{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# Tutorial 2: Monetary Policy Analysis\n",
    "\n",
    "Dauphine Minicourse\n",
    "\n",
    "Adrien Auclert\n",
    "\n",
    "January 2024"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This tutorial walks us through setting up the monetary policy models that we covered in lecture."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What we'll do in a nutshell:\n",
    "\n",
    "   1. Set up the model using blocks \n",
    "   2. Get the steady state\n",
    "   3. Get the impulse responses to `r_ante` shocks, compare to the RA model\n",
    "   4. Use Jacobians to decompose into direct/indirect effects\n",
    "   5. Repeat steps 1-3 for our alternative models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " We'll start by importing our usual three packages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# Import standard packages\n",
    "\n",
    "import numpy as np  \n",
    "import matplotlib.pyplot as plt \n",
    "import sequence_jacobian as sj  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Here is our predefined `calibration` dictionary for this session."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "calibration = {'eis': 0.5,     # EIS\n",
    "               'rho_e': 0.92,  # Persistence of idiosyncratic productivity shocks\n",
    "               'sd_e': 0.92,   # Standard deviation of idiosyncratic productivity shocks\n",
    "               'Y': 1.,        # Output\n",
    "               'r_ante': 0.01, # target real interest rate\n",
    "               'min_a': -1,    # Minimum asset level on the grid\n",
    "               'max_a': 1_000, # Maximum asset level on the grid\n",
    "               'n_a': 500,     # Number of asset grid points\n",
    "               'n_e': 11}      # Number of productivity grid points"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Because we already went over the canonical HANK model in Tutorial 1, here we'll instead follow what is actually a more common workflow in SSJ: load a predefined `HetBlock` and start working with that directly. \n",
    "\n",
    "We do this by preloading the household block and grid function from `sj.hetblocks.hh_sim` "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "hh = sj.hetblocks.hh_sim.hh\n",
    "make_grids = sj.hetblocks.hh_sim.make_grids"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we define the income input. For our baseline model, income is just $e\\times Y$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def income(Y, e_grid):\n",
    "    # post-tax labor income\n",
    "    y = Y * e_grid\n",
    "    return y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We're ready to define our simple `HetBlock`, with `make_grids` and `income` as `hetinputs`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "household_simple = hh.add_hetinputs([make_grids, income])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In addition, we have the two blocks we discussed in lecture: one that takes us from the exogenous, ex-ante `r` set by monetary policy to the (ex-post) `r` faced by households, and a market clearing block. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "@sj.simple\n",
    "def ex_post_rate(r_ante):\n",
    "    r = r_ante(-1)\n",
    "    return r\n",
    "\n",
    "@sj.simple\n",
    "def mkt_clearing_simple(A, Y, C):\n",
    "    asset_mkt = A\n",
    "    goods_mkt = C - Y\n",
    "    return asset_mkt, goods_mkt\n",
    "\n",
    "ha_simple = sj.create_model([household_simple, ex_post_rate, mkt_clearing_simple])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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   ],
   "source": [
    "sj.drawdag(ha_simple, exogenous=['r_ante'], unknowns=['Y'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll also define an RA model for comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "@sj.solved(unknowns={'C': 1, 'A': 1}, targets=[\"euler\", \"budget_constraint\"], solver=\"broyden_custom\")\n",
    "def household_ra_simple(C, A, Y, eis, beta, r):\n",
    "    euler = (beta * (1 + r(1))) ** (-eis) * C(1) - C\n",
    "    budget_constraint = (1 + r) * A(-1) + Y - C - A\n",
    "    return euler, budget_constraint\n",
    "\n",
    "ra = sj.create_model([household_ra_simple, ex_post_rate, mkt_clearing_simple], name=\"Representative Agent Model\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we define a dict for our three models: the HA model, the HA model with zero liquidity (an instance of `ha_simple` that we'll calibrate to have epsilon liquidity) and the RA model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "ss = {}\n",
    "models = {'ha': ha_simple, 'ha_zl': ha_simple, 'ra': ra}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calibration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's proceed to solving for the steady state. We know that we need to solve for $\\beta$ to hit the goods market clearing condition or (even better in practice) the asset market clearing condition. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we don't remember what we called $\\beta$, we look for it in the `inputs` of the model. Recall that these are not ouputs of any block, so they give us the candidate unknowns and exogenous variables. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OrderedSet(['beta', 'eis', 'rho_e', 'sd_e', 'n_e', 'min_a', 'max_a', 'n_a', 'Y', 'r_ante'])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ha_simple.inputs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So we found `beta`. Similarly, if we don't remember what we call our market clearing conditions, we look for them among the model's `outputs`. These are not inputs into any block, so they give us the candidate targets of our model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OrderedSet(['A', 'C', 'r', 'asset_mkt', 'goods_mkt'])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ha_simple.outputs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we get the steady state by calling the `solve_steady_state` function, giving it a reasonable range for `beta` to look over. We can check out the outcome steady state dict by calling `toplevel`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'eis': 0.5,\n",
       " 'rho_e': 0.92,\n",
       " 'sd_e': 0.92,\n",
       " 'Y': 1.0,\n",
       " 'r_ante': 0.01,\n",
       " 'min_a': -1,\n",
       " 'max_a': 1000,\n",
       " 'n_a': 500,\n",
       " 'n_e': 11,\n",
       " 'beta': 0.8233548425131579,\n",
       " 'r': 0.01,\n",
       " 'A': 6.5552563377480055e-12,\n",
       " 'C': 1.0000000000007723,\n",
       " 'asset_mkt': 6.5552563377480055e-12,\n",
       " 'goods_mkt': 7.722711359292589e-13}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ss['ha'] = models['ha'].solve_steady_state(calibration, {'beta': (0.75, 0.9)}, ['asset_mkt'])\n",
    "ss['ha'].toplevel"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the calibration function filled up all the variables that are implicitly defined in the DAG, such as  `r`. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To get the calibration of the ZL model, we just reset the minimal asset level on the grid and recalibrate. Of course, we'll get a much lower $\\beta$ to clear the asset market at the same `r` but with much lower liquidity. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Beta in main model: 0.8233548425131579  ; in ZL model :  0.42587415639128545\n"
     ]
    }
   ],
   "source": [
    "calibration_zl = calibration.copy()\n",
    "calibration_zl['min_a'] = -1e-6\n",
    "ss['ha_zl'] = models['ha_zl'].solve_steady_state(calibration_zl, {'beta': (0.35, 0.85)}, ['asset_mkt'])\n",
    "\n",
    "print(r'Beta in main model:', ss['ha']['beta'], ' ; in ZL model : ', ss['ha_zl']['beta'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we calibrate the RA model. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "calibration_ra = calibration.copy()\n",
    "calibration_ra['beta'] = 1 / (1 + calibration_ra['r_ante'])\n",
    "ss['ra'] = models['ra'].solve_steady_state(calibration_ra, {'C': 1., 'A': 0.8}, {'budget_constraint': 0., 'asset_mkt': 0.},\n",
    "                                           dissolve=['household_ra_simple'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Transition Dynamics: comparing HA and RA\n",
    "\n",
    "Now that we have a steady state, let's compute some simple impulse responses.\n",
    "\n",
    "To do this, we'll want to use `solve_impulse_linear`. If we don't remember the syntax, we can always look for the help. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on method solve_impulse_linear in module sequence_jacobian.blocks.block:\n",
      "\n",
      "solve_impulse_linear(ss: sequence_jacobian.classes.steady_state_dict.SteadyStateDict, unknowns: List[str], targets: List[str], inputs: Union[Dict[str, Any], sequence_jacobian.classes.impulse_dict.ImpulseDict], outputs: Optional[List[str]] = None, Js: Optional[Dict[str, sequence_jacobian.classes.jacobian_dict.JacobianDict]] = {}, options: Dict[str, dict] = {}, H_U_factored: Optional[sequence_jacobian.classes.jacobian_dict.FactoredJacobianDict] = None, **kwargs) -> sequence_jacobian.classes.impulse_dict.ImpulseDict method of sequence_jacobian.blocks.combined_block.CombinedBlock instance\n",
      "    Calculate a general equilibrium, linear impulse response to a set of shocks in `inputs`\n",
      "    around a steady state `ss`, given a set of `unknowns` and `targets` corresponding to the endogenous\n",
      "    variables to be solved for and the target conditions that must hold in general equilibrium\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(models['ha'].solve_impulse_linear)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We learn that we need to give this the model's steady state, and then `unknowns`, `targets`, and `inputs` (ie shocks). \n",
    "\n",
    "Again, `unknows` and `inputs` are among the model's inputs, and `targets` among the outputs.\n",
    "\n",
    "Inspecting the above, `r_ante` is our shock, `Y` is our unknown, and `asset_market` our natural target.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we are ready to look at the response of output to a decrease in the interest rate, with a per-period persistence of $0.7$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_irfs(irfs_list, variables, labels=[\" \"], ylabel=r\"Percentage points (dev. from ss)\", T_plot=50, figsize=(9, 4)):\n",
    "    if len(irfs_list) != len(labels):\n",
    "        labels = [\" \"] * len(irfs_list)\n",
    "    n_var = len(variables)\n",
    "    fig, ax = plt.subplots(1, n_var, figsize=figsize, sharex=True)\n",
    "    for i in range(n_var):\n",
    "        # plot all irfs\n",
    "        for j, irf in enumerate(irfs_list):\n",
    "            ax[i].plot(100 * irf[variables[i]][:T_plot], label=labels[j])\n",
    "        ax[i].set_title(variables[i])\n",
    "        ax[i].set_xlabel(r\"$t$\")\n",
    "        if i==0:\n",
    "            ax[i].set_ylabel(ylabel)\n",
    "        ax[i].legend()\n",
    "    plt.savefig('directindirect.pdf', transparent=True)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Find the linear impulse responses to an \"r\" shock\n",
    "T = 300\n",
    "dr = -0.01 * 0.7 ** np.arange(T)\n",
    "irf = {}\n",
    "for m in ['ha', 'ha_zl', 'ra']:\n",
    "    irf[m] = models[m].solve_impulse_linear(ss[m], ['Y'], ['asset_mkt'], {'r_ante': dr})\n",
    "\n",
    "show_irfs([irf['ha'], irf['ha_zl'], irf['ra']], variables=['Y', 'r'], labels=['HA', 'HA-ZL', 'RA'], T_plot=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This gives us the figures in the lecture: HA>RA in the baseline calibration, but HA=RA under zero liquidity. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Direct and indirect effects of monetary policy\n",
    "\n",
    "Now let's decompose the total response into its constituent effects discussed in class - the \"direct\" effect from the `r` and the \"indirect\" effect from the `Y`, ie the endogenous response of labor demand in GE to increased consumption, resulting in more labor income and increased consumption, etc."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this, we need to call the `jacobian` routine of SSJ, which gives us the Jacobians of any block's outputs with respect to its inputs. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see what we need to give `jacobian` by calling the help again"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on method jacobian in module sequence_jacobian.blocks.block:\n",
      "\n",
      "jacobian(ss: sequence_jacobian.classes.steady_state_dict.SteadyStateDict, inputs: List[str], outputs: Optional[List[str]] = None, T: Optional[int] = None, Js: Dict[str, sequence_jacobian.classes.jacobian_dict.JacobianDict] = {}, options: Dict[str, dict] = {}, **kwargs) -> sequence_jacobian.classes.jacobian_dict.JacobianDict method of sequence_jacobian.blocks.het_block.HetBlock instance\n",
      "    Calculate a partial equilibrium Jacobian to a set of `input` shocks at a steady state `ss`.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(models['ha']['hh'].jacobian)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we see that `.jacobian` takes arguments (in order):\n",
    "1. `SteadyStateDict` (the output of a call to `.steady_state`, or `.solve_steady_state`),\n",
    "2. a `list` of inputs the user wants to calculate the Jacobian with respect to\n",
    "\n",
    "Now we're ready to calculate the direct effect of a change in the interest rate on consumption. \n",
    "\n",
