{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Sudden Stop Model\n", "\n", "In this notebook we replicate the baseline model exposed in \n", "\n", "`From Sudden Stops to Fisherian Deflation, Quantitative Theory and Policy` by __Anton Korinek and Enrique G. Mendoza__\n", "\n", "The file `sudden_stop.yaml` which is printed below, describes the model, and must be included in the same directory as this notebook." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## importing necessary functions" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from matplotlib import pyplot as plt\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from dolo import *\n", "from dolo.algos import time_iteration\n", "from dolo.algos import plot_decision_rule, simulate" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## writing the model" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "'/home/pablo/Mobilhome/econforge/dolo/examples/notebooks'" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pwd" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false, "scrolled": true }, "outputs": [ { "data": { "text/html": [ "\n", " 
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# This file adapts the model described in\n",
       "# "From Sudden Stops to Fisherian Deflation, Quantitative Theory and Policy"\n",
       "# by Anton Korinek and Enrique G. Mendoza\n",
       "\n",
       "name: Sudden Stop (General)\n",
       "\n",
       "symbols:\n",
       "\n",
       "    exogenous: [y]\n",
       "    states: [l]\n",
       "    controls: [b, lam]\n",
       "    values: [V, Vc]\n",
       "    parameters: [beta, R, sigma, a, mu, kappa, delta_y, pi, lam_inf]\n",
       "\n",
       "\n",
       "definitions:\n",
       "    c: 1 + y + l*R - b\n",
       "\n",
       "equations:\n",
       "\n",
       "    transition:\n",
       "        - l = b(-1)\n",
       "\n",
       "    arbitrage:\n",
       "        - lam = b/c\n",
       "        - 1 - beta*(c(1)/c)^(-sigma)*R    |  lam_inf <= lam <= inf\n",
       "\n",
       "    value:\n",
       "        - V = c^(1.0-sigma)/(1.0-sigma) + beta*V(1)\n",
       "        - Vc = c^(1.0-sigma)/(1.0-sigma)\n",
       "\n",
       "calibration:\n",
       "\n",
       "    beta: 0.95\n",
       "    R: 1.03\n",
       "    sigma: 2.0\n",
       "    a: 1/3\n",
       "    mu: 0.8\n",
       "    kappa: 1.3\n",
       "    delta_y: 0.03\n",
       "    pi: 0.05\n",
       "    lam_inf: -0.2\n",
       "    y: 1.0\n",
       "    c: 1.0 + y\n",
       "    b: 0.0\n",
       "    l: 0.0\n",
       "    lam: 0.0\n",
       "\n",
       "    V: c^(1.0-sigma)/(1.0-sigma)/(1.0-beta)\n",
       "    Vc: c^(1.0-sigma)/(1.0-sigma)\n",
       "\n",
       "\n",
       "exogenous: !MarkovChain\n",
       "    values: [[ 1.0-delta_y ],  # bad state\n",
       "             [ 1.0 ]]          # good state\n",
       "    transitions: [[ 0.5, 1-0.5 ],   # probabilities   [p(L|L), p(H|L)]\n",
