diff --git a/examples/ConsIndShockModel/PerfForesightConsumerType.ipynb b/examples/ConsIndShockModel/PerfForesightConsumerType.ipynb index 0223b2733..9b44d2005 100644 --- a/examples/ConsIndShockModel/PerfForesightConsumerType.ipynb +++ b/examples/ConsIndShockModel/PerfForesightConsumerType.ipynb @@ -38,7 +38,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The module `HARK.ConsumptionSaving.ConsIndShockModel` concerns consumption-saving models with idiosyncratic shocks to (non-capital) income. All of the models assume CRRA utility with geometric discounting, no bequest motive, and income shocks are fully transitory or fully permanent.\n", + "The module `HARK.ConsumptionSaving.ConsIndShockModel` concerns consumption-saving models with idiosyncratic shocks to (non-capital) income. All of the models assume CRRA utility with geometric discounting, no bequest motive, and income shocks that are either fully transitory or fully permanent.\n", "\n", "`ConsIndShockModel` currently includes three models:\n", "1. A very basic \"perfect foresight\" model with no uncertainty.\n", @@ -59,40 +59,39 @@ "source": [ "## Statement of perfect foresight consumption-saving model\n", "\n", - "The `PerfForesightConsumerType` class the problem of a consumer with Constant Relative Risk Aversion utility\n", - "${\\CRRA}$\n", - "\\begin{equation}\n", + "The `PerfForesightConsumerType` class models the problem of a consumer with Constant Relative Risk Aversion utility specified by\n", + "\\begin{align*}\n", "U(C) = \\frac{C^{1-\\CRRA}}{1-\\rho},\n", - "\\end{equation}\n", - "has perfect foresight about everything except whether he will die between the end of period $t$ and the beginning of period $t+1$, which occurs with probability $\\DiePrb_{t+1}$. Permanent labor income $P_t$ grows from period $t$ to period $t+1$ by factor $\\PermGroFac_{t+1}$.\n", + "\\end{align*}\n", + "who has perfect foresight about everything except whether he will die between the end of period $t$ and the beginning of period $t+1$, which occurs with probability $\\DiePrb_{t+1}$. Permanent labor income $P_t$ grows from period $t$ to period $t+1$ by factor $\\PermGroFac_{t+1}$.\n", "\n", - "At the beginning of period $t$, the consumer has an amount of market resources $M_t$ (which includes both market wealth and currrent income) and must choose how much of those resources to consume $C_t$ and how much to retain in a riskless asset $A_t$, which will earn return factor $\\Rfree$. The consumer cannot necessarily borrow arbitarily; instead, he might be constrained to have a wealth-to-income ratio at least as great as some \"artificial borrowing constraint\" $\\underline{a} \\leq 0$.\n", + "At the beginning of period $t$, the consumer has an amount of market resources $M_t$ (which includes both market wealth and current income) and must choose how much of those resources to consume $C_t$, while retaining the rest in a riskless asset $A_t$, which will earn return factor $\\Rfree$. The consumer cannot necessarily borrow arbitarily; instead, he might be constrained to have a wealth-to-income ratio at least as great as some \"artificial borrowing constraint\" $\\underline{a} \\leq 0$.\n", "\n", - "The agent's flow of future utility $U(C_{t+n})$ from consumption is geometrically discounted by factor $\\DiscFac$ per period. If the consumer dies, he receives zero utility flow for the rest of time.\n", + "The agent's flow of future utility $U(C_{t+n})$ from consumption is geometrically discounted by factor $\\DiscFac^n$. If the consumer dies, he receives zero utility flow for the rest of time.\n", "\n", "The agent's problem can be written in Bellman form as:\n", "\n", - "\\begin{eqnarray*}\n", - "V_t(M_t,P_t) &=& \\max_{C_t}~U(C_t) ~+ \\DiscFac (1 - \\DiePrb_{t+1}) V_{t+1}(M_{t+1},P_{t+1}), \\\\\n", - "& s.t. & \\\\\n", - "A_t &=& M_t - C_t, \\\\\n", - "A_t/P_t &\\geq& \\underline{a}, \\\\\n", - "M_{t+1} &=& \\Rfree A_t + Y_{t+1}, \\\\\n", - "Y_{t+1} &=& P_{t+1}, \\\\\n", - "P_{t+1} &=& \\PermGroFac_{t+1} P_t.\n", - "\\end{eqnarray*}\n", + "\\begin{align*}\n", + "V_t(M_t,P_t) &= \\max_{C_t}U(C_t) + \\DiscFac (1 - \\DiePrb_{t+1}) V_{t+1}(M_{t+1},P_{t+1}), \\\\\n", + "& \\text{s.t.