{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Occasionally binding constraint model - Time Iteration with JAX\n",
    "\n",
    "This notebook solves the Bianchi (2011) model with occasionally binding collateral constraints using JAX"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Setup and Calibration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# %%\n",
    "import os\n",
    "from collections import namedtuple\n",
    "import numpy as np\n",
    "import jax\n",
    "import jax.numpy as jnp\n",
    "from jax import jit, vmap\n",
    "import matplotlib.pyplot as plt\n",
    "from quantecon.markov import tauchen\n",
    "\n",
    "# Set JAX to use 64-bit floats for better precision\n",
    "jax.config.update(\"jax_enable_x64\", True)\n",
    "\n",
    "# ---------------------------------------------------------------------------- #\n",
    "#                                 MODEL SETUP                                  #\n",
    "# ---------------------------------------------------------------------------- #\n",
    "\n",
    "# Define a container for all model parameters and grids\n",
    "Model = namedtuple('Model',\n",
    "    ('σ', 'κ', 'β', 'ω', 'η', 'τ', 'i_l', 'yN',\n",
    "     'l_grid', 'yT_grid', 'Π', 'n_l', 'n_s'))\n",
    "\n",
    "def create_model(\n",
    "        # --- Structural parameters --- #\n",
    "        σ = 2.0,           # Inverse of intertemporal elasticity of consumption\n",
    "        κ = 0.2808,      # Parameter in borrowing constraint\n",
    "        β = 0.91,        # Subjective discount factor\n",
    "        ω = 0.31,        # Weight on traded goods in CES aggregator\n",
    "        η = 0.5,         # Elasticity of substitution between traded/non-traded goods\n",
    "        τ = 0.2,         # Government default cost\n",
    "        i_l = 0.05,      # Interest rate\n",
    "        yN = 1.0,        # Endowment of non-traded goods\n",
    "        # --- Income Process Parameters --- #\n",
    "        yT_size = 5,\n",
    "        ρy = 0.945,\n",
    "        ηy = 0.025,\n",
    "        # --- Grid Parameters --- #\n",
    "        n_l = 400,\n",
    "        l_min = 0.001,\n",
    "        l_max = 0.85 # safe until 0.9\n",
    "    ):\n",
    "    \"\"\"\n",
    "    Creates and returns an instance of the Model namedtuple with all\n",
    "    parameters and discretized grids.\n",
    "    \"\"\"\n",
    "    # Discretize the income process using Tauchen\n",
    "    mc = tauchen(yT_size, ρy, ηy, 0, 1.5)\n",
    "    yT_grid_np = np.exp(mc.state_values)\n",
    "    Π_np = mc.P\n",
    "    n_s = yT_size\n",
    "\n",
    "    # Create the asset grid\n",
    "    l_grid_np = np.linspace(l_min, l_max, n_l)\n",
    "\n",
    "    # Convert to JAX arrays\n",
    "    yT_grid, Π, l_grid = jnp.array(yT_grid_np), jnp.array(Π_np), jnp.array(l_grid_np)\n",
    "\n",
    "    return Model(σ=σ, κ=κ, β=β, ω=ω, η=η, τ=τ, i_l=i_l, yN=yN,\n",
    "                 l_grid=l_grid, yT_grid=yT_grid, Π=Π, n_l=n_l, n_s=n_s)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## JAX Helper Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# ---------------------------------------------------------------------------- #\n",
    "#                         JAX-Optimized Helper Functions                       #\n",
    "# ---------------------------------------------------------------------------- #\n",
    "\n",
    "def dudcT(model, ct):\n",
    "    \"\"\"\n",
    "    Marginal utility of traded consumption, parameterized by the model object.\n",
    "    \"\"\"\n",
    "    ξ, a, σ, yn = model.η, model.ω, model.σ, model.yN\n",
    "    return jnp.where(\n",
    "        ct > 1e-9,\n",
    "        a * ct**(-1/ξ) * (a * ct**((ξ-1)/ξ) + (1-a) * yn**((ξ-1)/ξ))**((1 - σ*ξ)/(ξ-1)),\n",
    "        999_999.0\n",
    "    )\n",
    "\n",
    "# ---------------------------------------------------------------------------- #\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Vectorized Solver (JIT Compiled)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#          Vectorized Solver for the Household's Problem                     #\n",