    "Note that, as the DAG shows us, going from the primitive `r` to the household block requires first going through the `ex_post_rate` block to get the ex-post rate from the ex-ante rate. What we really want is this combined Jacobian."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A simple way to do this is to form a `CombinedBlock`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<CombinedBlock 'ha_combined'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ha_main = sj.combine([household_simple, ex_post_rate], name='ha_combined')\n",
    "ha_main"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now take the Jacobian of this block with respect to its two inputs `Y` and `r_ante`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "J = ha_main['ha_combined'].jacobian(ss['ha'],  inputs=['Y', 'r_ante'], T=T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.22517233, 0.14787708, 0.1068579 ],\n",
       "       [0.15589302, 0.18906426, 0.12392926],\n",
       "       [0.1211288 , 0.13060266, 0.17104103]])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "J['C']['Y'][0:3,0:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Play around a bit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# select a few columns\n",
    "col_list = [0, 5, 10, 15, 20]\n",
    "J_cols = [{'Y':J['C']['Y'][:, i], 'r_ante':J['C']['r_ante'][:, i]} for i in col_list]\n",
    "show_irfs(J_cols, ['Y', 'r_ante'], labels=col_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We use this to get the direct/indirect decomposition. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "dC, dC_dr, dC_dY = {}, {}, {}\n",
    "dC['ha'] = irf['ha']['C']\n",
    "dC_dr['ha'] = J['C']['r_ante']  @ dr\n",
    "dC_dY['ha'] = J['C']['Y'] @ dC['ha']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check that this the decomposition sums to the total: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.allclose(dC_dr['ha']+dC_dY['ha'], dC['ha'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we'll redo the same calculations in the RA model (getting the income effect from the IMPCs), and then compare the direct/indirect decomposition in both models. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Re-do the same calculations for the RA model\n",
    "dC['ra'] = irf['ra']['C']\n",
    "\n",
    "beta = calibration_ra['beta']\n",
    "Mra = (1 - beta) * beta ** (np.tile(np.arange(T), (T, 1)))\n",
    "dC_dY['ra'] = Mra @ dC['ra']\n",
    "dC_dr['ra'] = dC['ra'] - dC_dY['ra']\n",
    "\n",
    "show_irfs([dC, dC_dY, dC_dr], variables=['ha', 'ra'], labels=['total', 'indirect', 'direct'], T_plot=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We get back to the result from the lecture notes. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Cyclical income risk\n",
    "\n",
    "Before we introduce cyclical income risk, let's look at the baseline case of an impulse response to a future, anticipated interest rate cut (forward guidance) with our baseline HA model with acyclical income risk."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A simple way to do this is to get the general equilibrium Jacobian of the model, which we obtain with `solve_jacobian`. Then, the $s$th column of that Jacobian gives us the impulse response to a forward-guidance `r` shock at date $s$. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# Model jacobian in ra and ha models\n",
    "T = 300\n",
    "G = {}\n",
    "\n",
    "G['ra'] = models['ra'].solve_jacobian(ss['ra'], ['Y'], ['asset_mkt'], ['r_ante'], T=T)\n",
    "G['ha'] = models['ha'].solve_jacobian(ss['ha'], ['Y'], ['asset_mkt'], ['r_ante'], T=T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's plot this using for shocks at various horizons."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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S0tJiuj9D4RdLjyAIDSFez3sp+I9BdUqPVbGc6mwupsKv8EUG1LT0WJHDLyreSY+ug6/CmrWdKaBpdX64w+GIG5XHKv7yl7+Qm5vLyy+/bF7r0KGD+bmu68ycOZMpU6YwevRoAObNm0dWVhbz58/n9ttvj+n+ROEXhDhGzvsGIwX/MajO4dfRdT2UKqMCe/ivpJFP2oVqS4/SHH5p2m08+CogP8eatR/aBa4mdX74pk2byMnJwe12M3DgQPLz8+nUqVMMNxh/vPfee1x44YX8+te/ZtGiRbRp04axY8fy29/+FoCCggIKCwsZMWKE+TVut5shQ4awdOnSoxb8Ho8Hj8dj3i4pKan3/kThF4Q4Rs77BiMe/mPgtFX/aJRm8VuZ0qNY4ccZVvi9ksMvNF4GDhzIK6+8wscff8zzzz9PYWEhgwcPZv/+/VZvTSk//fQTs2fPpkuXLnz88cfccccd3H333bzyyisAFBYWApCVlVXr67Kyssz7DmfatGlkZGSYH7m5ufXenyj8giA0lHg+70XhPwZOR7Wi7wsETYtPzEmQSbsAmjP0vSr18EvTbuPBmRJSXqxau46MHDnS/Lx3794MGjSIU045hXnz5jFx4sRY7C4uCQaDDBgwgPz8fAD69+/P2rVrmT17NjfccIP5uMPfTT3eO6yTJ0+u9TMsKSmpd9FvpvSIwi8I8Yec9w1GCv5j4Kih8PtU2j8ssPSYBb9lTbsqFf5wwS9Nuyc/mhbR26zxQpMmTejduzebNm2yeitKad26NT169Kh17dRTT+XNN98EMD2vhYWFtG7d2nxMUVHREaq/gdvtxu12R2V/bqco/IIQt8h532DE0nMMjFhOAL9KNTiBLD3StCskIh6Ph/Xr19cqahOBs846iw0bNtS6tnHjRtq3bw9Ax44dyc7OZuHCheb9Xq+XRYsWMXjw4JjvL8khHn5BEKJLPJ33UvAfA03TzGm7ahV+Cy09FjXtKs3hl6ZdQTH3338/ixYtoqCggP/9739ceeWVlJSUcOONN1q9NaXce++9LFu2jPz8fDZv3sz8+fOZM2cO48aNA0Jn7oQJE8jPz+ftt9/mhx9+4KabbiIlJYUxY8bEfH+i8AuC0FDi+byPyNJz6NAh3n77bb788kt+/vlnKioqaNmyJf379+fCCy9UosKoxGHX8Ad1fCoVfnPwlgUpPao9/BYo/HZp2hUUs2PHDq699lr27dtHy5YtOfPMM1m2bJmpbCcKp59+Om+//TaTJ0/m0UcfpWPHjsycOZPf/OY35mMmTZpEZWUlY8eOpbi4mIEDB7JgwYKYZ/CDKPyCIDSceD7v61Tw7969mz/96U/861//Ijs7mzPOOIN+/fqRnJzMgQMH+Pzzz/nrX/9K+/btefjhh7n66qtjvW8lOO02qnxBtSk9dvWWHqty+M2UHp8VCr+oeIIaXnvtNau3EDf88pe/5Je//OUx79c0jby8PPLy8tRtKowo/IIgNJR4Pu/rVPD37duXG264gW+++YZevXod9TGVlZW88847zJgxg+3bt3P//fdHdaNWYCTzKFX4E2nSrhU5/A5p2hUE4UgMhT8QfldXWTKbIAiCAupU8K9du5aWLVse9zHJyclce+21XHvttezduzcqm7Oaag+/BZYehZN2jYI/qAcJBAPYbWrGQGuOcMFvQdOuWHoEQaiJofBDSOWXgl8QhMZEnU60ExX7DX18vFKt8Ftg6VHopzcsPaBW5a9W+FV6+MXSIwjCkRiDt0B8/IIgND4iljDmzZvHBx98YN6eNGkSTZs2ZfDgwWzdujWqm7MaI5ozUWI5QW3jrtG0qzalJxzLKSk9giDUQNM0XDJtVxCERkrEBX9+fj7JyckAfP3118yaNYvp06fTokUL7r333qhv0EosVfgtsPSA2sZda3L4wwq//EIXBOEwDJVfmcK/fwt88zwE1PZPCYKQeEQ8aXf79u107twZgHfeeYcrr7yS3/3ud5x11lkMHTo02vuzFIcVTbsWWHrsmh0NDR3dGkuPypQeadoVBOEYJDntlFb58fgUnPmeUph3GZTsgKbtoOuFsV9TEISEJWKFPzU1lf379wOwYMECLrjgAgCSkpKorKyM7u4sxrT0BBu3pSc0ZEx9Fr/mlBx+QRDiB1Ph9ytQ+D99NFTsA5Q3jqALQRDil4gV/uHDh3PbbbfRv39/Nm7cyCWXXAKEknw6dOgQ7f1ZijWWHmPSrjpLD4Qad31Bn9osfsPSY8mkXbH0CIJQmyRnKKEs5gr/tv+FrDwGvsYllgmCEH9ErPA//fTTDBo0iL179/Lmm2/SvHlzAFauXMm1114b9Q1aiTWxnOHXYIqn3hoKv09X+M6CFTn80rQrCMIxUKLw+z3w3l1AjTPIXxW79Y5CICgpRIKQaESs8Ddt2pRZs2Ydcf2RRx6JyobiCUPh96ssDm3qm3ahRsGvtGnX8PCr+16rFX4dXdfRNE3Z2oIgxDdKFP4vZ8C+DdCkJbQbBOvfA5+6gn/N3jXc8ckdXNP9Gu7qf5eydX07d+I/UExy76MP74wFuq5zYHc5zbJSTLFHEBKViP8HfPTRRyxZssS8/fTTT9OvXz/GjBlDcXFxVDdnNYaH36tU4TcsPQqtNVRn8VuTw6+wQdlRXeBL466ggsWLF3PppZeSk5ODpmm88847te7XdZ28vDxycnJITk5m6NChrF271prNJjhuM5YzRgp40Xr48m+hz0dOh/Sc0Od+NZaeoB5k6v+mUuIt4X+7/6dkTYBASQkFv76Kn6+9Fr/CwZwrP/yZ1x79hu8/36FsTUGI1zM/4oL/97//PSUlJQCsWbOG++67j4svvpiffvqJiRMnRn2DVuKwQuE3LT1qC35LmnaNHH6VKT01VB6x9QgqKC8vp2/fvkd9ZxRg+vTpzJgxg1mzZrF8+XKys7MZPnw4paWlincqxFThDwbg3fGhs73rSOh5BTiSQvcpUvjf2/Ie6/avA8AT8ChZE2Df7GcJHDgAfj++PUVK1iw9UMWKD0OzgYp3lytZUxAgfs/8iC09BQUF9OjRA4A333yTX/7yl+Tn57Nq1SouvvjiqG/QSlxGwd/IU3qgWuFXaumxIKXHsPRAOIvfZVe2thBddF2nUpEyejjJjuQ628FGjhzJyJEjj3qfruvMnDmTKVOmMHr0aCA03DArK4v58+dz++23R23PwomJqcK//AXYuQJcaXDJ30DTwBmaaaNC4S/3lfPkqifN21WK+ga8W7dy4J//NG/rHjXrLnt3C4HwCze/iphVIaacLOc9xO+ZH3HB73K5qKioAOCTTz7hhhtuACAzM9NU/hsLDsPSo3JIk0WWHlPhb+SWnloFvyj8JzWV/koGzh9oydr/G/M/UpwpDX6egoICCgsLGTFihHnN7XYzZMgQli5dKgW/YgyFvyraBWLhD/BJuM9teB5ktAl9rlDhf2HNC+yr3EeSPYmqQJUyhb/or3+FGqJOsCr23+ueghI2/m+PeVsK/pOfxnDeg7VnfsQF/9lnn83EiRM566yz+Oabb3j99dcB2LhxI23bto36Bq3EYTMUfgsm7Sq29JgefpXpQBZM2tU0DZtNIxjUJYtfsJzCwkIAsrKyal3Pyspi69atVmwpoYmawh8Mws6VsOED+PG/oSZdCDXpnnZL9eMUKfzbS7czb+08AG7veztPrnpSScFf/s03lC78BGw27JmZBPbtQ/fEdl1d1/nq35sAcKc48FT48Xul4BfiAyvP/IgL/lmzZjF27Fj+/e9/M3v2bNq0CSkVH374IRdddFHUN2glrnCDp9+KSbuJYOlxqFf4IaTyB4O6ZPGf5CQ7kvnfGHWNh4evHU0Of7tYEqSsoV4Kv65DaSHs2xj62L0aNi6A8hpedZsDOg6BS2eCrUbrnCKFf8aKGfiCPs5sfSYXtr+QJ1c9GXNLjx4MUvT4XwBoevVVeDdvoWLfPvQYK/xbVu1l95ZDOJw2ThvZgaVvbibgkxjSk53GdN6DNWd+xAV/u3bteP/994+4/ve//z0qG4onDIXfa0ksZyJZetR+rzaHDXxBsfSc5GiaFrW3Wa0iOzsbCKk+rVu3Nq8XFRUdoQAJsadOCr+vCrZ8Bhs/hD3rYN8m8Bw6ypOlQ5fh0O1i6HwBJDc98jEKFP7lhcv5ZNsn2DU7k06fhNvhBqAqUBXTIuPQO+9StW4dtrQ0Wt51F7seeBCAYFXsFP6AL8jXb28GoP+IdmS0DP18xdJz8tMYznuw9syPuOBPJAwPfyIo/Nbk8Ku39EC1jz8gCr9gMR07diQ7O5uFCxfSv39/ALxeL4sWLeIvf/mLxbtLPNzHUvh9VbDlU1j7Dmz4ELyHpWloNmjWEVp2gxZdodNQaH8WOFzHXzDGCn8gGOAv34T+Hf2666/p0qwLh8IvToJ6EH/Qj9P4nRNFguXl7A2LgC3uuANHZia2pNALjVg27X7/+Q5K9lWRkuGi/4j27N5yEEAsPULcYOWZHzcF/7Rp03jooYe45557mDlzJhB6i+ORRx5hzpw5FBcXM3DgQJ5++ml69uypZE9GSo/aSbsWe/hVKvyu8PeqMJYTwF5j+JYgxJqysjI2b95s3i4oKGD16tVkZmbSrl07JkyYQH5+Pl26dKFLly7k5+eTkpLCmDFjLNx1YlJL4fd7YPOnsPbtI4v8tBzocTm0GwgtukHzUyCsnEdEjBX+tza/xYbiDaS70hnXbxwAScaLDEIqfywK/v0vvoR/716cubk0u/46ADR3aN1YKfyVpV5W/LcAgDMvPwWn244j/ALOL5YeQSHxeubHRcG/fPly5syZQ58+fWpdN7JK586dS9euXZk6dSrDhw9nw4YNpKWlxXxfhsLvSyRLjwU5/OoV/tAv9aA07QoKWLFiBcOGDTNvG/NKbrzxRubOncukSZOorKxk7NixprCxYMECJWecUJtke5ChttX8ats8eGJZbatOeptQkd9jFLQ9vbYXv77ESOHXdZ3FOxbz1KqnABjbbyxNk5oC4LK50NDQ0fEEPKQR3X9nvsJC9r/0EgCt7r8fmyv0LocWY4X/m/cL8FYFaNkuje5nhmwTDlfo7ygglh5BIfF65lte8JeVlfGb3/yG559/nqlTp5rX65tV6vF48NRIAWhIVKjTihx+I5Yz6As1gylq3LOmaTdc8FvQtAtI066ghKFDh6Lrx35xqWkaeXl55OXlqduUUJv9W+Crmfxmzbvc4joExq+NtNahAr/nFdEr8msSA4V/2e5l/OPbf/D93u8B6NqsK1d1u8q8X9M03HY3VYGqqDfuVm3cSOHDeehVVSQPOI20EcPN+2ymwh/9Fzeblu9h7Ze7ADjrV53RbKEz3u4M/w4XS4+gkHg98y0v+MeNG8cll1zCBRdcUKvgr29W6bRp03jkkUeisjej4PepVILtNf5Kgv5qi0+MSZQcfgg37SKWHkEQwgR8sOoV3MBePZ3v0oZwwZV3hmI0o13k1ySKCv/qotX849t/8E3hNwAk2ZMYc+oYbul1iynoGLgd7qhm8fv2FLH3H09x6K23IRhEc7vJmjy5VkOwqfBH0dJT+NMhlryxiT0FoVdop/yiJW26NTPvNy09XrH0CELEBX9VVRX/+Mc/+PzzzykqKiJ4mPq9atWqOj/Xa6+9xqpVq1i+fPkR99U3q3Ty5Mnm2ycQUvhzc3PrvKeaOMIqgc+KSbsQ+iWkuuBv5Dn8IE27giAcRqvuMOQBvvZ347pPnZzepiUXdBgU+3VNhb9+Bb8/6OfLHV/y2obXWLpraegpbU6u6nYVt/W+jRbJLY76dW57dVJPQwiWl7P/pZfZ/9JL6JWhdynSLryQVhPvxdW+fa3H2pJC32uwquHvZpTsq+Trt7eweWUo+tThtvOLEe3oP7xdrccZlh6/LyhRt0LCE3HBf8stt7Bw4UKuvPJKzjjjjHr/B9q+fTv33HMPCxYsICkp6ZiPizSr1O1243bXo3nqKJgKv0ol2F4j1SHgBdTEUJmWHoXNwlbl8EvTriAIRzDsIcrW7SHAiuhP2j0WpsIfWRFcWF7IW5ve4s1Nb1JUESp67ZqdUZ1HcXuf22md2vq4X59kD63r8ddPbQ+UlXHozTfZ98ILBPbuAyC5Xz9aTZpEyi/6H/VroqHwlx/ysHrhNr7/YkeoB0uDUwe3ZuBlnWiSceTvfYfLXr1nf9BU/AUhEYm44P/ggw/473//y1lnndWghVeuXElRURGnnXaaeS0QCLB48WJmzZrFhg2hyYRW5lM7rYzlhJClRxFmLKfKgt9lUQ6/XSw9giAcSXVKj6Iz31D4gz4IBsB2/IL0m93f8Oq6V1m8czFBPbTHZu5mXN75cq7qehW56XV7N7tmFn8k+Hbt4sCr/+TgG28QLCsLfQu5ubS67z7SLhxxXDHO9PDXo2n3wK5yVn+yjQ3fFJphC227N+OsKzvTou2xGx0dzmo7lt8rBb+Q2ERc8Ldp0yYqncTnn38+a9asqXXt5ptvpnv37jzwwAN06tTJ8nxqSxR+TQPNDnogrPCrwcocfrwWWXpU/VIXBOGkwCz4VcU41ojIxFcJ7tSjPqyooojpy6fz8c8fm9cGZA3g111/zQXtL8BlP0He/2FEqvBXrlnDgZfnUvLxxxAI/WxcHTuSeeONNB19BZrrxOtHqvDrus6ujQf59pNtbF2z37ye3Smd00Z2oH2v5id0GNjsGpoWyr+QpB4h0Ym44P/b3/7GAw88wLPPPkv7wzx6kZCWlkavXr1qXWvSpAnNmzc3r1udT+2wIocfQrYef6XSaE5Lcvgtatq1O8TSIwjCkSSFFWBlCn/Ngt9fdUTB7w/6ee3H15i1ehblvnJsmo0ru1zJb079DZ2adqr3skYW/4madv3791P456mUfvSReS1l0Jk0v+kmmpxzDloEDc22sHW3LrGc+3aU8cW/fjSbcdGgU7+W9LugHa1PyajzmpqmYXfZ8XsCksUvJDwRF/wDBgygqqqKTp06kZKSgtNZu6n0wIEDUduc1fnUpqVHZdMuhGw9/kpLLD0JlcMvTbuCINTAHbaAVKkqDm02sLsh4DnCx//d3u+YumwqPx74EYA+LfrwhzP/wKnNT23wsidq2tV1ndIPP6Twz1MJFBeD3U7GpZeSedONJHXvXq816zJ4KxgIsurjbSz/oIBgQMfhtNF9cGv6npdL06z69bM5nLZQwS/RnEKCE3HBf+2117Jz507y8/PJysqKatf7F198Ueu21fnUllh6oNrHr9DSY0UOP5bn8IvCLwhCNUkOxQo/gDMpVPCHk3rKfeX8feXf+b8N/4eOTporjQm/mMCVXa/EpkUnIvR4lh7/3r0UPvoopQs/AcDdrRut8x8juYET7m2mpefoLzL27yrjs3nrKdoammjcsW8LhozpdtRm3EgwfPx+sfQICU7EBf/SpUv5+uuv6du3byz2E1eYsZyqlWALpu1amcNPMIgeCKDZ1TRUSdOuIAhHQ7nCD+BIBg6Br5Klu5aStzSP3eW7AbjslMuYeNpEmic3j+qSR2va1XWdkvffZ8/UxwgcOgQOBy3uuIMWv/ttnTz6J8JU+D21X2QEgzqrF27jf//5iaBfx53i4Jyru9L1jOgIikZST0AsPUKCE3HB3717dyorozcVMJ4xJ+1apfArTMyxxNJTww6m+/0KC35p2hUE4UgMhd8f1PEHgmYfV0xxJlGqafxtzbO8uftLANqktuGRwY8wsPXAmCxpKvxhD3/g0CF2P5xnevXdPU4lJz+/3vado3E0hb9kXyULX1pL4U8hr377Xs0Zdl13mjSNTrQ2yLRdQTCI+DR7/PHHue+++/jiiy/Yv38/JSUltT4aE07LmnbVK/zW5PBXv97UfepeaEgOv6CSxYsXc+mll5KTk4Omabzzzju17r/pppvQNK3Wx5lnnmnNZmNIXl7eEd9ndna2eb+u6+Tl5ZGTk0NycjJDhw5l7dq1SvforhHjqMrW86XbyRVtW5vF/rXdr+Wty96KWbEPNTz8/ioqli/np1FXhIp9h4MWd99Fx9dfj2qxD6Al1Vb4N63Yw+tTv6HwpxJcSXbOu6E7l4zrE9ViH8TSI6gnXs/8iBX+iy66CAjFatbEGIgVCDSet80c9gS09Fik8KMwi9/mEEuPoI7y8nL69u3LzTffzK9+9aujPuaiiy7i5ZdfNm+7omChiEd69uzJJ598Yt6213hXb/r06cyYMYO5c+fStWtXpk6dyvDhw9mwYYOyoAa3o3o/Hn+QJtGtPWtR5i1j+vLpvJ3sARzkupvz6NC/MiB7QOwWDeN2uLEHdNq/vpSt/3kOgkGc7dvR5q9/Jbl375isqYUHYvq9AT7/54+sW7ILCMVsDr+lJ+ktkmOybvW03cZTmwjxTbye+REX/J9//nks9hGXmJaeoDTtxgLNbscISVaZ1GNaeiSl56RG13V0i+yFWnJynf3FI0eOZOTIkcd9jNvtrqV2N1YcDsdRv09d15k5cyZTpkxh9OjRAMybN4+srCzmz5/P7bffrmR/dpuG067hC+h4/LErEFcUruAPX/2BnWU70XT4TUkJdw/9I8kKin2Apvs8PPLPAF13fQdAxujRZE95CFuTJjFb05aURFmTHH7ofisVS3aBBqdd2J7TL+2IPYbWKWPYllh6Tm5OlvMe4vfMj7jgHzJkSCz2EZcYsZw+1V5v08OvTm23IocfQiq/7vUqTeqxS9Nuo0CvrGTDL0478QNjQLdVK9FS6hcTeDS++OILWrVqRdOmTRkyZAiPPfYYrVq1itrzxwubNm0iJycHt9vNwIEDyc/Pp1OnThQUFFBYWMiIESPMx7rdboYMGcLSpUuPWfB7PB48NZpAo2ErTXLY8QX8VMXAAuIJeJj17SzmrZ2Hjk6b1DZMLYcBB7aBrub3TMmHH3L6Q6/hqARvspOOjz1O+sUXx3RNXddZ/10ZK06bRNDmJCXDxfCbe9C2e2ZM14VqS48M3jq5aUznPVhz5kdc8AMcPHiQF198kfXr16NpGj169OCWW24hI6PuAzFOBhzhoSI+1Qp/glh6IOTj171eSxT+oDTtCnHAyJEj+fWvf0379u0pKCjgj3/8I+eddx4rV67E7Y6hp0QxAwcO5JVXXqFr167s2bOHqVOnMnjwYNauXUthYSEAWVlZtb4mKyuLrVu3HvM5p02bxiOPPBLVfbqdNko9RF3h33BgAw9++SCbD24G4IrOVzDp9Emkvvm70AN8sVUvg14vRX+ZTvG//oUDWN8Wvh97NnkxLvZ9ngBfzP+Rjf/bAzYnzff/wKWP3ECTrKYxXdfA7pKmXSG+sOrMj7jgX7FiBRdeeCHJycmcccYZ6LrOjBkzeOyxx1iwYAG/+MUvYrFPS3CFJ7L6rZi0C9ZYehQ27YYWVj9tV3L4GwdacjLdVq20bO1ocfXVV5uf9+rViwEDBtC+fXs++OAD097SGKj5Fnfv3r0ZNGgQp5xyCvPmzTMb1g5/29zoDTsWkydPZuLEiebtkpIScnNzG7RPw8cfLYU/qAd5dd2rzFw1E3/QT2ZSJg8Pepjz2p0XeoAzPG3Xf+IJtPXFu2MHOyfcS9UPPwCw98pzeeSUrzg3I7bJaAf3VPDhc2s4sKsczQadNr1Nu+2f4nZeF9N1a2JaesTDf1LTWM57sO7Mj7jgv/fee7nssst4/vnncYRTVvx+P7fddhsTJkxg8eLFUd+kVZgKv/JYzvBfSyOftAvVjbsqU3qkabdxoGla1N9mjQdat25N+/bt2bRpk9VbiSlNmjShd+/ebNq0iVGjRgFQWFhI69atzccUFRUdofrXxO12R10RM5J6PFEoEA9WHWTKV1NYvCP0e3FY7jAeHvRw7Vx9R7iYiJHCX/rpp+ya/BDBkhLsGRnkTP8Lm9uWEFyy9JiTdqPBllVFfPrKenxVAZLTXVx4W09KfzUBHf2Yw7digaT0NA4a63kP6s78iDtlVqxYwQMPPGAW+xBqxJo0aRIrVqyI6uasRlJ6Yo8RzSlNu4IQYv/+/Wzfvr1W4dsY8Xg8rF+/ntatW9OxY0eys7NZuHCheb/X62XRokUMHjxY6b6MLP6qBlr+Vu1ZxZX/uZLFOxbjsrn445l/5MlhTx45RCtGCr/u97PnL9PZMW48wZISkvv2pePbb5E6ZAhJjto5/NEkEAjy1b838dGcH/BVBWjdOYOrp5xOm67NTKU0WBX9dY+FMXjL7xWFX4hPVJ35ESv86enpbNu2je6HZfRu375dWXSaKlyW5fAnjqXHjOZUGMspTbuCSsrKyti8ebN5u6CggNWrV5OZmUlmZiZ5eXn86le/onXr1vz888889NBDtGjRgiuuuMLCXUef+++/n0svvZR27dpRVFTE1KlTKSkp4cYbb0TTNCZMmEB+fj5dunShS5cu5Ofnk5KSwpgxY5Tus6EKf1AP8tIPLzHr21kE9AAd0jvw1yF/pVtmt6N/Qbj4jqbCHzh4kB333kvF18sAyLzpJlpNvNecmFszhz+aVJX5+GjOGnZuPAhAv+HtOHNUJ/PMtbndBAG9Sl3aSnUspwg8ghri9cyPuOC/+uqrufXWW/nrX//K4MGD0TSNJUuW8Pvf/55rr702Fnu0DGPKYlAPjf+22Ro+5rtOJJKlx0KFX5p2BRWsWLGCYcOGmbcNz/mNN97I7NmzWbNmDa+88goHDx6kdevWDBs2jNdff73RCSg7duzg2muvZd++fbRs2ZIzzzyTZcuW0b59ewAmTZpEZWUlY8eOpbi4mIEDB7JgwQLlP4eGKPzFVcVM/nIyX+36CoBLOl3CH8/8I02cx4m7dIYtPVEqvj2bN7N97Dh827ahpaSQ8/g00mukH8GRk3ajQXFhOR88/T2H9lbidNs5/8ZTOeUXtVNHzOFbChV+Y9JuQJp2BUXE65kfccH/17/+FU3TuOGGG/CHGy2dTid33nknjz/+eNQ3aCVGLCeALxjEbYttg5NJIin8RsEvTbtCI2Xo0KHo+rH/rX388ccKd2Mdr7322nHv1zSNvLw88vLy1GzoGNRX4d9ycAvjPh3HzrKdJNmTeGjgQ4zqPOrE+d1RVPhLP/+cXff/nmB5Oc42bWj7zDMkdet6xOPcjpDCH62Cf/v6A3w05we8lX7SMpO4ZFwfmrdJPeJxtqTQurpHpYdfmnYFtcTrmR9RwR8IBPj66695+OGHmTZtGlu2bEHXdTp37kxKI2ymcNYYBuIL6LjrFWJaDxLJw29BSo893LQbkIJfEITDqI/C/+WOL5m0eBJlvjLaprblqfOeokuzLnX74igo/Lqus/+FF9g74++g66QMGECbp57EkXn0nHtD4Y+GpeeHxTtZ/NpG9KBOdqcMRt7Rm5T0o08N1dyGwq+w4BdLjyAAERb8drudCy+8kPXr15OZmUnvGI3gjhccNSw8SqM5TUuP+oJffSynhZYeadoVBOEwIlH4dV3nX+v/xRMrniCoBzkt6zT+PvTvNEtqVvcFG6jw614vu/7wB0re+w8ATa++muwpD5l+/aNhePgbovAHA0G++vdmvv98BwBdB2Yx7LrupqJ+NDRT4VfYtGuk9IilR0hwItase/fuzU8//UTHjh1jsZ+4wm7T0DTQdcXRnKalR10RbE7aVe7htyCWUyw9giAcA3f4HUDPCRR+X9BH/v/y+ffGfwOhQVp/PPOPOI1J6XWlAQp/sKKCHXffQ/mSJWC3k/2HKTSrQy+dkdJT31hOvy/AghfWUvDdPgAGXt6J0y5qf0L7ks0KhT/8AiQglh4hwYm44H/ssce4//77+fOf/8xpp51Gkya1m5HS09Ojtjmr0TQNp82GNxBUm9RjoaXHqpQeXWFKj01SegRBOAZJ4QLxeAr/Ic8h7vviPv5X+D80NO4bcB839LjhxH79o2Eq/JEVwYGDB9l+x51Url6NlpxM26eeIvWcs+v0tYalxx/0EwgGsEfQn+bzBPjv7O/Z8WMxdqeN4Tf3OKI591gYTbu6yqZdsfQIAlCPgv+iiy4C4LLLLqt1uBkTEQOBxvUq2mnX8AbAr1ThD/+1KGzaTcSUnoCk9AiCcBiGwn8sD39heSF3fnInmw9uJsWRwvRzpzMkd0j9FzQV/rpbenx7ith+2214Nm3ClpFBu+eeJblfvzp/vdG0CyFbT4qtbj14ngof78/6nsKfDuF027lkbB/adKu7fcnmtqJpVyw9ggD1KPg///zzWOwjbglFcwbwKvXwhy09Cotv63P41TftisIvCMLhHE/h31y8mTs+uYM9FXtoldyKZy545tj5+nUlQoXfu20b2265Fd+OHThatiT3xRdI6npkEs/xMDz8ELL1pDhPXPBXlnp576nV7NtehjvFwS/v6kt2x4yI1rUillNSegQhRJ0K/tGjRzN37lzS09PZunUrV199ddTHmccrRjSnP5gYlh5/0G++W6MCS3P4pWlXEITDMBX+wywgK/es5K7P7qLUW0qnjE48e8GztE6NwmTMCBT+qg0b2HbbbQT27sPZrh3tXnoRV9u2ES9p02y4bC68QS8e/4mL7/KDHt6d+S3FhRUkpzm57J5+tGgbeWa4JbGcYUtPQCw9QoJjO/FD4P3336e8vByAm2++mUOHDsV0U/GEEc2p1tJjFPzqc/gB/Lo6tV0zU3qkaVcQBOsxFX5/tSL8ydZP+N2C31HqLaVfy368MvKV6BT7UGeFv3LtWrbecCOBvftwd+9Oh3/9s17FvoFh6zlR427Jvkre+utKigsrSG3m5or7flGvYh9qxnKqH7wllh4h0amTwt+9e3cmT57MsGHD0HWd//u//ztmc+4NN9wQ1Q1ajSNcHKq19ISLbwssPRBS+WvejiWSwy8IQjxxuML/+o+v89j/HkNHZ1juMKafO91MuYkKdVD4K9euZdsttxI8dIjkfv3InfMc9gYGZCTZkyil9LjRnKUHqnjn799Sur+K9BZJXD6hP+ktkuu9phnLaUFKjzTtColOnQr+Z599lokTJ/LBBx+gaRp/+MMfjmr5MCbwNiacNgsUfgstPaC4cddKS4807QqCcBhupzF4y8+sb2fx3PfPAXBl1yuZMnBKrbMyKpxA4a9V7PfvT+7zc7CnHjnFNlIMH/+xhm+VH/SYxX5Gy2SuuO8XNGnaMCuvGctpgaVHD+oEAkHs9joZGwSh0VGnf/mDBw9m2bJl7N27F13X2bhxI8XFxUd8HDhwINb7VU61pccChd+ClB5Q27hr5vArjeUUS4+gjmnTpnH66aeTlpZGq1atGDVqFBs2bKj1GF3XycvLIycnh+TkZIYOHcratWst2nFiE1L4g/ykv2IW+2P7juVPZ/4p+sU+1Fb49dpnUqyKfajO4j+awl9R4uXdmd9SsrcypOzf27/BxT7UVPjVD94CCIitR4gx8XzeR/xSt6CggJYtW8ZiL3FJolh6bJoNuxZ+61PhulZYeiSHX1DJokWLGDduHMuWLWPhwoX4/X5GjBhh9kUBTJ8+nRkzZjBr1iyWL19OdnY2w4cPp7S01MKdJyZ2e4CkNv+i2L4YDY0/nvlH7ux3Z+yCDGrag2o00May2IdjK/yVZV6zQTe1mZvLJ/QnLTM6FiZbknqF316j4BdbjxBr4vm8j1iuaN++fSz2EbdY0rRrU6/wQ0jlDwQCihX+8D9BK3L4JaXnpEbXdcsa8RwuW50LwI8++qjW7ZdffplWrVqxcuVKzj33XHRdZ+bMmUyZMoXRo0cDMG/ePLKyspg/fz6333571PcvHJ1SbykvbnoIZ/pa0B38bdh0hrcfHttFnTU88f5KcCbFvNiHGgV/jabdqnIf7z25mgO7ymmS4WLUxIZ59g/HisFbmqbhcNrw+4L4vRLNebIi533DicH7k40LI5ZT6aRdI4dfoYcfQo27noDHGoVfYUqP5PA3DvzeIHPuWWTJ2r97cghOd92nk9bESDnLzMwEQu+aFhYWMmLECPMxbrebIUOGsHTpUin4FbG3Ym9ooFbpBvSAm2Zlt8e+2IfQO7qaHfQA+Kqo+nl9zIt9ONLS46n0859wzn5yuovL7+1PRsu6DeSqKzaz4Fen8ENo2q7fFxSF/yRGzvuGI90rJ8ARbtr1BS2YtKt46q0V03arYzmlaVdo/Oi6zsSJEzn77LPp1asXAIWFhQBkZWXVemxWVpZ5nxBbtpZs5foPr2dD8QYyXJlUbL0dvfIUdRsIq/yejT9WF/t9+8as2Ifalh6fN8AHT39H0dZSklKdXD6hH82ym0R9TS08vyfoUafwQ42kHlH4BYXE23kvCv8JcDqsaNo1FH61lh5Lpu0aKT1KPfyhgl/XQ8kNmk3NkDEhujhcNn735BDL1q4P48eP5/vvv2fJkiVH3Hf4W8YqB+AlOuW+coqrislNy+X3ff/Kzd8VUOVUeOY7kvDsq2Tr3Q8RKD5IUq9e5L7wfMyKfQjFcgJUeT189Owadm8+hCvZwWX39KN5TmzWrVb4TzxkLJoYjbui8J+8yHnfcKTgPwFOmwWWHgtiOcEqhd+CHP4asWzBgI5dCv6TEk3T6v02qxXcddddvPfeeyxevJi2NQYmZWdnAyHlp3Xr6mFORUVFR6hAQmzo0bwHzw5/lty0XErKkoCCWoO3Yo23Ioltn7cgUHkQ96mn0u6F57Gn1W+4VV1xO9xouo3yjzIo3XIAh8vGL8f3pWVu7Na1YvAW1Ji2Kyk9Jy1y3jecqFl6HnroIW655ZZoPV3c4DA9/GLpiQVmLKcFlh6Qxl0h9ui6zvjx43nrrbf47LPP6NixY637O3bsSHZ2NgsXLjSveb1eFi1axODBg1VvN2Hp36o/LZJbVE/aVaQG+3buZOv7Ov5KO+72ObR78QXsTZvGfF23zc2QLVcT3JKKzaFx8R19aH1KRkzXtFkweAvAbg7fEkuPEFvi+byPmsK/c+dOtm/fHq2nixuMlB5rmnYbv6VHMy091hT80rgrxJpx48Yxf/583n33XdLS0kyfZkZGBsnJyWiaxoQJE8jPz6dLly506dKF/Px8UlJSGDNmjMW7TzyMSbveQJBgUMcWw3cAfYWFbL3pZvxlOq40P+2mjsMRbu6LJbquk7aiM832tkLXdC68tTe5PWK/rmbGcqr28IulR1BDPJ/3ERf8ixYtYsiQI31U8+bNi8qG4g1rYzmtsfQoLfjDlh4UWno0mwYaoEvBL8Se2bNnAzB06NBa119++WVuuukmACZNmkRlZSVjx46luLiYgQMHsmDBAtJibOsQjsRQ+AE8/iDJrtjYCPz79rHtppvxbd+Os6mdducW4kh1xWStw/nm/QIca1sBUHHWZjr1P1/Juja3NQq/YemxKtZRSBzi+byPuOAfPnw42dnZjBkzhuuuu87sPG6smLGcQSsm7aqP5QSLUnq8Cl9kaBo2u0bQrxOQpB4hxuj6iV9UappGXl4eeXl5sd+QcFwMhR/A4w/EpOD3Fxez7eZb8P78M46c1rQf5cJ5YDv4Y18If/fpdlZ88DMAX3b4N107toj5mgZmDr/Xix4MotnUBAUaKT0BsfQIMSaez/uI/7ft2rWLSZMm8eWXX9KnTx/69OnD9OnT2bFjRyz2ZzkOw9LjV+nhNybtJo7Cr7JpF6obd0XhFwShJg67DUfYxlMVAwtIoKSE7bfehmfTJhwtW9J+7lyczdNDd/pim17z47LdLHljEwDuM0tY2/rLWoO3Yo3RtAugK7T12MXSIwiRF/wtWrRg/PjxfPXVV2zZsoWrr76aV155hQ4dOnDeeefFYo+WYqT0+FUq/ImU0uNQn8MPNbL4pWlXEITDMFT+aCf1BMrK2f7b31G1bh32zEzazX0ZV7t24AwXwjFU+Au+28tnr/wIQN/zc0k7M9Qj5vGrK7yNpl2AoEJbj1h6BKGBKT0dO3bkwQcf5PHHH6d3794sWmTNFLRYUt20a4HCb5Glp7Hn8EPNgl8UfkEQauMOW0CiqfAHKyvZMXYsld99hy0jg3YvvYj7lPBwL0do8FasFP6dG4v5+Pm16EGd7mdmc9avOpPsrD1pVwWaw1F95itU+B2S0iMI9S/4v/rqK8aOHUvr1q0ZM2YMPXv25P3334/m3uIChyUpPdZaehp7Dj+A3SGWHkEQjk5SlBX+oNfLjrvupuKbb7A1aUK75+eQ1L179QNiqPDv3VbKf5/5noA/SIc+LRh2fXc0m1Y9aVehpQesadyVlB5BqEfT7kMPPcT/+3//j127dnHBBRcwc+ZMRo0aRUpKSiz2ZzlG067SSbsJZelRn8MP1Qq/NO2eXNSlISoRkJ9DbImmwq/7fOycOJHyJUvQkpPJnfMcyX361H5QjBT+g3sq+M8/VuOtCpDTpSkX/rYntrCIZUzaVWnpgXDjbnm50mhOuwzeOmmRsy5ENH4OERf8X3zxBffffz9XX301LVqo6+63CsPS41Vq6QlHs+kBCAZBUZKBJTn84ZQeFObwA+YvPVH4Tw6c4XeCKioqSE5Otng31lNRUQFU/1yE6BItD78eCLDrwcmUffIpmstF7tOzSDnttCMfGAOFv6zYw3tPrqay1EfLdmlcMraPaW2B0KRdsEbhD2CVwi+WnpMFOfNrE40zP+KCf+nSpfVe7GTEYYXCb6/x1xL0gc197MdGEUstPQpjOaGGwi9NuycFdrudpk2bUlRUBEBKSgqaFruBSPGKrutUVFRQVFRE06ZNsdtPnlHzJxPRUPj1YJDdDz9MyQcfgMNBmydn0uRYkzSjrPBXlfv4zz9WU3qgioxWyfxyfF9cybV/3ZsKv0IPP9QYvlVlhYdfzvuTBTnzQ0TzzK/XpN1XX32VZ599loKCAr7++mvat2/PzJkz6dixI5dffnm9NxOPuIzBW0ELFH4ITdt1qCn4rZ20K027wvHJzs4GMH8BJDJNmzY1fx5C9Gmoh1/XdfZMe5xD/34TbDba/PUJ0oYNO/YXGAp/FAp+nzfAB09/z4Fd5TTJcHHZ3f1IST9yoJfh4Vdv6Ql7+D2S0iMcHznzq4nGmR9xwT979mz+9Kc/MWHCBB577DECgYC5mZkzZza6gt/IY/Za4eEHpT5+awZvSdOuUDc0TaN169a0atUKn+Kej3jC6XSKsh9jGqrw7535JMWvvgpA68ceI/2ii47/BYbC729YwR8IBPn4+R8o/OkQ7hQHl97dj/QWR7dDWGbpSQrtR20spwzeOhmRMz9EtM78iAv+f/zjHzz//POMGjWKxx9/3Lw+YMAA7r///gZvKN4wUnrUNu3W+ItVWHxbYenB6hx+ado96bDb7VLwCjGlIQr/vmefY/9zzwGQ9ac/0vSKUSf+IlPhr38RrAd1Pn/1R7au2Y/daeOSsX1o3ib1mI83LD1VCqb71sRmKvwqLT2S0nMyI2d+dIi4G7SgoID+/fsfcd3tdlNeXh6VTcUTpqVHpRKsadW2noBX2bLWWHqsUfjF0iMIwrGor8J/4JVX2DtzJgCtfv97MseMqdsXRkHhX/r2FjYsK0SzaVz021607tz0uI83LD3eoJegrq4QNqbtqlT4zUm7YukREpiIC/6OHTuyevXqI65/+OGH9OjRI6Lnmj17Nn369CE9PZ309HQGDRrEhx9+aN6v6zp5eXnk5OSQnJzM0KFDWbt2baRbbhBG065SSw9YEs1pSdOuyyJLj5nSI78ABMEKpk2bhqZpTJgwwbwWD2c+1E/hL379/9iTPw2AFuPG0fzWW+q+YAMV/lULtrJ64TYAzruhOx36nDhBL8mRZH6udPiWofCrbNoNW3r8XrH0CIlLxAX/73//e8aNG8frr7+Orut88803PPbYYzz00EP8/ve/j+i52rZty+OPP86KFStYsWIF5513Hpdffrl5wE+fPp0ZM2Ywa9Ysli9fTnZ2NsOHD6e0tDTSbdcbpxUKP1Qn9TRyS49msaUnIAq/IChn+fLlzJkzhz6H5dHHw5kP4A4rwnVV+A+99x6FeXkAZN56Cy3Gj4tswQYo/D9+vZuv39oCwODRnel+Zus6fZ2h8IPaxl2bqfDHZqrw0RBLjyDUo+C/+eabefjhh5k0aRIVFRWMGTOGZ599lieffJJrrrkmoue69NJLufjii+natStdu3blscceIzU1lWXLlqHrOjNnzmTKlCmMHj2aXr16MW/ePCoqKpg/f36k2643xuAtpZN2IYEsPeEXNj6f0gEbksMvCNZQVlbGb37zG55//nmaNWtmXo+XMx8gyRFShOui8Jd89DG7HpwMuk6zMWNodf/9kccH1lPh/3nNPj579UcA+g1vR/8R7er8tQ6bA4cWOn9VNu5ao/BLwS8I9Zro9Nvf/patW7dSVFREYWEh27dv59Zbb23QRgKBAK+99hrl5eUMGjSIgoICCgsLGTFihPkYt9vNkCFDjjsLwOPxUFJSUuujITjCQ698KmM5IXEsPTWHSCi09dgcMmlXEKxg3LhxXHLJJVxwwQW1rtfnzI/2eW+uG1aEPScoEEu/+IKd998PwSAZvxpN1h+m1C8r3FT46154795yiI/n/IAe1Ol2ZjaDrzgl4mWNpB6Vlh5D4VcayxnuyQiIpUdIYBo0wrVFixa0atWqQRtYs2YNqampuN1u7rjjDt5++2169OhBYWEhAFlZWbUen5WVZd53NKZNm0ZGRob5kZub26D9OR0WpPQA2NUX/JYq/Kj18UvTriCo57XXXmPVqlVMmzbtiPvqc+ZH+7w3qIvCX750KTvvvgf8ftIvuYTWjz6KVt+p6BHm8B/YVc4HT3+H3xekfa/mDLu+O5ot8hcahq1HZVKPFYO37GLpEYS6xXL279+/zqrFqlWrItpAt27dWL16NQcPHuTNN9/kxhtvZNGiReb9h6+r6/px9zJ58mQmTpxo3i4pKWnQLwGnzSpLT7jgV1h8Gwq/0oK/hsKvsuCXpl1BUMv27du55557WLBgAUlJScd8XCRnfrTPe4MTKfwVK1awfdx4dK+X1AvOJ+fxaWgNiQ00GmjrUHiXHqjiP/9YjafCT1bHdC78bS/zPIsUK6bt2iwcvBUM6ASDOrZ6vDgShJOdOhX8o0aNMj+vqqrimWeeoUePHgwaNAiAZcuWsXbtWsaOHRvxBlwuF507dwZCWf7Lly/nySef5IEHHgBCqk/r1tVNSEVFRUcoQDVxu9243dGbTOuwqmk3QSw91Cz4FTbuisIvCGpZuXIlRUVFnHbaaea1QCDA4sWLmTVrFhs2bAAiO/Ojfd4bJBmxnEdR+CtWfcv2392OXllJk3POoc2MGbWtifXBGbb0nEDhryrz8Z+nVlNW7KFZdgq/HNcXp7v+LzSMpB6lKT1u9Qq/YemBUFKPKyniEUSCcNJTp3/1Dz/8sPn5bbfdxt13382f//znIx6zffv2Bm9I13U8Hg8dO3YkOzubhQsXmrn/Xq+XRYsW8Ze//KXB69QVs2k3KJaeWKBpGtjtEAig+1RaeqRpVxBUcv7557NmzZpa126++Wa6d+/OAw88QKdOneLizAdwO46u8Fd+/z3bf/c7ghUVpAw6k7b/eAqby9XwBQ2FXw+Eznz7kS8gfJ4A7z/9HcWFFaQ2c3Pp3f1ISm3YCw1rLD1G065KD3/1OyABXxCO/QaTIDRaIn6Z+8Ybb7BixYojrl933XUMGDCAl156qc7P9dBDDzFy5Ehyc3MpLS3ltdde44svvuCjjz4y85nz8/Pp0qULXbp0IT8/n5SUFMbUdZhJFDBiOX1+1bGc1ll6lCr8hGw9eiAAfoUKv8NQ+MXSIwgqSEtLo1evXrWuNWnShObNm5vX4+HMh6Mr/JVr17Lttt8SLCsj5fTTyX3mGWzHsSZFhKHwQ0jlP6zgDwSCfDRnDXsKSnCnOPjlXX1Jy2z42lYo/GYsp0JLj2bTsDk0gn5dfPxCwhJxwZ+cnMySJUvo0qVLretLliw5ri/zaOzZs4frr7+e3bt3k5GRQZ8+ffjoo48YPnw4AJMmTaKyspKxY8dSXFzMwIEDWbBgAWlpaZFuu96YOfzKFX4jllO9wq+84Hc40FFr6bEbOfyqX8gJgnBM4uHMhyMV/qoff2T7LbcSLCkh+Re/IPfZ2diSk4/3FJFRYwhWyMefbt7UgzqfzVvPtrUHcDht/HJ8X5rnpEZlWVPhb+SxnBCy9Xj9fhm+JSQsERf8EyZM4M4772TlypWceeaZQMjD/9JLL/GnP/0poud68cUXj3u/pmnk5eWRFx5oYgXmpF3V8Y1htV1lDr8VTbtQY/iW0pQesfQIgtV88cUXtW7Hw5kP4HZUK/xVGzey7eZbCBw6RHLfvuTOeQ5bkybRXVDTQkW/v6qWj1/XdZb8exMbv9mDzaZx0e29ye6UEbVlzaZdlYO3ktQr/BCy9XgrJalHSFwiLvgffPBBOnXqxJNPPmkOQzn11FOZO3cuV111VdQ3aDVOm6HwW2XpadyTdqE6qceKpt2AWHoEQTgMI6WnWdEOtt08mUBxMUm9epH7/BzsqdFR14/AKPhr+OlXfbyV7z/bAcB5N55K+17No7qkkcOvVOE3cvhVK/zhpJ6AFPxCglKvVvWrrrqqURb3R8MZ9norT+lJkEm7oYWtUPglpUcQhKPjdtjpcGgX47+eQ6CqDPepp9Luheexp6ef+IvrizMZqg6aCv+6JbtY9s5PAJz96y50G5gd9SUNS48lsZwKm3YBHK7QuzZi6RESlQYN3joWut54iihj0q43EFT7fZmWnsRo2gWUpvTYHZLDLwjC0UnaupnHv3qW9Koyknr0oP3LL2Fv2jS2i9bI4v/p27188a8fATjtovb0PT86A8UOxwpLj5YU6n0IelR7+GX4lpDY1KngP/XUU5k/fz5e7/HV5k2bNnHnnXcqj1CLJUYsJ0BApa3HAkuPdU271ll6gtK0KwhCDSp/WIvtvvFkeCvYnNmOdiqKfTCTerZvruDjF39A16HHWa0ZeHmnmC1phaXHKoXfnLbrlYJfSEzqZOl5+umneeCBBxg3bhwjRoxgwIAB5OTkkJSURHFxMevWrWPJkiWsW7eO8ePH12sAV7zirDHB0B/UcTRgmGJEJJClp7ppV2XBL027giDUpvK779h222+htJR1me2Zes7vuDQjek2yx8WRRKG3K/99Wyfoh079WzJkTLc6T7mvD1ZM2tXMpl3VHv7QL++ATyw9QmJSp4L/vPPOY/ny5SxdupTXX3+d+fPn8/PPP1NZWUmLFi3o378/N9xwA9dddx1NVSghCnHUUPi9gaCZzxxzEmXSLtK0KwiC9VSs+pbtv/0twfJyHP3684c2v6JSc6PrekyLboP9vlzeL/4Vfl0j99RmjLilpylMxAorBm/Z3NUKv6qfLVRbenyi8AsJSkRNu4MHD2bw4MGx2ktcYqT0gOLG3YSy9IT/GSps2rVL064gCGEqVn3L9ttuC03QPeMMms58isrpSwDw+GMv9BwsquC9H3+NR29CdpaXkXf0MS0oscQYvKU2h9+YKqyj+3xo0ZhUXAeMgl9SeoREpV4pPYmEzaZht2kEgjo+lWqwUfBLDn9MqLb0yOEvCImOs3U29sxMkvv1pe3TT+N3us37PL7YFvxlxR7ee3I1Fb4mNHcUcMlwG063mneSzZQelTn87uqfrV5VBYoKfruR0iOWHiFBkYK/DjisKPgTydLjssDS45CmXUEQQjhbt6b9P1/F3rQptqQknLqOTYOgDh5/AHDGZN3KMi/vPbWa0v1VZCSXcGnqoyTZJ8VkraNhxaRdnE6w2SAYJFhZFduo0xo4pGlXSHBi/55hI8AVVoMtsfQoLPgty+E3FH6FsZyGwh8QS48gCIAzO9ucAqtpWvW03RhZQDwVPv7z1HcU7y6nSVM3l53xFU3sB2tN2o01hqVHadOuppm2Hl3htF2J5RQSHSn464DRuGuJpUdh8W1d027oLV2VKT3VHn45/AVBOJKkcIEYUviji7fKz/uzvmPvtlKSUp1cdnc/0tPD4oPCBlorLD1QbesJKozmNFN6ZPCWkKBIwV8HjGhOn0o12EJLT0APENTVFcKmh9+KHH5R+AVBOAqxUvh93gAfPP09hT+V4E5xcNk9/cjMaQLOcDOrSoXfrr5pF6ih8Kt7oWEXhV9IcCIu+FetWsWaNWvM2++++y6jRo3ioYceOuFgrpMVo+D3B61o2lVv6QG1Kr8VKT2Swy8IwvGIhcLv9wX48Nk17Np0EGeSnUvv7kfL3LTQnY7k8IPUFd9WWHqgdjSnKsTSIyQ6ERf8t99+Oxs3bgTgp59+4pprriElJYU33niDSZPUNRupJNEsPaC44Lcihz/ctBvwy+EvCMKRRFvhD/iDfPz8WravO4DDbefS8X3J6lCjYdVU+BVaehzqc/ihxvCtKnUvNAxLj18sPUKCEnHBv3HjRvr16wfAG2+8wbnnnsv8+fOZO3cub775ZrT3FxdYYukxJ+1ao/CrbNzVnOpjOe2i8AuCcByiqfAHA0EWvrSWn7/fh91p45KxfWjduWntB5kKv3pLj2UKvwVNu5LDLyQqERf8uq4TDFtbPvnkEy6++GIAcnNz2bdvX3R3Fyc4bBYo/IbarjCH365VZz8rTeqxJKVHmnYFQTg2hsLvaeC7gMFAkE/mrmfLqr3YHBoj7+hN227NjnygFQq/0bSruOC3QuEXD7+Q6ERc8A8YMICpU6fy6quvsmjRIi655BIACgoKyMrKivoG4wGnlbGcKq01mmZJUo8llh5p2hUE4Ti4wwViVQMGNRnF/qble7DZNC68rRftezY/+oOtUPiNSbv+KnRd3VmoJalX+J1i6RESnIgL/r///e+sWrWK8ePHM2XKFDp37gzAv//9bwYPHhz1DcYDTks8/IalR20jtBVZ/JojXPBb0LQrOfyCIByNhir8wUCQT15eV13s/64Xnfq1PPYXWKjw6+hKz3yb21D41X2vdpco/EJiE/Gk3b59+9ZK6TF44okncDga5+BehyWxnIalR+0QLEsVfpU5/A6x9AiCcGySGqDwm8X+iiJsdo0Lf3uCYh8s9fBDKJrTZQhNMcZU+FU27TrDCr8U/EKCErHC36lTJ/bv33/E9aqqKrp27RqVTcUbLitjORUPwTIUfitiOdVaesJNu35d6VvZgiCcHNRX4Q8GgiysUexfdCJl38AChd9hc2DTjOZkdcW3LSn04iZoRdOuWHqEBCXigv/nn38mEDjyP4zH42HHjh1R2VS8YcRyelVGOFpk6TEUfitSetTm8Gvm53pQCn5BEGpTHw9/KI1nHZuNYv/23nTsW4diHyxR+DVNM209KodvWaLwi6VHSHDq7MF57733zM8//vhjMjIyzNuBQIBPP/2Ujh07Rnd3cYLDZij8jXvSLlik8BuWHq/6pl0I+fht9uM8WBCEhCMpQoU/4Auy4MW1/LR6b3Wx36dF3Re0QOGHkK2n0l+pVuF3G5N2FXr4JaVHSHDqXPCPGjUKCCkCN954Y637nE4nHTp04G9/+1tUNxcvuMJ+b78lg7cSyNJjQQ4/SFKPIAhHEonC7/MG+OjZNWxbdwC7w8ZFv+tFh0iKfbBE4Yfw8C2P2mhOQ+FXOngr7OEP+ILoQR3Npp3gKwShcVHngt/I3u/YsSPLly+nRYsID7OTGEPh91oRy5kAlh6cVqT0VB/20rgrCMLh1FXh91b6+eCZ79m16SAOl42Lx/Yht3tm5AtaqPCDWkuPLZzDrytM6TEsPQB+f9CM6RSERCHiWJ2CgoJY7COuMTz8ShV+iyw9lqT0WNC0q9k0NJuGHtQJ+kXhFwShNnVR+KvKffznqdUUbS3FlWTnl+P7HjlBt64YCn/AA8Eg2CJusasXpoffr9DDb8RyelQq/NU/z4BXCn4h8ahXjuann37Kp59+SlFRkan8G7z00ktR2Vg8UZ3SY4XCb42H35ocfrXfq82