       "                  [ 0.5, 0.5 ]]     # probabilities   [p(L|H), p(H|H)]\n",
       "\n",
       "domain:\n",
       "    l: [-1, 1]\n",
       "\n",
       "options:\n",
       "    grid: !Cartesian\n",
       "        orders: [10]\n",
       "
\n", "
\n", " " ], "text/plain": [ "" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# filename = 'https://raw.githubusercontent.com/EconForge/dolo/master/examples/models/compat/sudden_stop.yaml'\n", "filename = '../models/sudden_stop.yaml'\n", "# the model file is coded in a separate file called sudden_stop.yaml\n", "# note how the borrowing constraint is implemented as complementarity condition\n", "pcat(filename)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## importing the model\n", "\n", "Note, that residuals, are not zero at the calibration we supply. This is because the representative agent is impatient\n", "and we have $\\beta<1/R$. In this case it doesn't matter.\n", "\n", "By default, the calibrated value for endogenous variables are used as a (constant) starting point for the decision rules." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Model
nameSudden Stop (General)
typedtcc
filename../models/sudden_stop.yaml
\n", "\n", "\n", "\n", "\n", "
TypeEquationResidual
transition$l_{t} = b_{t-1}$0.000
arbitrage$\\lambda_{t} = \\frac{b_{t}}{c_{t}}$0.000
$1 - \\beta \\; \\left(\\frac{c_{t+1}}{c_{t}}\\right)^{- \\sigma} \\; R$0.0215
value$V_{t} = \\frac{c_{t}^{1.0 - \\sigma}}{1.0 - \\sigma} + \\beta \\; V_{t+1}$
$Vc_{t} = \\frac{c_{t}^{1.0 - \\sigma}}{1.0 - \\sigma}$
controls_lb$- inf$
$\\lambda_{inf}$
controls_ub$inf$
$inf$
definitions$c_{t} = 1 + y_{t} + l_{t} \\; R - b_{t}$
" ], "text/plain": [ "\n", " Model:\n", " ------\n", " name: \"Sudden Stop (General)\"\n", " type: \"dtcc\"\n", " file: \"../models/sudden_stop.yaml\n", "\n", "Equations:\n", "----------\n", "\n", "transition\n", " 1 : 0.0000 : l(0) == b(-(1))\n", "\n", "arbitrage\n", " 1 : 0.0000 : lam(0) == (b(0)) / (c(0))\n", " 2 : \u001b[31m0.0215\u001b[0m : (1) - (((beta) * (((c(1)) / (c(0))) ** (-(sigma)))) * (R))\n", "\n", "definitions\n", " 1 : c = 1 + y + l*R - b\n" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model = yaml_import(filename)\n", "model" ] }, { "cell_type": "code", "execution_count": 72, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Solving WITH complementarities.\n", "------------------------------------------------\n", "| N | Error | Gain | Time | nit |\n", "------------------------------------------------\n", "| 1 | 5.133e-01 | nan | 0.082 | 10 |\n", "| 2 | 1.703e-01 | 0.332 | 0.028 | 8 |\n", "| 3 | 8.433e-02 | 0.495 | 0.018 | 6 |\n", "| 4 | 5.005e-02 | 0.594 | 0.014 | 6 |\n", "| 5 | 3.290e-02 | 0.657 | 0.014 | 6 |\n", "| 6 | 2.315e-02 | 0.704 | 0.037 | 6 |\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[33mUserWarning\u001b[0m:/home/pablo/Mobilhome/econforge/dolo/dolo/numeric/optimize/newton.py:150\n", " Did not converge\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "| 7 | 1.705e-02 | 0.737 | 