} \\\\\n", + "A_t &= M_t - C_t, \\\\\n", + "A_t/P_t &\\geq \\underline{a}, \\\\\n", + "M_{t+1} &= \\Rfree A_t + Y_{t+1}, \\\\\n", + "Y_{t+1} &= P_{t+1}, \\\\\n", + "P_{t+1} &= \\PermGroFac_{t+1} P_t.\n", + "\\end{align*}\n", "\n", - "The consumer's problem is characterized by a coefficient of relative risk aversion $\\CRRA$, an intertemporal discount factor $\\DiscFac$, an interest factor $\\Rfree$, and age-varying sequences of the permanent income growth factor $\\PermGroFac_t$ and survival probability $(1 - \\DiePrb_t)$.\n", + "The consumer's problem is characterized by the coefficient of relative risk aversion $\\CRRA$, the intertemporal discount factor $\\DiscFac$, the interest factor $\\Rfree$, and age-varying sequences of the permanent income growth factor $\\PermGroFac_t$ and survival probability $(1 - \\DiePrb_t)$.\n", "\n", "While it does not reduce the computational complexity of the problem (as permanent income is deterministic, given its initial condition $P_0$), HARK represents this problem with *normalized* variables (represented in lower case), dividing all real variables by permanent income $P_t$ and utility levels by $P_t^{1-\\CRRA}$. The Bellman form of the model thus reduces to:\n", "\n", - "\\begin{eqnarray*}\n", - "v_t(m_t) &=& \\max_{c_t}~U(c_t) ~+ \\DiscFac (1 - \\DiePrb_{t+1}) \\PermGroFac_{t+1}^{1-\\CRRA} v_{t+1}(m_{t+1}), \\\\\n", - "& s.t. & \\\\\n", - "a_t &=& m_t - c_t, \\\\\n", - "a_t &\\geq& \\underline{a}, \\\\\n", - "m_{t+1} &=& \\Rfree/\\PermGroFac_{t+1} a_t + 1.\n", - "\\end{eqnarray*}" + "\\begin{align*}\n", + "v_t(m_t) &= \\max_{c_t}u(c_t) + \\DiscFac (1 - \\DiePrb_{t+1}) \\PermGroFac_{t+1}^{1-\\CRRA} v_{t+1}(m_{t+1}), \\\\\n", + "& \\text{s.t.} \\\\\n", + "a_t &= m_t - c_t, \\\\\n", + "a_t &\\geq \\underline{a}, \\\\\n", + "m_{t+1} &= \\Rfree a_t/\\PermGroFac_{t+1} + 1.\n", + "\\end{align*}" ] }, { @@ -101,7 +100,7 @@ "source": [ "## Solution method for PerfForesightConsumerType\n", "\n", - "Because of the assumptions of CRRA utility, no risk other than mortality, and no artificial borrowing constraint, the problem has a closed form solution. In fact, the consumption function is perfectly linear, and the value function composed with the inverse utility function is also linear. The mathematical solution of this model is described in detail in the lecture notes [PerfForesightCRRA](https://www.econ2.jhu.edu/people/ccarroll/public/lecturenotes/consumption/PerfForesightCRRA).\n", + "Because of the assumptions of CRRA utility and no risk other than mortality, the problem has a closed form solution when there is no artificial borrowing constraint. In fact, the consumption function is perfectly linear, and the value function composed with the inverse utility function is also linear. The mathematical solution of this model is described in detail in the lecture notes [PerfForesightCRRA](https://www.econ2.jhu.edu/people/ccarroll/public/lecturenotes/consumption/PerfForesightCRRA).\n", "\n", "The one period problem for this model is solved by the function `solveConsPerfForesight`, which creates an instance of the class `ConsPerfForesightSolver`. To construct an instance of the class `PerfForesightConsumerType`, several parameters must be passed to its constructor as shown in the table below." ] @@ -121,7 +120,7 @@ "|$\\PermGroFac_{t+1}$|Permanent income growth factor|$\\texttt{PermGroFac}$| $[1.01]$ | $\\surd$ |\n", "|$\\underline{a}$|Artificial borrowing constraint|$\\texttt{BoroCnstArt}$| $None$ | |\n", "|$(none)$|Maximum number of gridpoints in consumption function |$\\texttt{aXtraCount}$| $200$ | |\n", - "|$T$| Number of periods in this type's \"cycle\" |$\\texttt{T_cycle}$| $1$ | |\n", + "|$T$| Number of periods in this type's \"cycle\" |$\\texttt{T\\_cycle}$| $1$ | |\n", "|(none)| Number of times the \"cycle\" occurs |$\\texttt{cycles}$| $0$ | |\n", "\n", "Note that the survival probability and income growth factor have time subscripts; likewise, the example values for these parameters are *lists* rather than simply single floats. This is because those parameters are *time-varying*: their values can depend on which period of the problem the agent is in. All time-varying parameters *must* be specified as lists, even if the same value occurs in each period for this type.