uEQjqBEThFwThMJIcRnrN0c+HihIv7z35Lft3lpPUxMmld/elVfv0+i/orI7IxF8FrpT6P1cEuB3qm3ZtRtNupTr7ks1uw2bTCAZ1/L4A4FS2tiDEAxEX/I888giPPvooAwYMoHXr1mha4/fBWZPSY3j4E0Dht2DSLoDdrhHwIQq/IAhH4A57vj1HUfhLD1Tx3pOrObingpR0F5dN6EfznNSGLWgo/KC04DcsPSqbdq1Q+CE0fCtYFcDvFZFHSDwiLvifffZZ5s6dy/XXXx+L/cQlTkty+I1YzkRI6Qn/M/SpbVAOZfEHpGlXEIQjMAZvHa7w799Zxn/+8R3lBz2kZrq5fEJ/mraKQnFud4QGLgb94FOnfBuWHiuadlV6+CFk6/FVBSSpR0hIIi74vV4vgwcPjsVe4hZnAk7aVWvpUZ/SA9WNu4fb0gRBEIzBWzU9/Ls2HeS/s7/HU+GnWXYKl97dj7TMpGM9ReQ4ksFbGlL4FZHksK5pV7XCH0rq8YUtPYKQWETcFXTbbbcxf/78WOwlbnGE47t8lsRyiqUnVtjCcasBsfQIgnAYhyv8P63ey3tPrcZT4Se7Uwajf39adIt9qJHUY4HCr9TSY5HC7zKm7YrIIyQeESv8VVVVzJkzh08++YQ+ffrgdNZufJkxY0bUNhcvmJYepbGcNSw9ug6KeiWsaNrFMoU/9Pcqlh5BEA6npsK/9sudLJq/AV2HDn1acOFtPXHEIuXFzOJPFIVfbcEvw7eERCZihf/777+nX79+2Gw2fvjhB7799lvzY/Xq1THYovU47RYo/IalBx2C6t5+tMTSY0EOP4SadkFy+AVBBbNnz6ZPnz6kp6eTnp7OoEGD+PDDD837dV0nLy+PnJwckpOTGTp0KGvXrrVsv0lOG+hwSlGAL/4VKvZ7nNWakbf3ik2xD5Yo/GbTrkoPvzFpV+HgLageviWWHiERiVjh//zzz2Oxj7jGYYWH317jnZOgL9TQpQBrcvgtsvQYCr9YegQh5rRt25bHH3+czp07AzBv3jwuv/xyvv32W3r27Mn06dOZMWMGc+fOpWvXrkydOpXhw4ezYcMG0tLSlO/XicbICie9wsfSgIs7cMalHWObTBdW21Uq/Fbk8NusatoNW3okpUdIRNRM9jjJsTSlB5RO27Ukh99pWHrU5/ADksMvCAq49NJLufjii+natStdu3blscceIzU1lWXLlqHrOjNnzmTKlCmMHj2aXr16MW/ePCoqKizpGass8/LD/E308jkIojNkTDcGXtYp9jHUzrClR6WH32FFSo9FTbvhd2YCYukREpA6ycajR49m7ty5pKenM3r06OM+9q233orKxuIJayw9NRT+gDq1PZGadu0Ow9IjCr8gqCQQCPDGG29QXl7OoEGDKCgooLCwkBEjRpiPcbvdDBkyhKVLl3L77bcf9Xk8Hg+eGkVjSUlJg/dWXFjO+09/T8neSjzofJjh465z2zT4eeuEBQq/FZYeW7hpl0AA3eczfwfEGofp4RdLj5B41Kngz8jIMJWNjIyMmG4oHrEmltMGmh30gNKkHkty+B1W5vBLwS8IqlizZg2DBg2iqqqK1NRU3n77bXr06MHSpUsByMrKqvX4rKwstm7desznmzZtGo888kjU9rd9/QE+mvMD3ko/TTLdvOQ7xAGbjq7raoZMWqHwW2Dp0ZKrh4wFPR7sqgt+sfQICUidCv6XX375qJ8nCpbEckLIx+8PKLX0JGQOv1h6BEEJ3bp1Y/Xq1Rw8eJA333yTG2+8kUWLFpn3H15Un6jQnjx5MhMnTjRvl5SUkJubW6+9/bB4J4tf24ge1GndOYOzbuxO3t++AB28gaCZ2hNTrFD4HRY07bpcoeQ5XQ/5+FMbOKW4jthdRtOunPlC4lHvTtC9e/eyYcMGNE2ja9eutGzZMpr7iissieWEsK2nSunwrUSy9BgKv+TwC4IaXC6X2bQ7YMAAli9fzpNPPskDDzwAQGFhIa1btzYfX1RUdITqXxO3243bsIc0gC2rilg0fwMA3QZmM+y67vi16nPB41dU8Fup8CuM5dQ0Dc3tRq+qIqgwqcdQ+ANi6RESkIibdsvLy7nlllto3bo15557Lueccw45OTnceuutVFRUxGKPllNt6bFA4QelBb81OfzWxHKKwi8I1qLrOh6Ph44dO5Kdnc3ChQvN+7xeL4sWLVIy2b1j3xa065HJwMs7cf5Np2J32nDZq389elQpwlZ6+BUO3oJqH7+uMItfLD1CIhNxwT9x4kQWLVrEf/7zHw4ePMjBgwd59913WbRoEffdd18s9mg5DiuadsGSabuWKPwu44VNAF1hEpI07QqCOh566CG+/PJLfv75Z9asWcOUKVP44osv+M1vfoOmaUyYMIH8/HzefvttfvjhB2666SZSUlIYM2ZMzPdms9u4ZHxfBozsYFqINE3D7Qj9iqxSpQgnSEoP1EjqURjNacZyiqVHSEAitvS8+eab/Pvf/2bo0KHmtYsvvpjk5GSuuuoqZs+eHc39xQUuM5bTCksPlij8ljTtElL5NZfrOI+OHtK0Kwjq2LNnD9dffz27d+8mIyODPn368NFHHzF8+HAAJk2aRGVlJWPHjqW4uJiBAweyYMECZRn8NtuRvQJJTjsefxCPv/Eq/FZYegA0I4tfYTSn3Ri85RVLj5B4RFzwV1RUHNVT2apVq0Zr6alW+BUXhgli6alZ8OPzgbKCX3L4BUEVL7744nHv1zSNvLw88vLy1GyoDiSCwm+dpceYtmuBpUcUfiEBidjSM2jQIB5++GGqavwnrays5JFHHmHQoEFR3Vy84LBZ7OFv7JaeGpFsKht37YaHX5p2BUE4CklhRbhRK/wOqxR+w9KjsGlXJu0KCUzECv+TTz7JRRddRNu2benbty+aprF69WqSkpL4+OOPY7FHy3GFvd5+5QV/WOlu5JYe7NXpFyobd6stPXL4C4JwJIbC70kAhV9lDj/UaNqtUve9OpzGpF2x9AiJR8QFf69evdi0aRP//Oc/+fHHH9F1nWuuuYbf/OY3JNcYptGYqFb4VXv4w389FsRyKrX0aBo4neDzKS74pWlXEIRjkxAKv93qpl2VHn6x9AiJS71y+JOTk/ntb38b7b3ELZLSE3s0pxPd51Nq6bGF1buAFPyCIByFhPDwh19kBPQAvqDPfJc31tiSLIjlFEuPkMBE7OEH2LBhA+PHj+f888/nggsuYPz48fz4448RP8+0adM4/fTTSUtLo1WrVowaNYoNGzbUeoyu6+Tl5ZGTk0NycjJDhw5l7dq19dl2vbEspce09KibtGtJDj81pu36rFD45fAXBOFIEknhB7WNu5rbAg+/kdIjlh4hAYm44P/3v/9Nr169WLlyJX379qVPnz6sWrWK3r1788Ybb0T0XIsWLWLcuHEsW7aMhQsX4vf7GTFiBOXl5eZjpk+fzowZM5g1axbLly8nOzub4cOHU1paGunW643DGLyl6tA3MC096opgKxV+AN1vQdOuKPyCIBwF9Qp/uOD3WVPwK522a6HCHxBLj5CARGzpmTRpEpMnT+bRRx+tdf3hhx/mgQce4Ne//nWdn+ujjz6qdfvll1+mVatWrFy5knPPPRdd15k5cyZTpkxh9OjRAMybN4+srCzmz5/P7bffHun264XTsPQoHAoFVCv8CtV2S5p2qanwK7T0GE27ql/ICYJwUqBe4Q9bevzqLD2appFkT6IqUKXUx29zWzB4y8zhlzNfSDwiVvgLCwu54YYbjrh+3XXXUVhY2KDNHDp0CIDMzEwACgoKKCwsZMSIEeZj3G43Q4YMYenSpUd9Do/HQ0lJSa2PhuI0LD2W5fCrs/RY0bQLNbL4pWlXEIQ4IREUfqgxbVelpcdQ+K2I5RRLj5CARFzwDx06lC+//PKI60uWLOGcc86p90Z0XWfixImcffbZ9OrVC8B8AXH4oK+srKxjvriYNm0aGRkZ5kdubm6992TgCE9g9Ad1dF1hcZggKT1Qw9KjModfmnYFQTgO7gRQ+MGaabumwq/Q0lMzpUfp73JBiAMitvRcdtllPPDAA6xcuZIzzzwTgGXLlvHGG2/wyCOP8N5779V6bF0ZP34833//PUuWLDniPk2rPfJc1/UjrhlMnjyZiRMnmrdLSkoaXPQ7HdWvi3wB3czljzmmpUed6m2ZpccZtvRYovDL27uCIBxJoij85rRdhZYeLdmYtKtS4Q/PfNFDAxftTkW/ywUhDoi44B87diwAzzzzDM8888xR74NQkR4I1O2QvOuuu3jvvfdYvHgxbdu2Na9nZ2cDIaW/devW5vWioqIjVH8Dt9uN2+0+6n31xWmrWfAHcTnqFW4UOQlk6cFhKPxi6REEIT6w1MOv63AMYSvamNN2FaYDGQq/0qZdZ/Xvbr8vYCr+gpAIRPyvPRgM1umjLsW+ruuMHz+et956i88++4yOHTvWur9jx45kZ2ezcOFC85rX62XRokUMHjw40q3XGyOHHxT7+C209FiW0mNB027ALwW/IAhHYpnCrweVnvuWKPxhD7/KWE6bXTNfQ8nwLSHRqNfgrWgxbtw45s+fz7vvvktaWprpy8/IyCA5ORlN05gwYQL5+fl06dKFLl26kJ+fT0pKCmPGjFG2T8PDD4qTeswcfvUpPZbl8CuM5RRLjyAIx8MyhR9CKr/DpWRZSzz8SYalR2EUqKZhd9nxewKS1CMkHJYW/LNnzwZCjcA1efnll7npppuAUAxoZWUlY8eOpbi4mIEDB7JgwQLS0tKU7VPTNJx2DV9AVzttN8Em7YI1Tbti6REE4WgoV/gdbkAD9JCPPylDybKWpPSYTbvq1oSQrcfvCUhSj5BwWFrw16VLXtM08vLyyMvLi/2GjoPTbsMXCKi19Jge/sTJ4bcmllOUHkEQjkS5wq9poWm7/kqlST1WWHpsZiyn2gZlw8cvw7eEREM6VuqIYevxqiwObdYV/NZZeqRpVxCE+EC5wg+WTttV2bSrWRDLCdVJPX6vKPxCYiEFfx2xZPhWIll6XBZYeqRpVxCE46Bc4QdLsviTHFYq/GotPWYWv3j4hQSjXgX/li1b+MMf/sC1115LUVERAB999BFr166N6ubiCaPgt8TDb4HCr6MTCCpUQAyF35JYTjn4BUE4EkPh9ySKwq+waVdLskjhrzF8SxASiYgL/kWLFtG7d2/+97//8dZbb1FWVgbA999/z8MPPxz1DcYLRjSn0oLfAkuPofCDWluPZuTwi6VHEIQ4ITls/yhXaf+wQuE3PPxKm3atUfgdLqPgF0uPkFhEXPA/+OCDTJ06lYULF+JyVUeGDRs2jK+//jqqm4snXIalJ5gYlh5Qa+uxJIc/rN4FROEXBOEoZDYJ/Y47UK5u+KElCr/DuljOoPKmXcPDL+e+kFhEXPCvWbOGK6644ojrLVu2ZP/+/VHZVDxiicJv5vArnLSrWaXwW5nDLwq/IAhH0iI1VAgXV3jxqzr7LVD4LWnaTTJe2PjQ6zCoM1pISo+QqERc8Ddt2pTdu3cfcf3bb7+lTZs2UdlUPOKwGR5+KybtqlPa7TY7Ns14N6NxK/xG025QmnYFQTgKmU1caBroOhyoUCS8WKDwWxLLGbb0gNpoTrtLmnaFxCTign/MmDE88MADFBYWomkawWCQr776ivvvv58bbrghFnuMC5wOI6XHAoVfcUSmFVn8ksMvCEK8YbdpZKaEzuF9pYoK/nBijlKF3wJLj6nwo3b4lhnLKR5+IcGIuOB/7LHHaNeuHW3atKGsrIwePXpw7rnnMnjwYP7whz/EYo9xgdNmhaXHaNpV6B+l2sev1NLjtDKlRxR+QRCOjmHr2V+uqCh1hi09Vij8Kpt2bbbqd3YVKvyS0iMkKhFP2nU6nfzrX//i0Ucf5dtvvyUYDNK/f3+6dOkSi/3FDdUe/sZt6QGLsvitsPSYTbtS8AuCcHRapLnYsAf2lSkqhi1Q+K3I4YeQyq/7fAQVJvUYTbsBsfQICUbEBb/BKaecwimnnBLNvcQ15uCtYOJYeqxp2lWv8OtBHV3X0TRN2dqCIJwcNG8SUviVWXosUPityOEH0JLcUFqKrjCLX2I5hUQl4oJ/4sSJR72uaRpJSUl07tyZyy+/nMzMzAZvLp4wB2+pbPC02NKj1sNv5PCrT+mBkK3H7pCCXxCE2hiWnn2qLD2mwt+4LT0AtqRkAqiN5rSLpUdIUCIu+L/99ltWrVpFIBCgW7du6LrOpk2bsNvtdO/enWeeeYb77ruPJUuW0KNHj1js2RKchqVHqcJvFPxqLT2WKPwW5vADBPxB0+IjCIJg0CJNcdOuqfA37qZdAFtSePiWyqZdyeEXEpSIK5zLL7+cCy64gF27drFy5UpWrVrFzp07GT58ONdeey07d+7k3HPP5d57743Ffi3DYVh6lHr4E6hp18KUHpDGXUEQjk6LJoqbdq1U+FV7+N3qh28Zlp6AWHqEBCPigv+JJ57gz3/+M+np6ea19PR08vLymD59OikpKfzpT39i5cqVUd2o1Via0qPYw2+JpcdlgcJvk4JfEITjYyr8qpp2rVD4wx5+1ZYezVD4lTbtiqVHSEwiLvgPHTpEUVHREdf37t1LSUkJEBrO5fWqVaVjjenhV1kYWmzpsSKHX2Usp6ZpksUvCMJxUd60a4XCH15TuaUnrPArbdoVS4+QoNTL0nPLLbfw9ttvs2PHDnbu3Mnbb7/NrbfeyqhRowD45ptv6Nq1a7T3aikOs+BXeEgkkKUHC1J6QLL4BUE4Pi3Sqi09uq7gnLBQ4fcFfQSC6qwuxvAtlbGcdknpERKUiAv+5557jvPPP59rrrmG9u3b065dO6655hrOP/98nn32WQC6d+/OCy+8EPXNWonRtKt20q5Flh7NAkuPBU27UCOL3y9qjyDEkmnTpnH66aeTlpZGq1atGDVqFBs2bKj1GF3XycvLIycnh+TkZIYOHcratWst2nGI5k1Clh5fQKekUsGZaIHCbxT8oNbHb3MbTbvqB28FxNIjJBgRF/ypqak8//zz7N+/30zs2b9/P3PmzKFJkyYA9OvXj379+kV7r5ZiWnqCKi094Rx+1ZYeuxWWHiOWUxR+QWiMLFq0iHHjxrFs2TIWLlyI3+9nxIgRlJeXm4+ZPn06M2bMYNasWSxfvpzs7GyGDx9OaWmpZftOctpJc4dEkL0qfPwWKPyGpQfUFvxWKPyGpcfnFYVfSCzqPXgrNTWVPn36RHMvcY05aVelEmxO2m38lh7NaXj41Sr8RuOuFPyCEFs++uijWrdffvllWrVqxcqVKzn33HPRdZ2ZM2cyZcoURo8eDcC8efPIyspi/vz53H777VZsGwjZeko9fvaXeejcKjW2i1mg8Ns0G06bE1/Qp1bhN5t2rUjpEYVfSCzqVfAvX76cN954g23bth3RnPvWW29FZWPxhsuctGuBwm/RpF1LLD0KB29BdRZ/QJp2BUEphw4dAjCHNBYUFFBYWMiIESPMx7jdboYMGcLSpUuPWvB7PB48NTLcjeCIaNMi1UXBvnL2lSkQXyxQ+CEUzekL+qhS+ELDjOVUaOkxB29J066QYERs6Xnttdc466yzWLduHW+//TY+n49169bx2WefkZGREYs9xgUOmwVNu6aH3w8qmsXCWDJ4y8jhV5jSA2LpEQQr0HWdiRMncvbZZ9OrVy8ACgsLAcjKyqr12KysLPO+w5k2bRoZGRnmR25ubkz2ayb1qLD0WKDwQ/XwLbWWHitiOcMpPaLwCwlGxAV/fn4+f//733n//fdxuVw8+eSTrF+/nquuuop27drFYo9xgWnpUZrSU+MNmIC64jsRm3aD0rQrCMoYP34833//Pf/v//2/I+7TNK3WbV3Xj7hmMHnyZA4dOmR+bN++PSb7NbL49yv18Csu+MONu5V+de8s2MzBW+rWNCw9elCXd3aFhCLign/Lli1ccsklQOjt1vLycjRN495772XOnDlR32C84LJi0q5h6QGlth5rmnYlllMQEoG77rqL9957j88//5y2bdua17OzswGOUPOLioqOUP0N3G436enptT5iQYvUUDG8V4Wlx1T41Vt6IAEUfld12RMQW4+QQERc8GdmZpqJCW3atOGHH34A4ODBg1RUVER3d3GEofB7rbD0gNLGXWty+C1K6ZGmXUFQgq7rjB8/nrfeeovPPvuMjh071rq/Y8eOZGdns3DhQvOa1+tl0aJFDB48WPV2a9E8XPArVfgDXlCYiW+FpceWZIGH32GD8BtGYusREomIm3bPOeccFi5cSO/evbnqqqu45557+Oyzz1i4cCHnn39+LPYYFzisUPhrWXrUFcKJaOmRt3YFIbaMGzeO+fPn8+6775KWlmYq+RkZGSQnJ6NpGhMmTCA/P58uXbrQpUsX8vPzSUlJYcyYMZbuvWVq6N1WpR5+CPn4XU1ivybVCr8VTbsqFX5N03A4bPh9QfwSzSkkEBEX/LNmzaIqHKE1efJknE4nS5YsYfTo0fzxj3+M+gbjBZcxeCuosDDUtNC03aDPEkuPJbGcYukRhEbJ7NmzARg6dGit6y+//DI33XQTAJMmTaKyspKxY8dSXFzMwIEDWbBgAWlpaYp3WxvD0qM0pQdCPn5FBb/h4W/ssZwQmrbr9wVF4RcSiogLfiNCDcBmszFp0iQmTZoU1U3FI0ZKj1d1YWgPF/wqLT1WKPwOi3L4jYJfmnYFIabodUga0zSNvLw88vLyYr+hCFBq6bHZq4UehT5+Y/hWVUChwm9aetS9yIBQUo8Hv2TxCwlFxB5+u91OUVHREdf379+P3W6PyqbiEafDsPQoPiAMH79CS481Cn/4+1Rd8JuWHlH4BUE4Oi3Clp5yb4BKFTYQC5J6zKZdv3oPv2qF32Fm8YulR0gcIi74j6XSeDweXC7XUe9rDDjDzZ1KPfwQUnqg0Tft1kzpqYsSGC2kaVcQhBOR6nbgDosDarP41Sn8RtOuUoXfbZHCH07qEUuPkEjU2dLz1FNPAaG3XF944QVSU6vHiwcCARYvXkz37t2jv8M4wWjaVZrSAzWGbyVGDj+6DoEAOOo1BDpizBx+adoVBOEYaJpGi1Q3Ow9Wsq/MQ25mSmwXdIYLfoXTdhPKwy/Dt4QEpM5V1d///ncgpPA/++yztew7LpeLDh068Oyzz0Z/h3GC04qmXbDU0qOy4DdiOSGk8muKCn5p2hUEoS60SHWFC34F77amNIeD26B8X+zXCmOFpcc6D79YeoTEo85VVUFBAQDDhg3jrbfeolmzZjHbVDziDCv8Pn8CWHo0Cyw9zup/iiqTeqTgFwShLlQn9SgoTlNDQ8goKzz+46KIFZYem9sahd+w9EjTrpBIRCyjfv7557HYR9xjFvxWKfwqLT0261J6QG1Sj9m0Kyk9giAch+bhxl0lST1p4YK/VF3Bb82k3XDTrseDrutomqZkXYdYeoQEJOKCPxAIMHfuXD799FOKiooIHlYAf/bZZ1HbXDxhTNpV3rRrWnrU5/ArLfjtdrDZIBhUWvDbpWlXEIQ6oDSLP6116M/S3bFfK0yKM9SXUOYtU7am0bQLIZVfS04+zqOjh10sPUICEnHBf8899zB37lwuueQSevXqpewVudU4wzn8PtXNnTb1Bb8Vlh4INe7qHo/SaE6bNO0KglAHmqu09JgK/57YrxWmRXILAPZVqusbsDVJAacTfD4CxcXYFBX8SU1Cv1erytT+jhMEK4m44H/ttdf4v//7Py6++OJY7CducTpCL2x8yhX+cNSpBZN2lTbtErL16B6PJR5+yeEXBOF4GFn8agt+dQp/q5RWABRVHDlnJ1ZomoazZUt8u3bhLyrCmZOjZN0mTcNzFQ6pbRYWBCuJOIff5XLRuXPnWOwlrnFYpfDbEyOHH2pn8atCmnYFQagLLZVaetR7+FsmtwRgb+VepbNQHK1CLzR8RxnoGSuaZIT+LssPqfu9KghWE3HBf9999/Hkk08qPRDiATOWU7mlJ/wmjMpYTs0ahR9XaF2lHn7D0iNNu4IgHAfD0qOmaTfs4S/fq+zsb5kSKvg9AQ8l3hIla0J1we8v2qtsTbPgPygKv5A4RGzpWbJkCZ9//jkffvghPXv2xOl01rr/rbfeitrm4onqlB6x9MQKzWEU/KLwC4IQXxiWnuIKH75A0PydEBNSWoBmBz0A5UWQHnuri9vuJsOdwSHPIfZW7CXDnRHzNaFmwa9O4U8RS4+QgERc8Ddt2pQrrrgiFnuJa4yUnoSw9FjVtGtYelQ27YatWgFp2hUE4Tg0S3Fh0yCow4FyL1npSSf+ovpis0FqFpTuCvn4FRT8ELL1HPIcoqiyiM7N1Fh3rSj4DYXfU+7H7wuYMZ2C0JiJuOB/+eWXY7GPuMcVVnN0HQJB3YxzjDmJMmmXUEoPgO5XmdIjCr8gCCfGZtPIbOJmX5mHfWWe2Bb8EPLxl+5S6uNvldKKzQc3s7dCnb3G0SpkJVJZ8LtTHNidNgK+IBWHvKS3UJMOJAhWUq/3JP1+P5988gnPPfccpaWlAOzatYuyMnX5vapx1Hj7VqnKb7Nw8JauPqUntLC6de1i6REEoY5UJ/WozOJXW/BDqHFXFc6sLAD8e9WmAzVpGlL5y8THLyQIESv8W7du5aKLLmLbtm14PB6GDx9OWloa06dPp6qqimeffTYW+7QcRw1F3xcIkqTqLUArLT0Ks/+hhsJvRQ6/NO0KgnACWqa5+bGwVFHjbqgQtiKpR2U0p5nSs0fdmgBNMlyU7K2Uxl0hYYhY4b/nnnsYMGAAxcXFJNcYknHFFVfw6aefRnVz8UTNBi2l03YTydIjsZyCIMQxzZuozOJXP23Xiix+o+APlpQQrKxUtq6h8FdINKeQIERc8C9ZsoQ//OEPuFyuWtfbt2/Pzp07I3quxYsXc+mll5KTk4Omabzzzju17td1nby8PHJyckhOTmbo0KGsXbs20i1HBbtNwxD5LbH0JEDTLk6jaVcGbwmCEH+0sCKLv0zdtF0jmlOlh9+WmooWFg/9eyWaUxBiRcQFfzAYJBAIHHF9x44dpKWlRfRc5eXl9O3bl1mzZh31/unTpzNjxgxmzZrF8uXLyc7OZvjw4WbfgGocVkRz2i308FvVtKsyhz/8dxqUlB5BEE5AizSj4FdQJKZaMG03OazwV6r101vRuFs9fEsKfiExiLjgHz58ODNnzjRva5pGWVkZDz/8MBdffHFEzzVy5EimTp3K6NGjj7hP13VmzpzJlClTGD16NL169WLevHlUVFQwf/78SLcdFYykHqXDt0xLjwU5/Mqbdo2UHrH0CIIQf1RbehrptN2wwr+vYh9BXd3vOWdLC6I5JYtfSDAiLvj//ve/s2jRInr06EFVVRVjxoyhQ4cO7Ny5k7/85S9R21hBQQGFhYWMGDHCvOZ2uxkyZAhLly495td5PB5KSkpqfUQLS7L4beoLfsuads0cfnX2JVv4RVxAmnYFQTgBpsJfqnrarpqzuHlyczQ0/Lqf4qpiJWtCjcZdKxT+g+LhFxKDiFN6cnJyWL16Na+99horV64kGAxy66238pvf/KZWE29DKSwMqRpZ4cgug6ysLLZu3XrMr5s2bRqPPPJI1PZRE3PartKmXQsn7ep+dF1H09TMHKjO4Veo8EsOvyAIdaRl2MO/v1xBwZ/SHGwOCPqhrAgy2sR8SafNSWZSJvur9rO3ci/Nk5vHfE2oOXxLoYe/qXj4hcQi4oIfIDk5mZtvvpmbb7452vs5gsOLzRMVoJMnT2bixInm7ZKSEnJzc6OyF2e4a1dtSk/4r0hl066t+p+FP+g3XwDEGsnhFwQhnmkezuHfX+YlGNSxxXIAozFtt2RnyNajoOCHUFLP/qr9FFUU0T2zu5I1rZi2m5IR+rv0eQJ4q/y4kupVDgnCSUPElp5p06bx0ksvHXH9pZdeiqqlJzs75F80lH6DoqKiI1T/mrjdbtLT02t9RAujaddriaVHXRFsWHpAbVKPJTn80rQrCEIdad4kpAr7gzqHKhWcU2nqG3etSOqxouB3JTlwJYXm6YjKLyQCERf8zz33HN27H/mqv2fPnlEdutWxY0eys7NZuHChec3r9bJo0SIGDx4ctXUiwWk3FH6VTbvWWXpAceOuhbGcovALgnAiXA4b6WElWImtx/Dxl1kwfEthUo8zK1zw71EXQQo1bD2SxS8kABG/h1VYWEjr1q2PuN6yZUt2745MhSgrK2Pz5s3m7YKCAlavXk1mZibt2rVjwoQJ5Ofn06VLF7p06UJ+fj4pKSmMGTMm0m1HBWs8/BZYemoq/Aobd60ZvBVu2pWCXxCEOtAizU1JlZ+9pV46t4rxYqnqp+0aw7esUPh9e/cq7RtLyXBTXFghCr+QEERc8Ofm5vLVV1/RsWPHWte/+uorcnJyInquFStWMGzYMPO24b2/8cYbmTt3LpMmTaKyspKxY8dSXFzMwIEDWbBgQcR5/9HCLPiDjdvSo2kaDs2BX/crzeLXnKF3M5Tm8BtNu5LSIwhCHWiR6uanveVqFf7GbulpGVpTr6ggWF6OPTVVyboSzSkkEhEX/LfddhsTJkzA5/Nx3nnnAfDpp58yadIk7rvvvoiea+jQoej6sZVVTdPIy8sjLy8v0m3GBIfdiqZd9ZYeCNl6/H6/UktPtcKv0sMvlh5BEOpOi3DjrppoTsPDr87qYsXwLVtKCra0NIKlpfiLitQV/OFozgqJ5hQSgIgL/kmTJnHgwAHGjh2L1xv6T5KUlMQDDzzA5MmTo77BeMJpMyw9VgzeUnsgWZHFX53Dr75pNyBNu4Ig1IEWqca0XRXDtwyFX/3wLZUKP4RsPd5wwe/u1EnJmkbBXyaWHiEBiKjgDwQCLFmyhAceeIA//vGPrF+/nuTkZLp06YLb7Y7VHuMGp8OCwVt29ZYeCDfu+lBs6Ql/rzJpVxCEOKWFyiz+NMPDr87SY3j491ftxx/014ppjiWOVi3xbtmieNpuWOEXS4+QAESU0mO327nwwgs5dOgQqampnH766fTq1Sshin0AR1jhV2rpsVms8CuN5VSf0mMPK/zoEAxK0S8IwvExsvj3lipU+Cv2gV/N74Bm7mbYNTtBPcj+yv1K1gRwWhDN2SRDPPxC4hBxLGfv3r356aefYrGXuMeI5bRE4Vfs4TdUHSsUfqWWHkd1GoQ07gpCbFm8eDGXXnopOTk5aJrGO++8U+t+XdfJy8sjJyeH5ORkhg4dytq1a63Z7DGotvQoKBKTM6tFn3I1hbDdZjcn7O6ttCCpxwKFv/yg97j9hILQGIi44H/ssce4//77ef/999m9ezclJSW1Phoz1Sk9Kpt2LbT0oDiH35JYzhoFv9h6BCGmlJeX07dvX2bNmnXU+6dPn86MGTOYNWsWy5cvJzs7m+HDh1NaWqp4p8dGqaXHmLYLaqM5jcbdCnXFt6OlofCre5FhePgD/iCeCrW/YwVBNRGb8y666CIALrvsslpZuUZ2biAQiN7u4gxj0q5PpRJstaVHadNuWOG3IIcfpOAXhFgzcuRIRo4cedT7dF1n5syZTJkyhdGjRwMwb948srKymD9/PrfffrvKrR6T6pQeRWdyWjaU7FAfzblfcTRnVuiFjcrhW3anjaQmTqrKfZQf9JDUxHniLxKEk5SIC/7PP/88Fvs4KTAn7arM4bcwlhMSwNJj09A00HVJ6hEEKykoKKCwsJARI0aY19xuN0OGDGHp0qVHLfg9Hg8eT7XSruJdZkPhr/QFqPD6SXHFuKnVjOZUP3xLZTSno1UoHUilhx