0.029 | 6 |\n", "| 8 | 1.298e-02 | 0.761 | 0.021 | 5 |\n", "| 9 | 1.013e-02 | 0.780 | 0.013 | 5 |\n", "| 10 | 8.050e-03 | 0.795 | 0.012 | 5 |\n", "| 11 | 6.493e-03 | 0.807 | 0.011 | 5 |\n", "| 12 | 5.297e-03 | 0.816 | 0.046 | 5 |\n", "| 13 | 4.359e-03 | 0.823 | 0.010 | 4 |\n", "| 14 | 3.770e-03 | 0.865 | 0.032 | 4 |\n", "| 15 | 3.917e-03 | 1.039 | 0.015 | 4 |\n", "| 16 | 4.054e-03 | 1.035 | 0.010 | 4 |\n", "| 17 | 4.072e-03 | 1.004 | 0.019 | 4 |\n", "| 18 | 3.947e-03 | 0.969 | 0.020 | 4 |\n", "| 19 | 3.675e-03 | 0.931 | 0.012 | 4 |\n", "| 20 | 3.269e-03 | 0.890 | 0.007 | 3 |\n", "| 21 | 2.861e-03 | 0.875 | 0.008 | 3 |\n", "| 22 | 3.028e-03 | 1.058 | 0.007 | 3 |\n", "| 23 | 3.084e-03 | 1.018 | 0.007 | 3 |\n", "| 24 | 3.088e-03 | 1.001 | 0.007 | 3 |\n", "| 25 | 2.973e-03 | 0.963 | 0.007 | 3 |\n", "| 26 | 2.690e-03 | 0.905 | 0.007 | 3 |\n", "| 27 | 2.469e-03 | 0.918 | 0.007 | 3 |\n", "| 28 | 2.592e-03 | 1.050 | 0.007 | 3 |\n", "| 29 | 2.585e-03 | 0.997 | 0.034 | 3 |\n", "| 30 | 2.505e-03 | 0.969 | 0.007 | 3 |\n", "| 31 | 2.252e-03 | 0.899 | 0.010 | 3 |\n", "| 32 | 2.174e-03 | 0.965 | 0.008 | 3 |\n", "| 33 | 2.234e-03 | 1.028 | 0.008 | 3 |\n", "| 34 | 2.196e-03 | 0.983 | 0.007 | 3 |\n", "| 35 | 2.030e-03 | 0.924 | 0.007 | 3 |\n", "| 36 | 1.833e-03 | 0.903 | 0.007 | 3 |\n", "| 37 | 1.893e-03 | 1.032 | 0.007 | 3 |\n", "| 38 | 1.847e-03 | 0.976 | 0.007 | 3 |\n", "| 39 | 1.699e-03 | 0.920 | 0.007 | 3 |\n", "| 40 | 1.614e-03 | 0.950 | 0.007 | 3 |\n", "| 41 | 1.575e-03 | 0.976 | 0.043 | 3 |\n", "| 42 | 1.466e-03 | 0.931 | 0.010 | 3 |\n", "| 43 | 1.255e-03 | 0.856 | 0.035 | 3 |\n", "| 44 | 9.810e-04 | 0.781 | 0.006 | 2 |\n", "| 45 | 6.903e-04 | 0.704 | 0.009 | 2 |\n", "| 46 | 4.233e-04 | 0.613 | 0.006 | 2 |\n", "| 47 | 2.052e-04 | 0.485 | 0.012 | 2 |\n", "| 48 | 1.959e-04 | 0.955 | 0.005 | 2 |\n", "| 49 | 1.641e-04 | 0.838 | 0.005 | 2 |\n", "| 50 | 1.233e-04 | 0.751 | 0.005 | 2 |\n", "| 51 | 1.236e-04 | 1.002 | 0.005 | 2 |\n", "| 52 | 1.088e-04 | 0.880 | 0.005 | 2 |\n", "| 53 | 8.405e-05 | 0.773 | 0.005 | 2 |\n", "| 54 | 5.452e-05 | 0.649 | 0.005 | 2 |\n", "| 55 | 3.427e-05 | 0.629 | 0.005 | 2 |\n", "| 56 | 3.296e-05 | 0.962 | 0.005 | 2 |\n", "| 57 | 2.793e-05 | 0.847 | 0.006 | 2 |\n", "| 58 | 2.201e-05 | 0.788 | 0.005 | 2 |\n", "| 59 | 2.172e-05 | 0.987 | 0.005 | 2 |\n", "| 60 | 1.889e-05 | 0.869 | 0.005 | 2 |\n", "| 61 | 1.407e-05 | 0.745 | 0.005 | 2 |\n", "| 62 | 8.404e-06 | 0.597 | 0.003 | 1 |\n", "| 63 | 7.505e-06 | 0.893 | 0.003 | 1 |\n", "| 64 | 6.914e-06 | 0.921 | 0.003 | 1 |\n", "| 65 | 5.351e-06 | 0.774 | 0.003 | 1 |\n", "| 66 | 5.067e-06 | 0.947 | 0.003 | 1 |\n", "| 67 | 4.602e-06 | 0.908 | 0.022 | 1 |\n", "| 68 | 3.667e-06 | 0.797 | 0.015 | 1 |\n", "| 69 | 2.667e-06 | 0.727 | 0.007 | 1 |\n", "| 70 | 2.749e-06 | 1.031 | 0.013 | 1 |\n", "| 71 | 2.663e-06 | 0.969 | 0.010 | 1 |\n", "| 72 | 2.344e-06 | 0.880 | 0.003 | 1 |\n", "| 73 | 1.979e-06 | 0.844 | 0.004 | 1 |\n", "| 74 | 1.942e-06 | 0.981 | 0.004 | 1 |\n", "| 75 | 1.718e-06 | 0.885 | 0.005 | 1 |\n", "| 76 | 1.325e-06 | 0.772 | 0.003 | 1 |\n", "| 77 | 9.115e-07 | 0.688 | 0.003 | 1 |\n", "------------------------------------------------\n", "Elapsed: 0.9402523040771484 seconds.