    "# ---------------------------------------------------------------------------- #\n",
    "\n",
    "def solve_single_state(model, l, yT, pn, e_lambda_col):\n",
    "    \"\"\"\n",
    "    Solves for the optimal next-period asset holding (l') for a single\n",
    "    state (l, yT).\n",
    "    \"\"\"\n",
    "    # Unpack model parameters\n",
    "    κ, τ, i_l, yN, β, l_grid = model.κ, model.τ, model.i_l, model.yN, model.β, model.l_grid\n",
    "\n",
    "    # 1. Calculate borrowing constraint\n",
    "    borr_const = κ * (pn * yN + yT * (1 - τ))\n",
    "\n",
    "    # 2. Grid search over all possible next-period assets (l')\n",
    "    ct_vec = yT * (1 - τ) - l + l_grid / (1 + i_l)\n",
    "    dudcT_vec = vmap(dudcT, in_axes=(None, 0))(model, jnp.maximum(ct_vec, 1e-9))\n",
    "    euler_residual = dudcT_vec / (1 + i_l) - β * e_lambda_col\n",
    "\n",
    "    # 3. Find l' that minimizes the Euler residual\n",
    "    lp_idx = jnp.argmin(jnp.abs(euler_residual))\n",
    "    l_prime_candidate = l_grid[lp_idx]\n",
    "\n",
    "    # 4. Enforce the borrowing constraint\n",
    "    l_prime_optimal = jnp.minimum(l_prime_candidate, borr_const)\n",
    "\n",
    "    # 5. Calculate resulting consumption and multiplier\n",
    "    ct_optimal = yT * (1 - τ) - l + l_prime_optimal / (1 + i_l)\n",
    "    mu_val = dudcT(model, ct_optimal) / (1 + i_l) - β * e_lambda_col[lp_idx]\n",
    "\n",
    "    return l_prime_optimal, ct_optimal, mu_val\n",
    "\n",
    "# Vectorize the solver function to run across the entire state space at once.\n",
    "# First, vmap over all income states 's' for a given asset level 'l'.\n",
    "vmap_over_s = vmap(solve_single_state, in_axes=(None, None, 0, 0, 1))\n",
    "# Now, vmap the function above over all asset levels 'l'.\n",
    "solve_all_states = vmap(vmap_over_s, in_axes=(None, 0, None, 0, None))\n",
    "\n",
    "@jit\n",
    "def time_iteration_step(model, policies):\n",
    "    \"\"\"\n",
    "    Performs one full update of the policy functions. JIT-compiled for performance.\n",
    "    \"\"\"\n",
    "    LP_prev, CT_prev, PN_prev = policies\n",
    "\n",
    "    # 1. Calculate current period marginal utility of consumption\n",
    "    lambda_prev = vmap(vmap(dudcT, in_axes=(None, 0)), in_axes=(None, 0))(model, CT_prev)\n",
    "\n",
    "    # 2. Calculate expected marginal utility for the next period\n",
    "    E_lambda = lambda_prev @ model.Π.T\n",
    "\n",
    "    # 3. Solve for optimal policies for ALL states simultaneously\n",
    "    LP_next, CT_next, MU_next = solve_all_states(\n",
    "        model, model.l_grid, model.yT_grid, PN_prev, E_lambda\n",
    "    )\n",
    "\n",
    "    # 4. Calculate the new price of non-traded goods\n",
    "    PN_next = (1 - model.ω) / model.ω * (CT_next / model.yN)**(1 / model.η)\n",
    "\n",
    "    return LP_next, CT_next, PN_next, MU_next\n",
    "\n",
    "# ---------------------------------------------------------------------------- #\n",
    "#                               Main Solver Loop                               #\n",
    "# ---------------------------------------------------------------------------- #\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Main Solution Loop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def solve_model(tol=1e-5, n_iter=500, updt=0.2):\n",
    "    \"\"\"\n",
    "    Main function to solve the household's problem via time iteration.\n",
    "    \"\"\"\n",
    "    # --- Create model instance --- #\n",
    "    model = create_model()\n",
    "    l_grid, yT_grid = model.l_grid, model.yT_grid\n",
    "    n_l, n_s = model.n_l, model.n_s\n",
    "\n",
    "    # --- Initial Guesses --- #\n",
    "    L = l_grid.reshape(-1, 1)\n",
    "    LP_0 = jnp.tile(l_grid.reshape(-1, 1), (1, n_s))\n",
