 0.41734 0.41007 0.40477 0.40154 0.39917 0.39697 0.39418 0.39091 0.3876 0.38436 0.38091 0.3777 0.37421 0.37075 0.36725 0.36418 0.36151 0.35865 0.35567 0.35313 0.35067 0.3487 0.34678 0.34428 0.34209 0.33965 0.33774 0.33595 0.3344 0.33282 0.33127 0.32983 0.32845 0.32748 0.32618 0.32515 0.32418 0.3232 0.32233 0.32137 0.32076 0.31999 0.50295 0.48786 0.47343 0.46142 0.45238 0.44595 0.44145 0.43833 0.43632 0.43533 0.43536 0.43634 0.43803 0.44009 0.44212 0.4439 0.44551 0.44734 0.44985 0.4531 0.45682 0.45959 0.46096 0.45863 0.45354 0.44368 0.42991 0.41328 0.3967 0.38311 0.37492 0.37326 0.37713 0.38417 0.39049 0.39335 0.39167 0.38569 0.37751 0.36899 0.36211 0.35721 0.35436 0.35236 0.35056 0.34822 0.34546 0.34267 0.33997 0.33709 0.33448 0.33162 0.32876 0.32587 0.32345 0.32139 0.31912 0.31672 0.31477 0.31293 0.31159 0.31036 0.30858 0.30712 0.3054 0.30419 0.3031 0.3022 0.30127 0.30034 0.29949 0.29867 0.29827 0.29745 0.29684 0.29629 0.29572 0.29527 0.29469 0.29439 0.29385
2 0.00051498 0.74182 0.72635 0.71164 0.69952 0.69052 0.68421 0.67981 0.67678 0.67481 0.67381 0.67371 0.67438 0.67557 0.67686 0.67787 0.67837 0.67855 0.67892 0.68005 0.68197 0.68443 0.6861 0.68668 0.68364 0.67771 0.66669 0.65141 0.63312 0.61525 0.60063 0.59226 0.58949 0.59351 0.5997 0.605 0.60664 0.60353 0.59666 0.58771 0.57861 0.57114 0.56556 0.56154 0.55772 0.55351 0.5487 0.54371 0.53861 0.53356 0.52838 0.52331 0.51759 0.51175 0.50562 0.49945 0.49393 0.48753 0.48115 0.47511 0.4689 0.46333 0.45753 0.45172 0.44629 0.4408 0.43609 0.4321 0.42815 0.42441 0.42098 0.41806 0.41543 0.41305 0.41048 0.40844 0.40645 0.40473 0.40326 0.40162 0.40058 0.39907 0.74182 0.72635 0.71164 0.69952 0.69052 0.68421 0.67981 0.67678 0.67481 0.67381 0.67371 0.67438 0.67557 0.67686 0.67787 0.67837 0.67855 0.67892 0.68005 0.68197 0.68443 0.6861 0.68668 0.68364 0.67771 0.66684 0.65153 0.63327 0.61582 0.60097 0.5915 0.5895 0.59307 0.59945 0.60478 0.60626 0.6034 0.59639 0.58745 0.57853 0.57107 0.56547 0.56148 0.55761 0.55341 0.54863 0.54357 0.53836 0.53342 0.52837 0.52314 0.51742 0.51159 0.50509 0.49941 0.49339 0.48716 0.48085 0.47468 0.46871 0.46288 0.45742 0.45134 0.44602 0.44062 0.43594 0.43166 0.42782 0.42428 0.42104 0.41794 0.41501 0.41283 0.41043 0.40832 0.40637 0.40468 0.40309 0.40154 0.40037 0.39895 0.73275 0.718 0.70395 0.69244 0.68403 0.67831 0.67455 0.67216 0.67104 0.6706 0.67095 0.67236 0.67458 0.67719 0.67983 0.6818 0.68328 0.68454 0.68618 0.68839 0.69064 0.69193 0.69169 0.68778 0.68091 0.66883 0.65212 0.63204 0.61204 0.59552 0.58491 0.58067 0.58104 0.58433 0.58912 0.59197 0.59091 0.58631 0.57963 0.57252 0.5665 0.56145 0.55732 0.55328 0.54909 0.54378 0.5381 0.53233 0.52664 0.52062 0.51487 0.50858 0.50206 0.49542 0.48905 0.48319 0.47749 0.47152 0.4655 0.4595 0.454 0.44894 0.44409 0.43951 0.43473 0.43076 0.42711 0.42416 0.42119 0.4182 0.41539 0.41282 0.41083 0.40842 0.40663 0.40508 0.40344 0.40199 0.40057 0.39973 0.39845 0.5582 0.5429 0.52834 0.51626 0.5072 0.50077 0.49631 0.49322 0.49124 0.49027 0.49032 0.49131 0.49301 0.49507 0.49705 0.49872 0.50018 0.50189 0.50429 0.50734 0.51074 0.51312 0.5142 0.51161 0.50628 0.49613 0.48201 0.46501 0.44809 0.43426 0.42583 0.4239 0.4276 0.43429 0.44025 0.44287 0.44081 0.43463 0.42616 0.41731 0.40999 0.40469 0.40151 0.39913 0.39689 0.39405 0.39088 0.38754 0.38429 0.38085 0.37764 0.37414 0.37069 0.3672 0.36415 0.36146 0.35861 0.35562 0.35307 0.35063 0.34868 0.34674 0.34424 0.34204 0.33963 0.33771 0.33591 0.33435 0.3328 0.33124 0.3298 0.32842 0.32745 0.32614 0.32512 0.32415 0.32317 0.3223 0.32135 0.32073 0.31996 0.50294 0.48785 0.47342 0.46141 0.45238 0.44595 0.44145 0.43833 0.43632 0.43533 0.43537 0.43635 0.43808 0.44017 0.44221 0.44396 0.44553 0.44736 0.44991 0.45317 0.4568 0.45944 0.46082 0.45855 0.45356 0.44376 0.42997 0.41327 0.39662 0.38305 0.37489 0.37324 0.37723 0.38421 0.39046 0.39335 0.39157 0.38568 0.3775 0.36899 0.36207 0.35717 0.35436 0.35235 0.35051 0.34813 0.34546 0.34265 0.33993 0.33707 0.33446 0.33158 0.32873 0.32586 0.32345 0.32137 0.3191 0.3167 0.31474 0.31292 0.3116 0.31035 0.30857 0.3071 0.3054 0.30418 0.30308 0.30218 0.30128 0.30034 0.29949 0.29866 0.29826 0.29744 0.29684 0.29629 0.29572 0.29527 0.29469 0.29438 0.29385
3 0.0041199 0.74131 0.72479 0.70912 0.69655 0.68793 0.68245 0.67899 0.67677 0.67543 0.67483 0.67482 0.67525 0.67591 0.67653 0.67695 0.677 0.67684 0.67697 0.67787 0.68004 0.68253 0.68458 0.68514 0.68248 0.67673 0.66583 0.65037 0.63229 0.61447 0.60021 0.59196 0.58933 0.59332 0.59944 0.60477 0.60651 0.60347 0.5966 0.58764 0.57856 0.57115 0.56566 0.56166 0.5576 0.55324 0.54848 0.54356 0.5384 0.53323 0.52819 0.5231 0.5174 0.51142 0.50548 0.49939 0.49373 0.48728 0.481 0.47491 0.46877 0.46331 0.45752 0.45161 0.44598 0.44064 0.43596 0.432 0.42797 0.42441 0.42093 0.41798 0.41528 0.41293 0.41041 0.40837 0.40634 0.40468 0.40317 0.40154 0.40045 0.399 0.74131 0.72479 0.70912 0.69655 0.68793 0.68245 0.67899 0.67677 0.67543 0.67483 0.67482 0.67525 0.67591 0.67653 0.67695 0.677 0.67684 0.67697 0.67787 0.68004 0.68253 0.68458 0.68514 0.68248 0.67673 0.66611 0.65043 0.6325 0.61524 0.60033 0.5913 0.58935 0.59287 0.59918 0.60452 0.60611 0.60332 0.5963 0.58747 0.57858 0.57105 0.56561 0.5616 0.55746 0.5531 0.54842 0.54338 0.53813 0.53307 0.52814 0.52297 0.51723 0.51124 0.50493 0.49932 0.49326 0.48696 0.48058 0.47446 0.46846 0.46282 0.45736 0.45132 0.44572 0.44051 0.43583 0.43156 0.42759 0.42412 0.42088 0.41786 0.41491 0.41267 0.41036 0.40822 0.4063 0.4046 0.40299 0.40148 0.40028 0.39889 0.73085 0.7149 0.69988 0.68798 0.68005 0.67529 0.67258 0.6713 0.67088 0.67095 0.67149 0.67269 0.67433 0.67632 0.67861 0.68047 0.68191 0.6834 0.68547 0.68849 0.6915 0.69349 0.69333 0.69001 0.68327 0.67076 0.65354 0.63365 0.61365 0.59688 0.58593 0.58175 0.58332 0.5876 0.59031 0.59096 0.58917 0.58416 0.57725 0.56981 0.56364 0.55904 0.55513 0.55094 0.54662 0.54209 0.53662 0.53085 0.52498 0.51924 0.51327 0.50676 0.50006 0.49348 0.48734 0.48153 0.47579 0.46977 0.4637 0.45776 0.45238 0.4475 