\n", "------------------------------------------------\n" ] } ], "source": [ "# to avoid numerical glitches we choose a relatively high number of grid points\n", "mdr = time_iteration(model, verbose=True)" ] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [], "source": [ "# produce the plots\n", "n_steps = 100\n", "\n", "tab0 = tabulate(model, mdr, 'l', i0=0, n_steps=n_steps)\n", "tab1 = tabulate(model, mdr, 'l', i0=1, n_steps=n_steps)" ] }, { "cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [], "source": [ "lam_inf = model.calibration['lam_inf']" ] }, { "cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 0.98, 'Decision Rules')" ] }, "execution_count": 77, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.subplot(121)\n", "\n", "plt.plot(tab0['l'], tab0['l'], linestyle='--', color='black', label='')\n", "plt.plot(tab0['l'], lam_inf*tab0['c'], linestyle='--', color='black', label='')\n", "plt.plot(tab0['l'], tab0['b'], label='$b_t$ (bad state)' )\n", "plt.plot(tab0['l'], tab1['b'], label='$b_t$ (good state)')\n", "# plt.plot(tab0['l'], lam_inf*tab1['c'])\n", "plt.grid()\n", "plt.xlabel('$l_t$')\n", "\n", "plt.legend(loc= 'upper left')\n", "\n", "plt.subplot(122)\n", "plt.plot(tab0['l'], tab0['c'], label='$c_t$ (bad state)' )\n", "plt.plot(tab0['l'], tab1['c'], label='$c_t$ (good state)' )\n", "plt.legend(loc= 'lower right')\n", "plt.grid()\n", "plt.xlabel('$l_t$')\n", "\n", "plt.suptitle(\"Decision Rules\")" ] }, { "cell_type": "code", "execution_count": 84, "metadata": {}, "outputs": [], "source": [ "# if we want we can use altair/vega-lite instead" ] }, { "cell_type": "code", "execution_count": 86, "metadata": {}, "outputs": [], "source": [ "import altair as alt\n", "import pandas" ] }, { "cell_type": "code", "execution_count": 166, "metadata": {}, "outputs": [], "source": [ "# first we need to convert data into flat format\n", "df = pandas.concat([tab0, tab1], keys=['bad','good'], names=['experiment'])\n", "df = df.reset_index().drop(columns=['level_1']) # maybe there is a more elegant option here" ] }, { "cell_type": "code", "execution_count": 176, "metadata": {}, "outputs": [], "source": [ "lam_inf = model.calibration['lam_inf']" ] }, { "cell_type": "code", "execution_count": 208, "metadata": {}, "outputs": [ { "data": { "application/vnd.vegalite.v2+json": { "$schema": "https://vega.github.io/schema/vega-lite/v2.6.0.json", "config": { "view": { "height": 300, "width": 400 } }, "datasets": { "data-1c127afe96680b91933efa80a9111443": [ { "b": -0.235, "c": 1.1749999999999998, "experiment": "bad", "l": -1, "lam": -0.19999999999999998, "y": 0.97 }, { "b": -0.240094347181473, "c": 1.2009024279895537, "experiment": "bad", "l": -0.9797979797979798, "lam": -0.1999513084124451, "y": 0.97 }, { "b": -0.24519407801397336, "c": 