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QuantEcon
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auto publishing updates to notebooks
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BCG_complete_mkts.ipynb

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}
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],
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"metadata": {
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"date": 1618812137.2846944,
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"date": 1619230074.5343747,
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"filename": "BCG_complete_mkts.rst",
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"kernelspec": {
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"display_name": "Python",

BCG_incomplete_mkts.ipynb

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"$ C $’s that appear in the pricing functions, then\n",
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"\n",
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"- consumers’ Euler equations are satisfied if little $ c $’s are\n",
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" equated to Big C’s \n",
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" equated to Big $ C $’s \n",
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"- firms’ first-order necessary conditions for $ k, b $ are\n",
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" satisfied. \n",
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"- $ \\check q = q(K,B) $ and\n",
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" $ \\epsilon^* \\equiv \\log\\left(\\frac{b}{Ak^\\alpha}\\right) $. \n",
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"1. (In this step we abuse notation by freezing $ V, k, b $ and in\n",
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" effect temporarily treating them as Big $ K,B $ values. Thus, in\n",
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" this step 6 little k, b are frozen at guessed at value of K, B.)\n",
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" this step 6 little $ k, b $ are frozen at guessed at value of $ K, B $.)\n",
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" Fixing the values of $ V $, $ b $ and $ k $, compute\n",
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" optimal choices of consumption $ c^i $ with consumers’ FOCs.\n",
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" Assume that only agent 2 holds debt: $ \\xi^2 = b $ and that both agents\n",
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}
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],
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"metadata": {
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"date": 1619230074.8008502,
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"filename": "BCG_incomplete_mkts.rst",
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"kernelspec": {
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"display_name": "Python",

about_lectures.ipynb

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}
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],
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"metadata": {
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"date": 1619230074.956999,
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"filename": "about_lectures.rst",
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"kernelspec": {
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"display_name": "Python",

additive_functionals.ipynb

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}
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"metadata": {
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"date": 1619230075.0592115,
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"filename": "additive_functionals.rst",
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"kernelspec": {
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"display_name": "Python",

amss.ipynb

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"\n",
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"class RecursiveAllocationAMSS:\n",
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"\n",
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" def __init__(self, model, μgrid, tol_diff=1e-4, tol=1e-4):\n",
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" def __init__(self, model, μgrid, tol_diff=1e-7, tol=1e-7):\n",
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"\n",
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" self.β, self.π, self.G = model.β, model.π, model.G\n",
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" self.mc, self.S = MarkovChain(self.π), len(model.π) # Number of states\n",
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"outputs": [],
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"source": [
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"# Initialize μgrid for value function iteration\n",
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"μ_grid = np.linspace(-0.7, 0.01, 200)\n",
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"μ_grid = np.linspace(-0.7, 0.01, 300)\n",
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"\n",
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"time_example = CRRAutility()\n",
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"\n",
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}
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],
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"metadata": {
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"date": 1619230075.2505703,
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"filename": "amss.rst",
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"kernelspec": {
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"display_name": "Python",

amss2.ipynb

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"class RecursiveAllocationAMSS:\n",
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"\n",
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" def __init__(self, model, μgrid, tol_diff=1e-4, tol=1e-4):\n",
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" def __init__(self, model, μgrid, tol_diff=1e-7, tol=1e-7):\n",
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"\n",
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" self.β, self.π, self.G = model.β, model.π, model.G\n",
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" self.mc, self.S = MarkovChain(self.π), len(model.π) # Number of states\n",
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}
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],
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"metadata": {
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"date": 1619230075.4204001,
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"filename": "amss2.rst",
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"display_name": "Python",

amss3.ipynb

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"class RecursiveAllocationAMSS:\n",
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"\n",
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" def __init__(self, model, μgrid, tol_diff=1e-4, tol=1e-4):\n",
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" def __init__(self, model, μgrid, tol_diff=1e-7, tol=1e-7):\n",
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"\n",
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" self.β, self.π, self.G = model.β, model.π, model.G\n",
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" self.mc, self.S = MarkovChain(self.π), len(model.π) # Number of states\n",
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}
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],
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"metadata": {
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"date": 1619230075.6273031,
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"filename": "amss3.rst",
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"kernelspec": {
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"display_name": "Python",

arellano.ipynb

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}
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"metadata": {
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"date": 1619230075.9571571,
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"filename": "arellano.rst",
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"display_name": "Python",

arma.ipynb

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}
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"metadata": {
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"date": 1619230076.177326,
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"filename": "arma.rst",
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"kernelspec": {
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"display_name": "Python",

black_litterman.ipynb

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}
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"metadata": {
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"date": 1619230076.4078171,
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"filename": "black_litterman.rst",
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"kernelspec": {
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"display_name": "Python",

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