\n", @@ -130,7 +129,7 @@ "\n", "The last two parameters in the table specify the \"nature of time\" for this type: the number of (non-terminal) periods in this type's \"cycle\", and the number of times that the \"cycle\" occurs. *Every* subclass of `AgentType` uses these two code parameters to define the nature of time. Here, `T_cycle` has the value $1$, indicating that there is exactly one period in the cycle, while `cycles` is $0$, indicating that the cycle is repeated in *infinite* number of times-- it is an infinite horizon model, with the same \"kind\" of period repeated over and over.\n", "\n", - "In contrast, we could instead specify a life-cycle model by setting `T_cycle` to $1$, and specifying age-varying sequences of income growth and survival probability. In all cases, the number of elements in each time-varying parameter should exactly equal $\\texttt{T_cycle}$.\n", + "In contrast, we could instead specify a life-cycle model by setting `T_cycle` to $1$, and specifying age-varying sequences of income growth and survival probability. In all cases, the number of elements in each time-varying parameter should exactly equal $\\texttt{T\\_cycle}$.\n", "\n", "The parameter $\\texttt{AgentCount}$ specifies how many consumers there are of this *type*-- how many individuals have these exact parameter values and are *ex ante* homogeneous. This information is not relevant for solving the model, but is needed in order to simulate a population of agents, introducing *ex post* heterogeneity through idiosyncratic shocks. Of course, simulating a perfect foresight model is quite boring, as there are *no* idiosyncratic shocks other than death!\n", "\n", @@ -196,7 +195,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "[]\n" + "[]\n" ] } ], @@ -222,7 +221,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "{'cFunc': , 'vFunc': , 'vPfunc': , 'vPPfunc': , 'mNrmMin': -50.49994992551661, 'hNrm': 50.49994992551661, 'MPCmin': 0.04428139169919579, 'MPCmax': 0.04428139169919579}\n" + "{'cFunc': , 'vFunc': , 'vPfunc': , 'vPPfunc': , 'mNrmMin': -50.49994992551661, 'hNrm': 50.49994992551661, 'MPCmin': 0.04428139169919579, 'MPCmax': 0.04428139169919579}\n" ] } ], @@ -251,7 +250,7 @@ }, { "data": { - "image/png": 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TbnIyMZvKiIiI9Lgd++vI2VjGSYcTqwXunzKchzNGYvezmR1N+gCVERER6TFNznaefbeC14uPARAfGUx+VgppcQNMTiZ9icqIiIj0iF2H6llUUEbNly0A3HPTMB6bPoqgAE1D5EIqIyIi0q1aWl2s2FrJK7uOABAbEcTKzBQmxl9lbjDps1RGRESk25R8dpqFG8qorj8LwJ3pcTxx6xhC7Hq5kYvTnw4REbli59pcvPDeAdbtPIzbgOiwQFZkJjMlYaDZ0cQDqIyIiMgVKa9pJPvNPRysawJgbtrV5M5KJDzI3+Rk4ilURkRE5LK0trtZs72KtdurcLkNIkPs5M25lmmJUWZHEw+jMiIiIl1WWesge30pFSccAMxMHsyy25KICA4wOZl4IpURERHptHaXm5c+OMzq9w/Q5jIY0M+fZ2YnMTN5iNnRxIOpjIiISKdU1TXx6IZSSo81AJAxJorlc5IYFBpobjDxeCojIiJySW63wcsfVrNy236c7W5CA/1YOmssc9JisFgsZscTL6AyIiIiF3X0VDMLC0oprj4NwKSRkTyfmczg8CCTk4k3URkREZFvMAyD1z46yvItn9Lc6iI4wMaSGYncMSFW0xDpdiojIiJygeMNLeRsLGPnwXoA0odFkD8vhdiIfiYnE2+lMiIiIsD5aUhBSQ3LCis442zH7mcl55bR3H3jUKxWTUOk56iMiIgIdY5zLH6rnKLKOgDGxfUnf14KwweGmJxMfIHKiIiIDzMMg8KyE+Ru3ktDcxsBNiuPTEvgvsnx2DQNkV6iMiIi4qNONTl5cvNetpTXAjB2SBirslIZFR1qcjLxNSojIiI+aNu+WpZsKqe+qRU/q4UHp47ggZtH4G+zmh1NfJDKiIiID2lsbmNp4T42ffI5AAlRIazKSiUpJtzkZOLLLqsCr127lqFDhxIYGEh6ejrFxcUX3fett95i/Pjx9O/fn+DgYFJTU3n11VcvO7CIiFyeHfvr+P7qv7Lpk8+xWuD/fG84hQ/9i4qImK7Lk5H169eTnZ3Niy++SHp6OqtXr2b69Ons37+fQYMGfWP/iIgIlixZwujRowkICOCdd95hwYIFDBo0iOnTp3fLkxARkYtrcrbz7LsVvF58DID4yGDys1JIixtgcjKR8yyGYRhdOSA9PZ3rr7+eNWvWAOB2u4mNjeWhhx7i8ccf79R9pKWlMWPGDJ555plO7e9wOAgPD6exsZGwsLCuxBUR8Wm7DtWzqKCMmi9bALjnpmE8Nn0UQQE2k5OJL+js63eXJiOtra2UlJSwePHijm1Wq5WMjAx27979nccbhsFf/vIX9u/fz4oVKy66n9PpxOl0dnztcDi6ElNExOe1tLpYsbWSV3YdASA2IoiVmSlMjL/K3GAi36JLZaS+vh6Xy0VUVNQF26OioqisrLzocY2NjcTExOB0OrHZbPzyl79k2rRpF90/Ly+Pp59+uivRRETkf5V8dpqFG8qorj8LwJ3pcTxx6xhC7PqdBembeuVPZmhoKHv27KGpqYmioiKys7OJj4/ne9/73rfuv3jxYrKzszu+djgcxMbG9kZUERGPda7NxQvvHWDdzsO4DYgOC2RFZjJTEgaaHU3kkrpURiIjI7HZbJw8efKC7SdPniQ6Ovqix1mtVkaMGAFAamoqn376KXl5eRctI3a7Hbvd3pVoIiI+rbymkew393CwrgmAuWlXkzsrkfAgf5OTiXy3Lv1qb0BAANdddx1FRUUd29xuN0VFRdxwww2dvh+3233BOSEiInJ5WtvdrHrvALN/+SEH65qIDLGzbv54fpaVoiIiHqPLb9NkZ2dz1113MX78eCZMmMDq1as5e/YsCxYsAGD+/PnExMSQl5cHnD//Y/z48QwfPhyn08mWLVt49dVX+dWvftW9z0RExMdU1jrIXl9KxYnzJ/nPTB7MstuSiAgOMDmZSNd0uYzcfvvtfPHFF+Tm5lJbW0tqaipbt27