0.44252 0.43782 0.43323 0.42925 0.42553 0.42259 0.41974 0.41675 0.41396 0.41137 0.40936 0.40695 0.4052 0.40364 0.40201 0.40053 0.39913 0.39828 0.39702 0.55734 0.54098 0.52546 0.51293 0.50425 0.49866 0.49512 0.49286 0.4915 0.49095 0.49109 0.49183 0.49302 0.49439 0.4958 0.49702 0.49815 0.49962 0.5018 0.5051 0.50854 0.5113 0.51237 0.51016 0.50501 0.495 0.48069 0.46391 0.44712 0.4335 0.42535 0.4235 0.42717 0.43377 0.43977 0.44249 0.44051 0.43434 0.42592 0.41708 0.40971 0.40456 0.40141 0.39878 0.39637 0.39359 0.39047 0.38711 0.3837 0.38042 0.37721 0.37369 0.37011 0.36681 0.36383 0.36105 0.35815 0.35519 0.35264 0.35025 0.34839 0.3465 0.34396 0.34159 0.33936 0.3374 0.33557 0.33395 0.33258 0.33097 0.32953 0.32813 0.32715 0.32586 0.32487 0.32388 0.32291 0.32203 0.32109 0.32045 0.31971 0.50242 0.48627 0.47088 0.45843 0.44977 0.44417 0.4406 0.4383 0.43692 0.43634 0.43646 0.43721 0.43841 0.43982 0.44128 0.44257 0.4438 0.44538 0.44772 0.45122 0.45489 0.45791 0.45927 0.45738 0.45256 0.44289 0.42891 0.41242 0.39591 0.38255 0.37466 0.37309 0.37706 0.38394 0.39024 0.39323 0.39152 0.38564 0.37751 0.36902 0.36204 0.35729 0.3545 0.35224 0.35024 0.34791 0.34528 0.34246 0.33958 0.33687 0.33427 0.33136 0.3284 0.32572 0.32337 0.3212 0.31889 0.3165 0.31454 0.31277 0.31155 0.31033 0.30851 0.30685 0.30534 0.30409 0.30294 0.30199 0.30126 0.30027 0.29942 0.29857 0.29815 0.29735 0.29677 0.2962 0.29564 0.29518 0.29461 0.29428 0.29378
4 0.013905 0.69437 0.6887 0.68682 0.6856 0.68485 0.68443 0.68424 0.6842 0.68431 0.68432 0.68368 0.68185 0.67849 0.6733 0.66626 0.6577 0.64865 0.64029 0.63405 0.63081 0.63066 0.6349 0.63987 0.64479 0.6465 0.64347 0.63512 0.62286 0.60915 0.59777 0.5895 0.58628 0.58779 0.59106 0.59371 0.59298 0.58873 0.58184 0.57381 0.56715 0.56213 0.55812 0.55443 0.55028 0.54541 0.54003 0.53454 0.52911 0.52439 0.51966 0.51448 0.50915 0.50356 0.4976 0.49158 0.48564 0.47893 0.47301 0.46682 0.46091 0.45555 0.44969 0.44359 0.43765 0.43277 0.42799 0.42432 0.42015 0.4167 0.41327 0.41019 0.40722 0.40501 0.40257 0.40057 0.39846 0.39684 0.39526 0.3937 0.39252 0.39113 0.69437 0.6887 0.68682 0.6856 0.68485 0.68443 0.68424 0.6842 0.68431 0.68432 0.68368 0.68185 0.67849 0.6733 0.66626 0.6577 0.64865 0.64029 0.63405 0.63081 0.63066 0.6349 0.63987 0.64479 0.64649 0.64378 0.63516 0.62307 0.6099 0.59733 0.58909 0.5861 0.58739 0.59083 0.59339 0.59274 0.58851 0.58149 0.57369 0.56703 0.56208 0.55807 0.5542 0.55009 0.54525 0.53991 0.53423 0.52899 0.52428 0.51952 0.51439 0.50891 0.50313 0.497 0.49143 0.48525 0.47881 0.47277 0.46631 0.4605 0.45495 0.44938 0.44353 0.43725 0.43252 0.42776 0.42366 0.41943 0.416 0.41287 0.40994 0.40707 0.40467 0.40244 0.40041 0.39846 0.39674 0.39512 0.39368 0.39243 0.39111 0.67671 0.67128 0.67005 0.66966 0.6698 0.67031 0.67127 0.67234 0.67335 0.67413 0.67431 0.67346 0.67128 0.66771 0.66224 0.65523 0.64772 0.64102 0.63668 0.63522 0.63663 0.6419 0.64801 0.65403 0.65664 0.6541 0.64582 0.63269 0.61757 0.60346 0.59252 0.58597 0.58376 0.58394 0.58411 0.58225 0.57752 0.57008 0.56135 0.55356 0.5475 0.54294 0.53929 0.53598 0.53211 0.52738 0.52223 0.51707 0.51227 0.50692 0.50093 0.4946 0.48806 0.48175 0.47576 0.46984 0.46361 0.45765 0.45133 0.44561 0.44044 0.43566 0.43068 0.42564 0.42159 0.41744 0.41399 0.41091 0.40817 0.40507 0.40245 0.39977 0.3977 0.39532 0.39374 0.39216 0.39051 0.38902 0.38765 0.38677 0.38555 0.50948 0.50398 0.50225 0.50107 0.50025 0.49973 0.49946 0.49937 0.49948 0.49954 0.49904 0.49753 0.49471 0.49029 0.48425 0.47689 0.46916 0.46213 0.45719 0.45511 0.45592 0.46088 0.46637 0.47175 0.47406 0.47192 0.46476 0.45357 0.44111 0.43007 0.42245 0.41962 0.42109 0.42477 0.42809 0.42839 0.4251 0.41892 0.41151 0.40497 0.40002 0.39636 0.39349 0.3909 0.38797 0.38452 0.38087 0.37733 0.3743 0.37127 0.36804 0.36477 0.36147 0.35835 0.35541 0.35245 0.3493 0.34668 0.34404 0.34181 0.34001 0.33807 0.33557 0.3328 0.33108 0.32892 0.32728 0.32548 0.32417 0.32263 0.32121 0.31977 0.31874 0.31754 0.3166 0.31559 0.31461 0.31374 0.31282 0.31215 0.31145 0.45543 0.45013 0.44854 0.44743 0.44664 0.44611 0.44581 0.44569 0.44576 0.44579 0.44528 0.44376 0.44094 0.43655 0.43054 0.42324 0.41558 0.40866 0.40385 0.40195 0.40297 0.40819 0.41396 0.41965 0.42229 0.42048 0.41363 0.40273 0.39054 0.37976 0.37241 0.36985 0.37161 0.37559 0.37919 0.37976 0.37675 0.37084 0.36374 0.35755 0.35299 0.34971 0.34719 0.34498 0.34243 0.33944 0.33628 0.33327 0.33077 0.32832 0.3257 0.32306 0.32037 0.31785 0.31554 0.3132 0.31063 0.30858 0.30652 0.30491 0.30373 0.30246 0.30065 0.2986 0.29758 0.29612 0.29517 0.29404 0.29337 0.29243 0.29159 0.2907 0.29022 0.28949 0.28897 0.28837 0.2878 0.28734 0.28678 0.28642 0.28596
5 0.032959 0.62728 0.6255 0.62438 0.62423 0.62492 0.62615 0.62765 0.62925 0.63085 0.63236 0.63368 0.63472 0.63535 0.63552 0.63517 0.63432 0.63302 0.63112 0.62839 0.62466 0.62077 0.61614 0.61153 0.60576 0.59896 0.59104 0.58258 0.57414 0.56646 0.55956 0.55344 0.54944 0.54661 0.54573 0.54596 0.54663 0.5475 0.54802 0.54775 0.54593 0.542 0.53627 0.52991 0.52356 0.51757 0.51199 0.50686 0.50206 0.49756 0.49316 0.4886 0.48388 0.4788 0.47329 0.46735 0.46123 0.4549 0.44859 0.44259 0.43695 0.43141 0.42524 0.41919 0.41406 0.40882 0.40442 0.40022 0.39653 0.39263 0.38947 0.38628 0.38344 0.38089 0.37874 0.37684 0.3747 0.37313 0.37146 0.36993 0.36872 0.36737 0.62728 0.6255 0.62438 0.62423 0.62492 0.62615 0.62765 0.62925 0.63085 0.63236 0.63368 0.63472 0.63535 0.63552 0.63517 0.63432 0.63302 0.63112 0.62839 0.62466 0.62077 0.61614 0.61153 0.60576 0.59927 0.59107 0.58283 0.57484 0.56644 0.55911 0.55322 0.54894 0.54644 0.54556 0.54556 0.54639 0.5472 0.5478 0.54768 0.54584 0.54183 0.53616 0.52963 0.52325 0.51734 0.51184 0.50653 0.50182 0.49748 0.49294 0.48841 0.48364 0.47828 0.47278 0.46693 0.46079 0.45459 0.44831 0.4425 0.43671 0.43098 0.42478 0.41922 0.41337 0.40814 0.40374 0.39978 0.39579 0.39204 0.38882 0.38579 0.38337 0.38063 0.37846 0.37657 0.37461 0.37303 0.3712 0.36997 0.36865 0.36743 0.5916 0.58984 0.58933 0.59012 0.59215 