1.226810239630135, "experiment": "bad", "l": -0.9595959595959596, "lam": -0.19990505140426795, "y": 0.97 }, { "b": -0.2503045761485284, "c": 1.2527288185727707, "experiment": "bad", "l": -0.9393939393939394, "lam": -0.19986366355484625, "y": 0.97 }, { "b": -0.25543122523616557, "c": 1.2786635484684887, "experiment": "bad", "l": -0.9191919191919192, "lam": -0.19982957944355784, "y": 0.97 }, { "b": -0.2605794089279122, "c": 1.3046198129683164, "experiment": "bad", "l": -0.898989898989899, "lam": -0.19980523364978037, "y": 0.97 }, { "b": -0.26575451087479557, "c": 1.3306029957232806, "experiment": "bad", "l": -0.8787878787878788, "lam": -0.19979306075289166, "y": 0.97 }, { "b": -0.27096191472784315, "c": 1.3566184803844088, "experiment": "bad", "l": -0.8585858585858586, "lam": -0.19979549533226942, "y": 0.97 }, { "b": -0.27620700413808225, "c": 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"experiment": "bad", "l": -0.696969696969697, "lam": -0.20047717755803818, "y": 0.97 }, { "b": -0.31949748122375304, "c": 1.592426774153046, "experiment": "bad", "l": -0.6767676767676767, "lam": -0.20057212615377024, "y": 0.97 }, { "b": -0.3248340927014572, "c": 1.6185714664388309, "experiment": "bad", "l": -0.6565656565656566, "lam": -0.20063299063821385, "y": 0.97 }, { "b": -0.3300684148096416, "c": 1.644613869355096, "experiment": "bad", "l": -0.6363636363636364, "lam": -0.20064759811448032, "y": 0.97 }, { "b": -0.3351735292931693, "c": 1.6705270646467045, "experiment": "bad", "l": -0.6161616161616161, "lam": -0.20060377568568094, "y": 0.97 }, { "b": -0.3401225178969035, "c": 1.6962841340585197, "experiment": "bad", "l": -0.5959595959595959, "lam": -0.20048935045492688, "y": 0.97 }, { "b": -0.3448884623657075, "c": 1.7218581593354045, "experiment": "bad", "l": -0.5757575757575757, "lam": -0.20029214952532948, "y": 0.97 }, { "b": -0.34944444444444445, "c": 1.7472222222222222, 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", "text/plain": [ "\n", "\n", "If you see this message, it means the renderer has not been properly enabled\n", "for the frontend that you are using. For more information, see\n", "https://altair-viz.github.io/user_guide/troubleshooting.html\n" ] }, "execution_count": 208, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# then we can play\n", "base = alt.Chart(df).mark_line()\n", "ch1 = base.encode(x='l', y='b', color='experiment').interactive()\n", "ch1_min = base.mark_line(color='grey').transform_calculate(minc=f'{lam_inf}*datum.c').encode(x='l',y=alt.Y('minc:Q', aggregate='min'))\n", "ch1_max = base.mark_line(color='grey').encode(x='l',y='l')\n", "ch2 = base.encode(x='l', y='c', color='experiment')\n", "\n", "(ch1_min+ch1_max+ch1|ch2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## stochastic simulations" ] }, { "cell_type": "code", "execution_count": 78, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "\n", "array([[[ 1. , 0.5 , ..., 0.220895, 2.059955]],\n", "\n", " [[ 0.97 , 0.455045, ..., 0.185854, 2.056478]],\n", "\n", " ...,\n", "\n", " [[ 0.97 , -0.332575, ..., -0.175531, 1.973936]],\n", "\n", " [[ 0.97 , -0.346488, ..., -0.179044, 1.964891]]])\n", "Coordinates:\n", " * T (T) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 ...