tOKn16NGjWK3/HLicPXuW//t//y81NTUEBQUxevRo/vCHP3D77bd337MQEfEh7S43L31wmNXvH6DNZTCgnz/PzE5iZvIQs6OJXJYuX2fEDLrOiIjIeVV1TTy6oZTSYw0AZIyJYvmcJAaFBpobTORb9Mh1RkRExBxut8HLH1azctt+nO1uQgP9WDprLHPSYrBYLGbHE7kiKiMiIn3c0VPNLCwopbj6NACTRkbyfGYyg8ODTE4m0j1URkRE+ijDMHjto6Ms3/Ipza0uggNsLJmRyB0TYjUNEa+iMiIi0gcdb2ghZ2MZOw/WA5A+LIL8eSnERvQzOZlI91MZERHpQwzDoKCkhmWFFZxxtmP3s5Jzy2juvnEoVqumIeKdVEZERPqIOsc5Fr9VTlFlHQDj4vqTPy+F4QNDTE4m0rNURkRETGYYBoVlJ8jdvJeG5jYCbFYemZbAfZPjsWkaIj5AZURExESnmpw8uXkvW8prARg7JIxVWamMig41OZlI71EZERExybZ9tSzZVE59Uyt+VgsPTh3BAzePwN/WpY8NE/F4KiMiIr2ssbmNpYX72PTJ5wAkRIWwKiuVpJhwk5OJmENlRESkF+3YX0fOxjJOOpxYLXD/lOE8nDESu5/N7GgiplEZERHpBU3Odp59t4LXi48BEB8ZTH5WCmlxA0xOJmI+lRERkR6261A9iwrKqPmyBYB7bhrGY9NHERSgaYgIqIyIiPSYllYXK7ZW8squIwDERgSxMjOFifFXmRtMpI9RGRER6QEln51m4YYyquvPAnBnehxP3DqGELt+7Ip8nf5WiIh0o3NtLl547wDrdh7GbUB0WCArMpOZkjDQ7GgifZbKiIhINymvaST7zT0crGsCYG7a1eTOSiQ8yN/kZCJ9m8qIiMgVam13s2Z7FWu3V+FyG0SG2Mmbcy3TEqPMjibiEVRGRESuQGWtg+z1pVSccAAwM3kwy25LIiI4wORkIp5DZURE5DK0u9y89MFhVr9/gDaXwYB+/jwzO4mZyUPMjibicVRGRES6qKquiUc3lFJ6rAGAjDFRLJ+TxKDQQHODiXgolRERkU5yuw1e/rCaldv242x3Exrox9JZY5mTFoPFYjE7nojHUhkREemEo6eaWVhQSnH1aQAmjYzk+cxkBocHmZxMxPOpjIiIXIJhGLz20VGWb/mU5lYXwQE2lsxI5I4JsZqGiHQTlRERkYs43tBCzsYydh6sByB9WAT581KIjehncjIR76IyIiLyNYZhUFBSw7LCCs4427H7Wcm5ZTR33zgUq1XTEJHupjIiIvIVdY5zLH6rnKLKOgDGxfUnf14KwweGmJxMxHupjIiIcH4aUlh2gtzNe2lobiPAZuWRaQncNzkem6YhIj1KZUREfN6pJidPbt7LlvJaAMYOCWNVViqjokNNTibiG1RGRMSnbdtXy5JN5dQ3teJntfDg1BE8cPMI/G1Ws6OJ+AyVERHxSY3NbSwt3MemTz4HICEqhFVZqSTFhJucTMT3qIyIiM/Zsb+OnI1lnHQ4sVrg/inDeThjJHY/m9nRRHySyoiI+IwmZzvPvlvB68XHAIiPDCY/K4W0uAEmJxPxbSojIuITdh2qZ1FBGTVftgBwz03DeGz6KIICNA0RMZvKiIh4tZZWFyu2VvLKriMAxEYEsTIzhYnxV5kbTEQ6qIyIiNcq+ew0CzeUUV1/FoA70+N44tYxhNj1o0+kL9HfSBHxOufaXLzw3gHW7TyM24DosEBWZCYzJWGg2dFE5FuojIiIVymvaST7zT0crGsCYG7a1eTOSiQ8yN/kZCJyMSojIuIVWtvdrNlexdrtVbjcBpEhdvLmXMu0xCizo4nId1AZERGPV1nrIHt9KRUnHADMTB7MstuSiAgOMDmZiHSGyoiIeKx2l5uXPjjM6vcP0OYyGNDPn2dmJzEzeYjZ0USkC1RGRMQjVdU18eiGUkqPNQCQMSaK5XOSGBQaaG4wEekylRER8Shut8HLH1azctt+nO1uQgP9WDprLHPSYrBYLGbHE5HLoDIiIh7j6KlmFhaUUlx9GoBJIyN5PjOZweFBJicTkSuhMiIifZ5hGLz20VGWb/mU5lYXwQE2lsxI5I4JsZqGiHgBlRER6dOON7SQs7GMnQfrAUgfFkH+vBRiI/qZnExEuovKiIj0SYZhUFBSw7LCCs4427H7Wcm5ZTR33zgUq1XTEBFvojIiIn1OneMci98qp6iyDoBxcf3Jn5fC8IEhJicTkZ6gMiIifYZhGBSWnSB3814amtsIsFl5ZFoC902Ox6ZpiIjXUhkRkT7hVJOTJzfvZUt5LQBjh4SxKiuVUdGhJicTkZ6mMiIiptu2r5Ylm8qpb2rFz2rhwakjeODmEfjbrGZHE5FeoDIiIqZpbG5jaeE+Nn3yOQAJUSGsykolKSbc5GQi0ptURkTEFDv215GzsYyTDidWC9w/ZTgPZ4zE7mczO5qI9DKVERHpVU3Odp59t4LXi48BEB8ZTH5WCmlxA0xOJiJmURkRkV6z61A9iwrKqPmyBYB7bhrGY9NHERSgaYiIL1MZEZEe19LqYsXWSl7ZdQSA2IggVmamMDH+KnODiUifoDIiIj2q5LPTLNxQRnX9WQDuTI/jiVvHEGLXjx8ROU8/DUSkR5xrc/HCewdYt/MwbgOiwwJZkZnMlISBZkcTkT5GZUREul15TSPZb+7hYF0TAHPTriZ3ViLhQf4mJxORvkhlRES6TWu7mzXbq1i7vQqX2yAyxE7enGuZlhhldjQR6cNURkSkW1TWOsheX0rFCQcAM5MHs+y2JCKCA0xOJiJ9ncqIiFyRdpeblz44zOr3D9DmMhjQz59nZicxM3mI2dFExEOojIjIZauqa+LRDaWUHmsAIGNMFMvnJDEoNNDcYCLiUVRGRKTL3G6Dlz+sZuW2/Tjb3YQG+rF01ljmpMVgsVjMjiciHkZlRES65OipZhYWlFJcfRqASSMjeT4zmcHhQSYnExFPdVmfz7127VqGDh1KYGAg6enpFBcXX3TfdevWMWnSJAYMGMCAAQPIyMi45P4i0jcZhsEf/t9n3PJfH1BcfZrgABvL//Vafn/PBBUREbkiXS4j69evJzs7m6eeeoqPP/6YlJQUpk+fTl1d3bfuv2PHDu644w62b9/O7t27iY2N5fvf/z6ff/75FYcXkd5xvKGF+S8X89O399Lc6iJ9WARbH57MnelxeltGRK6YxTAMoysHpKenc/3117NmzRoA3G43sbGxPPTQQzz++OPfebzL5WLAgAGsWbOG+fPnd+oxHQ4H4eHhNDY2EhYW1pW4InIFDMOgoKSGZYUVnHG2Y/ezknPLaO6+cShWq0qIiFxaZ1+/u3TOSGtrKyUlJSxevLhjm9VqJSMjg927d3fqPpqbm2lrayMiIuKi+zidTpxOZ8fXDoejKzFFpBvUOc6x+K1yiirPTz3HxfUnf14KwweGmJxMRLxNl8pIfX09LpeLqKgLr6YYFRVFZWVlp+4jJyeHIUOGkJGRcdF98vLyePrpp7sSTUS6iWEYFJadIHfzXhqa2wiwWXlkWgL3TY7HpmmIiPSAXv1tmueee4433niDHTt2EBh48esQLF68mOzs7I6vHQ4HsbGxvRFRxKedanLy5Oa9bCmvBWDskDBWZaUyKjrU5GQi4s26VEYiIyOx2WycPHnygu0nT54kOjr6ksfm5+fz3HPP8f7775OcnHzJfe12O3a7vSvRROQKbdtXy5JN5dQ3teJntfDg1BE8cPMI/G2X9Ut3IiKd1qWfMgEBAVx33XUUFRV1bHO73RQVFXHDDTdc9Ljnn3+eZ555hq1btzJ+/PjLTysi3a6xuY1H1u/h/ldLqG9qJSEqhLcfuImHMxJURESkV3T5bZrs7Gzuuusuxo8fz4QJE1i9ejVnz55lwYIFAMyfP5+YmBjy8vIAWLFiBbm5ufzxj39k6NCh1NaeH/+GhIQQEqIT4UTMtGN/HTkbyzjpcGK1wP1ThvNwxkjsfjazo4mID+lyGbn99tv54osvyM3Npba2ltTUVLZu3dpxUuvRo0exWv/5r6lf/epXtLa2kpmZecH9PPXUUyxduvTK0ovIZWlytvPsuxW8XnwMgPjIYPKzUkiLG2ByMhHxRV2+zogZdJ0Rke6z61A9iwrKqPmyBYB7bhrGY9NHERSgaYiIdK8euc6IiHiullYXK7ZW8squIwDERgSxMjOFifFXmRtMRHyeyoiIDyj57DQLN5RRXX8WgDvT43