0.59464 0.59738 0.6002 0.60299 0.60582 0.6084 0.61092 0.61306 0.61481 0.616 0.61678 0.6173 0.61725 0.61627 0.61422 0.61154 0.60814 0.60451 0.59941 0.59309 0.58586 0.57843 0.57137 0.56492 0.55918 0.55405 0.54986 0.54674 0.54486 0.54379 0.54306 0.54177 0.53986 0.53673 0.53148 0.52392 0.51473 0.50567 0.49821 0.4924 0.48727 0.48267 0.47842 0.47471 0.47086 0.4666 0.46172 0.45646 0.45137 0.44572 0.43964 0.43341 0.42689 0.42087 0.41556 0.4105 0.40544 0.4008 0.39631 0.39214 0.38845 0.38522 0.38208 0.37892 0.37622 0.37332 0.37101 0.36861 0.36659 0.36496 0.36331 0.36179 0.36023 0.35894 0.358 0.35684 0.44068 0.43908 0.43812 0.43802 0.43865 0.43977 0.44119 0.44274 0.44433 0.4459 0.44739 0.44876 0.44995 0.45093 0.45161 0.45199 0.45202 0.45148 0.45007 0.44752 0.44463 0.44074 0.43667 0.43138 0.42521 0.41821 0.4109 0.4037 0.3969 0.39072 0.38541 0.38138 0.37891 0.37835 0.37922 0.38095 0.38272 0.38403 0.38426 0.38258 0.37869 0.37329 0.36773 0.36294 0.35891 0.3553 0.35199 0.34903 0.34626 0.34356 0.34095 0.33835 0.33575 0.33299 0.33001 0.32698 0.32412 0.32124 0.31884 0.31697 0.31492 0.31249 0.3102 0.30808 0.30602 0.30418 0.30255 0.30085 0.29909 0.29776 0.29631 0.29521 0.29396 0.29289 0.292 0.29095 0.29007 0.28908 0.28824 0.28757 0.2869 0.38824 0.38684 0.386 0.38597 0.38662 0.38774 0.38913 0.39065 0.39221 0.39374 0.3952 0.39654 0.39772 0.39869 0.39938 0.39977 0.39987 0.39941 0.39811 0.39572 0.39301 0.38934 0.38554 0.38054 0.37468 0.36798 0.36097 0.35404 0.34751 0.34159 0.33654 0.3328 0.33063 0.33036 0.3315 0.3335 0.33554 0.33714 0.33769 0.33636 0.33285 0.32781 0.32259 0.31817 0.31454 0.31137 0.30856 0.30612 0.30387 0.30174 0.29974 0.29776 0.29576 0.29362 0.29127 0.28884 0.28655 0.28423 0.28242 0.28113 0.27969 0.27789 0.27627 0.27486 0.27347 0.27234 0.2714 0.27037 0.26923 0.26849 0.26759 0.26703 0.26629 0.26568 0.2652 0.26456 0.26408 0.2635 0.26301 0.26266 0.26221
6 0.064373 0.55114 0.54963 0.54908 0.54953 0.55084 0.55275 0.55497 0.55742 0.55996 0.56245 0.56474 0.56673 0.5683 0.56939 0.56985 0.56948 0.56793 0.56619 0.56392 0.56225 0.56049 0.55876 0.55706 0.55518 0.55294 0.55058 0.54731 0.54414 0.54069 0.53734 0.53352 0.52942 0.52504 0.51975 0.51349 0.50697 0.50055 0.49489 0.49061 0.48778 0.48612 0.48509 0.48365 0.48169 0.47901 0.47568 0.47159 0.46722 0.46286 0.45832 0.45361 0.44841 0.44244 0.43624 0.43061 0.42497 0.41945 0.41384 0.40787 0.40205 0.39574 0.39019 0.38477 0.37939 0.37453 0.36972 0.36544 0.36146 0.35813 0.3548 0.35201 0.3493 0.34685 0.3446 0.34268 0.34067 0.33905 0.33736 0.33622 0.33478 0.33352 0.55013 0.54859 0.54788 0.54814 ...Graph Mean Values:
st_title = ['MEAN(MN\_V\_U\_GAIN\_CHECK(A,Z)), welf\_checks=' num2str(welf_checks) ', TR=' num2str(mp_params('TR')) ''];
mp_support_graph('cl_st_graph_title') = {st_title};
mp_support_graph('cl_st_ytitle') = {'MEAN(MN\_V\_U\_GAIN\_CHECK(a,z))'};
ff_graph_grid((tb_az_v{1:end, 3:end})', ar_st_eta_HS_grid, agrid, mp_support_graph);
Graph Mean Consumption (MPC: Share of Check Consumed):
st_title = ['MEAN(MN\_MPC\_U\_GAIN\_CHECK(A,Z)), welf\_checks=' num2str(welf_checks) ', TR=' num2str(mp_params('TR')) ''];
mp_support_graph('cl_st_graph_title') = {st_title};
mp_support_graph('cl_st_ytitle') = {'MEAN(MN\_MPC\_U\_GAIN\_CHECK(a,z))'};
ff_graph_grid((tb_az_c{1:end, 3:end})', ar_st_eta_HS_grid, agrid, mp_support_graph);
1.5 Analyze Marginal Value and MPC over Y(a,eta), Conditional On Kids, Marry, Age, Education
Income is generated by savings and shocks, what are the income levels generated by all the shock and savings points conditional on kids, marital status, age and educational levels. Plot on the Y axis MPC, and plot on the X axis income levels, use colors to first distinguish between different a levels, then use colors to distinguish between different eta levles.
Set Up date, Select Age 37vn
, unmarried, no kids, lower education:
% NaN(n_jgrid,n_agrid,n_etagrid,n_educgrid,n_marriedgrid,n_kidsgrid);
% 38 year old, unmarried, no kids, lower educated
% Only Household Head Shock Matters so select up to 'n_eta_H_grid'
mn_total_inc_jemk_ss = total_inc_ss(19,:,1:mp_params('n_eta_H_grid'),1,1,1);
mn_V_W_gain_check_use_07 = ev07_jaeemk_check2 - ev07_jaeemk_check0;
mn_C_W_gain_check_use_07 = ec07_jaeemk_check2 - ec07_jaeemk_check0;Select Age, Education, Marital, Kids Count:s
% Selections
it_age = 21; % +18
it_marital = 1; % 1 = unmarried
it_kids = 1; % 1 = kids is zero
it_educ = 1; % 1 = lower education
% Select: NaN(n_jgrid,n_agrid,n_etagrid,n_educgrid,n_marriedgrid,n_kidsgrid);
mn_C_W_gain_check_jemk_07 = mn_C_W_gain_check_use_07(it_age, :, 1:mp_params('n_eta_H_grid'), it_educ, it_marital, it_kids);
mn_V_W_gain_check_jemk_07 = mn_V_W_gain_check_use_07(it_age, :, 1:mp_params('n_eta_H_grid'), it_educ, it_marital, it_kids);
% Reshape, so shock is the first dim, a is the second
mt_total_inc_jemk = permute(mn_total_inc_jemk_ss,[3,2,1]);
mt_C_W_gain_check_jemk_07 = permute(mn_C_W_gain_check_jemk_07,[3,2,1]);
mt_C_W_gain_check_jemk_07(mt_C_W_gain_check_jemk_07<=1e-10) = 1e-10;
mt_V_W_gain_check_jemk_07 = permute(mn_V_W_gain_check_jemk_07,[3,2,1]);
mt_V_W_gain_check_jemk_07(mt_V_W_gain_check_jemk_07<=1e-10) = 1e-10;
% Generate meshed a and shock grid
[mt_eta_H, mt_a] = ndgrid(eta_H_grid(1:mp_params('n_eta_H_grid')), agrid);1.6 Marginal Value Gains, Color as Shock, Conditional on Age, Marital, Kids, and Education
How do shocks and a impact marginal value. First plot one asset level, variation comes only from increasingly higher shocks:
figure();
it_a = 1;
scatter((mt_total_inc_jemk(:,it_a)), (mt_V_W_gain_check_jemk_07(:,it_a)), 100);
title({'MN\_V\_W\_GAIN\_CHECK(Y(A, eta)), Lowest A, J38M0E0K0', ...
'Each Circle is A Different Shock Level'});
xlabel('Y(a,eta) = Spouse + Household head Income Joint');
ylabel('MN\_V\_W\_GAIN\_CHECK(A, eta)');
grid on;
grid minor;
figure();
it_shock = 1;
scatter(log(mt_total_inc_jemk(:,it_a)), log(mt_V_W_gain_check_jemk_07(:,it_a)), 100);
title({'MN\_V\_W\_GAIN\_CHECK(Y(A, eta)), Lowest A, J38M0E0K0', ...