9CWfxV5T7KD3lo3kZNHKggWEHEJ9WQIUNisY+TgupYTism7ap9u9FQ+Bt7Dj+EVP6APygKvyBYSGFhqKDNCiu9BllZWWzduvWoXzNt2jQeeeSRmO+tJk3cDpKddip9AfaVemnXPNYFv/poTium7dZs2lU5bbdJhpv9O8splyx+oZETsYcf4Msvv+S6665j8ODB7Ny5E4BXX32VJUuWRHVz8YbDiqZdqyw9NgssPeGUHhQq/FDt4w9I064gWM7hhd7xir/Jkydz6NAh82P79u0qtlid1KOicTdNvYe/ZXJIbVep8NuNabs+H4GDB5Wtm2I27kpSj9C4ibjgf/PNN7nwwgtJTk5m1apV5tuppaWl5OfnR32D8YTRtJsok3YBfLrKgt+w9Kh9N8NI6hGFXxCsIzs7ZF0xlH6DoqKiI1R/A7fbTXp6eq0PFZiNu0oK/rDCX9a4FX6by4W9WTNAdeOuRHMKiUHEBf/UqVN59tlnef7553E6qxtcBg8ezKpVq6K6uXjDjOVU6uE3LD2KYzktaNq1IqUHqht3peAXBOvo2LEj2dnZLFy40Lzm9XpZtGgRgwcPtnBnR6J22q56D7+V03ZBdRa/KPxCYhCx+XDDhg2ce+65R1xPT0/noMK34aygOqXHisFbksMfK+zmtF2x9AhCLCkrK2Pz5s3m7YKCAlavXk1mZibt2rVjwoQJ5Ofn06VLF7p06UJ+fj4pKSmMGTPGwl0fiZnUo1LhVzltNxzLWewpxhvw4jLeaY4xjlat8GzYYMm03fJD4uEXGjcRF/ytW7dm8+bNdOjQodb1JUuW0KlTp2jtKy4xLT2JkNJjU5/Db0UsJ1R7+EXhF4TYsmLFCoYNG2benjhxIgA33ngjc+fOZdKkSVRWVjJ27FiKi4sZOHAgCxYsIC0tzaotHxWllp7UsMJfsT80bdcR++I7w52B0+bEF/Sxr3IfOak5MV8TaiT17FVf8FeIpUdo5ERc8N9+++3cc889vPTSS2iaxq5du/j666+5//77+dOf/hSLPcYNTpuFk3b1IAQDYLMrWdaSpl3D0qO8aTf0Qk6adgUhtgwdOvS4E001TSMvL4+8vDx1m6oHRtPuzoOVsV8sJTxtN+iDsj3QNDfmS2qaRquUVuws20lRRZHCgt9CS88hL3pQR7OpSQcSBNVEXPBPmjSJQ4cOMWzYMKqqqjj33HNxu93cf//9jB8/PhZ7jBucDitiOWsMAgn4lBX8luTwuwyFX7GlR5p2BUGIgNPah5pLP9+wl5/3ldOhRZPYLaZpIVvPoW0hH7+Cgh9CST07y3ayt1J9NKdvj7qCPyXdCRroQZ3KMh8p6WrsS4KgmnrFcj722GPs27ePb775hmXLlrF3717+/Oc/R3tvcYcj/Mrfb0UsJyi19ViZw4/qlB5p2hUEIQL6tG3KsG4tCQR1nvx0U+wXNKM5FU/bBYoqFA7fMqbtKlT4bXYbKWnhpB5p3BUaMXUu+CsqKhg3bhxt2rShVatW3HbbbXTo0IEzzjiD1NTEmE5nePgtVfgVkViWHsnhFwQhMiYO7wbAO6t3smlPaWwXM5J6yvbEdp0aWBHN6Wip3tIDNRp3peAXGjF1Lvgffvhh5s6dyyWXXMI111zDwoULufPOO2O5t7ijuuBXqfDbQQv/NSksvi1p2nVK064gCCcHvdtmcGHPLHQdZn4SY5XfgqQec/iWSoXf8PDv24ceCChbV7L4hUSgzh7+t956ixdffJFrrrkGgOuuu46zzjqLQCCA3a7GV241xqRdf1BxYWhzQsCjdNquFQq/5Tn8KtOXBEE46bl3eFcWrNvDB2t2M3bXIXrmZMRmIQuy+A2FX+W0XUfzTLDZIBAgcOAAjvD03Vgj03aFRKDOCv/27ds555xzzNtnnHEGDoeDXbt2xWRj8Yg5eEt1Xrth61Ho4TcVfqU5/CGVRXkOv9G0q3K+giAIJz3ds9O5tE8owebvC2Oo8hvRnBZ4+FVaejSHA0fz5gD4LErqEYTGSp0L/kAggMtVu3vd4XDgV6zGWokllh6oLvgD6n7W5uAtpZYembQrCMLJxT0XdMGmwSfr97B6+8HYLGIq/Ao9/MnqPfxgVTSnWHqExk+dLT26rnPTTTfhdrvNa1VVVdxxxx00aVIdSfbWW29Fd4dxhMNmQdMu1Ji2q059MBR+K5p28fvRdR1NU5OHLE27giDUl1NapjL6F23598od/G3BBl69dWD0F7HCwx9W+Et9pVT4KkhxpihZ19GqFaxdi79I3QsNadoVEoE6F/w33njjEdeuu+66qG4m3nE5LIjlBEum7Zo5/BY07QLg84FLTR6yXZp2BUFoAPec34V3vt3Jl5v28U3BAc7omBndBQyFv/IA+D3gcB//8VEg1ZlKsiOZSn8l+yr30c7ZLuZrgkUKvxT8QgJQ54L/5ZdfjuU+TgosU/jt4b8mlZYeI4dfpYffUf3PUff70RQV/GLpEQShIeRmpnDV6bnM/982/rpgA6//7szovkOZ3Cwk/AS84Wm7sS++NU2jZXJLtpVuo6iiiHbpqgr+0DsLVkzbrSz1EQgEsdvrNaJIEOIa+VcdAQ6rmnYtsPRYmcMPaht3TUuP6r9XQRAaDXed1xmXw8Y3BQf4ctO+6D65plmS1GM27qqcthsevuUrUtevkJzqxBYerFkhjbtCI0UK/ghwhV/1K4/ltMLSY0EOPzUsPSobd20OUfgFQWgYrTOS+c3AkAp+/xvfsaekKroLWODjNxp3LcniV+jh12waKdK4KzRypOCPAEe44Peqbu40LT2NfNKuplmSxV89eEsUfkEQ6s99I7rRNSuVolIPv3t1JVW+KA6PSg0p3yqTeqyI5rTCww/VPv6Kg6LwC40TKfgjwGkO3rKoaVflpN1w065PV5uJb07bVWjpMZt2JYdfEIQGkOp28PwNA2ia4uS77Qd56K016HqUzhUrFH4rhm+FC/7A/v1Kfw9UZ/GLwi80TqTgjwAjh99vVSynQkuPFU27UO3jV+vhF0uPIAjRoX3zJjwz5hfYbRpvfbuTF74siM4TWzhtV6XCb2/a1LR3+vdFuRfiOJhZ/JLUIzRSpOCPAEe4qcerPJYzMSw9YFXBL027giBEj8GdW/CnX/YAYNqH6/l8QxQU8jQLpu0mq2/a1Ww2HC1bAGptPSkSzSk0cqTgjwDLFH4rLD1WNO1SI4tfoYff7pAcfkEQossNg9pzzem5BHW4+/99y5a9ZQ17QqPgL1M4bTelumk3atakOuBsGVrXp7DgT20qlh6hcSMFfwSYBb9qD78Vlh6bxZYepU27hqVHFH5BEKKDpmk8enkvTu/QjNIqP7+dt4KDFQ1oCLXAw98iOaS0V/orKfM18AVLBFgyfMv08EvTrtA4kYI/Aqpz+HWlake1pceCHH6FLzIAcFpo6ZGmXUEQoojLYWP2daeRk5HET/vKueKZpWwuqmfhbE7bLQZvRfQ2eRxSnCmkOdMAq5J61K2Z0lQ8/ELjRgr+CHDWmL6nNIvftPSoU71NS49qhd9M6bFC4ZeCXxCE6NIi1c3cW86gTdNkCvaVc8XTX9XP05/UFFJCijvvjlP2+8CI5rQiqce/R519yVD4PRV+/N4oxqkKQpwgBX8EGLGcoHjaboJM2gXQHOpjOSWHXxCEWNI1K413x58Vsvd4/NwydznPLdoS2TvFmgajngn9Plj7FrxzBwRjX5haksWfpd7S405xYHeGSiKx9QiNESn4I6Cmwu9TqQbb1Xv4jRx+q5p2db/CHH5p2hUEIca0SHXzr9vO5NozctF1mPbhj0z8v+8iG87V9UK4ah7YHLDmjZDSH+Oi35i2u7F4Y0zXqYnTUPj3qiv4NU2rjuaUxl2hESIFfwQYsZwAfpVqsFHwK7T0WJ7DL027giA0MlwOG/lX9ObRy3tit2m8/e1Orn7uazbtKa37k3S/BK58CTQ7fPf/4D93QwyDJPq16gfA3LVzeXHNi0r615xt2gDg2byFA6/+M+brGaQ1TwJgxX9/xlul9nefIMQaKfgjQNM0s+hXqvBbYOkxPPyqm3aNgh9p2hUEoRGiaRo3DOrAq7ecEZrIu+MQFz35JXnvra17ik+Py+FXz4Nmg2//Ce9PiFnR/+uuv+bmXjcDMHPVTJ5Y8QRBPbbiiKt9e5rdcD3oOnsee4yiv/0NXUE63oCLO+Jw2ti+7gDvzPiWihKx9giNByn4I8Sw9Sj18Fth6bG6aVdlDr807QqCoJjBnVvwn/FnM6JHFoGgztylPzP0r18wb+nPdXsHudev4Io5oaJ/1Tx4bzxUHYr6PjVNY+JpE7l/wP0AvLruVaYsmRJzMShr8mRaTpgAwP7nX2DXgw+ie2NbgLft1ozLJ/YnKdXJ3m2lvDl9BQf3qElEEoRYIwV/hBjRnGpTeiyw9FiUw18dy6nS0iNNu4IgqCc3M4U5NwzgX7cNpFtWGgcrfDz83lpGPvklX2yow7CrPr+Gy58BNFj9L3jqF7Di5Zj4+m/seSP5Z+fj0By8/9P73PXZXVT4YlcMa5pGiztup3V+PtjtlLz3H7bfOZZAWXnM1gTI7pjBr35/GuktkijZV8WbT6yksCD6L6QEQTVS8EeIJQq/lSk9yi091qX0BEThFwTBAs7q3IIP7j6bP4/qRbMUJ5uKyrjp5eWM+PtiXvn6Z0qrjnMe9rsWrnsTmneBin0he89zQ+DnJVHf56WnXMpT5z1Fkj2Jr3Z+xW8X/JafDv0U9XVq0nT0FeQ+OxstJYXyr75i6w3Xx3wCb9OsFH41aQCt2qdRVebj3Rnf8vP3+2K6piDEGin4I8RpDt9SaekJ5/BbYOkJ6kECCqLfDKyw9NgcYukRBMFaHHYb15/Zni/uH8atZ3ckxWVnU1EZf3p3LQPzP2XK22v4sbDk6F/c+XwY+zVc9DgkZcCeNTD3Enj9etgb3XSdc9qewwsXvkCGO4Pv933PqHdG8ftFv2dT8aaorlOT1HPOof28edgzM/GsW8+Wi0ay5y/T8e2JXeGfku7i8nv7065nc/y+IB888z0fPP0du7eI2i+cnEjBHyEOm6HwWzFpV13Bbyj8oDaa00zpsSKH3y+WHkEQrCUjxckff9mDZQ+dzyOX9aRzq1QqvAH+9b9tXDTzS0Y9/RXPfLGZjXtKa1t+7E44806461sYcGvI27/+PXj6dJgzDJbNhrLoFMh9W/blnyP/ydDcoejofPTzR4x+bzT3fn4v6/evj8oah5PcuxcdXvt/JPXogV5RwYGXX2bLBRew++E8vNu3x2RNV5KDi8f2pteQNqDBz2v289YTK3n7b6vYuna/ksQiQYgWjhM/RKiJK6wGq43lNCbtqs/hh5CP3213K1nXkhx+adoVBCHOSE9ycuPgDtwwqD3LfjrAP5dt5eO1hazefpDV2w8y/aMN5GYmc373LC44NYszOmaGfj81aQ6/nAGn3wqf/hk2LYBdq0IfHz8EnYZC76tCmf4pmfXeX4eMDvzjvH/w44EfmfP9HBZuXcgn2z7hk22fcHabsxnRfgRntznbHNwVDVzt2tHhzX9T/uWX7HtuDpUrV3Lw9dc5+MYbpF98MU1/NZrk007D5nJFbU273caQa7vR97xcvl2wlR+XFbJr00F2bTpIi9xU+p6fS/uezUlOi96aghALpOCPEEtjORVaeowcflDbuGvGcirN4ZemXUEQ4hNN0xh0SnMGndKcotIqFqzdw6fr9/DVlv1sP1DJ3KU/M3fpz7gdNnq3yeAX7ZvRP7cpv2h/ClljXoOyvbD2bfj+ddi5ArZ8FvoAaNUD2g2C9oNDH+k5Ee+ve2Z3ZgydwebizcxZM4ePCj5iyc4lLNkZ6iE4NfNUzml7Due0OYfeLXpjt9kb/PNIPfdcUs89l4oVK9g3Zw7li7+k5P33KXn/fbTkZFLOOJ3Us8+hydln4erQAU3TTvzEJ6BpVgrDrj+V03/ZidWfbmPtl7vYt72MT+euBw1atUsjt0cm7Xo0J6tTuikkCUK8IAV/hDgsieVUb+mx2+xoaOjoSht3Nad1lh5p2hUEIZ5plZbEdWe257oz21Ph9bNk0z4+XV/Epz8Wsa/Mw4qtxazYWmw+PicjiZ5tMujS6lw6n3YxPQfvp2Phf3H9+A7s/RGK1oU+VrwY+oKm7aF1H2h5KrTqHvqzeWdwnFi97tysM9PPnc7YvmP5sOBDFu9YzA/7f2D9gfWsP7CeOd/PoYmzCd2adaN7Zne6Z3anW2Y3Tml6Sr3fQU4ZMIB2AwZQtW4dB/71L8oXf4l/717KFy2mfNFiIDTEK6l3b5K6dcXdrRvurt1wtsmp94uA1GZuzr6yCwMu6sCaRTvYsmov+3eWUbS1lKKtpaz8cCuuJDvZp2TQvE2q+dEsOwW7Q14ECNZxUhT8zzzzDE888QS7d++mZ8+ezJw5k3POOceSvbjMWM7GbemBUOOuN+hVq/Ablh6FsZx2adoVhLgins78eCXF5WBEz2xG9MxG13UK9pWzattBvt1WzKptB9lQWMKuQ1XsOlTFwnV7anxlH9o0HUjvbC+DnBvp7V9Lh4rvaVbyI9rBrXBwK6z/T/XDbQ7I7BR6MdA0FzLaQka70OfpbaBJS3AmmQ/vkNGBO/vdyZ397mRf5T6W7lrK4h2LWbpzKaW+UlYVrWJV0Srz8XbNTm5aLm3S2tCmSRvapLUhJzWHtqltyUrJollSs1o9ZUcjqUcPch57DF3X8WzcSPmXX1K25CsqVq7Et3Mnvp07Kf3oo+pvKTUVd5cuONu2xZmTg7N1a5xtcszPbSkpJ/z5J6U6Of2Sjpx+SUfKD3nYvu4A29YdYPv6A1SV+di29gDb1h6oXtOm0TQ7haatUkjLTCKteRJpmUmkZrpJa55EUhNnVN6JEIRjEfcF/+uvv86ECRN45plnOOuss3juuecYOXIk69ato127dsr3U63wN25LD4Qad71Br9poTqNpVyw9gpCQxNuZfzKgaRqdWqbSqWUqV57WFoByj5/vdxxiQ2EJm4rK2Bz+2F/uZefBSnYehI84BTgFuIxUKuhn20I3bTunOnbSzb6LTvp2mgQrYN/G0McxCLrS0FNaoKW2DH2ktIDkprRIyuCypAwuyzwTf+sL+MlfzoaqIjaU7+LH0m38eGgzh7wl/FzyMz+X/HzM52/qbkrzpOY0T25O86TmZLgzSHOlke5KJ82VZn6kOFNIaZVCyjUjSbtuNC29EPx+HZ4NG/Fs3EDVho14tmwhWFZG5bffUvntt0f/eSYn48jMxN68OY5mzbA3b469WVPsaWnYUtOwp6ViS0sP/dmkCY7kZE7plEKXnrlo7i7sK6xi77ZS9u8oY9/OMg7sKsdT4efArnIO7Dr6HAGbXSMp1UlymovkGn+6Uxy4kkMf7uTqz51uOw6XDafbjtNlx+60yQsG4bhoepy3mQ8cOJBf/OIXzJ4927x26qmnMmrUKKZNm3bCry8pKSEjI4NDhw6Rnp7e4P1cM+drlv10gN+e05HT2jdr8PPVheztH9Lvf/dSmt6FzT3vUrImwJ17ZlGuV3Fd2nk0s6cqWbP9x2tp99kGDnTPovD0DkrWDPiT2bv710CQps0XK1lTEOpCk5ZNGTVhYkRfE+0zTzUNOfNP9u9dBfvLPGzZW86O4gp2Fley61AlO4or2Xmwkl0HK6ny1RQ+dLI5QGfbLnK0fbTR9tFW20cO+2mj7SVbO4BLq39ssw7ssdvZ7EpmhzOJHU4nuxx2djls7LZrHLTpBBtYw2qACztO7Lg0O+6AnTYHoM0+neYlOpmHAjQ9FKTpoQAZh/y4PQ0XfoJ2jYDDRtBhJ+C0EXDY8CQ1ozwlhypXczyuZvicTfHam+JzZOC3pTV4TdDR8KNpfjQCQABNC38QAC2IRjD8Z83beuhrtSAQRAvf5rA/Q48NrRN6fPXn1ddrXINa1zUOfzw1Hn+0z4/+mLq9ptGPe1MdkS987i1jaNe1R0RfU9dzL64Vfq/Xy8qVK3nwwQdrXR8xYgRLly496td4PB48Ho95u6TkGLnF9STJGWo4ev7LAp7/siCqz30szrft4EUXpJVsov/XdytZE6BJbg7lDgf/LP1M2ZpX+IO0AzJ/3EPmj3tO+Pho4HM0Ye/ZvwZsHNw/VMmaglAXqrb/YPUWlBLpmR/r874x0jzVTfNUN2d0PDKhR9d1yr0B9pd52FfmYW+pl/3lHvaXeTlU6WNHpY+1lT5KqnyUVPopqfRi85aS7N1PeuAgzbUSWmiHyKSUNK2CdCpI18rNP9OoJEXzkEIVqVoVGpAdCJBdWQaVZUfsJwActNnYb7ez3278aafEZqPUZqPUHv7TplFis1Gp2aiwaVRqGlXhCG0d8BDAQyB0wwa7W8CKFkf76dhI9mikV0B6OaRX6mSUQ0YFpFbqpHggxQNNqiDFE7qd5IUkH7i9YA/Xd7aAji0QAE/1i6E0KmjBzqP+nQQ1B15XKj5nKl5nGj5X+E9nKn5HCn5HEn5HcujDHvo8YHcRtLkIGpZfNHSc6Hp1wp51ha5QX7asWhFxwV9X4rrg37dvH4FAgKysrFrXs7KyKCwsPOrXTJs2jUceeSRme7rlrI5U+QL4FVp6PMGz+KpkOZlBtZP+rijxsaiJT+mZsbuzxobtOkmeEz82elTQ9MACqpJPUbmoIJwQzbHf6i0oJdIzP9bnfaKhaRqpbgepbgftmzeJ6Gv9gSAVvgAVngDlXj8eX5Aqf8D8c6cvgMcfxBfQ8QWC+Px+gt5KdG8Z+KrQ/FVogSo0XxVawBO6HfRiC/qwBXxoug9bwEu67iNDD6DpfmwBPzZ/AJvuxxYMKds2PYimhxRuH368mp+AHsCnBQloAXwE8Yf/DKIT0IL4NZ1A+LZf0wnadALpEEzXCaAT0OAAOvsJveMQ0sJDn+vo6EBQ19GC4PCD3RfE7gd7AGx+HXsA7AEdhx9sQbAFwn8GQ/fZAmDTy7AFS9H03eH7Qh+aDloQbDpoQR27H5xV4es66LqGhgs0F+AGzUGotHOi4wx9rjkBO2BH10J/otnRcQAaaDZ0bDWua4AtNMsBW43bWujx2NBrfo4WVu21wz7C1zStls5fW+IP3W8WGodJ+Dp1kvRrP98Rl04eq1NyRuuYPXdcF/wGh/vSdF0/pldt8uTJTJxY/RZ4SUkJubm5UdvLuV1bcm7X6OUK153zla94KjBe+arAJCsWFQQhXqjrmR/r816oOw67jXS7jfQk54kfLAiCcuK64G/RogV2u/0IZaeoqOgIBcjA7XbjdqsZEiUIgiBEj0jPfDnvBUEQ6kZch8K6XC5OO+00Fi5cWOv6woULGTx4sEW7EgRBEGKBnPmCIAixIa4VfoCJEydy/fXXM2DAAAYNGsScOXPYtm0bd9xxh9VbEwRBEKKMnPmCIAjRJ+4L/quvvpr9+/fz6KOPsnv3bnr16sV///tf2rdvb/XWBEEQhCgjZ74gCEL0ifsc/oYiucyCICQSiXzmJfL3LghCYlLXcy+uPfyCIAiCIAiCIDQMKfgFQRAEQRAEoREjBb8gCIIgCIIgNGKk4BcEQRAEQRCERowU/IIgCIIgCILQiJGCXxAEQRAEQRAaMXGfw99QjNTRkpISi3ciCIIQe4yzrpEnLh8VOe8FQUg06nrmN/qCv7S0FIDc3FyLdyIIgqCO0tJSMjIyrN6GUuS8FwQhUTnRmd/oB28Fg0F27dpFWloamqbV+etKSkrIzc1l+/btjX6Ai3yvjRP5XhsnJ/pedV2ntLSUnJwcbLbEcm3W97wH+TfUWEmU7zVRvk+Q7/Vw6nrmN3qF32az0bZt23p/fXp6eqP/B2Ug32vjRL7XxsnxvtdEU/YNGnreg/wbaqwkyveaKN8nyPdak7qc+Ykl/wiCIAiCIAhCgiEFvyAIgiAIgiD8//buJSTKPQ7j+DPlLSzkdHO0IOxOpUKWZXSjiyAVRZuKFkGrwkKpTZeFEYHSIii6EUXUyhZltAkSqrGIQmsGB4sQ7AZp0iITo/vvLA7npUldnJw5r/P3+4EBfd9Z/B7n5fHXNDM6jIW/H+np6aqqqlJ6errfoyQcWd1EVjcNpaz/p6H0cyWre4ZKTomsf8r5N+0CAAAAQxnP8AMAAAAOY+EHAAAAHMbCDwAAADiMhR8AAABwGAt/P06fPq28vDxlZGSoqKhI9+7d83ukAWtoaNC6deuUm5urQCCg69evx5w3Mx06dEi5ubkaMWKEli9frpaWFn+GHYDq6mrNnz9fo0aN0vjx47VhwwY9f/485j6uZD1z5owKCgq8P8pRUlKimzdveuddydmX6upqBQIBVVZWesdcyXvo0CEFAoGYWzAY9M67knOwoO+T+xqi893vfPp+4DlZ+Ptw5coVVVZW6uDBgwqHw1qyZInKysr0+vVrv0cbkJ6eHhUWFurkyZN9nj969KiOHTumkydPqrGxUcFgUKtXr1Z3d/f/POnAhEIhlZeX6+HDh6qvr9f3799VWlqqnp4e7z6uZJ04caJqamrU1NSkpqYmrVixQuvXr/fKwJWcv2tsbNS5c+dUUFAQc9ylvLNnz1Z7e7t3i0aj3jmXcvqNvk/+a4jOd7vz6fs45TT0UlxcbDt27Ig5NnPmTNu3b59PE8WfJKurq/O+//nzpwWDQaupqfGOff782bKysuzs2bM+TBg/nZ2dJslCoZCZuZ3VzOyvv/6y8+fPO5uzu7vbpk2bZvX19bZs2TKrqKgwM7ce16qqKissLOzznEs5BwP6/h8uXUN0vjs56fv45eQZ/t98/fpVjx8/Vmlpaczx0tJSPXjwwKepEu/Fixfq6OiIyZ2enq5ly5Ylfe6uri5J0ujRoyW5m/XHjx+qra1VT0+PSkpKnM1ZXl6uNWvWaNWqVTHHXcvb2tqq3Nxc5eXlafPmzWpra5PkXk4/0fduXkN0vjs56fv45UyJ68QOeP/+vX78+KHs7OyY49nZ2ero6PBpqsT7N1tfuV+9euXHSHFhZtqzZ48WL16sOXPmSHIvazQaVUlJiT5//qyRI0eqrq5Os2bN8srAlZySVFtbqydPnqixsbHXOZce1wULFujy5cuaPn263r17pyNHjmjRokVqaWlxKqff6Hv3riE6352c9H18+56Fvx+BQCDmezPrdcxFruXetWuXmpubdf/+/V7nXMk6Y8YMRSIRffjwQVevXtW2bdsUCoW8867kfPPmjSoqKnTr1i1lZGT0ez8X8paVlXlf5+fnq6SkRFOmTNGlS5e0cOFCSW7kHCyG6s/Sxdx0vhs56fv49z0v6fnN2LFjNXz48F7P7nR2dvb6F5ZL/n1HuEu5d+/erRs3bujOnTuaOHGid9y1rGlpaZo6darmzZun6upqFRYW6vjx487lfPz4sTo7O1VUVKSUlBSlpKQoFArpxIkTSklJ8TK5kvdXmZmZys/PV2trq3OPq5/oe7dy0/nu5KTv49/3LPy/SUtLU1FRkerr62OO19fXa9GiRT5NlXh5eXkKBoMxub9+/apQKJR0uc1Mu3bt0rVr13T79m3l5eXFnHcpa1/MTF++fHEu58qVKxWNRhWJRLzbvHnztHXrVkUiEU2ePNmpvL/68uWLnj17ppycHOceVz/R925cQ3S+e51P3yeg7//TW3yHiNraWktNTbULFy7Y06dPrbKy0jIzM+3ly5d+jzYg3d3dFg6HLRwOmyQ7duyYhcNhe/XqlZmZ1dTUWFZWll27ds2i0aht2bLFcnJy7OPHjz5P/t/s3LnTsrKy7O7du9be3u7dPn365N3Hlaz79++3hoYGe/HihTU3N9uBAwds2LBhduvWLTNzJ2d/fv3UBjN38u7du9fu3r1rbW1t9vDhQ1u7dq2NGjXK6yBXcg4G9H3yX0N0/tDofPp+YDlZ+Ptx6tQpmzRpkqWlpdncuXO9j/dKZnfu3DFJvW7btm0zs38+/qmqqsqCwaClp6fb0qVLLRqN+jv0H+groyS7ePGidx9Xsm7fvt27TseNG2crV670it/MnZz9+f0XgCt5N23aZDk5OZaammq5ubm2ceNGa2lp8c67knOwoO+T+xqi84dG59P3A8sZMDP7w/91AAAAADDI8Rp+AAAAwGEs/AAAAIDDWPgBAAAAh7HwAwAAAA5j4QcAAAAcxsIPAAAAOIyFHwAAAHAYCz8AAADgMBZ+AAAAwGEs/ECCVFZWasOGDX6PAQBIMPoegx0LP5AgjY2NKi4u9nsMAECC0fcY7AJmZn4PAbjk27dvyszM1Ldv37xjxcXFevTokY9TAQDijb5HskjxewDANcOHD9f9+/e1YMECRSIRZWdnKyMjw++xAABxRt8jWbDwA3E2bNgwvX37VmPGjFFhYaHf4wAAEoS+R7LgNfxAAoTDYcofAIYA+h7JgIUfSIBIJMIvAAAYAuh7JAMWfiABotGoCgoK/B4DAJBg9D2SAQs/kAA/f/5Uc3Oz3r59q66uLr/HAQAkCH2PZMDCDyTAkSNHdOXKFU2YMEGHDx/2exwAQILQ90gGfA4/AAAA4DCe4QcAAAAcxsIPAAAAOIyFHwAAAHAYCz8AAADgMBZ+AAAAwGEs/AAAAIDDWPgBAAAAh7HwAwAAAA5j4QcAAAAcxsIPAAAAOIyFHwAAAHDY32sizBwq5R9RAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 900x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# select a few columns\n",
    "col_list = [0, 5, 10, 15, 20]\n",
    "plot_models = ['ra', 'ha']\n",
    "J_cols = [{k: -G[k]['Y']['r_ante'][:, i] for k in plot_models} for i in col_list]\n",
    "show_irfs(J_cols, plot_models, labels=col_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As discussed in class, the standard HA model with acyclical income risk does not solve the forward guidance puzzle. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "To go beyond this, we want to move away from income being just $e \\times Y$, so that low-`e` agents are more or less sensitive to `Y`. \n",
    "\n",
    "To do this, we'll change the `income` hetinput. We'll use the following specification from Auclert \\& Rognlie (2018)\n",
    "\n",
    "$$ y_{it} = Y \\cdot \\frac{e_{it}^{1 + \\zeta \\log(Y)}}{\\mathbb{E}[e_{it}^{1 + \\zeta \\log(Y)}]}$$\n",
    "\n",
    "Call this new function `income_cyclical`. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "def income_cyclical(Y,e_grid, e_pdf, zeta):\n",