    "    CT_0 = jnp.tile(yT_grid, (n_l, 1)) * (1 - model.τ) - L + LP_0 / (1 + model.i_l)\n",
    "    PN_0 = (1 - model.ω) / model.ω * (jnp.maximum(CT_0, 1e-9) / model.yN)**(1 / model.η)\n",
    "\n",
    "    print(\"--- Starting JAX Time Iteration ---\")\n",
    "    for iter_num in range(n_iter):\n",
    "        # Perform one full, JIT-compiled update step\n",
    "        LP, CT, PN, MU = time_iteration_step(model, (LP_0, CT_0, PN_0))\n",
    "\n",
    "        # Check for Convergence\n",
    "        dist = jnp.max(jnp.abs(LP - LP_0))\n",
    "        if dist < tol:\n",
    "            print(f\"\\nConverged at iteration {iter_num + 1} with distance: {dist:.2e}\")\n",
    "            return model, LP, PN, MU\n",
    "\n",
    "        if iter_num % 10 == 0:\n",
    "            print(f\"Iter: {iter_num + 1:<4} | Distance: {dist:.4e}\")\n",
    "\n",
    "        # Damped Update for Stability\n",
    "        LP_0 = (1 - updt) * LP_0 + updt * LP\n",
    "        CT_0 = (1 - updt) * CT_0 + updt * CT\n",
    "        PN_0 = (1 - updt) * PN_0 + updt * PN\n",
    "\n",
    "    print(f\"\\nWarning: Did not converge after {n_iter} iterations.\")\n",
    "    return model, LP, PN, MU\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualization and Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<>:24: SyntaxWarning: invalid escape sequence '\\m'\n",
      "<>:26: SyntaxWarning: invalid escape sequence '\\m'\n",
      "<>:24: SyntaxWarning: invalid escape sequence '\\m'\n",
      "<>:26: SyntaxWarning: invalid escape sequence '\\m'\n",
      "/tmp/ipykernel_1174447/4044857485.py:24: SyntaxWarning: invalid escape sequence '\\m'\n",
      "  ax2.set_title(\"Kuhn-Tucker Multiplier: $\\mu(l,s)$\")\n",
      "/tmp/ipykernel_1174447/4044857485.py:26: SyntaxWarning: invalid escape sequence '\\m'\n",
      "  ax2.set_ylabel('Multiplier ($\\mu$)')\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--- Starting JAX Time Iteration ---\n",
      "Iter: 1    | Distance: 3.6673e-01\n",
      "Iter: 11   | Distance: 1.2190e-01\n",
      "Iter: 21   | Distance: 5.0308e-02\n",
      "Iter: 31   | Distance: 2.3541e-02\n",
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      "Iter: 51   | Distance: 9.2060e-03\n",
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      "Iter: 71   | Distance: 5.0798e-03\n",
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      "Iter: 831  | Distance: 1.0672e-06\n",
      "\n",
      "Converged at iteration 838 with distance: 9.98e-07\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if __name__ == '__main__':\n",
    "    # --- Solve the model --- #\n",
    "    model, LP_policy, PN_policy, mu_policy = solve_model(tol=1e-6, n_iter=1000, updt=0.2)\n",
    "\n",
    "    # --- Visualization --- #\n",
    "    # Convert JAX arrays back to NumPy for plotting\n",
    "    l_grid_np = np.array(model.l_grid)\n",
    "    LP_policy_np = np.array(LP_policy)\n",
    "    mu_policy_np = np.array(mu_policy)\n",
    "\n",
    "    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 6), tight_layout=True)\n",
    "    fig.suptitle(\"JAX-Optimized Model Results\", fontsize=16)\n",
    "\n",
    "    ax1.plot(l_grid_np, LP_policy_np)\n",
    "    ax1.plot(l_grid_np, l_grid_np, linestyle='--', color='black', label='45-degree line')\n",
    "    ax1.set_title(\"Policy Function: $l'(l,s)$\")\n",
    "    ax1.set_xlabel('Current Assets ($l$)')\n",
    "    ax1.set_ylabel(\"Next Period's Assets ($l'$)\")\n",
    "    ax1.legend()\n",
    "    ax1.grid(True, linestyle='--', alpha=0.6)\n",
    "\n",
    "    ax2.plot(l_grid_np, mu_policy_np)\n",
    "    ax2.axhline(0, linestyle='--', color='black')\n",
    "    ax2.set_title(\"Kuhn-Tucker Multiplier: $\\mu(l,s)$\")\n",
    "    ax2.set_xlabel('Current Assets ($l$)')\n",
    "    ax2.set_ylabel('Multiplier ($\\mu$)')\n",
    "    ax2.grid(True, linestyle='--', alpha=0.6)\n",
    "\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "# %%\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}