'Each Circle is A Different Shock Level'});
xlabel(' of Y(a,eta) = Spouse + Household head Income Joint');
ylabel(' of MN\_V\_W\_GAIN\_CHECK(A, eta)');
grid on;
grid minor;
Plot all asset levels:
figure();
scatter((mt_total_inc_jemk(:)), (mt_V_W_gain_check_jemk_07(:)), 100, mt_a(:));
title({'(MN\_V\_W\_GAIN\_CHECK(Y,eta)), All A (Savings) Levels, J38M0E0K0', ...
'Color Represent different A Savings State, Circle-Group=Shock'});
xlabel('income(a,eps)');
ylabel('MN\_V\_W\_GAIN\_CHECK(EM,J)');
grid on;
grid minor;
figure();
scatter((mt_total_inc_jemk(:)), log(mt_V_W_gain_check_jemk_07(:)), 100, mt_a(:));
title({'(MN\_V\_W\_GAIN\_CHECK(Y,eta)), All A (Savings) Levels, J38M0E0K0', ...
'Color Represent different A Savings State, Circle-Group=Shock'});
xlabel('income(a,eps)');
ylabel('log of (MN\_V\_W\_GAIN\_CHECK(EM,J))');
xlim([0,7]);
grid on;
grid minor;
1.7 Marginal Consumption Gains, Color as Shock, Conditional on Age, Marital, Kids, and Education
How do shocks and a impact marginal value. First plot one asset level, variation comes only from increasingly higher shocks:
figure();
it_a = 50;
scatter(log(mt_total_inc_jemk(:,it_a)), mt_C_W_gain_check_jemk_07(:,it_a), 100);
title({'MN\_C\_W\_GAIN\_CHECK(Y(A, eta)), Given A Savings Level, J38M0E0K0', ...
'Each Circle is A Different shock Level'});
xlabel('Y(a,eta) = Spouse + Household head Income Joint');
ylabel('MN\_C\_W\_GAIN\_CHECK(A, eta)');
grid on;
grid minor;
Plot all asset levels:
figure();
scatter((mt_total_inc_jemk(:)), (mt_C_W_gain_check_jemk_07(:)), 100, mt_a(:));
title({'(MN\_C\_W\_GAIN\_CHECK(Y,eta)), All A (Savings) Levels, J38M0E0K0', ...
'Color Represent different A Savings State, Circle-Group=Shock'});
xlabel('income(a,eps)');
ylabel('MN\_C\_W\_GAIN\_CHECK(EM,J)');
grid on;
grid minor;
figure();
scatter(log(mt_total_inc_jemk(:)), log(mt_C_W_gain_check_jemk_07(:)), 100, mt_a(:));
title({'(MN\_C\_W\_GAIN\_CHECK(Y,eta)), All A (Savings) Levels, J38M0E0K0', ...
'Color Represent different A Savings State, Circle-Group=Shock'});
xlabel('log of income(a,eps)');
ylabel('log of (MN\_V\_W\_GAIN\_CHECK(EM,J))');
grid on;
grid minor;
1.8 Analyze Kids and Marriage and Age
Aggregating over education, savings, and shocks, what are the differential effects of Marriage and Age.
% Generate some Data
mp_support_graph = containers.Map('KeyType', 'char', 'ValueType', 'any');
ar_row_grid = [...
"k0M0", "K1M0", "K2M0", "K3M0", "K4M0", ...
"k0M1", "K1M1", "K2M1", "K3M1", "K4M1"];
mp_support_graph('cl_st_xtitle') = {'Age'};
mp_support_graph('st_legend_loc') = 'best';
mp_support_graph('bl_graph_logy') = true; % do not log
mp_support_graph('st_rounding') = '6.2f'; % format shock legend
mp_support_graph('cl_scatter_shapes') = {...
'o', 'd' ,'s', 'x', '*', ...
'o', 'd', 's', 'x', '*'};
mp_support_graph('cl_colors') = {...
'red', 'red', 'red', 'red', 'red'...
'blue', 'blue', 'blue', 'blue', 'blue'};MEAN(VAL(KM,J)), MEAN(AP(KM,J)), MEAN(C(KM,J))
Tabulate value and policies:
% Set
% NaN(n_jgrid,n_agrid,n_etagrid,n_educgrid,n_marriedgrid,n_kidsgrid);
ar_permute = [2,3,4,1,6,5];
% Value Function
st_title = ['MEAN(MN_V_U_GAIN_CHECK(KM,J)), welf_checks=' num2str(welf_checks) ', TR=' num2str(mp_params('TR'))];
tb_az_v = ff_summ_nd_array(st_title, mn_V_U_gain_check_07, true, ["mean"], 3, 1, cl_mp_datasetdesc, ar_permute);
xxx MEAN(MN_V_U_GAIN_CHECK(KM,J)), welf_checks=2, TR=0.0018238 xxxxxxxxxxxxxxxxxxxxxxxxxxx
group kids marry mean_age_18 mean_age_19 mean_age_20 mean_age_21 mean_age_22 mean_age_23 mean_age_24 mean_age_25 mean_age_26 mean_age_27 mean_age_28 mean_age_29 mean_age_30 mean_age_31 mean_age_32 mean_age_33 mean_age_34 mean_age_35 mean_age_36 mean_age_37 mean_age_38 mean_age_39 mean_age_40 mean_age_41 mean_age_42 mean_age_43 mean_age_44 mean_age_45 mean_age_46 mean_age_47 mean_age_48 mean_age_49 mean_age_50 mean_age_51 mean_age_52 mean_age_53 mean_age_54 mean_age_55 mean_age_56 mean_age_57 mean_age_58 mean_age_59 mean_age_60 mean_age_61 mean_age_62 mean_age_63 mean_age_64 mean_age_65 mean_age_66 mean_age_67 mean_age_68 mean_age_69 mean_age_70 mean_age_71 mean_age_72 mean_age_73 mean_age_74 mean_age_75 mean_age_76 mean_age_77 mean_age_78 mean_age_79 mean_age_80 mean_age_81 mean_age_82 mean_age_83 mean_age_84 mean_age_85 mean_age_86 mean_age_87 mean_age_88 mean_age_89 mean_age_90 mean_age_91 mean_age_92 mean_age_93 mean_age_94 mean_age_95 mean_age_96 mean_age_97 mean_age_98 mean_age_99
_____ ____ _____ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________
1 1 0 0.031908 0.030377 0.028045 0.025708 0.023751 0.0221 0.020698 0.019501 0.018475 0.017591 0.016828 0.016166 0.015591 0.015092 0.014657 0.01428 0.013952 0.013668 0.013423 0.013213 0.013033 0.012881 0.012755 0.012651 0.012567 0.012502 0.012455 0.012423 0.012406 0.012403 0.012412 0.012433 0.012465 0.012506 0.012557 0.012618 0.012688 0.012767 0.012854 0.012949 0.013053 0.013163 0.01328 0.01341 0.013516 0.013047 0.0094497 0.014632 0.014515 0.014397 0.014275 0.01415 0.014024 0.013896 0.013765 0.01363 0.01349 0.013346 0.0132 0.013049 0.012894 0.012737 0.01258 0.01242 0.012266 0.012114 0.011955 0.011798 0.01163 0.011473 0.011342 0.011242 0.011174 0.011105 0.011053 0.011012 0.010979 0.010927 0.010835 0.010697 0.010401 0.0098008
2 2 0 0.043916 0.04186 0.038596 0.035292 0.032514 0.030161 0.028153 0.026428 0.024939 0.023646 0.02252 0.021535 0.020672 0.019912 0.019244 0.018653 0.018132 0.017673 0.017267 0.016909 0.016593 0.016317 0.016075 0.015864 0.015682 0.015526 0.015394 0.015283 0.015193 0.015122 0.015068 0.015031 0.015009 0.015002 0.015009 0.015031 0.015068 0.015119 0.015185 0.015266 0.015363 0.015477 0.015606 0.015711 0.01574 0.015454 0.010609 0.016996 0.016844 0.016689 0.016532 0.016375 0.016216 0.016054 0.01589 0.015722 0.015551 0.015383 0.015217 0.01505 0.014878 0.014706 0.014533 0.014359 0.014175 0.013993 0.013827 0.01367 0.013529 0.013394 0.013264 0.013164 0.013057 0.012964 0.01287 0.012797 0.012701 0.012636 0.012536 0.012415 0.012226 0.011807