    "    y = Y * e_grid ** (1 + zeta * np.log(Y)) / np.vdot(e_grid ** (1 + zeta * np.log(Y)), e_pdf)\n",
    "    return y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This `hetinput` maps `zeta`, a variable that scales the degree of cyclicality of income risk, to `y` the post-tax labor income of households. When `zeta` = 0, income risk is acyclical but when `zeta` >/< 0, income risk is pro-/counter-cyclical\n",
    "\n",
    "Note that this function requires the pdf of `e`. Since the standard SSJ implementation of `make_grids` doesn't this to us, we rewrite it here with this extra output."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_grids_pdf(rho_e, sd_e, n_e, min_a, max_a, n_a):\n",
    "    e_grid, e_pdf, Pi = sj.grids.markov_rouwenhorst(rho_e, sd_e, n_e)\n",
    "    a_grid = sj.grids.asset_grid(min_a, max_a, n_a)\n",
    "    return e_grid, e_pdf, Pi, a_grid"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now define a new `hetblock` and a new `model` with this new functionality added. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "household_cyc = hh.add_hetinputs([make_grids_pdf, income_cyclical])\n",
    "ha_cyc = sj.create_model([household_cyc, ex_post_rate, mkt_clearing_simple], name=\"HA Model with cyclical income risk\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "calib_cyc = calibration.copy()\n",
    "calib_cyc['zeta'] = -0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "ss['ha_cyc'] = ha_cyc.solve_steady_state(calib_cyc, {'beta': (0.75, 0.9)}, ['asset_mkt'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`zeta` should not change the steady state, we check this. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.isclose(ss['ha_cyc']['beta'], ss['ha']['beta'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Model jacobian in ha models with cyclical risk\n",
    "for zeta, mod in zip([-0.5, 0.5], ['ha_counter', 'ha_pro']):\n",
    "    ss_cyc = ss['ha_cyc'].copy()\n",
    "    ss_cyc['zeta'] = zeta    # income risk does not change the steady state\n",
    "    G[mod] = ha_cyc.solve_jacobian(ss_cyc, ['Y'], ['asset_mkt'], ['r_ante'], T=T)\n",
    "\n",
    "col_list = [0, 5, 10, 15, 20]\n",
    "plot_models = ['ha_counter', 'ha_pro']\n",
    "J_cols = [{k: -G[k]['Y']['r_ante'][:, i] for k in plot_models} for i in col_list]\n",
    "show_irfs(J_cols, plot_models, labels=col_list)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Maturity structure\n",
    "\n",
    "As we saw in lecture, allowing for varying maturity/duration of assets can affect the equilibrium response of consumption to interest rate shocks. \n",
    "\n",
    "Recall the pricing (no-arbitrage) equation for Calvo bonds\n",
    "\n",
    "$$\n",
    "1 + r_t^{ante} = \\frac{1 + \\delta q_{t+1}}{q_t}\n",
    "$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "We implement this equation as a `SolvedBlock` that returns `q` taking `r_ante` and `delta` as inputs\n",
    "\n",
    "Recall from the fiscal tutorial that the syntax `q(1)` here would denote $q_{t+1}$, given `q` denotes $q_t$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "@sj.solved(unknowns={'q': (0.1, 25)}, targets=['qres'], solver=\"brentq\")\n",
    "def longbonds_price(q, r_ante, delta):\n",
    "    qres = q - (1 + delta * q(+1)) / (1 + r_ante)\n",
    "    return qres"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Additionally, we will create another block, which yields the ex-post return of the Calvo bonds. The reason we need this additional block is in this model there are valuation effects, i.e. when a shock occurs at period $t = 0$, it re-values the bond's price $q$ but because this shock was unanticipated as of $t = -1$, the actual realized return `r_post` will differ from the expected return as of $t = -1$, i.e. the $t = -1$ ex-ante rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "@sj.simple\n",
    "def ex_post_longbonds_rate(q, delta):\n",
    "    r = (1 + delta * q)/q(-1) - 1\n",
    "    return r"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Let's now create a new model object called `long`, solve for its steady state and recreate the figure we saw in lecture"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "calibration_long = calibration.copy()\n",
    "calibration_long['delta'] = 0.95\n",
    "\n",
    "models['long'] = sj.create_model([household_simple, ex_post_longbonds_rate, longbonds_price, mkt_clearing_simple], name=\"HA model with long-duration bonds\")\n",
    "ss['long'] = models['long'].solve_steady_state(calibration_long, {'beta': (0.75, 0.9)}, ['asset_mkt'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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kCCu5TTPGuM+ke9Seu6h4DqNjlXg/jDGvG2NSjDEpzZufx9Bnhbmw80twuarehlKqxg0YMICDBw+WvH7//fe55ZZbGDZsGPPmzavFyFR18+dYlKuBziLSATiI1QHkpjJl5gEPiMgMoB+QaYw5LCKCNf35NmPM8x7q3IY1dfltWPMWFS9/X0SeB9pgdVxZVf2bZds6F+b8DO7+GuL6+O1tlKpPnvxkC1sPVXQypnK6tWnMH69J9qms0+lk0aJF3HXXXSXLPvjgAxYuXMiOHTt46aWX9FRlPeK3IzhjTBHwAPAFVieRmcaYLSJyj4jcYxebD+zB6hDyBnCfvfxSrBl0fyIiG+zHKHvdM8BQEdkFDLVfY4zZAswEtgILgPuNMU5/bR+dh4E4YMdnfnsLpVT1yM3NpWfPnjRt2pRTp04xdOhQAFavXk3z5s1p3749V155JevWreP06dO1HK2qLg16wtOUlBRzXrMJTB0N2cfh/pUVl1VK1ZqIiAiysrLIzMxk9OjRTJgwgQcffJBHHnmEd955h8jISABOnTrF888/z913313LETcsIrLWGJNS3e3qSCbno8vVcHw7nNxd25EopXwQFRXFiy++yHPPPUd+fj6zZs1i06ZNpKWlkZaWxty5c5k+fXpth6mqiSa485FknzXdrqcplbpQ9OrVi4svvpiZM2cSGxtLbOyPdxMNGTKErVu3cvjw4VqMUFUXPUV5vhOevjoIQiLgzgXVE5RSSjUweoqyrupyNexfAVl6T51SStUlmuDOV5dRgIGdegSnlFJ1iSa489XqIohqq9fhlFKqjtEEd75ErM4mexZDgQ7zo5RSdYUmuOrQ5WooyoPdX9d2JEoppWya4KpD+4EQGgXb59d2JEoppWya4KqDIwgSR8DOz8FZVNvRKKWUQhNc9UkaBbmn4cCK2o5EKVVGREREqddTp07lgQceKLXMlznh/v3vf/Puu+96Xf+nP/2J5557ruqBAn/9619LnhcUFDBkyBCKivQf56rQBFddOl0JjhDtTanUBciXOeGKiop46623uOmmspOiVA9jDC6Xq1SCCw4O5sorr+SDDz7wy3vWd/6cLqdhCYmEjpdZCW74X63elUqp0j5/DI78UL1ttuoBI585ryaK54Tbtm0b8+bN83gk9/XXX9O7d28CA60/my+++CKvvfYagYGBdOvWjRkzZgCwdetWLr/8cvbv389DDz3Egw8+CMDzzz/PW2+9BcDdd9/NQw89RFpaGiNHjuSKK65g+fLl9OzZs2Tmg+TkZKZNm8a1117L448/zuTJk89rGxsiTXDVqcvVsOtLOLoFWnWv7WiUUrbipFHs1KlTjBkzpuS1L3PCfffdd/Tp8+Pcj8888wx79+4lJCSEjIyMkuXbt29n8eLFnD17lqSkJO699142bdrE22+/zcqVKzHG0K9fPy677DJiYmLYsWMHb7/9Nq+88goAs2bNYsOGDSXtde/endWrV1ffzmhANMFVp8SRwEOwY74mOKU8Oc8jraoKCwsrlTSmTp1K8Ti07nPCxcXFceedd3L69GliYmJKtXH48GG6du1a8vqiiy5i8uTJXHvttVx77bUly6+++mpCQkIICQmhRYsWHD16lGXLljFu3DjCw8MBGD9+PEuXLmXMmDG0b9+e/v37e43d4XAQHBzM2bNnS6b1Ub7Ra3DVKbIlxPWF7Z/WdiRKKR9Nnz6d7du3Ex8fT0JCAmfOnOHDDz88p1xYWBh5eXklrz/77DPuv/9+1q5dS58+fUo6goSEhJSUcTgcFBUVUd6g9sVJrzz5+fmEhoZWZrMUmuCqX5dRcHgjZKbXdiRKqQq4XC6f54Tr2rUrqampJfUOHDjAFVdcwbPPPktGRgZZWVle32fIkCF8/PHH5OTkkJ2dzZw5cxg8eLDHskFBQRQWFpa8PnnyJM2bNycoKOg8t7bh0QRX3ZKutn7qTd9K1XlLlizxeU64kSNHsmTJEgCcTic333wzPXr0oFevXjz88MNER0d7fZ/evXtz++23c8kll9CvXz/uvvtuevXq5bHslClTSk5/AixevJhRo0ad55Y2TDof3PnOB+fJ/6VAVCzcOrf621ZK1Zpx48bx7LPP0rlz5xp7z/Hjx/O3v/2NpKSkGnvPmqbzwV1IuoyCtGWQm1HbkSilqtEzzzxTo7N9FxQUcO2119br5OZPmuD8octocBXBroW1HYlSqholJSUxZMiQGnu/4OBgbr311hp7v/pGE5w/xKZAeAvtTamUUrVIE5w/BARA0khI/QqK8ms7GqWUapA0wflLl6uhIAv2Lq3tSJRSqkHSBOcvHS6DoHA9TamUUrXErwlOREaIyA4RSRWRxzysFxF50V6/SUR6u617S0SOicjmMnU+EJEN9iNNRDbYy+NFJNdt3Wv+3LYKBYVaMwzs+BxcrloNRSmlGiK/JTgRcQAvAyOBbsCNItKtTLGRQGf7MQV41W3dVGBE2XaNMTcYY3oaY3oCHwIfua3eXbzOGHNPdW1LlXUZDVlH4NC62o5EqQavojnh5syZg4iwfft2r23k5uZy2WWX4XQ6Pbbpb5mZmYwbN44+ffrQo0cP/vvf/1apnQULFpCUlESnTp145hnv44O+8MILdO/eneTkZP7973+XLI+Pj6dHjx707NmTlJQfb1+ra/PX+fMI7hIg1RizxxhTAMwAxpYpMxZ411hWANEi0hrAGLMEOOWtcRERYCJw7pg6dUXnoSAOnSNOqQvA9OnTGTRoUMm0N5689dZbjB8/HofDUYOR/ejDDz8kMjKStWvX8sMPP1RpCh2n08n999/P559/ztatW5k+fTpbt249p9zmzZt54403WLVqFRs3buTTTz9l165dJesXL17Mhg0bcB8so67NX+fPBBcLHHB7nW4vq2wZbwYDR40xu9yWdRCR9SLyrYh4HOhNRKaIyBoRWXP8+HEf36qKGjWB+Es1wSlVx2VlZfHdd9/x5ptvlpvgpk2bxtixZf9Ptzz//PN0796d7t27lxztpKWl0bVrV37605+SnJzMsGHDyM3NBeCpp56iS5cuDB06lBtvvNGnmcB79+7Nt99+S0pKCn/84x9LDezsq1WrVtGpUyc6duxIcHAwkyZNYu7cc0dd2rZtG/3796dRo0YEBgZy2WWXMWfOnArbv/baa5k2bVql4/IHf06X42nGz7LjgvlSxpsbKX30dhhoZ4w5KSJ9gI9FJNkYc6ZU48a8DrwO1lBdPr5X1SVdDQsehROp0KyT399Oqbrs76v+zvZT3k8BVkWXJl149JJHKyxX3pxwH3/8MSNGjCAxMZEmTZqwbt06evfuXap+QUEBe/bsIT4+/py2165d63W+t127djF9+nTeeOMNJk6cyIcffkiXLl348MMPWb9+PUVFRfTu3bvUXHOeZGZm8pvf/IZNmzYRHh7OT37yE3r27Mm4ceNKygwePJizZ8+eU/e5557jqquuAuDgwYO0bdu2ZF1cXBwrV648p0737t154oknOHnyJGFhYcyfP7/kdKSIMGzYMESEn/3sZ0yZMqVUvboyf50/E1w60NbtdRxwqAplziEigcB4oOQbYYzJB/Lt52tFZDeQCPhhsMlK6DLKSnA7PoNmv6jVUJRqyMqbE2769Ok89NBDAEyaNInp06efk+BOnDjhdUDl8uZ769ChQ0li7dOnD2lpaZw4cYKxY8cSFhYGwDXXXFNh/P/5z38YPnw4UVFRAAwYMIAjR46UKrN0acW3JXkaf9i64lNa165defTRRxk6dCgRERFcfPHFJbOZf/fdd7Rp04Zjx44xdOhQunTpUjLCS12av86fCW410FlEOgAHgUnATWXKzAMeEJEZQD8g0xjjy0BvVwHbjTElc9KISHPglDHGKSIdsTqu7KmG7Tg/0e2gVQ9rdoFLNcGphs2XI62advLkSb7++ms2b96MiOB0OhERnn322VJ/+MvOB+euvEHry84Pl5ubW255b9avX89tt91W6nXZxOjLEVxcXBwHDvx4ZSg9PZ02bdp4fM+77rqLu+66C4Df/va3xMXFAZSUb9GiBePGjWPVqlWlhjCrK/PX+e0anDGmCHgA+ALYBsw0xmwRkXtEpLiH43ysJJQKvAHcV1xfRKYDy4EkEUkXkbvcmp/EuZ1LhgCbRGQjMBu4xxjjtZNKjeoyGg6shKxjtR2JUqqM2bNnc+utt7Jv3z7S0tI4cOAAHTp0YNmyZaXKxcTE4HQ6PSa5ysz3BjBo0CA++eQT8vLyyMrK4rPPSl+nv/LKKzl48OA5779+/XrAmmz1zJkzDBw4sFSZpUuXsmHDhnMexckNoG/fvuzatYu9e/dSUFDAjBkzSk7VlnXsmPU3a//+/Xz00UfceOONZGdnlyTR7OxsvvzyS7p3715Spy7NX+fPIziMMfOxkpj7stfcnhvgfi91byyn3ds9LPsQ67aBuidpFHzzN9i5AHrrwKlK1SXTp0/nscdK36Z73XXX8f7775+TpIYNG8ayZctKJQwoPd8bUDLfW1pamsf37Nu3L2PGjOHiiy+mffv2pKSklJx6dLlcpKam0qRJk1J1fv3rX3PDDTcwY8YMOnTowEcffURAQOWPUQIDA3nppZcYPnw4TqeTO++8k+Tk5JL1o0aN4r///S9t2rThuuuu4+TJkwQFBfHyyy8TExPDnj17Sq77FRUVcdNNNzFixI93dNWp+euMMQ320adPH1MjXC5jnu9uzLSJNfN+Sim/WLdunbn55purpa2zZ88aY4zJzs42ffr0MWvXrjXGGPPDDz+Yhx9+uFreozaMGzfObN++vVJ1gDXGD3/j/XoEp2wiVmeTNW9DfhaE1OzNoUqp6tGrVy+uuOIKnE7ned8LN2XKFLZu3UpeXh633XZbSaeW7t278/zzz1dHuDWurs1fpzN6+2NGb0/2LoF3roGJ70E3z+e7lVKqIdIZvS907QZCaDTsmF9hUaWUUudPE1xNcQRC4giro4mzbozTppRS9ZkmuJrUZRTknob9y2s7EqWUqvc0wVXR2n2nuOPtVWTmFPpeKeFKcITo2JRKKVUDNMFVUZHTsHjHcVbuPel7pZAI6Hi5NWxXA+7co5RSNUETXBX1ahdDaFAA3++uRIID6HI1ZOyHo5srLquUUqrKNMFVUXBgAH3jm/D97hOVq5g0EhBrbEqllFJ+ownuPAxMaMbOo1kcP5vve6WIFtD2Etj+qf8CU0oppQnufAxMaArA8j2VPE2ZNAqObIKMAxWXVUopVSWa4M5DcpvGRIYGsryypym7jLZ+6k3fSinlN5rgzkOgI4B+HZpWvqNJs07QLFFvF1BKKT/SBHeeBiY0Zd/JHNJP51SuYperIW2ZdeO3UkqpaqcJ7jwN7GRfh6vsUVzS1WCcsGuhH6JSSimlCe48JbaIpGl4cOUTXGwfiGipvSmVUspPNMGdp4AAoX+CdR2uUlMPBQRY98SlLoLCPP8FqJRSDZQmuGowMKEpR87ksfdEduUqJl0NBVnWtTillFLVShNcNRiY0Ayg8r0pOwyGwDBrCh2llFLVShNcNYhv2og2UaGVH7YrKAwSroCdX+jgy0opVc00wVUDEWFAQjOW7z6Jy1XJRJU4HDL3w7Gt/glOKaUaKE1w1WRgQlNO5xSy/cjZylXsPNz6qacplVKqWmmCqyYD7HEpK32asnFraN3TOk2plFKq2vg1wYnICBHZISKpIvKYh/UiIi/a6zeJSG+3dW+JyDER2Vymzp9E5KCIbLAfo9zWPW63tUNEhvtz28pqEx1Gh2bhlb8fDiBxBBxYBdmVTI5KKaW88luCExEH8DIwEugG3Cgi3coUGwl0th9TgFfd1k0FRnhp/l/GmJ72Y779ft2ASUCyXe8VO4YaMyChKSv3nqLI6apcxcThgNFRTZRSqhr58wjuEiDVGLPHGFMAzADGlikzFnjXWFYA0SLSGsAYswQ4VYn3GwvMMMbkG2P2Aql2DDVmYEJTsvKL+OFgZuUqtu4JEa30OpxSSlUjfya4WMB9wrN0e1lly3jygH1K8y0RialMWyIyRUTWiMia48eP+/BWvuvfsfg6XCVPUwYEQOIw2P01FBVUa0xKKdVQ+TPBiYdlZfvQ+1KmrFeBBKAncBj4Z2XaMsa8boxJMcakNG/evIK3qpxmESF0aRVZ9etw+Wdg//fVGpNSSjVU/kxw6UBbt9dxwKEqlCnFGHPUGOM0xriAN/jxNGSl2/KHAQlNWZ12ivwiZ+UqdrwcHCHam1IppaqJPxPcaqCziHQQkWCsDiDzypSZB9xq96bsD2QaYw6X12jxNTrbOKC4l+U8YJKIhIhIB6yOK6uqY0MqY2BCM/KLXKzbl1G5isHh0GEI7PhcRzVRSqlq4LcEZ4wpAh4AvgC2ATONMVtE5B4RuccuNh/Yg9Uh5A3gvuL6IjIdWA4kiUi6iNxlr3pWRH4QkU3AFcDD9vttAWYCW4EFwP3GmEoeRp2/fh2bECCwvLL3w4HVm/L0Xjixq/oDU0qpBkYqNcVLPZOSkmLWrFlT7e2Offk7ggKE2fcOrFzFjAPw7+4w9Cm49MFqj0sppeoiEVlrjEmp7nZ1JBM/GJjQlA0HMsjOL6pcxei20LK7XodTSqlqoAnODwYmNKXIZVidVpnb+GyJw2H/csg9Xf2BKaVUA6IJzg9S2jchyCFVv13AOK2ZvpVSSlWZJjg/CAt20KtdTOVv+AaI7QONmumoJkopdZ40wfnJwISmbD6USWZOYeUqBjig8zBrXEpnJa/hKaWUKqEJzk8GJjTDGFixtyqnKYdDXgYcWFntcSmlVEOhCc5PeraNJjQooGrX4RJ+AgFBeppSKaXOgyY4PwkODKBvfJPKT4AKENoY4i/V2wWUUuo8aILzo4EJzdh5NItjZ/MqXzlxBJzYAaf2VH9gSinVAGiC86OBCdb0OVW7XcCekFyP4pRSqko0wflR99goIkMDq5bgmnSEZkl6HU4ppapIE5wfOQKE/h2bVu1+OLCO4tK+g7wz1RuYUko1AJrg/GxgQlP2n8rhwKmcyldOGgmuQmumb6WUUpWiCc7PBiY0A2D5niocxcVdAqHReh1OKaWqoMIEJyLhIhJgP08UkTEiEuT/0OqHxJYRNA0Prtp1OEcgdB4Ku74AV41PbaeUUhc0X47glgChIhILLALuAKb6M6j6REQYkNCU73efoEpz7yWOgJyTcHBt9QenlFL1mC8JTowxOcB44P+MMeOAbv4Nq34ZmNCMo2fy2XMiu/KVO10J4tDelEopVUk+JTgRGQBMBj6zlwX6L6T6p/h+uCr1pgyLgXYD9DqcUkpVki8J7iHgcWCOMWaLiHQEFvs1qnqmfdNGtIkK5fvUKgzbBZA0Ao5uhoz91RuYUkrVYxUmOGPMt8aYMcaYv9udTU4YYx6sgdjqDes6XDOW7zmJy1XF63CgR3FKKVUJvvSifF9EGotIOLAV2CEiv/Z/aPXLwISmZOQUsu1IFW7abtrJGtlEE5xSSvnMl1OU3YwxZ4BrgflAO+AWfwZVHw3sdB7jUopA4kjYuwQKqtBRRSmlGiBfElyQfd/btcBcY0whUIXzbA1b66gwOjYLP79hu5z5sOebao1LKaXqK18S3H+ANCAcWCIi7QEdHLEKBiQ0ZeWekxQ6XZWv3G4AhDTW2wWUUspHvnQyedEYE2uMGWWsO5X3A1f40riIjBCRHSKSKiKPeVgvIvKivX6TiPR2W/eWiBwTkc1l6vxDRLbb5eeISLS9PF5EckVkg/14zZcYa9LAhGZkFzj54WBm5SsHBlszfe/8AlxVSJBKKdXAVHosSmMpqqiciDiAl4GRWDeG3ygiZW8QHwl0th9TgFfd1k0FRnhoeiHQ3RhzEbAT6xaGYruNMT3txz0+blKN6d+xCVDF63BgDb6cdRQOb6i+oJRSqp7y52DLlwCpxpg9xpgCYAYwtkyZscC7dtJcAUSLSGsAY8wS4FTZRo0xX7ol2BVAnN+2oJo1jQihS6tIvt9dxfvhOg0FRHtTKqWUD/yZ4GKBA26v0+1llS1TnjuBz91edxCR9SLyrYgM9lRBRKaIyBoRWXP8+PFKvFX1GJjQjDVpp8krdFLoKuTAmQMVVyoW3hTaXqLX4ZRSyge+3AfnsGcQeFBEHil++NC2eFhWtvelL2W8xfUEUARMsxcdBtoZY3oBjwDvi0jjcxo35nVjTIoxJqV58+a+vFW1GpjQlPwiF1/v2smdC+7k6jlXs/3Udt8bSBxhnaI8c9hvMSqlVH3gyxHcJ8DtQFMg0u1RkXSgrdvrOOBQFcqcQ0RuA0YDk+2OLxhj8o0xJ+3na4HdQKIPcdaoSzo2ITB8F39Yezc7T+8kKCCImTtm+t5A8agmu/Q0pVJKlceXBBdnjBlvjPmjMebJ4ocP9VYDnUWkg4gEA5OAeWXKzANutXtT9gcyjTHlHpqIyAjgUWCMPctB8fLmdscW7PEyOwN7fIizxjhdTqZt/y9hbd/CFEUwY/QMRnQYwWd7PiO70McbuFt0hah2eh1OKaUq4EuC+1xEhlW2YbsjyAPAF8A2YKY9WPM9IlLcw3E+VhJKBd4A7iuuLyLTgeVAkoiki8hd9qqXsI4gF5a5HWAIsElENgKzgXuMMed0Uqktp/JOcd+i+3hl4yt0CBtMZuq9NA9ty4TECeQU5TB/73zfGhKxBl/evRgKc/0btFJKXcB8mfZmBTDHHmi5EOu6mTHGnHN9qyxjzHysJOa+7DW35wa430vdG70s7+Rl+YfAhxXFVBs2HNvAL7/9JRl5GfxxwB9pwRBuXb+a1WmnuDzxYjrHdGbWjllMSJzgW4OJw2HV67B3KSRW+n8PpZRqEHw5gvsnMABoZIxpbIyJ9CW5KTDG8O6Wd7ljwR0EBwTzv1H/4/rE6+kb35RgRwDLd59ERJiQOIFtp7ax5cQW3xpuPwiCwrU3pVJKlcOXBLcL2FzcmUP55mzBWR755hH+seYfDIkbwgfXfEDXpl0BCAt20KtddMn9cKM7jiYsMIxZO2f51nhQKCRcYV2H049FKaU88iXBHQa+EZHHK3mbQIO1/dR2Jn06icUHFvOrlF/x7yv+TePg0ge9AxOaseXQGTJyCogMjmRE/Ajm751PVkGWb2+SOALOpFsToSqllDqHLwluL7AICKZytwk0SHN2zeHm+TeTV5THW8Pf4rbk2xA593a/gZ2aYgys2GP1g5mQOIHcolw+2/OZb2/U2b72pqcplVLKowo7mRTfEiAikdZL4+MhRsOSW5TL0yueZu7uufRr3Y+/D/47TcOaei1/cVw0YUEOlu8+wYjurejerDtdmnRh1s5ZTEya6DEplhLZEmL7WKcph+j8s0opVZYvI5l0F5H1wGZgi4isFZFk/4d24UjLTGPy/MnM2z2Pn130M/5z1X/KTW4AwYEB9O3QpGR+uOLOJjtO7+CHEz/49saJIyB9DWTV/JBjSilV1/lyivJ14BFjTHtjTHvgl1j3rCngi7QvmPTZJI7nHOfVq17lgV4P4Ahw+FR3YEJTdh3L4nCmdT/bqA6jKtfZJHE4YGDXl1WMXiml6i9fEly4MWZx8QtjzDdYk582aIXOQv6+6u/86ttfkRCdwKxrZnFp7KWVamN4cisA5m6wRieLCI5gVIdRLNi7gDMFPswp2+oiiGyj1+GUUsoDXxLcHhH5vT2haLyI/A6r40mD9umeT/nftv9xc9ebmTp8Kq3CW1W6jQ7NwundLpoP16ZTfBfGhKQJ5Dnz+HT3pxU3IGIdxe3+GgrzKv3+SilVn/mS4O4EmgMf2Y9mwB3+DOpCMLbTWN4e/jaPXvIoQY6gKrczvnccu45lseWQdcSW3DSZbk27MWvnLHy69bDbWCjIgm2fVDkGpZSqj8pNcPbgxbOMMQ8aY3rbj4eMMadrKL46K0ACSGmVct7tXHNRG4IdAcxem16ybELiBFIzUtl4fGPFDXS4DJp0hDVvnXcsSilVn5Sb4IwxTiBHRKJqKJ4GJ6pREFd1a8G8jYcodLoAq7NJeFC4b51NAgKgz+2w/3s4ts2/wSql1AXEl1OUecAPIvKmiLxY/PB3YA3Jdb3jOJVdwDc7rO7+jYIacXWHq/ki7Qsy8zMrbqDnZHAEw9qp/g1UKaUuIL4kuM+A3wNLgLVuD1VNhiQ2p2l4MB+tcztNmTSBfGc+n+z24dpaeDPrWtyG6VCQU3F5pZRqALwmOBFZZD/tZox5p+yjhuJrEIIcAYzp2YZF246RkVMAQJcmXejRrIfvnU1S7oT8TNjykZ+jVUqpC0N5R3CtReQyYIyI9BKR3u6PmgqwobiudxwFThefbPpxQvMJiRPYk7mHdcfWVdxAuwHQLEk7myillK28BPcH4DEgDngea1644sdz/g+tYUlu05iklpGlTlMOjx9ORFCEb51NRKyjuINr4bAPvS+VUqqe85rgjDGzjTEjgWeNMVeUefykBmNsEESE6/rEsn5/BruPW+NZNwpqxOiOo1mYtpCMvIyKG7n4BggMgzVv+zdYpZS6AFTYycQY81RNBKJgbM9YAgTmrDtYsmxC0gQKXAXM3T234gbCYqD7dfDDLMg/68dIlVKq7vOlF6WqIS0bhzKoc3PmrD+Iy2V1LEmMSeTi5hcze+dsHzub3GGNbLJppp+jVUqpuk0TXB1zXe9YDmbksmLvyZJlExInkHYmjTVH11TcQGwfaNXDOk3pS0JUSql6yqcEJyIOEWkjIu2KH/4OrKEa1q0VESGBfOR2mnJ4/HAigyOZtaMSnU2O/mB1OFFKqQbKlwlPfw4cBRZi3fT9GeDDUPeqKsKCHVzdozWf/3CYnIIiAEIDQxmTMIaF+xdyKu9UxY30mADBEXrLgFKqQfPlCO4XQJIxJtkY08N+XOTvwBqy8b1jyS5w8sWWIyXLJiROoMhVxNxUHzqbhERaSW7zh5Db4MfFVko1UL4kuAOADwMinktERojIDhFJFZHHPKwXe2zLVBHZ5H4DuYi8JSLHRGRzmTpNRGShiOyyf8a4rXvcbmuHiAyvSsx1Qd/4JsTFhJU6TZkQnUDvFr2ZvXM2LuOquJGUO6AoDzZ+4MdIlVKq7vJpwlPgGzt5PFL8qKiSPdXOy8BIoBtwo4h0K1NsJNDZfkwBXnVbNxUY4aHpx4BFxpjOwCL7NXbbk4Bku94rdgwXnIAAYXzvOJalnuBwZm7J8usTr2f/2f2sOrKq4kZaXwyxKdZpSu1sopRqgHxJcPuxrr8FA5Fuj4pcAqQaY/YYYwqAGcDYMmXGAu8aywogWkRaAxhjlgCeLjiNBYrHwnwHuNZt+QxjTL4xZi+QasdwQRrfKxZj4OP1h0qWDYsfRlRIlG+dTcDqbHJiB+z73k9RKqVU3eXLjd5PGmOexB6uy+11RWKxTm8WS7eXVbZMWS2NMYft2A4DLSrTlohMEZE1IrLm+PHjFW5EbYlvFk5K+xg+XJdecv9biCOEMQlj+Hr/15zIPVFxI8njICRKO5sopRokX3pRdheR9cBmYIuIrBWRZB/aFg/Lyp4r86WMr3xqyxjzujEmxRiT0rx58yq+Vc0Y3zuO1GNZ/HDwx0ug1ydeT5Ep4uPUjytuILgR9LwRts2DbB8SolJK1SO+nKJ8HXjEGNPeGNMe+CXwhg/10oG2bq/jgENVKFPW0eLTmPbPY+fRVp129UWtCQ4MKNXZpGNUR1JapvDhzg9962zS5w5wFsCGaX6MVCml6h5fEly4MWZx8QtjzDdAuA/1VgOdRaSDiARjdQCZV6bMPOBWuzdlfyCz+PRjOeYBt9nPbwPmui2fJCIhItIBq+OKD70x6q6osCCGdmvJ3A0HKSj6MZlNSJxAelY6Kw6tqLiRFl2g/aXWyCYuHxKiUkrVEz71ohSR34tIvP34HbC3okrGmCLgAeALYBsw0xizRUTuEZF77GLzsXpppmIdFd5XXF9EpgPLgSQRSReRu+xVzwBDRWQXMNR+jTFmCzAT2AosAO43xjh92L467bresZzOKeSbHcdKll3V/ipiQmJ8m0YHrKO403th77d+ilIppeoeqWgAX/s+syeBQVjXuZYAfzLGXPB3EKekpJg1a3wY37EWFTld9P/bIvq0j+E/t6SULP/nmn/y3tb3WHj9Qpo3quBaYlE+PN/VOpK74T0/R6yUUpUjImuNMSkVl6wcX3pRnjbGPGiM6W2M6WWM+UV9SG4XikBHAGN7xvL19mOczi4oWX594vU4jZM5qXN8aCQEek6G7Z/BmYrOACulVP3gNcGJyL/tn5+IyLyyjxqLUDG+dyyFTsOnm37sM9O+cXv6terHhzs/xOny4Uxsn9vBOGH9//wXqFJK1SHlHcEVn8t6Dvinh4eqIcltoujSKpLZbr0pAa5Pup5D2Yf4/pAPN3I3TYCOl8O6d8CXhKiUUhc4rwnOGFM810pPY8y37g+gZ41Ep0pc1zuOjQcySD2WVbLsyrZX0iS0ie+dTVLuhMwDkPqVn6JUSqm6w5delLd5WHZ7NcehKjC2VxsCBD5al16yLMgRxLWdruXb9G85cPZAObVtSaMgoqWObKKUahDKuwZ3o4h8AnQoc/1tMXDSWz3lHy0iQxmS2Jw56w/icv3Y8/XmrjcTFBDEaxtfq7gRRxD0ugV2fQkZPiREpZS6gJV3BPc91rW27ZS+9vZLPI/yr/zsut5xHM7MY8WeH/+/aN6oOZOSJvHpnk/Zm1nh7YnQ5zZrdoF17/oxUqWUqn3lXYPbZ4z5xhgzoMw1uHX2Tdyqhg3t1pLIkEBmu52mBLizx52EOEJ4dcOrXmq6iW4HnYdZCc5Z6KdIlVKq9vky2HJ/EVktIlkiUiAiThE5UxPBqdJCgxxcfVFrFmw+Qnb+j/9jNAltws1db2ZB2gJ2nt5ZcUMpd0LWEdjxuR+jVUqp2uVLJ5OXgBuBXUAYcDfwf/4MSnl3XZ84cgqcLNh8pNTy25JvIzwonFc2vFJxI52HQuM47WyilKrXfElwGGNSAYcxxmmMeRu4wr9hKW9S2sfQrkkjPlpf+jRlVEgUtybfyqL9i9hyckv5jQQ4rGtxexbDqT1+jFYppWqPLwkux54NYIOIPCsiD+PbbALKD0SE8b1j+X73SQ5l5JZad0vXW4gKieLl9S9X3FCvW0AcsHaqfwJVSqla5kuCuwVwYM0MkI0159p1/gxKlW98rziMgTnrS49sEhEcwR3Jd7D04FI2HNtQfiONW0OXUdbQXUX5/gtWKaVqiS+DLe8zxuQaY84YY540xjxin7JUtaRd00b0jY/ho3XplJ0N4sYuN9IktAkvbXip4ob63AE5J2HbJ36KVCmlak95N3rPtH/+ICKbyj5qLkTlyXW949h9PJuN6ZmlljcKasTdPe5m5eGVrD6yuvxGOl4BMfHWZKhKKVXPlHcE9wv752jgGg8PVYtGXdSakMCAUkN3FZuYNJEWYS14af1L5xzhlRIQYB3F7VsGx3f4MVqllKp55d3oXTxx2HigyD5VWfKomfCUN41DgxiW3Ip5Gw9RUOQqtS7EEcKUi6aw7ti6imca6HUzBATpUZxSqt7xpZNJY+BLEVkqIveLSEt/B6V8M753LBk5hXy9/di56zqPp014m4qP4sKbQbcxsPF9yMv0Xk4ppS4wvnQyedIYkwzcD7QBvhURnW+lDhjcqRnNI0M8nqYMcgRxz8X3sPnkZr458E35DQ180Epuy/7llziVUqo2+HSjt+0YcARrJoEW/glHVUagI4Bre7bh6+3HOJyZe876axKuoV1kO17e8DIu4/LQgq1NT7hoEix/BTL2+y9gpZSqQb6MRXmviHwDLAKaAT81xlzk78CUb24dEI8IvLjo3Ds3AgMCubfnvew4vYOF+xaW39CVvwcRWPRnP0WqlFI1y5cjuPbAQ8aYZGPMH40xW/0dlPJd2yaNmNyvPTPXHGDviexz1o+MH0lCVAKvbHgFp8vpvaGoOBhwP/wwC9LXei+nlFIXCF+uwT0GRIjIHQAi0lxEOvg9MuWz+6/oRLAjgOcXnjuTgCPAwX0972NP5h7m751ffkODHobw5vDl76w545RS6gLmyynKPwKPAo/bi4KA//kzKFU5zSNDuHNQPJ9sPMSWQ+f2hLyq/VUkxSTx2sbXKHSVMwdcSCRc8VvY/z1s/9SPESullP/5copyHDAGaxxKjDGHgEhfGheRESKyQ0RSReQxD+tFRF60128Skd4V1RWRD0Rkg/1IE5EN9vJ4Ecl1W/eaLzHWF1OGJBAVFsRzX5x7w3aABPBArwfYf3Y/n+yuYFiuXrdC8y6w8A9QVOCnaJVSyv98SXAFxrqRygCIiE8zCYiIA3gZGAl0A24UkW5lio0EOtuPKcCrFdU1xtxgjOlpjOkJfAh85Nbe7uJ1xph7fImzvogKC+KeyxJYvOM4q9NOnbP+srjL6NGsB69tfI0CZzmJyxEIQ5+yptHR+eKUUhcwXxLcTBH5DxAtIj8FvgLe8KHeJUCqMWaPMaYAmAGMLVNmLPCusayw36O1L3VFRICJwHQfYmkQbh8YT4vIEJ5dsP2cm7tFhAd6PsDh7MN8tOsjLy3YOg+FjpfDt89A7mn/BayUUn7kSyeT54DZWEdLScAfjDG+zOgdCxxwe51uL/OljC91BwNHjTG73JZ1EJH1IvKtiAz2FJSITBGRNSKy5vjx4z5sxoUjLNjBz6/szOq003yz89xtG9BmAL1b9OaNTW+QV5TnvSERGPYXyM2AJc/5L2CllPIjX2f0XmiM+bUx5lfGmApuqCohnprysYwvdW+k9NHbYaCdMaYX8Ajwvog0PqcRY143xqQYY1KaN2/uNfgL1Q0pbWnXpBH/WLADl8vDUVyvBziWe4yZO2aW31CrHtBzMqx6HU7t9WPESinlH+VNl3NWRM54e/jQdjrW5KjF4oBDPpYpt66IBGINAv1B8TJjTL4x5qT9fC2wG0j0Ic56JTgwgIeHdmbr4TN89sPhc9b3bdWXfq378ebmN8kpzCm/sZ/8DgICYdGTfopWKaX8p7zZBCKNMY2BfwOPYZ0ijMO6ZeAvPrS9GugsIh1EJBiYBMwrU2YecKvdm7I/kGnPYlBR3auA7caYkkEY7fvzHPbzjlgdV/b4EGe9M+biWJJaRvL8wp0UOs8douuBng9wKu8U729/v/yGGre2xqncMgcOrPJTtEop5R++nKIcbox5xRhz1p7V+1XguooqGWOKgAeAL4BtwExjzBYRuUdEins4zsdKQqlYHVfuK6+uW/OTOLdzyRBgk4hsxLpmeI8x5tzuhA2AI0D41fAk9p7IZvbacwdi7tmiJ4NjB/P25rc5W3C2/MYG/hwiWsIXT+jN30qpC4qUO5UKICLfY3XZn4F1HexG4H5jzED/h+dfKSkpZs2aNbUdhl8YY7ju1e85lJHHN7++nNAgR6n1W05uYdKnk7jv4vu4t+e95Te27l2Y93OYMBWSx/kvaKVUgyQia40xKdXdri9HcDdhdcc/aj8m2MtUHSYi/Hp4F46cyeO95efOT5vcNJkr213Ju1vfJTO/gnngek6Glt1h4R+hKN9PESulVPXy5TaBNGPMWGNMM2NMc2PMtcaYtBqITZ2nAQlNGdy5Ga98k8rZvHOH6Lqv531kF2YzdcvU8hsKcMCwpyBjH6zy5RZIpZSqfZWZD05dgH4zvAuncwp5Y+m5Xf0TYxIZET+CadumcTL3ZPkNJfwEOl0FS56FnAZ5aVMpdYHRBFfP9YiLYlSPVry5dA8ns849vXhvz3vJd+bz1mYfhuUa9hfIPwvfPuuHSJVSqnppgmsAHhmaSG6hk1e+2X3Oug5RHRjdcTQzts9gb2YFN3S36Aq9b4XVb8DJc9tSSqm6xOcEJyL9ReRrEflORK71Y0yqmnVqEcl1veN4b8U+DmXknrP+od4PERYUxhPLnqDIVVR+Y5f/FgJD4as/+ilapZSqHuWNZNKqzKJHsKbNGQE85c+gVPV7aGgiGHjhq13nrGveqDm/6/87fjjxA2/+8Gb5DUW2hEsfgm2fwL7v/ROsUkpVg/KO4F4Tkd+LSKj9OgPr9oAbAF+G6lJ1SGx0GJP7t2PW2gPsPp51zvoR8SMY2WEkr218ja0nt5bf2ID7IbKNdfO369yRUpRSqi4ob6iua4ENwKcicgvwEOACGgHX+j80Vd3uv6IToUEOnv9yp8f1T/R7giahTXhi2RPkO8u53y24EVz5Bzi0DrZUMPWOUkrVknKvwRljPgGGA9FYE4vuMMa8aIypX/PMNBDNIkK4e1AHPvvhMJsPnntzd1RIFH++9M+kZqTy0vqXym/sohug1UXw1ZNQWM7UO0opVUvKuwY3RkSWAV8Dm7HGfxwnItNFJKGmAlTV6+4hHYluFMSzX+zwuP7S2Eu5IekG3tnyDmuOlDOMWUAADH8aMvfDylf9FK1SSlVdeUdwf8E6ersO+LsxJsMY8wjwB+DpmghOVb/GoUHcd3kCS3YeZ8Uezzd3P9LnEeIi4/jdd78juzDbe2MdhkDiSFj6PGSf8FPESilVNeUluEyso7ZJwLHihcaYXcaYSf4OTPnPrQPiadk4hGcXbMfTYNuNghrx9KCnOZx9mH+s/kf5jQ39MxRkwzfP+ClapZSqmvIS3DisDiVF6ODK9UpokIMHr+zMuv0ZLNp2zGOZXi16cUfyHXy460OWpC/x3ljzREi5A9a8Bcc9d15RSqnaUF4vyhPGmP8zxrxmjNHbAuqZiSltiW/aiOe+3IHL5XnKpPt63kdiTCJ/+O4PnM477b2xyx+H4HBY+HudM04pVWfoUF0NVJAjgIeHJrL9yFk+2XTIY5lgRzB/HfRXMgsyeWrFUx5PZwIQ3gyG/Bp2LoC1b/sxaqWU8p0muAbsmova0LV1Y55fuJNCp+cbtpOaJHF/z/tZuG8h8/fO997YgAcg4Ur4/FE4uM5PESullO80wTVgAQHCr4cnsu9kDh+sPuC13B3Jd9CzeU+eXvk0R7KPeGsMxr8BES1h5m06pY5SqtZpgmvgrkhqQUr7GF5YtIuMnAKPZRwBDp4e9DRFriL+8N0fyjlV2RQmvANnD8Ocn+kwXkqpWqUJroETEf5wTTcycgr41axNXpNXu8bt+FXKr1h+eDkf7PjAe4NxfWDE32DXl7D0n36KWimlKqYJTnFRXDSPj+zKV9uO8uYy73PCTUicwKVtLuX5tc+z78w+7w32vRt6TITFT8PuxX6IWCmlKqYJTgFwx6XxDE9uyTOfb2fdfs+3BIgITw58ksCAwPLnjhOBa/4NzbvAh3dB5kH/Ba6UUl5oglOAlbyevf5iWkeH8sC0dZzO9nw9rmV4S37X73dsPL6RqVumem8wOBxueA+K8mHWbVDkuT2llPIXTXCqRFRYEC/f1JvjWfn8ctZGrzeAj+wwkuHxw3l5w8tsP7Xde4PNOsPYlyB9tXUTuFJK1SC/JjgRGSEiO0QkVUQe87BeRORFe/0mEeldUV0R+ZOIHBSRDfZjlNu6x+3yO0RkuD+3rb66KC6aJ0Z15evtx3hj6R6PZUSE3/X7HdEh0Ty+9HEKnOUcnSWPg/73wcrXYPOHfopaKaXO5bcEJyIO4GVgJNANuFFEupUpNhLobD+mAK/6WPdfxpie9mO+Xacb1sDQycAI4BW7HVVJtw2MZ1SPVjz7xQ7WpHm+ny06NJonBz5pzR23oYK544b+Gdr2g3kPwnHP0/QopVR18+cR3CVAqjFmjzGmAJgBjC1TZizwrrGsAKJFpLWPdcsaC8wwxuQbY/YCqXY7qpJEhGeuu4jY6DB+Pn09p7xcjxsSN4TrE69n6uaprDtazugljiCYMBUCQ+GDWyA/yz+BK6WUG38muFjAfXiMdHuZL2UqqvuAfUrzLRGJqcT7KR81Dg3ilcm9OZlVwCMzN3i9HverlF/RJqINTyx7gpzCnHIabAPXvwknd8Env9BBmZVSfufPBCcelpX9q+atTHl1XwUSgJ7AYaD4bmJf3g8RmSIia0RkzfHjxz1UUcW6x0bx+9Fd+WbHcV5bsttjmfCgcJ4e9DQHsw7y7Opny2+w4+VwxROweTas/m/1B6yUUm78meDSgbZur+OAssPWeyvjta4x5qgxxmmMcQFv8ONpSF/eD2PM68aYFGNMSvPmzSu9UQ3Nzf3bc/VFrfnnlztZtdfz9bg+LftwR3dr7ri3N1cwm8CgRyBxBCx4HA6s9kPESill8WeCWw10FpEOIhKM1QFkXpky84Bb7d6U/YFMY8zh8ura1+iKjQM2u7U1SURCRKQDVseVVf7auIZCRHhmfA/axoTx8+nrOJmV77Hcg70eZET8CJ5f+zyzd8723mBAAIx7DRq3hlm3Q/ZJ/wSulGrw/JbgjDFFwAPAF8A2YKYxZouI3CMi99jF5gN7sDqEvAHcV15du86zIvKDiGwCrgAetutsAWYCW4EFwP3GGKe/tq8hiQwN4uXJvTmdU8jDMz3fH+cIcPDXQX9lcOxg/rz8z3y+93PvDYbFwMT3IPs4fHQ3uPRjUkpVP/E6MnwDkJKSYtasWVPbYVwwpq3cxxNzNvPr4Uncf0Unj2Vyi3K596t72XhsIy/85AWGxA3x3uDaqVaHk8segyse90/QSqk6T0TWGmNSqrtdHclE+eymS9ox5uI2/PPLHazY4/nUYlhgGC/95CUSmyTyyDePsPpIOdfZet8GPSfDt3+HXV/5KWqlVEOlCU75TET46/gexDcN58Hp6zl+1vP1uIjgCF676jViI2L5+dc/Z8uJLR7LIQKjnoOWydapyoz9foxeKdXQaIJTlRIREsjLk3uTmVvIwx9swOnl/riY0BheH/o60SHR/Oyrn5F6OtVzg8GNYOK71nW4mbdZgzMrpVQ10ASnKq1r68Y8OSaZZakneHmxl8SFNfPAG0PfIDggmCkLp3Dg7AHPBZsmwLWvwKF18Plv9CZwpVS10ASnquSGvm25tmcb/v3VTr7ffcJrubaN2/Kfof+hwFXAlC+ncCznmOeCXa+BQQ9bHU8+ewRcLv8ErpRqMDTBqSoREZ4e14MOzcJ5cPoGjp3N81q2c0xnXr3yVU7lneJnC39GRl6G54JX/hEufQjWvAVzpoCz0C+xK6UaBk1wqsrCQwJ5ZXIfsvILeWiG9+txAD2a9+ClK19i/5n93PPVPWQVeBhwWQSGPmkluh9mWQMzF+b6cQuUUvWZJjh1XpJaRfLnMd35fvdJXli0q9yyfVv15fnLn2fHqR38/Oufk1fk5ahv8CNw9T9h5wKYNgHyz/ohcqVUfacJTp23CSlxXNc7jhcX7eJ1L4MyF7us7WU8Pehp1h5dy6++/RWFLi+nIfveDePfgH3fwztjIMfzOJhKKeWNJjh13kSEv43vweiLWvPX+dt5dsF2yhshZ1THUfyu/+/4Nv1bnlj6BE5vQ3VdNAEmTYOjW+DtkXDmnLGzlVLKK01wqloEBwbwwqRe3NSvHa98s5snPt5c7jW5iUkTebjPw3ye9jlPr3zae0JMGgk3fwiZ6fDWCDi1109boJSqbzTBqWrjCBCevrY7916ewPsr9/OLGespKPLe3f/O7ndyd4+7mbVzFv9a9y/vSa7DYLhtHuSfsZLc0a1+2gKlVH2iCU5VKxHh0RFdeHxkFz7ddJgp760ht8D7bAEP9nqQG5Ju4O3Nb/Pm5je9NxzbB+6wZyh4eySkr63myJVS9Y0mOOUXP7ssgWfG92DJzuPc8uZKMnM9dyYREX7b77eM7jiaF9a9wLRt07w32qIr3LkAwqLh3TGwd4l/gldK1Qua4JTfTLqkHS/d1JuN6RlMen2F18GZAySAP1/6Z65oewXPrHqGv6z4CwXOAs+NNukAd34BUW3hf9fD9vl+3AKl1IVME5zyq1E9WvPmbX1JO5HNhNe+58CpHI/lggKC+Ofl/+T25Nv5YMcH3L7gdg5nHfbcaGQruGM+tOoOH9wMGz/w4xYopS5UmuCU3w1JbM7/7u7HqewCJry2nF1HPd+4HRQQxC9Tfsm/Lv8XezL3MPHTiXx38DvPjTZqArfOhfYDrWG9Vr3hxy1QSl2INMGpGtGnfQwf/GwATmOY8J/lbDyQ4bXsVe2vYsbVM2jeqDn3fnUvr258FZfx0BszJBImz4akUTD/V7DkOZ2JQClVQhOcqjFdWzdm9j0DiAwN5KY3VpQ7C0F8VDzTRk1jdMfRvLLhFe5bdJ/nQZqDQq355HpMhK+fgoV/0CSnlAI0waka1r5pOLPvGUhsTBi3v72aL7Yc8Vo2LDCMpwc9ze/7/55Vh1cx8dOJbD6x+dyCjiAY9x/o+1P4/kWYez8UZPtxK5RSFwJNcKrGtWwcygdTBtC1dWPu/d9aZq9N91pWRJiYNJH3Rr6HINz6+a3M3DHz3JvCAwJg1D/gskdhw/vw6qWwb7mft0QpVZdpglO1IiY8mPfv7seAhKb8atZG3lpW/hBcyc2S+WD0B1zS+hKeWvEUv132W3IKy/TIFIErfgu3fwbGZd0Q/sUTOuWOUg2UJjhVa8JDAnnr9r6MSG7Fnz/dyvNf7ih3kObo0GheufIV7u95P5/t+YzJ8yeTlpl2bsH4S+He7yHlTlj+Erw2GNLX+G9DlFJ1kiY4VatCAh28dFMvJvSJ48WvU3ni483kFXof2itAArjn4nt47arXOJF7gkmfTeKrfV95aDgCRj8Pt3xsHcG9ORS++hMUeb7ZXClV/2iCU7Uu0BHAs9dfxM8u68j7K/cz8oWlrNxzstw6A2MHMnP0TDpGdeThbx7mudXPeZ5bLuEKuO976HkTLPsX/OcyOLTeT1uilKpL/JrgRGSEiOwQkVQReczDehGRF+31m0Skd0V1ReQfIrLdLj9HRKLt5fEikisiG+zHa/7cNlW9RITHR3Zl2t39KHK5uOH1Ffz+481k5Rd5rdM6ojVTR0xlUtIk3tn6Dnd/cTfHco6dWzA0Csa+DDfNgrwMeONKWPxXKPIyHJhSql6Q8q55nFfDIg5gJzAUSAdWAzcaY7a6lRkF/BwYBfQDXjDG9CuvrogMA742xhSJyN8BjDGPikg88KkxpruvMaakpJg1a/TaTF2TU1DEc1/s5O3v99K6cSh/Hd+Dy5NalFvnsz2f8eTyJ2kU2Ii/D/k7/Vr381ww9zR8/ihs+gBa9bBuL2iZ7IetUEr5SkTWGmNSqrtdfx7BXQKkGmP2GGMKgBnA2DJlxgLvGssKIFpEWpdX1xjzpTGm+N/6FUCcH7dB1YJGwYH84ZpuzL5nII1CArn97dU8MnMDGTnej7iu7ng17496n8jgSO7+8m5++c0vOXDmwLkFw2Jg/OtwwzQ4e8Q6ZbnkOXB6P1JUSl2Y/JngYgH3vzDp9jJfyvhSF+BO4HO31x1EZL2IfCsigz0FJSJTRGSNiKw5fvy4b1uiakWf9jF89uAgfv6TTszbcIirnv+W+T94GYAZ6BTTiQ9Gf8B9F9/H0oNLGTN3DM+ufpbM/MxzC3cdDfethC5XWyOgvDUMju/w49YopWqaPxOceFhW9nyotzIV1hWRJ4AioHgCscNAO2NML+AR4H0RaXxOI8a8boxJMcakNG/evIJNULUtJNDBL4clMfeBS2kVFcp909Zxz3trOXYmz2P5RkGNuLfnvXw67lPGJIzhf1v/x6iPRvHulncpdJbphBLeFCa+A9e/Daf2WrcTfPciuLz34lRKXTj8meDSgbZur+OAQz6WKbeuiNwGjAYmG/siojEm3xhz0n6+FtgNJFbLlqhal9wmio/vu5RHR3Th6x3HuOr5b5m15oDX++ZaNGrBkwOfZNY1s0humsw/1vyDsXPH8mXal+fW6T4e7lsBna6Chb+Ht0fBidQa2CqllD/5M8GtBjqLSAcRCQYmAfPKlJkH3Gr3puwPZBpjDpdXV0RGAI8CY4wxJUNZiEhzu3MKItIR6Azs8eP2qRoW6Ajg3ssT+PwXg0lqFcmvZ2/itrdXk37a8xxzAElNknh92Ou8etWrhDhC+OW3v+TWz29l4/GNpQtGtoRJ06xOJ8e2wcuXwMf3wcndft4qpZS/+K0XJZT0kvw34ADeMsY8LSL3ABhjXhMRAV4CRgA5wB3GmDXe6trLU4EQoPhGqRXGmHtE5Drgz1inLZ3AH40xn5QXn/aivHC5XIb/rdzHM59vB+DREV24pX97AgI8nd22FLmKmJs6l5c2vMSJ3BOMiB/BL3r/grjIMv2Uzh6BZf+GtW+DswCSx8OQX0GLrn7cIqUaLn/1ovRrgqvrNMFd+NJP5/DbOZtZsvM4feNjeOa6i0hoHlFunZzCHN7e8jZTN0/FaZxM7jqZu3vcTVRIVOmCWcfg+/+D1W9CYTZ0vQaG/BpaX+zHLVKq4dEE5wea4OoHYwwfrjvIU59uJbfQyf2Xd+L2gfFENQoqt97R7KO8tOEl5qbOpXFIY+69+F4mJk4kyFGmXs4pWPEKrPwP5J+BxBFWoour9t9HpRokTXB+oAmufjl2No8/zdvC/B+OEB7s4Ia+7bhzUDxxMY3Krbf91HaeW/McKw+vpF1kOx7p8wg/afcTrDPobnIzYNUbsOJl64bxjlfAZb+B9gP9t1FKNQCa4PxAE1z9tOVQJv9dupdPNh7CAFf3aM2UIR3pHhvltY4xhqUHl/L8mufZnbmb7k27MzFpIiM6jCAsMKx04fyz1mnL5S9B9nFof6l1RNfxcmvKHqVUpWiC8wNNcPXboYxc3lq2l+mr9pNd4OTSTk2ZMiSBIZ2bnXt0ZityFTEndQ7vbX2PvZl7iQyKZHTCaK5PvJ7EmDJ3nRTkwLp34LsX4OxhiOtrJbrOwzTRKVUJmuD8QBNcw5CZW8j0Vft5+7u9HD2TT5dWkfx0cEeuubgNwYGe75QxxrD26Fpm75rNwrSFFLgKuKj5RUxInMDw+OGlj+qK8mH9/6yel5n7rU4oQ34NSVdbM40rpcqlCc4PNME1LAVFLuZtPMQbS/aw4+hZWjUO5Y5L47mxXzsah3rvkJKRl8G83fOYvWt2+Ud1zkJrEOel/4RTe6BJR+gxwXo061wDW6jUhUkTnB9ogmuYjDF8s/M4byzZw/e7TxIREshN/dpxx6XxtI4KK7de2aO6i5tfzPWJ15c+qnMWwZY5sP492LsEMNZRXY8J1j11UZ6GVVWq4dIE5wea4NQP6Zm8vnQP8384jABjLm7DT4d0pGvrc4YxLaX4qG7WzlmknUkrOaqbkDiBzjFuR2tnDlvJ7odZcGgdIFanlB7XQ7ex0KiJX7dPqQuBJjg/0ASnih04lcNb3+3lg9UHyClw0q9DE0b1aM2w5JY+HdXN2jmLhfsWUugq9HxUB9awXz/MtpLdyV0QEGSNf9njekgaCcHhNbClStU9muD8QBOcKiszp5D/rdzHnPUHST2WBcDFbaMZkdyK4ckt6VjOKCmn805b1+p2zibtTBohjhD6turL4NjBDI4dTNvG9vjhxsDhjVai2/wRnD0EQeHQZZR1GjPhJ1D2ZnOl6jFNcH6gCU6VJ/XYWb7YcpQvthxhU7o1p1xiywhGJLdiWHIrkts09ni7QfFR3aL9i1h6cCn7zuwDIL5xPINiBzE4djB9WvUhxBECLhfs/95Kdls+hrwMCGsCyddC9+uh3QDtianqPU1wfqAJTvkq/XQOX9rJbnXaKVwG4mLCGJHcihHdW9G7XYzXgZ73n9nP0oNLWXpwKWuOrCHfmU9YYBiXtLqEwbGDGRQ3iNiIWCgqgN2LrGS3fT4U5UKjphA/COIHQ4ch0CxR77FT9Y4mOD/QBKeq4mRWPl9tO8qCzUf4LvUkBU4XzSJCGJbckuHJrRjQsanX++tyi3JZfWQ1S9OthHcw6yAAHaM6liS7Pi36EFSUDzs+h9SvIG0pnLHKEd7CSngdBkP8EGiaoAlPXfA0wfmBJjh1vs7mFbJ4x3G+2HyExTuOkVPgJDI0kKu6tuTypOb0aR9DbHSY11OZaWfSWHZwGUvTl7Lm6BoKXYU0CmxE/9b9GRQ3iP6t+hMXEYuc3gtpy6xkt3cpZB2xGolsbR/dDbYSX0wHTXjqgqMJzg80wanqlFfoZNmuEyzYcoSvth0lI6cQgBaRIfRuF0Pv9tH0bhdD99goQoMc59TPKcxh1ZFVJUd3h7MPA9A4uDHJTZPp3qw7yc2S6d40mZa5Z39MdmlLrTExARrH2cnOTnrR7Wps+5WqKk1wfqAJTvlLkdPF9iNnWbf/NOv2nWbd/gz2n7JmHg9yCMltokolvTbRpW9FMMawJ3MP64+tZ/OJzWw5uYVdp3fhNE4Amoc1J7lZspX4mibTnVCiD22wkl3aMsix5wOObg9tL4GW3a1Hq+4Q0VKP8lSdognODzTBqZp0/Gy+lfD2n2b9vgw2pmeQX+QCoHVUKL3bxdCrXTS928eQ3KYxIYGlj/LyivLYfmo7W05uYcuJLWw+uZm0zDQM1u9wbEQs3Zt1p3uTZJId4XTLOEr4/hVwaAOcSf+xoUbNoGUytOphJ75kaJ4EgSE1tSuUKkUTnB9oglO1qaDIxbbDZ+ykl8G6fac5mJELQHBgAN3bNKZHbBSdWkSQ0DyChBYRtIgMKXU9L6sgi60nt7L55GbrSO/EFg5lHwJAEDpEdSApJon2jVrS3iW0zzlL+4zDND6+HY5tg6I8q6GAQGiWZCe+7j8e8UW2rPH9ohoeTXB+oAlO1TVHz+TZpzStpLf98BmyC5wl6yNCAkloHl6S8Iqft28aXtJz81TeqZIjvC0ntrA7YzeHsg/hMq6SdpqENqF9ZDvahzShvRHic3Non3mEtsdSCS3usQkQ3txKdM0SISYeYtpbP6PbQ4j3m96VqgxNcH6gCU7VdcYYjp7JZ/fxLOtxLIvdx7PZczyLQ5l5JeUcAUK7Jo1+TH7NI0hoYT2PbhRMgbOA9LPppJ1JY9+ZfaUex3OPl7QjCK0btaRdcDTtCSQ+P5f2mUeJPX2QlrlnCHf/e9GoWemkV5z4YuKhcSw4AmtqN6kLnCY4P9AEpy5k2flF7D2RXSrx7T6exZ4T2RQU/Xi0FhkaSJuoMFpFhdI6KtTtZxito0KJbOTkVP5B9p/d/2MCzLSS39nCs6XeM9wRSougCFpIEC2dhpYFebTIyaTl2RO0KCqgpdNJE6eLgIBAiIo7N+lFtrQ6uUS0hLAY7eyiAE1wfqEJTtVHTpfh4Olcdh/PIvVYFgczcjmcmcuRzDwOZ+ZxPCufsr/24cEOO/H9mAhbNg4hMjwPZ8Bx8uUk2UWnOJF3jGM5xziac5Sj2Uc5kXuipGdnsUACaO4IpYURWhQV0jI3m5Z5WTR1OYlyuohxuoh2OYk2DiLCmyPFCS+ihfXTPQkWLwvyPuC1uvBpgvMDTXCqISp0ujh2Np8jmbkczswrSXzWTysRHj2bj9N17t+GyJBAYsKDiWkUZP0MCyQ0LJfgkDMQmIkzIJMCc5oc10nOFJ7gVP4JjuccI6cox2MsgQhRBBDjMkQVFRFTmGclQZeTaKeLaJeLGKeTKEcjYkKbEBkWQ0RoE4LCYqwjwLBo62dodJnn9jodtPqC4K8EpyfJlWpgghwBxEaHERvt/aioyOniRFZBScI7kV3A6ewCTudYP0/lFHIqu4DUY1lk5BSSle8CIu1HXKm2IkICiY5w0igsl5DgPIKDc3EE5RDgyMEEZOMKyKaILE6YLNJdZ8gtyiC76CxOXGWiKgCOQtFRgs9ARIaLcJeTCJch3OUiwuUi3Bjrp8tlLQ8IIsIRRnhwOJHBjQkPjiQsuDFhIZGEBkcSGhJFSEgUAaGR1nRFwfbPkIjSr4PC9HTqBcivCU5ERgAvAA7gv8aYZ8qsF3v9KCAHuN0Ys668uiLSBPgAiAfSgInGmNP2useBuwAn8KAx5gt/bp9S9VWgI4BW9vU6X+QXOcnIKeR0TgGnsgs4nV1YkgxP28vP5hVyNq+IrDNFZOUXkZ1fxNm8opJ7AUszEJCPOLIRRw7iyCE0JJfg4AIcgfkEBhZQ6MjnTEAu2UHZiGRjyMVJHoUUkE8BTnFvN9d6FB6FQiC79LuFuVyEGmM9XNbPMOMi1GUIK14ugYQFBBEaEERw8cMRREhAMEGOEIIDQwh2hBASGEqQI5TgoDCCA8MIDgq3ngdFEBzUiOCQCIKDIgkKaoQjMAQJDLWONB3B1r2IjiBwhFivtaPOefHb3hMRB/AyMBRIB1aLyDxjzFa3YiOBzvajH/Aq0K+Cuo8Bi4wxz4jIY/brR0WkGzAJSAbaAF+JSKIxZS4QKKWqXUigg5aNHbRs7FtCdFdQ5CI730p6pR55pX+ezSsit9BJfqGTXPuRV+gkN89VsqygwFqWV+iiwFWABORZiTIgD3EUPy9ApBACCggMyCNIcnEG5JEfkEdRQB65UoAEFIAUQkAhOIpwBTgpEidFAS4KxYlLnIDdi9VlPwqrtu8CjSHIGAINBGEIdHvuMNYf6UCEQCMEIjgQAiXA+kkAARJAAIKDABxiPQIIwCEOAsT6aT0CcAQElrwOCAjEEWA9FwkgQBw4AhylfgYEBJa8doiDAEcgAQEOHBKII8B+HhDIRUljiWkaX7Ud4Ef+/PfgEiDVGLMHQERmAGMB9wQ3FnjXWBcCV4hItIi0xjo681Z3LHC5Xf8d4BvgUXv5DGNMPrBXRFLtGJZ7C/DkyZNs2LCBnj174nQ6ee+99+jduzcXXXQRhYWFTJs2jZSUFLp3705eXh4zZsygX79+dO3alZycHGbOnMmAAQNISkoiKyuL2bNnM2jQIDp16kRmZiZz5sxhyJAhdOzYkdOnTzN37lwuv/xy4uPjOXHiBJ9++ilXXnklbdu25dixY8yfP5+hQ4cSGxvLkSNHWLBgASNGjKBVq1YcPHiQhQsXMmrUKFq0aMGBAwdYtGgRo0ePplmzZqSlpfHNN98wduxYYmJi2LNnD0uWLGHcuHFERUWRmprKsmXLuP7664mIiGDHjh0sX76ciRMn0qhRI7Zt28bKlSuZNGkSoaGhbN68mTVr1jB58mSCgoLYtGkT69at45ZbbsHhcLBhwwY2bNjA7bffDsDatWvZsmULt956KwCrV69m586dTJ48GYAVK1awd+9ebrzxRgC+//570tPTmThxIgDLli3jyJEjXH/99QB8++23nDx5kvHjxwOwePFizpw5w9ixYwH46quvyM3N5ZprrgHgyy+/pLCwkKuvvhqABQsWADBixAgAPvvsM4KCghg2bBgAn3zyCWFhYVx11VUAzJ07l8aNG3PFFVcA8NFHH9G0aVMuu+wyAGbPnk2rVq0YNGgQADNnziQuLo6BAwcCMH36dDp06ED//v0BmDZtGomJifTt2xeAd999l+TkZPr06QPA1KlT6dmzp373GjVi964dJd+9tk0as3nzZrZ4+O49WOq79wO331H+d2/SjTeRV+hkxcoV7E9LY/CIG8ktcLFt42pOHj1M10uHU+g07NuyjqyM47TpeQX5Thcndm0gPyuDRokDKShykbt/E87cbAri+lBQ5CLw8GZMUT4nmiZRaAqJPrkT4ypif+PWFLoKaHvmMC5c7AoLQ0wOnXOyMRSxNyQHIZ9OuaEUSSEHQo4hUkhCbhsKAvI4FJaOiJMOOQnkBWRzpNFejLiIO5tMTtAZDofvxuCiU2ZvzgSfIi1iFwZD15N9ORFyjPTIVFwYLjo2iGNhh9gXuRsXcMmRIaSHH2BP5F6MS7js8GWkRaSxL3InYoQhR4awN3Iv+yP243A5GHR0ELsb7yY9PJ1AVyCXHr2UXY13cSj8EMHOYAYcG8DOqJ0cbnSYkKIQ+h/vz56DH3HHhEeq/N3zF38muFjggNvrdKyjtIrKxFZQt6Ux5jCAMeawiLRwa2uFh7ZKEZEpwBSA2NhzViul6glHgBAeEkh4cCChQQ46tYgE4Oz+RpAdwuVJ1p+OZaciOSLZXN/XmnH92/w0Tp50Mv7KzgAsXnyIM2eCGTu2BwBffXXc/ufqUgC+/LLgvP65+vjjj4ls3JhBQy7D5YJP5n1MdEwTUvpfitNl+OLTj2nSrAU9+vTD6TJ8/flcmrVoTeeL+uAyhu++mEez1nF06NYTl4GVCz9mSGwH4hJ7YIxhzVdzubTdDbRK6IrT5WTT1/NIaX8t0W07UFBYSNrZr+kRO4KIVq1wFuZx+MxaujYfTFizaFwF+RzP2EnnJr0JiQnHmZ9P5ulDdIxIIigqiKKCQrJPZ5LQtq/fP8+q8FsvShGZAAw3xtxtv74FuMQY83O3Mp8BfzPGLLNfLwJ+A3T0VldEMowx0W5tnDbGxIjIy8ByY8z/7OVvAvONMR96i1F7USqlVO3zVy9Kz7MyVo90oK3b6zjgkI9lyqt71D6Nif3zWCXeTymlVAPhzwS3GugsIh1EJBirA8i8MmXmAbeKpT+QaZ9+LK/uPOA2+/ltwFy35ZNEJEREOmB1XFnlr41TSilVt/ntGpwxpkhEHgC+wOrq/5YxZouI3GOvfw2Yj3WLQCrWbQJ3lFfXbvoZYKaI3AXsBybYdbaIyEysjihFwP3ag1IppRouHclEr8EppVStuhCvwSmllFK1RhOcUkqpekkTnFJKqXpJE5xSSql6SROcUkqpekkTnFJKqXpJE5xSSql6qUHfBycix4F959FEM+BENYXjbxdKrBdKnHDhxKpxVr8LJdYLJc72xpjm1d1og05w50tE1vjj5kR/uFBivVDihAsnVo2z+l0osV4ocfqLnqJUSilVL2mCU0opVS9pgjs/r9d2AJVwocR6ocQJF06sGmf1u1BivVDi9Au9BqeUUqpe0iM4pZRS9ZImOKWUUvWSJjgfiMgIEdkhIqki8piH9SIiL9rrN4lI71qKs62ILBaRbSKyRUR+4aHM5SKSKSIb7McfainWNBH5wY7hnEn56sI+FZEkt/20QUTOiMhDZcrU2v4UkbdE5JiIbHZb1kREForILvtnjJe65X6nayDOf4jIdvuznSMi0V7qlvs9qaFY/yQiB90+41Fe6tb2Pv3ALcY0EdngpW6N7tNaZYzRRzkPrBnFdwMdgWBgI9CtTJlRwOeAAP2BlbUUa2ugt/08EtjpIdbLgU/rwH5NA5qVs75O7NMy34MjWDek1on9CQwBegOb3ZY9CzxmP38M+LuXbSn3O10DcQ4DAu3nf/cUpy/fkxqK9U/Ar3z4ftTqPi2z/p/AH+rCPq3Nhx7BVewSINUYs8cYUwDMAMaWKTMWeNdYVgDRItK6pgM1xhw2xqyzn58FtgGxNR1HNakT+9TNlcBuY8z5jHxTrYwxS4BTZRaPBd6xn78DXOuhqi/fab/GaYz50hhTZL9cAcT56/0rw8s+9UWt79NiIiLARGC6v97/QqEJrmKxwAG31+mcmzR8KVOjRCQe6AWs9LB6gIhsFJHPRSS5ZiMrYYAvRWStiEzxsL6u7dNJeP+DURf2Z7GWxpjDYP3DA7TwUKau7ds7sY7WPanoe1JTHrBPp77l5bRvXdqng4GjxphdXtbXlX3qd5rgKiYelpW9t8KXMjVGRCKAD4GHjDFnyqxeh3Wa7WLg/4CPazi8YpcaY3oDI4H7RWRImfV1Zp+KSDAwBpjlYXVd2Z+VUZf27RNAETDNS5GKvic14VUgAegJHMY6/VdWndmnwI2Uf/RWF/ZpjdAEV7F0oK3b6zjgUBXK1AgRCcJKbtOMMR+VXW+MOWOMybKfzweCRKRZDYeJMeaQ/fMYMAfrFI+7OrNPsf4QrDPGHC27oq7sTzdHi0/l2j+PeShTJ/atiNwGjAYmG/viUFk+fE/8zhhz1BjjNMa4gDe8xFBX9mkgMB74wFuZurBPa4omuIqtBjqLSAf7P/lJwLwyZeYBt9o9//oDmcWniWqSfe79TWCbMeZ5L2Va2eUQkUuwvgMnay5KEJFwEYksfo7V4WBzmWJ1Yp/avP5HXBf2ZxnzgNvs57cBcz2U8eU77VciMgJ4FBhjjMnxUsaX74nflbn2O85LDLW+T21XAduNMemeVtaVfVpjaruXy4XwwOrRtxOrl9QT9rJ7gHvs5wK8bK//AUippTgHYZ0W2QRssB+jysT6ALAFq5fXCmBgLcTZ0X7/jXYsdXmfNsJKWFFuy+rE/sRKuoeBQqwjiLuApsAiYJf9s4ldtg0wv7zvdA3HmYp1zar4e/pa2Ti9fU9qIdb37O/gJqyk1bou7lN7+dTi76Zb2Vrdp7X50KG6lFJK1Ut6ilIppVS9pAlOKaVUvaQJTimlVL2kCU4ppVS9pAlOKaVUvaQJTimlVL2kCU4ppVS9pAlOqRpmj86yTERGui2bKCIL/PBeYSLyrYg47NdxInKD/TxYRJbYwzspVe9oglOqhhlrdIV7gOdFJNQeMulp4P7zaddOnGV/p+8EPjLGOO3XV2LNI4axpnVZBNxwPu+rVF2lI5koVUtE5FkgGwgHzhpjnrKX3ww8iDVx5krgPmOMU0Q+xhrQNxR4wRjzuj0t0ufAYmAAcK1xm7NORL4HbjLGpInIIKyxKTOAs1jjKjYG/maM8ThLtVIXMk1wStUS+8htHVCANdZmvoh0xZqVe7wxplBEXgFWGGPeFZEmxphTIhKGNbjvZVgzt+/BGgNzRZn2g4H9xphWbssWYM1Ovdl+7QCOGGOa+3+LlapZeu5dqVpijMkWkQ+ALGNMvr34SqAPsNqepCCMH6e8eVBExtnP2wKdgSPAvrLJzdYM62jNXRKwwy0Gp4gUiEiksWaBV6re0ASnVO1y2Y9iArxjjHncvZCIXI41FcoAY0yOiHyDdaoSrNOcnuS6lUFEmmJNO1RYplwIkFfF+JWqs7STiVJ1yyLgehFpASAiTUSkPRAFnLaTWxegf0UNGWNOAw4RKU5yHSgzCaed9I57SHpKXfA0wSlVhxhjtgK/A74UkU3AQqA1sAAItJc9hTX3nC++xJonEGA70ExENovIQHvZFcD86opfqbpEO5koVY+JSC/gEWPMLV7WfwQ8bozZ4Wm9UhcyPYJTqh4zxqwHFhff6O3O7mX5sSY3VV/pEZxSSql6SY/glFJK1Uua4JRSStVLmuCUUkrVS5rglFJK1Uua4JRSStVLmuCUUkrVS/8PclS+33llDzoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "irf_long = {}\n",
    "for mod in ['ha', 'ra', 'long']:\n",
    "    hh_name = 'household_ra' if mod == 'ra' else 'household'\n",
    "    irf_long[mod] = models[mod].solve_impulse_linear(ss[mod], ['Y'], ['asset_mkt'], {'r_ante': dr})\n",
    "\n",
    "\n",
    "fig = plt.subplots(1, 1, figsize=(6, 5))\n",
    "plt.plot(irf_long['ra']['Y'][:20], label='RA')\n",
    "plt.plot(irf_long['ha']['Y'][:20], label='HA (short)')\n",
    "plt.plot(irf_long['long']['Y'][:20], label='HA (long, $\\delta=0.95$)')\n",
    "plt.axhline(y=0, color='#808080', linestyle=':')\n",
    "plt.title('Impulse response on output to monetary policy with long bonds')\n",
    "plt.xlabel(r\"Year $(t)$\")\n",
    "plt.ylabel('% deviation from ss')\n",
    "plt.legend(framealpha=0)\n",
    "plt.tight_layout()\n",
    "#plt.savefig('Export/FG_RA_HA_incomeinc_lec2.pdf', format='pdf', transparent=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## BONUS: Nominal assets - the \"Fisher\" effect\n",
    "\n",
    "If instead of real assets households held nominal assets then in spite of following a real rate rule, inflation will matter due to a valuation effect on nominal debt due to inflation surprises, which we call the \"Fisher effect\"\n",
    "\n",
    "First, we will build out the nominal side of the model, writing down a block to represent the New Keynesian Phillips Curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "@sj.simple\n",
    "def nkpc(pi, Y, C, theta_w, vphi, frisch, markup_ss, eis, beta):\n",
    "    kappa_w = (1 - theta_w) * (1 - beta * theta_w)/theta_w\n",
    "    piw = pi\n",
    "    piwres = kappa_w * (vphi * (Y)**(1/frisch) - 1/markup_ss * C**(-1/eis)) + beta * piw(1) - piw\n",
    "    return piwres, piw\n",
    "\n",
    "\n",
    "@sj.simple\n",
    "def ex_post_nom_asset_rate(r_ante, pi):\n",
    "    i = r_ante + pi(1)\n",
    "    r = i(-1) - pi\n",
    "    return r\n",
    "\n",
    "calibration_nom_asset = calibration.copy()\n",
    "calibration_nom_asset['pi'] = 0.  # look at the zero-inflation steady state\n",
    "calibration_nom_asset['markup_ss'] = 1.015\n",
    "calibration_nom_asset['theta_w'] = 0.66\n",
    "calibration_nom_asset['frisch'] = 0.5\n",
    "\n",
    "models['nom_assets'] = sj.create_model([household_simple, nkpc, ex_post_nom_asset_rate, \n",
    "                                        mkt_clearing_simple], name=\"HA model with nominal, short-term bonds\")\n",
    "ss['nom_assets'] = models['nom_assets'].solve_steady_state(calibration_nom_asset, {'beta': 0.8, 'vphi': 0.8},\n",
    "                                                           ['asset_mkt', 'piwres'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compute IRF in different models\n",
    "G, irf_Y, irf_r_post = {}, {}, {}\n",
    "theta_list = [1 - 1e-10, 0.8, 0.66]\n",
    "for i, theta_w in enumerate(theta_list):\n",
    "    calibration_theta = calibration_nom_asset.copy()\n",
    "    calibration_theta[\"theta_w\"] = theta_w\n",
    "    ss_nom = models['nom_assets'].solve_steady_state(calibration_theta, {'beta': 0.8, 'vphi': 0.8}, ['asset_mkt', 'piwres'])\n",
    "    irf_here = models['nom_assets'].solve_impulse_linear(ss_nom, ['Y', 'pi'], ['asset_mkt', 'piwres'], {'r_ante': dr})\n",
    "    irf_Y[i], irf_r_post[i] = irf_here[\"Y\"], irf_here[\"r\"]\n",
    "\n",
    "fig = plt.subplots(1, 1, figsize=(6, 5))\n",
    "for i, theta_w in enumerate(theta_list):\n",
    "    plt.plot(irf_Y[i][:20], label='theta = ' + str(theta_w))\n",
    "plt.axhline(y=0, color='#808080', linestyle=':')\n",
    "plt.title('Impulse response of output')\n",
    "plt.xlabel(r\"Year $(t)$\")\n",
    "plt.ylabel('% deviation from ss')\n",
    "plt.legend(framealpha=0)\n",
    "plt.tight_layout()\n",
    "#plt.savefig('Export/FG_RA_HA_incomeinc_lec2.pdf', format='pdf', transparent=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercises"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 1**: obtaining the solution using the GE Jacobian"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Instead of `solve_impulse_linear`, calculate the general equilibrium Jacobian using the `solve_jacobian` routine. Then, calculate the output response to the interest rate shock `dr`, and check that you get the same solution. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "**Exercise 2**: Instead of using a `CombinedBlock` to get the direct effect of monetary policy through `r`, do the same by manually chaining the relevant Jacobians along the DAG using the matrix multiply (`@`) operator. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 3**: Code up the fiscal policy model from class, replicate the result about the ranking of the output effect of monetary policy vs that of the fiscal effect on demand.\n",
    "\n",
    "Take the initial steady state levels of $G = 0.2$ and $B = 0.5$ and set the adjustment coefficients $\\phi_G = \\phi_T = 0.1$.\n",
    "Also, set the shock to the ex-ante interest rate to have an impact effect of 0.1 percentage point and a persistence of $0.7$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 4**: Code up the investment model from class, replicate the result on the complementarity between HA and investment, using a *unit* shock to the ex-ante real interest rate with persistence $0.7$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise 5**: Code up the Taylor rule model from class, replicate the result on the effect of a monetary policy shock (a shock to the Taylor rule) depending on $\\phi$"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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