\n", " * N (N) int64 0\n", " * V (V) ]" ] }, "execution_count": 79, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.subplot(211)\n", "plt.plot(sim.sel(V='y'))\n", "plt.subplot(212)\n", "plt.plot(sim.sel(V='b'))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Sensitivity analysis\n", "\n", "Here we want to compare the saving behaviour as a function of risk aversion $\\sigma$.\n", "We contrast the baseline $\\sigma=2$ with the high aversion scenario $\\sigma=16$." ] }, { "cell_type": "code", "execution_count": 80, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Solving WITH complementarities.\n", "------------------------------------------------\n", "| N | Error | Gain | Time | nit |\n", "------------------------------------------------\n", "| 1 | 5.133e-01 | nan | 0.036 | 10 |\n", "| 2 | 1.703e-01 | 0.332 | 0.021 | 8 |\n", "| 3 | 8.433e-02 | 0.495 | 0.014 | 6 |\n", "| 4 | 5.005e-02 | 0.594 | 0.014 | 6 |\n", "| 5 | 3.290e-02 | 0.657 | 0.014 | 6 |\n", "| 6 | 2.315e-02 | 0.704 | 0.014 | 6 |\n", "| 7 | 1.705e-02 | 0.737 | 0.014 | 6 |\n", "| 8 | 1.298e-02 | 0.761 | 0.012 | 5 |\n", "| 9 | 1.013e-02 | 0.780 | 0.012 | 5 |\n", "| 10 | 8.050e-03 | 0.795 | 0.012 | 5 |\n", "| 11 | 6.493e-03 | 0.807 | 0.011 | 5 |\n", "| 12 | 5.297e-03 | 0.816 | 0.011 | 5 |\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[33mUserWarning\u001b[0m:/home/pablo/Mobilhome/econforge/dolo/dolo/numeric/optimize/newton.py:150\n", " Did not converge\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "| 13 | 4.359e-03 | 0.823 | 0.014 | 4 |\n", "| 14 | 3.770e-03 | 0.865 | 0.044 | 4 |\n", "| 15 | 3.917e-03 | 1.039 | 0.015 | 4 |\n", "| 16 | 4.054e-03 | 1.035 | 0.010 | 4 |\n", "| 17 | 4.072e-03 | 1.004 | 0.010 | 4 |\n", "| 18 | 3.947e-03 | 0.969 | 0.013 | 4 |\n", "| 19 | 3.675e-03 | 0.931 | 0.010 | 4 |\n", "| 20 | 3.269e-03 | 0.890 | 0.008 | 3 |\n", "| 21 | 2.861e-03 | 0.875 | 0.007 | 3 |\n", "| 22 | 3.028e-03 | 1.058 | 0.007 | 3 |\n", "| 23 | 3.084e-03 | 1.018 | 0.007 | 3 |\n", "| 24 | 3.088e-03 | 1.001 | 0.007 | 3 |\n", "| 25 | 2.973e-03 | 0.963 | 0.007 | 3 |\n", "| 26 | 2.690e-03 | 0.905 | 0.007 | 3 |\n", "| 27 | 2.469e-03 | 0.918 | 0.007 | 3 |\n", "| 28 | 2.592e-03 | 1.050 | 0.007 | 3 |\n", "| 29 | 2.585e-03 | 0.997 | 0.007 | 3 |\n", "| 30 | 2.505e-03 | 0.969 | 0.007 | 3 |\n", "| 31 | 2.252e-03 | 0.899 | 0.007 | 3 |\n", "| 32 | 2.174e-03 | 0.965 | 0.007 | 3 |\n", "| 33 | 2.234e-03 | 1.028 | 0.015 | 3 |\n", "| 34 | 2.196e-03 | 0.983 | 0.008 | 3 |\n", "| 35 | 2.030e-03 | 0.924 | 0.009 | 3 |\n", "| 36 | 1.833e-03 | 0.903 | 0.007 | 3 |\n", "| 37 | 1.893e-03 | 1.032 | 0.008 | 3 |\n", "| 38 | 1.847e-03 | 0.976 | 0.008 | 3 |\n", "| 39 | 1.699e-03 | 0.920 | 0.007 | 3 |\n", "| 40 | 1.614e-03 | 0.950 | 0.007 | 3 |\n", "| 41 | 1.575e-03 | 0.976 | 0.007 | 3 |\n", "| 