3 3 0 0.051104 0.04891 0.044943 0.04117 0.038001 0.035317 0.033027 0.031062 0.029364 0.027891 0.026608 0.025486 0.024501 0.023635 0.022871 0.022197 0.021601 0.021074 0.020608 0.020196 0.019833 0.019513 0.019233 0.018987 0.018774 0.018591 0.018434 0.018302 0.018194 0.018107 0.01804 0.017992 0.017962 0.01795 0.017956 0.017979 0.01802 0.01808 0.01816 0.018261 0.018382 0.018526 0.018688 0.018822 0.018863 0.018449 0.012272 0.020246 0.020082 0.01992 0.019756 0.019594 0.019432 0.019271 0.019111 0.01895 0.018786 0.018616 0.018449 0.018279 0.018101 0.017917 0.017735 0.017562 0.0174 0.017267 0.017142 0.017016 0.016909 0.016808 0.016677 0.016553 0.016442 0.016336 0.01624 0.016141 0.016037 0.015952 0.015885 0.015826 0.015756 0.015342
4 4 0 0.057927 0.055555 0.051064 0.046812 0.043241 0.040216 0.037636 0.035422 0.033509 0.031849 0.030403 0.029138 0.028028 0.027051 0.02619 0.02543 0.024758 0.024164 0.023638 0.023174 0.022764 0.022404 0.022088 0.021811 0.021572 0.021366 0.02119 0.021043 0.020923 0.020828 0.020756 0.020707 0.020678 0.020671 0.020684 0.020719 0.020776 0.020856 0.020959 0.021087 0.021239 0.021415 0.021609 0.021774 0.021804 0.021164 0.01392 0.023339 0.023161 0.022983 0.022805 0.022627 0.022452 0.022278 0.022105 0.021932 0.021756 0.021578 0.021403 0.021225 0.021047 0.020867 0.020694 0.020537 0.020394 0.020254 0.020125 0.020005 0.019914 0.019822 0.019743 0.019684 0.019585 0.019481 0.019391 0.019286 0.019185 0.019064 0.018962 0.018877 0.018694 0.018188
5 5 0 0.06325 0.060842 0.055977 0.051401 0.047557 0.044303 0.041529 0.03915 0.037097 0.035317 0.033767 0.032413 0.031226 0.030183 0.029265 0.028455 0.027741 0.027111 0.026554 0.026064 0.025633 0.025254 0.024924 0.024636 0.024388 0.024176 0.023998 0.02385 0.023732 0.023641 0.023576 0.023536 0.023519 0.023526 0.023556 0.02361 0.02369 0.023794 0.023925 0.024081 0.024261 0.024463 0.02468 0.024878 0.024909 0.024017 0.015797 0.026641 0.026458 0.026277 0.026094 0.025907 0.025718 0.025531 0.025347 0.025155 0.024952 0.024746 0.024541 0.024328 0.024112 0.023898 0.02369 0.023504 0.023345 0.023207 0.023081 0.02296 0.022842 0.022734 0.022665 0.022588 0.022537 0.022486 0.022381 0.022287 0.022184 0.022069 0.021922 0.021741 0.02144 0.020713
6 1 1 0.005762 0.0053279 0.0048412 0.0043955 0.0040141 0.0036902 0.003409 0.0031673 0.0029621 0.0027884 0.00264 0.002513 0.0024067 0.0023175 0.0022411 0.0021754 0.0021201 0.0020744 0.0020376 0.0020089 0.0019876 0.001973 0.0019648 0.0019624 0.0019657 0.0019743 0.0019882 0.0020071 0.002031 0.0020597 0.0020934 0.002132 0.0021755 0.0022243 0.0022788 0.0023393 0.0024062 0.0024789 0.0025594 0.0026497 0.0027523 0.0028693 0.0030054 0.0031693 0.0033734 0.0035763 0.003712 0.0056096 0.0056907 0.0057721 0.0058534 0.0059362 0.0060213 0.0060931 0.0061612 0.0062188 0.0062674 0.0063194 0.0063619 0.0064066 0.0064424 0.0064683 0.00648 0.0064851 0.0064864 0.0064906 0.0064964 0.0064921 0.0064801 0.0064745 0.006485 0.0064918 0.0064922 0.0064913 0.006484 0.0064666 0.0064459 0.0064241 0.00638 0.0063004 0.0061431 0.0056628
7 2 1 0.0081705 0.0075587 0.0068473 0.0061989 0.005658 0.0051977 0.0047997 0.0044575 0.0041644 0.0039084 0.0036843 0.0034908 0.0033249 0.0031825 0.0030596 0.0029537 0.002863 0.0027861 0.0027215 0.0026683 0.0026253 0.0025917 0.0025667 0.0025495 0.0025397 0.002537 0.0025411 0.0025517 0.0025687 0.0025919 0.0026213 0.0026567 0.0026983 0.0027461 0.0028005 0.0028622 0.0029325 0.0030108 0.0030973 0.0031933 0.0033018 0.0034252 0.0035671 0.0037328 0.003938 0.0041358 0.0041162 0.0061558 0.006242 0.0063293 0.0064142 0.0064977 0.006576 0.0066486 0.0067164 0.0067793 0.0068365 0.0068895 0.006932 0.0069705 0.0070118 0.0070462 0.0070648 0.0070675 0.0070792 0.0070993 0.0071092 0.0071147 0.00712 0.0071274 0.0071306 0.0071278 0.0071135 0.0071011 0.0070937 0.007081 0.007075 0.0070735 0.0070479 0.0069785 0.0068067 0.0063252
8 3 1 0.0099025 0.0091765 0.0083275 0.0075396 0.0068765 0.0063167 0.0058397 0.0054356 0.0050891 0.004789 0.0045267 0.0042981 0.0041005 0.0039299 0.0037817 0.0036527 0.0035414 0.0034464 0.0033665 0.0033004 0.0032467 0.0032045 0.0031726 0.0031503 0.003137 0.0031323 0.0031357 0.003147 0.0031662 0.0031929 0.0032268 0.0032678 0.0033156 0.00337 0.0034317 0.0035016 0.0035799 0.0036672 0.0037644 0.0038716 0.0039903 0.004124 0.0042772 0.0044541 0.0046704 0.0048436 0.0045867 0.006773 0.0068727 0.0069705 0.0070702 0.0071641 0.0072445 0.0073244 0.0074034 0.0074806 0.0075568 0.0076246 0.0076857 0.0077304 0.0077747 0.0078186 0.0078607 0.007892 0.0079176 0.00795 0.0079823 0.0080042 0.0080285 0.0080547 0.0080733 0.0080897 0.0080947 0.0080851 0.0080739 0.0080785 0.0080835 0.0080945 0.0080947 0.0080388 0.0078724 0.0073638
9 4 1 0.012339 0.011465 0.01043 0.0094589 0.008631 0.0079256 0.0073234 0.006814 0.0063754 0.0059955 0.0056685 0.0053867 0.0051428 0.0049301 0.0047442 0.0045814 0.0044406 0.00432 0.0042176 0.0041319 0.0040613 0.0040043 0.0039598 0.0039269 0.0039049 0.0038932 0.0038912 0.0038985 0.0039149 0.0039401 0.0039739 0.0040161 0.0040662 0.0041237 0.0041893 0.0042644 0.0043494 0.0044459 0.0045551 0.0046763 0.0048091 0.0049557 0.005122 0.0053132 0.0055267 0.005675 0.0050931 0.0073946 0.0075071 0.007618 0.0077306 0.0078407 0.0079374 0.0080237 0.0081134 0.0081995 0.0082882 0.0083745 0.0084519 0.0085099 0.00856 0.008619 0.0086758 0.0087206 0.0087531 0.008795 0.0088396 0.0088761 0.0089092 0.0089474 0.0089825 0.0090061 0.0090256 0.0090269 0.009021 0.0090281 0.0090421 0.0090582 0.0090687 0.0090197 0.0088404 0.0082615
10 5 1 0.015374 0.014388 0.013133 0.01196 0.010966 0.01013 0.0094148 0.0088033 0.0082715 0.0078058 0.0074009 0.0070508 0.0067458 0.0064773 0.0062437 0.0060412 0.0058663 0.0057162 0.0055881 0.0054805 0.0053916 0.00532 0.005264 0.0052224 0.0051945 0.0051793 0.0051762 0.0051849 0.0052049 0.0052361 0.0052779 0.0053296 0.0053913 0.0054625 0.0055435 0.005634 0.0057348 0.0058479 0.0059737 0.0061118 0.0062611 0.0064224 0.0065978 0.0067894 0.006998 0.0071029 0.0059534 0.0085898 0.0087069 0.0088218 0.0089374 0.0090544 0.0091714 0.0092787 0.0093835 0.009478 0.0095666 0.0096645 0.0097624 0.0098449 0.009899 0.0099594 0.010021 0.010076 0.010125 0.010182 0.01024 0.010281 0.010316 0.010346 0.010371 0.01038 0.010401 0.010416 0.010419 0.010423 0.010446 0.01047 0.010474 0.01042 0.010197 0.0094983
% Consumption Function
st_title = ['MEAN(MN_MPC_U_GAIN_CHECK(KM,J)), welf_checks=' num2str(welf_checks) ', TR=' num2str(mp_params('TR'))];
tb_az_c = ff_summ_nd_array(st_title, mn_MPC_U_gain_share_check_07, true, ["mean"], 3, 1, cl_mp_datasetdesc, ar_permute);
xxx MEAN(MN_MPC_U_GAIN_CHECK(KM,J)), welf_checks=2, TR=0.0018238 xxxxxxxxxxxxxxxxxxxxxxxxxxx
group kids marry mean_age_18 mean_age_19 mean_age_20 mean_age_21 mean_age_22 mean_age_23 mean_age_24 mean_age_25 mean_age_26 mean_age_27 mean_age_28 mean_age_29 mean_age_30 mean_age_31 mean_age_32 mean_age_33 mean_age_34 mean_age_35 mean_age_36 mean_age_37 mean_age_38 mean_age_39 mean_age_40 mean_age_41 mean_age_42 mean_age_43 mean_age_44 mean_age_45 mean_age_46 mean_age_47 mean_age_48 mean_age_49 mean_age_50 mean_age_51 mean_age_52 mean_age_53 mean_age_54 mean_age_55 mean_age_56 mean_age_57 mean_age_58 mean_age_59 mean_age_60 mean_age_61 mean_age_62 mean_age_63 mean_age_64 mean_age_65 mean_age_66 mean_age_67 mean_age_68 mean_age_69 mean_age_70 mean_age_71 mean_age_72 mean_age_73 mean_age_74 mean_age_75 mean_age_76 mean_age_77 mean_age_78 mean_age_79 mean_age_80 mean_age_81 mean_age_82 mean_age_83 mean_age_84 mean_age_85 mean_age_86 mean_age_87 mean_age_88 mean_age_89 mean_age_90 mean_age_91 mean_age_92 mean_age_93 mean_age_94 mean_age_95 mean_age_96 mean_age_97 mean_age_98 mean_age_99
_____ ____ _____ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________
1 1 0 0.078069 0.086102 0.087377 0.085109 0.082559 0.080767 0.07873 0.077117 0.075492 0.07432 0.073127 0.072205 0.071201 0.07035 0.069594 0.068988 0.06847 0.067978 0.067589 0.067243 0.06689 0.06671 0.066431 0.066338 0.066143 0.06609 0.066013 0.066028 0.066126 0.066113 0.066306 0.066495 0.066813 0.067178 0.067577 0.06802 0.068617 0.069298 0.070087 0.070959 0.072196 0.073563 0.075491 0.077951 0.081722 0.093897 0.092723 0.1268 0.13006 0.13335 0.13566 0.13855 0.14224 0.14502 0.14801 0.15117 0.15458 0.1583 0.16224 0.16646 0.17112 0.17651 0.18245 0.18895 0.19435 0.20086 0.20798 0.21588 0.22435 0.23451 0.24458 0.25648 0.27051 0.28656 0.30061 0.32101 0.34085 0.37187 0.40959 0.47436 0.60097 0.99996
2 2 0 0.088091 0.096475 0.099705 0.096801 0.094582 0.092454 0.090527 0.08901 0.087428 0.086529 0.085406 0.084508 0.083799 0.083165 0.08265 0.082251 0.08198 0.081513 0.081145 0.08108 0.080841 0.080584 0.080561 0.080339 0.080366 0.080134 0.080071 0.079989 0.079909 0.079918 0.079964 0.080204 0.08035 0.080618 0.080936 0.08139 0.081735 0.082408 0.082886 0.083785 0.084899 0.086132 0.087788 0.089687 0.092844 0.10379 0.10485 0.15361 0.15635 0.1591 0.1614 0.16416 0.16737 0.16993 0.17268 0.17564 0.17889 0.18268 0.18702 0.19168 0.19652 0.2009 0.20635 0.21206 0.21709 0.22278 0.22961 0.23713 0.24462 0.25426 0.26432 0.2757 0.28802 0.30288 0.3174 0.3354 0.35711 0.38688 0.42627 0.49219 0.61465 0.99996
3 3 0 0.096309 0.10647 0.11111 0.10818 0.10451 0.10207 0.1001 0.097812 0.09648 0.094761 0.093751 0.092504 0.091499 0.090721 0.090226 0.089651 0.089295 0.089148 0.088721 0.088749 0.088662 0.088387 0.088508 0.088375 0.088443 0.088422 0.088383 0.088413 0.088476 0.088525 0.088659 0.088791 0.089172 0.089281 0.089701 0.090064 0.090596 0.091231 0.091883 0.092695 0.093665 0.094791 0.096219 0.097927 0.10118 0.11269 0.11588 0.1673 0.16987 0.17257 0.17541 0.17841 0.18156 0.18483 0.18829 0.19196 0.19589 0.20004 0.20447 0.20865 0.21314 0.21724 0.22272 0.2288 0.23564 0.2433 0.25167 0.25988 0.26789 0.27797 0.28924 0.3009 0.31178 0.32607 0.34221 0.35742 0.3803 0.40733 0.4467 0.50738 0.63072 0.99996
4 4 0 0.10137 0.11245 0.11806 0.11424 0.11063 0.1079 0.10493 0.1027 0.10134 0.098884 0.098181 0.096517 0.095399 0.094556 0.093826 0.09329 0.092955 0.092801 0.092339 0.092264 0.092286 0.09213 0.09219 0.09217 0.092133 0.092333 0.092235 0.092295 0.092371 0.092403 0.092525 0.092609 0.092989 0.092999 0.093358 0.093856 0.094241 0.09474 0.095202 0.095783 0.096533 0.09756 0.098766 0.10042 0.10373 0.11688 0.12067 0.17015 0.17263 0.17528 0.17809 0.18105 0.18421 0.18752 0.19103 0.19476 0.19871 0.20298 0.20713 0.21064 0.21494 0.22007 0.22597 0.23272 0.24034 0.24861 0.25729 0.26459 0.27458 0.28498 0.29626 0.30701 0.31836 0.33278 0.3473 0.3626 0.38292 0.40902 0.44616 0.50379 0.62262 0.99996
5 5 0 0.10569 0.11834 0.12441 0.11996 0.11559 0.11262 0.10956 0.10628 0.10445 0.1022 0.10048 0.098874 0.097407 0.096582 0.095566 0.094834 0.094282 0.093923 0.093396 0.093287 0.093117 0.092929 0.093056 0.092966 0.092822 0.09294 0.092892 0.093068 0.093087 0.093187 0.093269 0.093356 0.093586 0.093792 0.094082 0.094645 0.095102 0.095437 0.095818 0.096316 0.097015 0.098068 0.099339 0.10112 0.10464 0.11842 0.1225 0.16936 0.17176 0.17425 0.17693 0.17976 0.1827 0.18584 0.18923 0.19282 0.19663 0.20074 0.20398 0.20745 0.21206 0.21732 0.22346 0.23046 0.23822 0.2465 0.25456 0.26247 0.27246 0.28317 0.2947 0.30509 0.31658 0.3305 0.34503 0.35958 0.3796 0.40291 0.43747 0.49343 0.61617 0.99996
6 1 1 0.091639 0.097614 0.095796 0.09274 0.094336 0.09373 0.093919 0.096512 0.096935 0.0949 0.092119 0.088152 0.082991 0.081448 0.08265 0.083788 0.085636 0.085849 0.085144 0.084232 0.083582 0.08323 0.082557 0.081871 0.081256 0.080302 0.080495 0.079529 0.078838 0.078922 0.078429 0.077727 0.077877 0.077663 0.077578 0.077361 0.076374 0.074457 0.074348 0.075412 0.077061 0.077994 0.078939 0.080666 0.082149 0.084417 0.08413 0.10689 0.11371 0.11523 0.12365 0.12879 0.12989 0.12399 0.12407 0.11595 0.11897 0.12811 0.13643 0.14596 0.15588 0.15301 0.14793 0.15431 0.1698 0.18028 0.17324 0.19281 0.20495 0.21845 0.22882 0.23647 0.2524 0.26677 0.27995 0.29255 0.31641 0.34686 0.38608 0.4562 0.58808 0.99997
7 2 1 0.098891 0.10394 0.10413 0.10026 0.097592 0.097894 0.095839 0.093721 0.093869 0.096087 0.097758 0.097439 0.095911 0.095047 0.093894 0.092277 0.092409 0.092203 0.091505 0.090771 0.090094 0.089168 0.089067 0.088422 0.088549 0.088069 0.088302 0.087686 0.087248 0.087107 0.08655 0.086364 0.086177 0.086405 0.087161 0.087832 0.087556 0.085936 0.084745 0.084842 0.085541 0.085936 0.085121 0.08533 0.088656 0.092314 0.094609 0.12268 0.12125 0.12542 0.12868 0.12385 0.12638 0.12944 0.13321 0.13796 0.1343 0.14008 0.14076 0.15097 0.1604 0.15947 0.16325 0.16861 0.18443 0.19303 0.18883 0.20371 0.21793 0.22941 0.23945 0.24814 0.26258 0.27254 0.28889 0.30249 0.32542 0.35545 0.39668 0.46362 0.59654 0.99997
8 3 1 0.10228 0.10811 0.10782 0.10839 0.10652 0.10731 0.10359 0.10036 0.098628 0.098137 0.096914 0.09509 0.095163 0.095329 0.096677 0.097223 0.099076 0.099204 0.099851 0.098927 0.099101 0.098414 0.098337 0.097697 0.09759 0.096997 0.096946 0.096296 0.096081 0.095414 0.09441 0.093798 0.092811 0.092242 0.092366 0.091277 0.090565 0.089864 0.088943 0.088335 0.088579 0.09021 0.091675 0.092382 0.096412 0.099931 0.1021 0.12872 0.13197 0.13297 0.13369 0.13036 0.1247 0.13086 0.13984 0.14709 0.153 0.15351 0.14996 0.15211 0.1628 0.16706 0.17588 0.18396 0.19698 0.20489 0.20876 0.21726 0.23166 0.2411 0.25044 0.26284 0.27478 0.28146 0.29875 0.31668 0.33898 0.3677 0.40856 0.47186 0.60345 0.99997