42 | 1.466e-03 | 0.931 | 0.007 | 3 |\n", "| 43 | 1.255e-03 | 0.856 | 0.007 | 3 |\n", "| 44 | 9.810e-04 | 0.781 | 0.005 | 2 |\n", "| 45 | 6.903e-04 | 0.704 | 0.005 | 2 |\n", "| 46 | 4.233e-04 | 0.613 | 0.005 | 2 |\n", "| 47 | 2.052e-04 | 0.485 | 0.005 | 2 |\n", "| 48 | 1.959e-04 | 0.955 | 0.005 | 2 |\n", "| 49 | 1.641e-04 | 0.838 | 0.005 | 2 |\n", "| 50 | 1.233e-04 | 0.751 | 0.005 | 2 |\n", "| 51 | 1.236e-04 | 1.002 | 0.005 | 2 |\n", "| 52 | 1.088e-04 | 0.880 | 0.005 | 2 |\n", "| 53 | 8.405e-05 | 0.773 | 0.005 | 2 |\n", "| 54 | 5.452e-05 | 0.649 | 0.005 | 2 |\n", "| 55 | 3.427e-05 | 0.629 | 0.005 | 2 |\n", "| 56 | 3.296e-05 | 0.962 | 0.005 | 2 |\n", "| 57 | 2.793e-05 | 0.847 | 0.005 | 2 |\n", "| 58 | 2.201e-05 | 0.788 | 0.005 | 2 |\n", "| 59 | 2.172e-05 | 0.987 | 0.005 | 2 |\n", "| 60 | 1.889e-05 | 0.869 | 0.005 | 2 |\n", "| 61 | 1.407e-05 | 0.745 | 0.005 | 2 |\n", "| 62 | 8.404e-06 | 0.597 | 0.003 | 1 |\n", "| 63 | 7.505e-06 | 0.893 | 0.003 | 1 |\n", "| 64 | 6.914e-06 | 0.921 | 0.003 | 1 |\n", "| 65 | 5.351e-06 | 0.774 | 0.012 | 1 |\n", "| 66 | 5.067e-06 | 0.947 | 0.003 | 1 |\n", "| 67 | 4.602e-06 | 0.908 | 0.003 | 1 |\n", "| 68 | 3.667e-06 | 0.797 | 0.003 | 1 |\n", "| 69 | 2.667e-06 | 0.727 | 0.005 | 1 |\n", "| 70 | 2.749e-06 | 1.031 | 0.004 | 1 |\n", "| 71 | 2.663e-06 | 0.969 | 0.003 | 1 |\n", "| 72 | 2.344e-06 | 0.880 | 0.003 | 1 |\n", "| 73 | 1.979e-06 | 0.844 | 0.003 | 1 |\n", "| 74 | 1.942e-06 | 0.981 | 0.003 | 1 |\n", "| 75 | 1.718e-06 | 0.885 | 0.003 | 1 |\n", "| 76 | 1.325e-06 | 0.772 | 0.003 | 1 |\n", "| 77 | 9.115e-07 | 0.688 | 0.003 | 1 |\n", "------------------------------------------------\n", "Elapsed: 0.6573052406311035 seconds.\n", "------------------------------------------------\n" ] } ], "source": [ "# we solve the model with sigma=16\n", "model.set_calibration(sigma=16.0)\n", "mdr_high_gamma = time_iteration(model, verbose=True)" ] }, { "cell_type": "code", "execution_count": 81, "metadata": {}, "outputs": [], "source": [ "# now we compare the decision rules with low and high risk aversion" ] }, { "cell_type": "code", "execution_count": 82, "metadata": { "collapsed": false }, "outputs": [], "source": [ "tab0 = tabulate(model, mdr, 'l', i0=0)\n", "tab1 = tabulate(model, mdr, 'l', i0=1)\n", "tab0_hg = tabulate(model, mdr_high_gamma, 'l', i0=0)\n", "tab1_hg = tabulate(model, mdr_high_gamma, 'l', i0=1)" ] }, { "cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(tab0['l'], tab0['b'], label='$b_t$ (bad)' )\n", "plt.plot(tab0['l'], tab1['b'], label='$b_t$ (good)' )\n", "\n", "plt.plot(tab0['l'], tab0_hg['b'], label='$b_t$ (bad) [high gamma]' )\n", "plt.plot(tab0['l'], tab1_hg['b'], label='$b_t$ (good) [high gamma]' )\n", "plt.plot(tab0['l'], tab0['l'], linestyle='--', color='black', label='')\n", "plt.plot(tab0['l'], -0.2*tab0['c'], linestyle='--', color='black', label='')\n", "plt.legend(loc= 'upper left')\n", "plt.grid()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.8" } }, "nbformat": 4, "nbformat_minor": 2 }