9 4 1 0.10459 0.11283 0.11208 0.11053 0.10913 0.10771 0.10849 0.1077 0.1048 0.10324 0.10131 0.10058 0.099204 0.097342 0.095981 0.09514 0.095595 0.095642 0.096159 0.095849 0.096264 0.095997 0.095929 0.09602 0.095639 0.095607 0.095184 0.094893 0.094589 0.094173 0.093514 0.093029 0.092684 0.092379 0.092777 0.092491 0.092564 0.093725 0.094782 0.094925 0.095522 0.096738 0.098445 0.098833 0.099295 0.10531 0.10561 0.12946 0.14014 0.13557 0.13796 0.14086 0.12785 0.13004 0.14197 0.14458 0.16066 0.16005 0.15855 0.15021 0.16268 0.17474 0.17786 0.18446 0.19997 0.21091 0.21481 0.22283 0.23346 0.24597 0.25477 0.26823 0.27851 0.28907 0.29995 0.31991 0.34395 0.371 0.41032 0.47114 0.60349 0.99997
10 5 1 0.11468 0.12506 0.12335 0.12035 0.11807 0.11752 0.11373 0.11058 0.10833 0.1073 0.10446 0.10206 0.10217 0.10244 0.10148 0.10071 0.099862 0.10031 0.10076 0.10056 0.10081 0.10043 0.10045 0.10045 0.10011 0.10007 0.099776 0.099657 0.098951 0.098471 0.097656 0.096522 0.095803 0.095045 0.094605 0.094012 0.093773 0.094498 0.095692 0.096656 0.097292 0.098634 0.10035 0.10289 0.10467 0.11042 0.11065 0.1308 0.13086 0.13264 0.13851 0.14268 0.14655 0.14263 0.14848 0.14292 0.15406 0.16213 0.16615 0.1567 0.16645 0.18342 0.18928 0.18929 0.20299 0.2153 0.22176 0.227 0.23607 0.24903 0.25786 0.2686 0.2807 0.29212 0.29982 0.31952 0.34252 0.36844 0.40994 0.47024 0.59898 0.99998 Graph Mean Values:
st_title = ['MEAN(MN\_V\_U\_GAIN\_CHECK(KM,J)), welf\_checks=' num2str(welf_checks) ', TR=' num2str(mp_params('TR')) ''];
mp_support_graph('cl_st_graph_title') = {st_title};
mp_support_graph('cl_st_ytitle') = {'MEAN(MN\_V\_U\_GAIN\_CHECK(KM,J))'};
ff_graph_grid((tb_az_v{1:end, 4:end}), ar_row_grid, age_grid, mp_support_graph);
Graph Mean Consumption (MPC: Share of Check Consumed):
st_title = ['MEAN(MN\_MPC\_U\_GAIN\_CHECK(KM,J)), welf\_checks=' num2str(welf_checks) ', TR=' num2str(mp_params('TR')) ''];
mp_support_graph('cl_st_graph_title') = {st_title};
mp_support_graph('cl_st_ytitle') = {'MEAN(MN\_MPC\_U\_GAIN\_CHECK(KM,J))'};
ff_graph_grid((tb_az_c{1:end, 4:end}), ar_row_grid, age_grid, mp_support_graph);
1.9 Analyze Education and Marriage
Aggregating over education, savings, and shocks, what are the differential effects of Marriage and Age.
% Generate some Data
mp_support_graph = containers.Map('KeyType', 'char', 'ValueType', 'any');
ar_row_grid = ["E0M0", "E1M0", "E0M1", "E1M1"];
mp_support_graph('cl_st_xtitle') = {'Age'};
mp_support_graph('st_legend_loc') = 'best';
mp_support_graph('bl_graph_logy') = true; % do not log
mp_support_graph('st_rounding') = '6.2f'; % format shock legend
mp_support_graph('cl_scatter_shapes') = {'*', 'p', '*','p' };
mp_support_graph('cl_colors') = {'red', 'red', 'blue', 'blue'};MEAN(VAL(EM,J)), MEAN(AP(EM,J)), MEAN(C(EM,J))
Tabulate value and policies:
% Set
% NaN(n_jgrid,n_agrid,n_etagrid,n_educgrid,n_marriedgrid,n_kidsgrid);
ar_permute = [2,3,6,1,4,5];
% Value Function
st_title = ['MEAN(MN_V_U_GAIN_CHECK(EM,J)), welf_checks=' num2str(welf_checks) ', TR=' num2str(mp_params('TR'))];
tb_az_v = ff_summ_nd_array(st_title, mn_V_U_gain_check_07, true, ["mean"], 3, 1, cl_mp_datasetdesc, ar_permute);
xxx MEAN(MN_V_U_GAIN_CHECK(EM,J)), welf_checks=2, TR=0.0018238 xxxxxxxxxxxxxxxxxxxxxxxxxxx
group edu marry mean_age_18 mean_age_19 mean_age_20 mean_age_21 mean_age_22 mean_age_23 mean_age_24 mean_age_25 mean_age_26 mean_age_27 mean_age_28 mean_age_29 mean_age_30 mean_age_31 mean_age_32 mean_age_33 mean_age_34 mean_age_35 mean_age_36 mean_age_37 mean_age_38 mean_age_39 mean_age_40 mean_age_41 mean_age_42 mean_age_43 mean_age_44 mean_age_45 mean_age_46 mean_age_47 mean_age_48 mean_age_49 mean_age_50 mean_age_51 mean_age_52 mean_age_53 mean_age_54 mean_age_55 mean_age_56 mean_age_57 mean_age_58 mean_age_59 mean_age_60 mean_age_61 mean_age_62 mean_age_63 mean_age_64 mean_age_65 mean_age_66 mean_age_67 mean_age_68 mean_age_69 mean_age_70 mean_age_71 mean_age_72 mean_age_73 mean_age_74 mean_age_75 mean_age_76 mean_age_77 mean_age_78 mean_age_79 mean_age_80 mean_age_81 mean_age_82 mean_age_83 mean_age_84 mean_age_85 mean_age_86 mean_age_87 mean_age_88 mean_age_89 mean_age_90 mean_age_91 mean_age_92 mean_age_93 mean_age_94 mean_age_95 mean_age_96 mean_age_97 mean_age_98 mean_age_99
_____ ___ _____ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________
1 0 0 0.051256 0.049485 0.046969 0.044331 0.041985 0.039891 0.038018 0.036339 0.034831 0.033473 0.032249 0.031145 0.030147 0.029244 0.028428 0.027689 0.02702 0.026416 0.025869 0.025376 0.024931 0.024532 0.024175 0.023857 0.023576 0.023329 0.023114 0.02293 0.022775 0.022648 0.022548 0.022474 0.022425 0.0224 0.022399 0.022423 0.022472 0.022545 0.022644 0.022766 0.022912 0.023077 0.023257 0.023416 0.023419 0.022487 0.01442 0.023239 0.023058 0.022877 0.022694 0.022512 0.022329 0.022145 0.021962 0.021773 0.021579 0.021381 0.021185 0.020985 0.02078 0.020574 0.02037 0.020173 0.019988 0.019817 0.019656 0.019506 0.019365 0.019228 0.019102 0.019003 0.018919 0.018834 0.018732 0.018633 0.018542 0.018449 0.018327 0.018158 0.017893 0.017284
2 1 0 0.047986 0.045532 0.040481 0.035822 0.032041 0.028948 0.026399 0.024286 0.022523 0.021045 0.019801 0.01875 0.01786 0.017105 0.016463 0.015917 0.015453 0.01506 0.014727 0.014447 0.014211 0.014016 0.013854 0.013723 0.013618 0.013536 0.013474 0.013431 0.013404 0.013392 0.013393 0.013405 0.013428 0.013462 0.013506 0.01356 0.013625 0.013701 0.01379 0.013892 0.014008 0.01414 0.014288 0.014422 0.014514 0.014366 0.010399 0.017503 0.017366 0.017228 0.01709 0.016949 0.016808 0.016667 0.016525 0.016382 0.016236 0.016087 0.015939 0.015787 0.015633 0.015476 0.015323 0.01518 0.015044 0.014917 0.014795 0.014674 0.014564 0.014464 0.014375 0.01429 0.014199 0.014115 0.014042 0.013976 0.013892 0.013811 0.013729 0.013664 0.013514 0.013056
3 0 1 0.01129 0.010552 0.0097415 0.0089796 0.0083154 0.0077436 0.0072422 0.0068036 0.0064181 0.0060776 0.0057797 0.0055192 0.0052915 0.0050912 0.0049149 0.0047597 0.0046245 0.0045078 0.0044082 0.0043243 0.004255 0.0041993 0.004156 0.0041244 0.0041038 0.0040938 0.004094 0.004104 0.0041236 0.0041527 0.004191 0.0042382 0.0042941 0.0043587 0.0044322 0.0045154 0.004609 0.0047143 0.0048322 0.0049633 0.0051094 0.0052715 0.0054541 0.0056642 0.0059085 0.0060754 0.0055161 0.0079996 0.0081159 0.0082266 0.0083339 0.0084462 0.0085517 0.0086466 0.0087426 0.0088293 0.0089078 0.0089863 0.0090634 0.0091254 0.0091774 0.0092306 0.0092671 0.0092886 0.0093164 0.0093584 0.0093947 0.0094154 0.0094325 0.0094498 0.0094691 0.0094846 0.0094975 0.0094978 0.0094888 0.0094826 0.0094735 0.0094699 0.009459 0.0093928 0.0091967 0.0085264
4 1 1 0.0093296 0.0086141 0.0076904 0.0068414 0.0061429 0.0055604 0.0050725 0.0046675 0.0043269 0.0040372 0.0037885 0.0035766 0.0033968 0.0032437 0.0031132 0.0030021 0.0029081 0.0028294 0.0027643 0.0027117 0.00267 0.0026381 0.0026151 0.0026003 0.0025929 0.0025926 0.0025989 0.0026117 0.0026306 0.0026556 0.0026863 0.0027227 0.0027646 0.002812 0.0028653 0.0029252 0.0029921 0.003066 0.0031478 0.0032378 0.0033365 0.0034472 0.0035737 0.0037193 0.0038941 0.004058 0.0038684 0.0058096 0.0058918 0.005978 0.0060684 0.006151 0.0062285 0.0063007 0.0063686 0.0064332 0.0064984 0.0065627 0.0066141 0.0066595 0.0066979 0.006734 0.0067739 0.0068078 0.0068281 0.0068483 0.0068724 0.0068917 0.0069092 0.0069302 0.006948 0.0069535 0.0069534 0.0069502 0.0069477 0.0069483 0.0069633 0.0069782 0.0069673 0.0069103 0.0067472 0.0063182
% Consumption
st_title = ['MEAN(MN_MPC_U_GAIN_CHECK(EM,J)), welf_checks=' num2str(welf_checks) ', TR=' num2str(mp_params('TR'))];
tb_az_c = ff_summ_nd_array(st_title, mn_MPC_U_gain_share_check_07, true, ["mean"], 3, 1, cl_mp_datasetdesc, ar_permute);
xxx MEAN(MN_MPC_U_GAIN_CHECK(EM,J)), welf_checks=2, TR=0.0018238 xxxxxxxxxxxxxxxxxxxxxxxxxxx
group edu marry mean_age_18 mean_age_19 mean_age_20 mean_age_21 mean_age_22 mean_age_23 mean_age_24 mean_age_25 mean_age_26 mean_age_27 mean_age_28 mean_age_29 mean_age_30 mean_age_31 mean_age_32 mean_age_33 mean_age_34 mean_age_35 mean_age_36 mean_age_37 mean_age_38 mean_age_39 mean_age_40 mean_age_41 mean_age_42 mean_age_43 mean_age_44 mean_age_45 mean_age_46 mean_age_47 mean_age_48 mean_age_49 mean_age_50 mean_age_51 mean_age_52 mean_age_53 mean_age_54 mean_age_55 mean_age_56 mean_age_57 mean_age_58 mean_age_59 mean_age_60 mean_age_61 mean_age_62 mean_age_63 mean_age_64 mean_age_65 mean_age_66 mean_age_67 mean_age_68 mean_age_69 mean_age_70 mean_age_71 mean_age_72 mean_age_73 mean_age_74 mean_age_75 mean_age_76 mean_age_77 mean_age_78 mean_age_79 mean_age_80 mean_age_81 mean_age_82 mean_age_83 mean_age_84 mean_age_85 mean_age_86 mean_age_87 mean_age_88 mean_age_89 mean_age_90 mean_age_91 mean_age_92 mean_age_93 mean_age_94 mean_age_95 mean_age_96 mean_age_97 mean_age_98 mean_age_99
_____ ___ _____ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________
1 0 0 0.081794 0.085652 0.08723 0.08665 0.085947 0.085754 0.08552 0.085067 0.084889 0.08466 0.084504 0.084411 0.084169 0.084203 0.084122 0.084088 0.084035 0.083968 0.08393 0.083998 0.08401 0.08392 0.084081 0.083995 0.084015 0.084007 0.083954 0.084014 0.083974 0.083957 0.083952 0.084012 0.084258 0.084272 0.084703 0.08517 0.085683 0.08624 0.086916 0.087644 0.088598 0.089744 0.091304 0.093165 0.096742 0.11012 0.11196 0.1554 0.15776 0.16027 0.16299 0.16619 0.16973 0.17268 0.17584 0.17924 0.18292 0.18691 0.19085 0.19477 0.19924 0.20408 0.20984 0.21631 0.2229 0.23002 0.23781 0.24568 0.25426 0.26427 0.2751 0.28642 0.29867 0.31351 0.32835 0.34554 0.3666 0.39411 0.43147 0.49245 0.61562 0.99996
2 1 0 0.10602 0.12228 0.12903 0.12307 0.1172 0.11257 0.10802 0.1041 0.10119 0.098017 0.095873 0.093432 0.091552 0.089946 0.088623 0.087518 0.086758 0.086177 0.085346 0.085051 0.084708 0.084376 0.084218 0.084081 0.083948 0.083961 0.083883 0.083903 0.084013 0.084102 0.084337 0.08457 0.084907 0.085276 0.085558 0.086019 0.086433 0.087006 0.087434 0.088171 0.089125 0.090302 0.091737 0.093676 0.096902 0.10816 0.11068 0.15948 0.1625 0.16555 0.168 0.17058 0.1735 0.17658 0.17986 0.1833 0.18696 0.19099 0.19509 0.19919 0.20388 0.20874 0.21454 0.22089 0.22736 0.2348 0.24263 0.25029 0.2593 0.26969 0.28054 0.29165 0.30342 0.31801 0.33266 0.34887 0.36972 0.39709 0.43501 0.49601 0.61843 0.99996
3 0 1 0.093649 0.097104 0.096702 0.095946 0.095996 0.096866 0.097909 0.098784 0.098354 0.09721 0.096147 0.095263 0.093051 0.09237 0.092407 0.092521 0.092978 0.09299 0.093276 0.093219 0.093374 0.093125 0.092903 0.092771 0.092461 0.092225 0.091882 0.091108 0.090523 0.089995 0.089146 0.088572 0.088034 0.087606 0.087435 0.087153 0.087019 0.08692 0.08702 0.087912 0.089198 0.090643 0.092117 0.093411 0.094514 0.098896 0.10166 0.1276 0.12623 0.12157 0.12553 0.13011 0.12909 0.1295 0.13897 0.1401 0.1399 0.14432 0.15041 0.15595 0.16383 0.16486 0.1625 0.17255 0.19251 0.20152 0.20145 0.21036 0.22079 0.22978 0.24149 0.2577 0.273 0.283 0.29277 0.30593 0.32664 0.35671 0.40134 0.47128 0.59947 0.99997
4 1 1 0.11118 0.12192 0.12057 0.11696 0.11426 0.1128 0.10832 0.10476 0.10267 0.10265 0.10088 0.098063 0.097127 0.096271 0.095865 0.095134 0.096053 0.096294 0.09609 0.094915 0.094565 0.09377 0.093633 0.093014 0.092797 0.092195 0.0924 0.092116 0.09176 0.09164 0.091078 0.090404 0.090107 0.089888 0.09036 0.090036 0.089314 0.088472 0.088384 0.088156 0.0884 0.089162 0.089693 0.090631 0.093961 0.098061 0.097183 0.11982 0.12893 0.13516 0.13946 0.13651 0.13306 0.13328 0.13605 0.1353 0.14849 0.15323 0.15033 0.14643 0.15945 0.17022 0.17918 0.17971 0.18915 0.20024 0.20151 0.21509 0.22884 0.2438 0.25104 0.25601 0.26659 0.27779 0.29417 0.31453 0.34027 0.36706 0.40329 0.46194 0.59675 0.99998 Graph Mean Values:
st_title = ['MEAN(MN\_V\_U\_GAIN\_CHECK(EM,J)), welf\_checks=' num2str(welf_checks) ', TR=' num2str(mp_params('TR')) ''];
mp_support_graph('cl_st_graph_title') = {st_title};
mp_support_graph('cl_st_ytitle') = {'MEAN(MN\_V\_U\_GAIN\_CHECK(EM,J))'};
ff_graph_grid((tb_az_v{1:end, 4:end}), ar_row_grid, age_grid, mp_support_graph);
Graph Mean Consumption (MPC: Share of Check Consumed):
st_title = ['MEAN(MN\_MPC\_U\_GAIN\_CHECK(EM,J)), welf\_checks=' num2str(welf_checks) ', TR=' num2str(mp_params('TR')) ''];
mp_support_graph('cl_st_graph_title') = {st_title};
mp_support_graph('cl_st_ytitle') = {'MEAN(MN\_MPC\_U\_GAIN\_CHECK(EM,J))'};
ff_graph_grid((tb_az_c{1:end, 4:end}), ar_row_grid, age_grid, mp_support_graph);