ji1jGE2PUjQETMp59EIl7sXJuLF947wLqdh3EbEB0WyIrMZKYkDDQ7mohIB5URES9VXtNI9pt7OFjXBMDctKvJnZVIeJC/yclERC6kMiLiZVrb3azZXsXa7VW43AaRIXby5lzLtMSo7z5YRMQEKiMiXqSy1kH2+lIqTpz/cMmZyYNZdlsSEcEBJicTEbk4lRERL9DucvPSB4dZ/f4B2lwGA/r588zsJGYmDzE7mojId1IZEfFwVXVNPLqhlNJjDQBkjIli+ZwkBoVe/MMoRUT6EpUREQ/ldhu8/GE1K7ftx9nuJjTQj6WzxjInLQaLxWJ2PBGRTlMZEfFAR081s7CglOLq0wBMGhnJ85nJDA4PMjmZiEjXqYyIeBDDMHjto6Ms3/Ipza0uggNsLJmRyB0TYjUNERGPpTIi4iGON7SQs7GMnQfrAUgfFkH+vBRiI/qZnExE5MqojIj0cYZhUFBSw7LCCs4427H7Wcm5ZTR33zgUq1XTEBHxfCojIn1YneMci98qp6iyDoBxcf3Jn5fC8IEhJicTEek+KiMifZBhGBSWnSB3814amtsIsFl5ZFoC902Ox6ZpiIh4GZURkT7mVJOTJzfvZUt5LQBjh4SxKiuVUdGhJicTEekZKiMifci2fbUs2VROfVMrflYLD04dwQM3j8DfZjU7mohIj1EZEekDGpvbWFq4j02ffA5AQlQIq7JSSYoJNzmZiEjPUxkRMdmO/XXkbCzjpMOJ1QL3TxnOwxkjsfvZzI4mItIrVEZETNLkbOfZdyt4vfgYAPGRweRnpZAWN8DkZCIivUtlRMQEuw7Vs6igjJovWwC456ZhPDZ9FEEBmoaIiO9RGRHpRS2tLlZsreSVXUcAiI0IYmVmChPjrzI3mIiIiVRGRHpJyWenWbihjOr6swDcmR7HE7eOIcSuv4Yi4tv0U1Ckh51rc/HCewdYt/MwbgOiwwJZkZnMlISBZkcTEekTVEZEelB5TSPZb+7hYF0TAHPTriZ3ViLhQf4mJxMR6TtURkR6QGu7mzXbq1i7vQqX2yAyxE7enGuZlhhldjQRkT5HZUSkm1XWOsheX0rFCQcAM5MHs+y2JCKCA0xOJiLSN6mMiHSTdpeblz44zOr3D9DmMhjQz59nZicxM3mI2dFERPo0lRGRblBV18SjG0opPdYAQMaYKJbPSWJQaKC5wUREPIDKiMgVcLsNXv6wmpXb9uNsdxMa6MfSWWOZkxaDxWIxO56IiEdQGRG5TEdPNbOwoJTi6tMATBoZyfOZyQwODzI5mYiIZ1EZEekiwzB47aOjLN/yKc2tLoIDbCyZkcgdE2I1DRERuQwqIyJdcLyhhZyNZew8WA9A+rAI8uelEBvRz+RkIiKeS2VEpBMMw6CgpIZlhRWccbZj97OSc8to7r5xKFarpiEiIldCZUTkO9Q5zrH4rXKKKusAGBfXn/x5KQwfGGJyMhER76AyInIRhmFQWHaC3M17aWhuI8Bm5ZFpCdw3OR6bpiEiIt1GZUTkW5xqcvLk5r1sKa8FYOyQMFZlpTIqOtTkZCIi3kdlRORrtu2rZcmmcuqbWvGzWnhw6ggeuHkE/jar2dFERLySyojI/2psbmNp4T42ffI5AAlRIazKSiUpJtzkZCIi3k1lRATYsb+OnI1lnHQ4sVrg/inDeThjJHY/m9nRRES8nsqI+LQmZzvPvlvB68XHAIiPDCY/K4W0uAEmJxMR8R0qI+Kzdh2qZ1FBGTVftgBwz03DeGz6KIICNA0REelNKiPic1paXazYWskru44AEBsRxMrMFCbGX2VuMBERH6UyIj6l5LPTLNxQRnX9WQDuTI/jiVvHEGLXXwUREbPoJ7D4hHNtLl547wDrdh7GbUB0WCArMpOZkjDQ7GgiIj5PZUS8XnlNI9lv7uFgXRMAc9OuJndWIuFB/iYnExERUBkRL9ba7mbN9irWbq/C5TaIDLGTN+dapiVGmR1NRES+QmVEvFJlrYPs9aVUnHAAMDN5MMtuSyIiOMDkZCIi8nUqI+JV2l1uXvrgMKvfP0Cby2BAP3+emZ3EzOQhZkcTEZGLUBkRr1FV18SjG0opPdYAQMaYKJbPSWJQaKC5wURE5JJURsTjud0GL39Yzcpt+3G2uwkN9GPprLHMSYvBYrGYHU9ERL6Dyoh4tKOnmllYUEpx9WkAJo2M5PnMZAaHB5mcTEREOktlRDySYRi89tFRlm/5lOZWF8EBNpbMSOSOCbGahoiIeBiVEfE4xxtayNlYxs6D9QCkD4sgf14KsRH9TE4mIiKXQ2VEPIZhGBSU1LCssIIzznbsflZybhnN3TcOxWrVNERExFOpjIhHqHOcY/Fb5RRV1gEwLq4/+fNSGD4wxORkIiJypVRGpE8zDIPCshPkbt5LQ3MbATYrj0xL4L7J8dg0DRER8QoqI9JnnWpy8uTmvWwprwVg7JAwVmWlMio61ORkIiLSnVRGpE/atq+WJZvKqW9qxc9q4cGpI3jg5hH426xmRxMRkW6mMiJ9SmNzG0sL97Hpk88BSIgKYVVWKkkx4SYnExGRnqIyIn3Gjv115Gws46TDidUC908ZzsMZI7H72cyOJiIiPUhlREzX5Gzn2XcreL34GADxkcHkZ6WQFjfA5GQiItIbVEbEVLsO1bOooIyaL1sAuOemYTw2fRRBAZqGiIj4CpURMUVLq4sVWyt5ZdcRAGIjgliZmcLE+KvMDSYiIr3usn41Ye3atQwdOpTAwEDS09MpLi6+6L779u1j7ty5DB06FIvFwurVqy83q3iJks9Oc+vPd3YUkTvT4/j/fjJZRURExEd1uYysX7+e7OxsnnrqKT7++GNSUlKYPn06dXV137p/c3Mz8fHxPPfcc0RHR19xYPFc59pc5G35lHkv7qa6/izRYYH87p4JLP/Xawmxa0gnIuKrLIZhGF05ID09neuvv541a9YA4Ha7iY2N5aGHHuLxxx+/5LFDhw7l4Ycf5uGHH+5SSIfDQXh4OI2NjYSFhXXpWOkbymsayX5zDwfrmgCYm3Y1ubMSCQ/yNzmZiIj0lM6+fnfpn6Otra2UlJSwePHijm1Wq5WMjAx27959+WnFa7W2u1mzvYq126twuQ0iQ+zkzbmWaYlRZkcTEZE+oktlpL6+HpfLRVTUhS8kUVFRVFZWdlsop9OJ0+ns+NrhcHTbfUvvqax1kL2+lIoT59dvZvJglt2WRERwgMnJRESkL+mTb9Tn5eXx9NNPmx1DLlO7y81LHxxm9fsHaHMZDOjnzzOzk5iZPMTsaCIi0gd16QTWyMhIbDYbJ0+evGD7yZMnu/Xk1MWLF9PY2NhxO3bsWLfdt/Ssqrom5r64m5Xb9tPmMsgYE8W2RyariIiIyEV1qYwEBARw3XXXUVRU1LHN7XZTVFTEDTfc0G2h7HY7YWFhF9ykb3O7Df5752Fm/HwnpccaCA3042fzUlg3/zoGhQaaHU9ERPqwLr9Nk52dzV133cX48eOZMGECq1ev5uzZsyxYsACA+fPnExMTQ15eHnD+pNeKioqO//7888/Zs2cPISEhjBgxohufipjl6KlmFhaUUlx9GoBJIyN5PjOZweFBJicTERFP0OUycvvtt/PFF1+Qm5tLbW0tqampbN26teOk1qNHj2K1/nPgcvz4ccaNG9fxdX5+Pvn5+UyZMoUdO3Zc+TMQ0xiGwWsfHWX5lk9pbnURHGBjyYxE7pgQi8ViMTueiIh4iC5fZ8QMus5I33O8oYWcjWXsPFgPQPqwCPLnpRAb0c/kZCIi0lf0yHVGRAzDoKCkhmWFFZxxtmP3s5Jzy2juvnEoVqumISIi0nUqI9JpdY5zLH6rnKLK85f+HxfXn/x5KQwfGGJyMhER8WQqI/KdDMOgsOwEuZv30tDcRoDNyiPTErhvcjw2TUNEROQKqYzIJZ1qcvLk5r1sKa8FYOyQMFZlpTIqOtTkZCIi4i1URuSitu2rZcmmcuqbWvGzWnhw6ggeuHkE/rYuf9iziIjIRamMyDc0NrextHAfmz75HICEqBBWZaWSFBNucjIREfFGKiNygR3768jZWMZJhxOrBe6fMpyHM0Zi97OZHU1ERLyUyogA0ORs59l3K3i9+PznAMVHBpOflUJa3ACTk4mIiLdTGRF2HapnUUEZNV+2AHDPTcN4bPooggI0DRERkZ6nMuLDWlpdrNhaySu7jgAQGxHEyswUJsZfZW4wERHxKSojPqrks9Ms3FBGdf1ZAO5Mj+OJW8cQYtcfCRER6V165fEx59pcvPDeAdbtPIzbgOiwQFZkJjMlYaDZ0URExEepjPiQ8ppGst/cw8G6JgDmpl1N7qxEwoP8TU4mIiK+TGXEB7S2u1mzvYq126twuQ0iQ+zkzbmWaYlRZkcTERFRGfF2lbUOsteXUnHCAcDM5MEsuy2JiOAAk5OJiIicpzLipdpdbl764DCr3z9Am8tgQD9/npmdxMzkIWZHExERuYDKiBeqqmvi0Q2llB5rACBjTBTL5yQxKDTQ3GAiIiLfQmXEi7jdBi9/WM3KbftxtrsJDfRj6ayxzEmLwWKxmB1PRETkW6mMeImjp5pZWFBKcfVpACaNjOT5zGQGhweZnExEROTSVEY8nGEYvPbRUZZv+ZTmVhfBATaWzEjkjgmxmoaIiIhHUBnxYMcbWsjZWMbOg/UApA+LIH9eCrER/UxOJiIi0nkqIx7IMAwKSmpYVljBGWc7dj8rObeM5u4bh2K1ahoiIiKeRWXEw9Q5zrH4rXKKKusAGBfXn/x5KQwfGGJyMhERkcujMuIhDMOgsOwEuZv30tDcRoDNyiPTErhvcjw2TUNERMSDqYx4gFNNTp7cvJct5bUAjB0SxqqsVEZFh5qcTERE5MqpjPRx2/bVsmRTOfVNrfhZLTw4dQQP3DwCf5vV7GgiIiLdQmWkj2psbmNp4T42ffI5AAlRIazKSiUpJtzkZCIiIt1LZaQP2rG/jpyNZZx0OLFa4P4pw3k4YyR2P5vZ0URERLqdykgf0uRs59l3K3i9+BgA8ZHB5GelkBY3wORkIiIiPUdlpI/YdaieRQVl1HzZAsA9Nw3jsemjCArQNERERLybyojJWlpdrNhaySu7jgAQGxHEyswUJsZfZW4wERGRXqIyYqKSz06zcEMZ1fVnAbgzPY4nbh1DiF3LIiIivkOveiY41+bihfcOsG7nYdwGRIcFsiIzmSkJA82OJiIi0utURnpZeU0j2W/u4WBdEwBz064md1Yi4UH+JicTERExh8pIL2ltd7NmexVrt1fhchtEhtjJm3Mt0xKjzI4mIiJiKpWRXlBZ6yB7fSkVJxwAzEwezLLbkogIDjA5mYiIiPlURnpQu8vNSx8cZvX7B2hzGQzo588zs5OYmTzE7GgiIiJ9hspID6mqa+LRDaWUHmsAIGNMFMvnJDEoNNDcYCIiIn2Mykg3c7sNXv6wmpXb9uNsdxMa6MfSWWOZkxaDxWIxO56IiEifozLSjY6eamZhQSnF1acBmDQykuczkxkcHmRyMhERkb5LZaQbGIbBax8dZfmWT2ludREcYGPJjETumBCraYiIiMh3UBm5QscbWsjZWMbOg/UApA+LIH9eCrER/UxOJiIi4hlURi6TYRgUlNSwrLCCM8527H5Wcm4Zzd03DsVq1TRERESks1RGLkOd4xyL3yqnqLIOgHFx/cmfl8LwgSEmJxMREfE8KiNdYBgGhWUnyN28l4bmNgJsVh6ZlsB9k+OxaRoiIiJyWVRGOulUk5MnN+9lS3ktAGOHhLEqK5VR0aEmJxMREfFsKiOdsG1fLUs2lVPf1Iqf1cKDU0fwwM0j8LdZzY4mIiLi8VRGLqGxuY2lhfvY9MnnACREhbAqK5WkmHCTk4mIiHgPlZGL2LG/jpyNZZx0OLFa4P4pw3k4YyR2P5vZ0URERLyKysjXNDnbefbdCl4vPgZAfGQw+VkppMUNMDmZiIiId1IZ+Ypdh+pZVFBGzZctANxz0zAemz6KoABNQ0RERHqKygjQ0upixdZKXtl1BIDYiCBWZqYwMf4qc4OJiIj4AJ8vIyWfnWbhhjKq688CcGd6HE/cOoYQu8//rxEREekVPvuKe67NxQvvHWDdzsO4DYgOC2RFZjJTEgaaHU1ERMSn+GQZKa9pJPvNPRysawJgbtrV5M5KJDzI3+RkIiIivsenykhru5s126tYu70Kl9sgMsRO3pxrmZYYZXY0ERERn+UzZaSy1kH2+lIqTjgAmJk8mGW3JRERHGByMhEREd/m9WWk3eXmpQ8Os/r9A7S5DAb08+eZ2UnMTB5idjQRERHBy8tIVV0Tj24opfRYAwAZY6JYPieJQaGB5gYTERGRDl5ZRtxug5c/rGbltv04292EBvqxdNZY5qTFYLFYzI4nIiIiX+F1ZeToqWYWFpRSXH0agEkjI3k+M5nB4UEmJxMREZFv4zVlxDAMXvvoKMu3fEpzq4vgABtLZiRyx4RYTUNERET6MK8oI8cbWsjZWMbOg/UApA+LIH9eCrER/UxOJiIiIt/Fo8uIYRgUlNSwrLCCM8527H5Wcm4Zzd03DsVq1TRERETEE3hsGalznGPxW+UUVdYBMC6uP/nzUhg+MMTkZCIiItIV1ss5aO3atQwdOpTAwEDS09MpLi6+5P4bNmxg9OjRBAYGcu2117Jly5bLCgvnpyF/Kj3O91d/QFFlHQG289OQgh/fqCIiIiLigbpcRtavX092djZPPfUUH3/8MSkpKUyfPp26urpv3X/Xrl3ccccd/OhHP+KTTz5h9uzZzJ49m71793Y57OkmJw/88WP+4/VPaGhuY+yQMAof+hf+z/eGY9PbMiIiIh7JYhiG0ZUD0tPTuf7661mzZg0Abreb2NhYHnroIR5//PFv7H/77bdz9uxZ3nnnnY5tEydOJDU1lRdffLFTj+lwOAgPDyd1ySa+bPfHz2rhwakjeODmEfjbLmu4IyIiIj3sH6/fjY2NhIWFXXS/Lr2St7a2UlJSQkZGxj/vwGolIyOD3bt3f+sxu3fvvmB/gOnTp190fwCn04nD4bjgBnDqbBsJUSG8/cBNPJyRoCIiIiLiBbr0al5fX4/L5SIq6sJPuY2KiqK2tvZbj6mtre3S/gB5eXmEh4d33GJjYwH40b8Mo/ChfyEpJrwrsUVERKQP65OjhcWLF9PY2NhxO3bsGACPTEvA7mczOZ2IiIh0py79am9kZCQ2m42TJ09esP3kyZNER0d/6zHR0dFd2h/Abrdjt9u7Ek1EREQ8VJcmIwEBAVx33XUUFRV1bHO73RQVFXHDDTd86zE33HDDBfsDvPfeexfdX0RERHxLly96lp2dzV133cX48eOZMGECq1ev5uzZsyxYsACA+fPnExMTQ15eHgA/+clPmDJlCj/72c+YMWMGb7zxBn//+9/59a9/3b3PRERERDxSl8vI7bffzhdffEFubi61tbWkpqaydevWjpNUjx49itX6z4HLjTfeyB//+Ed++tOf8sQTTzBy5EjefvttkpKSuu9ZiIiIiMfq8nVGzNDZ31MWERGRvqNHrjMiIiIi0t1URkRERMRUKiMiIiJiKpURERERMZXKiIiIiJhKZURERERMpTIiIiIiplIZEREREVOpjIiIiIipunw5eDP84yKxDofD5CQiIiLSWf943f6ui717RBk5c+YMALGxsSYnERERka46c+YM4eHhF/2+R3w2jdvt5vjx44SGhmKxWHrkMRwOB7GxsRw7dkyff2MyrUXfobXoO7QWfYfWovMMw+DMmTMMGTLkgg/R/TqPmIxYrVauvvrqXnmssLAw/eHqI7QWfYfWou/QWvQdWovOudRE5B90AquIiIiYSmVERERETKUy8r/sdjtPPfUUdrvd7Cg+T2vRd2gt+g6tRd+hteh+HnECq4iIiHgvTUZERETEVCojIiIiYiqVERERETGVyoiIiIiYyufLyNChQ7FYLBfcnnvuuQv2KSsrY9KkSQQGBhIbG8vzzz9vUlrf4XQ6SU1NxWKxsGfPngu+t23bNiZOnEhoaCgDBw5k7ty5HDlyxJScvuBSa2EYBvn5+SQkJGC324mJieHZZ581J6gPuNRa/ENVVRWhoaH079+/V7P5moutxY4dO7jtttsYPHgwwcHBpKam8tprr5kX1EP4fBkBWLZsGSdOnOi4PfTQQx3fczgcfP/73+eaa66hpKSElStXsnTpUn7961+bmNj7LVq0iCFDhnxje3V1NbfddhtTp05lz549bNu2jfr6eubMmWNCSt9wsbUA+MlPfsJ///d/k5+fT2VlJX/605+YMGFCLyf0HZdaC4C2tjbuuOMOJk2a1IupfNPF1mLXrl0kJyezceNGysrKWLBgAfPnz+edd94xIaUHMXzcNddcY7zwwgsX/f4vf/lLY8CAAYbT6ezYlpOTY4waNaoX0vmmLVu2GKNHjzb27dtnAMYnn3zS8b0NGzYYfn5+hsvl6tj2pz/9ybBYLEZra6sJab3bpdaioqLC8PPzMyorK80L6EMutRb/sGjRIuPf/u3fjN/+9rdGeHh4r2f0FZ1Zi6+69dZbjQULFvROOA+lyQjw3HPPcdVVVzFu3DhWrlxJe3t7x/d2797N5MmTCQgI6Ng2ffp09u/fz5dffmlGXK928uRJ7r33Xl599VX69ev3je9fd911WK1Wfvvb3+JyuWhsbOTVV18lIyMDf39/ExJ7r+9ai8LCQuLj43nnnXcYNmwYQ4cO5d///d85ffq0CWm923etBcBf/vIXNmzYwNq1a3s5nW/pzFp8XWNjIxERET2czLP5fBn5j//4D9544w22b9/O/fffz/Lly1m0aFHH92tra4mKirrgmH98XVtb26tZvZ1hGNx99938+Mc/Zvz48d+6z7Bhw/jzn//ME088gd1up3///tTU1PDmm2/2clrv1pm1OHz4MJ999hkbNmzg97//Pa+88golJSVkZmb2clrv1pm1OHXqFHfffTevvPKKPritB3VmLb7uzTff5G9/+xsLFizo4XSezSvLyOOPP/6Nk1K/fqusrAQgOzub733veyQnJ/PjH/+Yn/3sZ/ziF7/A6XSa/Cy8R2fX4xe/+AVnzpxh8eLFF72v2tpa7r33Xu666y7+9re/8de//pWAgAAyMzMxdDHh79Sda+F2u3E6nfz+979n0qRJfO973+M3v/kN27dvZ//+/b34rDxTd67Fvffey5133snkyZN78Rl4j+5ci6/avn07CxYsYN26dYwdO7aHn4Vn88rLwX/xxRecOnXqkvvEx8df8NbLP+zbt4+kpCQqKysZNWoU8+fPx+Fw8Pbbb3fss337dqZOncrp06cZMGBAd8f3Op1dj6ysLAoLC7FYLB3bXS4XNpuNH/zgB/zud7/jySefZOvWrfztb3/r2KempobY2Fh2797NxIkTe+x5eIPuXIunnnqK5cuX09bW1rFPS0sL/fr1489//jPTpk3rsefhDbpzLfr3709TU1PH9w3DwO12Y7PZ+PWvf80999zTY8/DG3TnWvzDX//6V2bMmMGqVau47777eiy7t/AzO0BPGDhwIAMHDrysY/fs2YPVamXQoEEA3HDDDSxZsoS2traOcxLee+89Ro0apSLSSZ1dj5///Of853/+Z8fXx48fZ/r06axfv5709HQAmpubsVovHOjZbDbg/L/U5dK6cy1uuukm2tvbOXToEMOHDwfgwIEDAFxzzTU9kN67dOda7N69G5fL1bHP5s2bWbFiBbt27SImJqb7w3uZ7lwLOP/rvTNnzmTFihUqIp1l3rmz5tu1a5fxwgsvGHv27DEOHTpk/OEPfzAGDhxozJ8/v2OfhoYGIyoqyvjhD39o7N2713jjjTeMfv36GS+99JKJyX1DdXX1N85ULyoqMiwWi/H0008bBw4cMEpKSozp06cb11xzjdHc3GxeWC/3bWvhcrmMtLQ0Y/LkycbHH39s/P3vfzfS09ONadOmmRfUB3zbWnydfpumd3zbWvzlL38x+vXrZyxevNg4ceJEx+3UqVPmBfUAXnnOSGfZ7XbeeOMNpkyZwtixY3n22Wd55JFHLriGSHh4OH/+85+prq7muuuu49FHHyU3N1dt1yRTp07lj3/8I2+//Tbjxo3jlltuwW63s3XrVoKCgsyO51OsViuFhYVERkYyefJkZsyYwZgxY3jjjTfMjiZimt/97nc0NzeTl5fH4MGDO266FtKleeU5IyIiIuI5fHoyIiIiIuZTGRERERFTqYyIiIiIqVRGRERExFQqIyIiImIqlRERERExlcqIiIiImEplREREREylMiIiIiKmUhkRERERU6mMiIiIiKlURkRERMRU/z+dvV5iS4AepgAAAABJRU5ErkJggg==", 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", 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", 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5uVq0aJECgUBMmz179qi0tFQZGRkaOXKkli9fLmNMTJvXX39dU6dOVXp6usaNG6e1a9f21dfqtp1HmrWvwSe3067Zn2B0BwCAZOnTy4UCgYC+/OUvq6SkROvWrbtseygU0syZM5WXl6etW7fq1KlTmjdvnowxWrNmjSTJ5/NpxowZmj59unbs2KGDBw+qoqJCmZmZeuihhyRJhw4d0p133qnKyko988wzeuONN7RgwQLl5eXpnnvu6cuv2KWfdYzu3D1lpLIzXUmrAwCA657pBz/72c+Mx+O5bP3GjRuN3W43x44di65bv369cbvdxuv1GmOMefLJJ43H4zGtra3RNqtWrTIFBQUmHA4bY4x5+OGHzYQJE2L2/eCDD5pbb7212zV6vV4jKfq516rxTIsZt+RlM+Zbvzf7jvXOPgEAQKzu9t9JncOzbds2TZ48WQUFBdF15eXl8vv92rlzZ7RNaWmp3G53TJuGhgYdPnw42qasrCxm3+Xl5aqpqVEwGOz7L5LAi389qlDY6BNF2ZpUkJWUGgAAQLukBp6mpiYNHz48Zl12drZcLpeampo6bRN5f6U2bW1tOnnyZMLP9vv98vl8MUtvMcboxb8elSR9mSuzAABIuh4HnmXLlslms3W51NTUdHt/NpvtsnXGmJj18W1Mx4Tlnra51KpVq+TxeKJLYWHvBZPdR716/8R5pafZ9fnJ+b22XwAAcHV6PGl54cKFmj17dpdtioqKurWv/Px8bd++PWZdc3OzgsFgdMQmPz8/OpITcfz4cUm6Yhun06mcnJyEn71kyRJVVVVF3/t8vl4LPb/tGN0pm5SvIelpvbJPAABw9XoceHJzc5Wbm9srH15SUqIVK1aosbFRI0aMkCRVV1fL7XZr6tSp0TZLly5VIBCQy+WKtikoKIgGq5KSEm3YsCFm39XV1SouLlZaWuLA4Xa7Y+YF9ZZAW1gbdjdKkv6fj4/s9f0DAICe69M5PHV1ddq1a5fq6uoUCoW0a9cu7dq1S+fOnZMklZWVadKkSZo7d65qa2u1efNmLV68WJWVlcrKap/oO2fOHLndblVUVGjv3r166aWXtHLlSlVVVUVPV82fP19HjhxRVVWVDhw4oKefflrr1q3T4sWL+/LrJfSnv53Q6fMB5Q526398qHeCIQAAuEZ9eanYvHnzjKTLli1btkTbHDlyxMycOdNkZGSYYcOGmYULF8Zcgm6MMbt37za33367cbvdJj8/3yxbtix6SXrEa6+9Zj72sY8Zl8tlioqKzFNPPdWjWnvrsvTFL+wyY771e/Pd/7vnmvYDAACurLv9t82YuFsWX6d8Pp88Ho+8Xm90dKmn2kJhfWLFq2q+ENR/Vk7Tp8YzwgMAQF/qbv/Ns7R6Uc2RZjVfCGrooDR9smhYsssBAAAdCDy96I/72q8Uu2PCcDkd/GkBABgo6JV7iTFGrx74QJJUfvPwK7QGAAD9icDTSw6fuqD60y1Kc9h0G1dnAQAwoBB4esl/HzwhSSoeM0yZ7j59CD0AAOghAk8v+dPf2gPPp2/MS3IlAAAgHoGnFwTawtr23ilJ0u0f5nQWAAADDYGnF/y1rlnnAyHlDnZp0oiru4cPAADoOwSeXrD9/dOSpJLxubLbEz+dHQAAJA+BpxfsONweeD45lpsNAgAwEBF4rlEwFNbOI82SxN2VAQAYoAg812hfg08twZCGDkrTh28YnOxyAABAAgSea7TjUPvprOIxw5i/AwDAAEXguUbbOwLPNObvAAAwYBF4roExRrvqz0iSPj4mO7nFAACAThF4rkGjt1Unz/nltNt0cwH33wEAYKAi8FyD3UfPSJJuHD5E6WmO5BYDAAA6ReC5BruPeiVJHy30JLkSAADQFQLPNYgEno+MHJrcQgAAQJcIPFfJGBM9pXXLKEZ4AAAYyAg8V+nIqQvytbbJ5bTrpvwhyS4HAAB0gcBzlfY2tJ/Ompg/RGkO/owAAAxk9NRX6WDTWUnShHwuRwcAYKAj8FyltzsCD6ezAAAY+Ag8V+ngBwQeAABSBYHnKlwItOnI6QuSCDwAAKQCAs9VePf4ORkj5WS6lDvYnexyAADAFRB4rgLzdwAASC0EnqsQuULrxuEEHgAAUgGB5yq880HkknQCDwAAqYDAcxXeP3FekvShGwYnuRIAANAdBJ4eag2G1OBtkSQV5WYmuRoAANAdBJ4eqjt9QcZIQ9xO5WS6kl0OAADoBgJPDx062X46qyg3UzabLcnVAACA7iDw9NDhjsAzltNZAACkDAJPDx0+dXGEBwAApAYCTw8dio7wDEpyJQAAoLsIPD10+GT7M7SKchjhAQAgVRB4eqAlEFKTr1USc3gAAEglBJ4eiMzfGTooTUMHcUk6AACpgsDTA3Wn209njeF0FgAAKYXA0wPHmtvvsDxqaEaSKwEAAD1B4OmBhjPtgadgaHqSKwEAAD1B4OmByDO0ChjhAQAgpRB4eiBySmskgQcAgJRC4OmBY2faL0lnhAcAgNRC4Omm1mBIJ8/5JTHCAwBAqiHwdFOjt310Z5DLoaGD0pJcDQAA6AkCTzddvEIrQzabLcnVAACAniDwdFNkwjLzdwAASD0Enm46diZyhRb34AEAINUQeLrpYuBhhAcAgFRD4OmmyByeER4CDwAAqYbA003Hz7Zfkp7v4ZQWAACphsDTTSc6As8NQ9xJrgQAAPQUgacb/G0heVuCkqQ8Ag8AACmnzwLP4cOH9fWvf11jx45VRkaGxo8fr0cffVSBQCCmXV1dnWbNmqXMzEzl5uZq0aJFl7XZs2ePSktLlZGRoZEjR2r58uUyxsS0ef311zV16lSlp6dr3LhxWrt2ba99l8jojsthlyeDmw4CAJBqnH2147ffflvhcFj/8R//oQ996EPau3evKisrdf78ea1evVqSFAqFNHPmTOXl5Wnr1q06deqU5s2bJ2OM1qxZI0ny+XyaMWOGpk+frh07dujgwYOqqKhQZmamHnroIUnSoUOHdOedd6qyslLPPPOM3njjDS1YsEB5eXm65557rvm7RAJP3hA3Nx0EACAVmX70wx/+0IwdOzb6fuPGjcZut5tjx45F161fv9643W7j9XqNMcY8+eSTxuPxmNbW1mibVatWmYKCAhMOh40xxjz88MNmwoQJMZ/14IMPmltvvbXbtXm9XiMp+rmX+uPeRjPmW783d/1ka7f3BwAA+l5X/fel+nUOj9fr1bBhw6Lvt23bpsmTJ6ugoCC6rry8XH6/Xzt37oy2KS0tldvtjmnT0NCgw4cPR9uUlZXFfFZ5eblqamoUDAYT1uL3++Xz+WKWzpzoeGho3mDm7wAAkIr6LfC89957WrNmjebPnx9d19TUpOHDh8e0y87OlsvlUlNTU6dtIu+v1KatrU0nT55MWM+qVavk8XiiS2FhYae1H/ddPKUFAABST48Dz7Jly2Sz2bpcampqYn6noaFBn/vc5/TlL39ZDzzwQMy2RHNijDEx6+PbmI4Jyz1tc6klS5bI6/VGl/r6+k6/c2SEh0vSAQBITT2etLxw4ULNnj27yzZFRUXR1w0NDZo+fbpKSkr005/+NKZdfn6+tm/fHrOuublZwWAwOmKTn58fHcmJOH78uCRdsY3T6VROTk7CGt1ud8xpsq5cOmkZAACknh4HntzcXOXm5nar7bFjxzR9+nRNnTpVP/vZz2S3xw4olZSUaMWKFWpsbNSIESMkSdXV1XK73Zo6dWq0zdKlSxUIBORyuaJtCgoKosGqpKREGzZsiNl3dXW1iouLlZZ27ZeRE3gAAEhtfTaHp6GhQZ/5zGdUWFio1atX68SJE2pqaooZiSkrK9OkSZM0d+5c1dbWavPmzVq8eLEqKyuVlZUlSZozZ47cbrcqKiq0d+9evfTSS1q5cqWqqqqip6vmz5+vI0eOqKqqSgcOHNDTTz+tdevWafHixb3yXbjLMgAAqa3P7sNTXV2td999V++++65GjRoVsy0yv8bhcOjll1/WggULdNtttykjI0Nz5syJ3qdHkjwejzZt2qR//Md/VHFxsbKzs1VVVaWqqqpom7Fjx2rjxo365je/qX//939XQUGBnnjiiV65B48xhhEeAABSnM2YuFsWX6d8Pp88Ho+8Xm90dEmSvBeC+ujyaknS29/7nNLTHMkqEQAAxOms/47Hs7Su4MS5VklSVrqTsAMAQIoi8FzBibPtz/XidBYAAKmLwHMFzRfaA09OJoEHAIBUReC5gtPn2wPP0EE8JR0AgFRF4LmC5o7AMyzTleRKAADA1SLwXMHpjlNa2QQeAABSFoHnCqIjPIMIPAAApCoCzxWcvhCUxAgPAACpjMBzBWcip7SYtAwAQMoi8FxB5CotRngAAEhdBJ4rYA4PAACpj8DThdZgSOcDIUmM8AAAkMoIPF040zFh2WG3KSu9zx4sDwAA+hiBpwvNl0xYttlsSa4GAABcLQJPFyKBZyjzdwAASGkEni74WtpPaXkyuCQdAIBURuDpgq+lTZKYvwMAQIoj8HTBywgPAACWQODpgq+1PfBkEXgAAEhpBJ4uMMIDAIA1EHi6EJm0nJVO4AEAIJUReLrACA8AANZA4OmCr7XjKq0MrtICACCVEXi6ED2lxQgPAAApjcDTBS9zeAAAsAQCTxcil6UzhwcAgNRG4OmEvy2k1mBYEqe0AABIdQSeTkQeK2GzSUPcTFoGACCVEXg6EZm/M8TtlN1uS3I1AADgWhB4OsFjJQAAsA4CTyfOddyDZwhXaAEAkPIIPJ045+8IPMzfAQAg5RF4OhEJPJluR5IrAQAA14rA04nIKa1MRngAAEh5BJ5OnI+c0kon8AAAkOoIPJ2IntJyEXgAAEh1BJ5ORALPYEZ4AABIeQSeTkQDD3N4AABIeQSeTpwn8AAAYBkEnk6c5SotAAAsg8DTifMB5vAAAGAVBJ5ORO7DwyktAABSH4GnE+f8IUkEHgAArIDA04lz/vanpRN4AABIfQSeBNpCYbUGw5IIPAAAWAGBJ4HzHaezJK7SAgDACgg8CZzruELL5bTL5eRPBABAqqM3T4ArtAAAsBYCTwLRB4e6HUmuBAAA9AYCTwItgfY5PDwpHQAAayDwJHChYw5PehojPAAAWAGBJ4GWYPsIzyAXgQcAACsg8CRwIUDgAQDASgg8CUQCTwZzeAAAsAQCTwKtkVNazOEBAMASCDwJRCYtZ3BKCwAAS+jTwHPXXXdp9OjRSk9P14gRIzR37lw1NDTEtKmrq9OsWbOUmZmp3NxcLVq0SIFAIKbNnj17VFpaqoyMDI0cOVLLly+XMSamzeuvv66pU6cqPT1d48aN09q1a6+67ountAg8AABYQZ8GnunTp+uFF17QO++8oxdffFHvvfee/u7v/i66PRQKaebMmTp//ry2bt2q5557Ti+++KIeeuihaBufz6cZM2aooKBAO3bs0Jo1a7R69Wo99thj0TaHDh3SnXfeqdtvv121tbVaunSpFi1apBdffPGq6o7ch4dTWgAAWITpR7/73e+MzWYzgUDAGGPMxo0bjd1uN8eOHYu2Wb9+vXG73cbr9RpjjHnyySeNx+Mxra2t0TarVq0yBQUFJhwOG2OMefjhh82ECRNiPuvBBx80t956a7dr83q9RpLxer1m0fq/mjHf+r35//77vav+rgAAoO9d2n93pd/m8Jw+fVrPPvusPvWpTyktLU2StG3bNk2ePFkFBQXRduXl5fL7/dq5c2e0TWlpqdxud0ybhoYGHT58ONqmrKws5vPKy8tVU1OjYDCYsB6/3y+fzxezRHBKCwAAa+nzwPOtb31LmZmZysnJUV1dnX73u99FtzU1NWn48OEx7bOzs+VyudTU1NRpm8j7K7Vpa2vTyZMnE9a1atUqeTye6FJYWBjd1sJ9eAAAsJQeB55ly5bJZrN1udTU1ETb//M//7Nqa2tVXV0th8Ohr33tazETjm0222WfYYyJWR/fJvL7PW1zqSVLlsjr9UaX+vr66LboVVpp3IcHAAAr6HGPvnDhQs2ePbvLNkVFRdHXubm5ys3N1Y033qiJEyeqsLBQb775pkpKSpSfn6/t27fH/G5zc7OCwWB0xCY/Pz86khNx/PhxSbpiG6fTqZycnIQ1ut3umNNkl2oJhiUxwgMAgFX0OPBEAszViIy6+P1+SVJJSYlWrFihxsZGjRgxQpJUXV0tt9utqVOnRtssXbpUgUBALpcr2qagoCAarEpKSrRhw4aYz6qurlZxcXF0vlBPtHSM8BB4AACwhj6bw/OXv/xFP/nJT7Rr1y4dOXJEW7Zs0Zw5czR+/HiVlJRIksrKyjRp0iTNnTtXtbW12rx5sxYvXqzKykplZWVJkubMmSO3262Kigrt3btXL730klauXKmqqqro6ar58+fryJEjqqqq0oEDB/T0009r3bp1Wrx48VXVHpm0zNPSAQCwhj4LPBkZGfrtb3+rO+64QzfddJPuv/9+TZ48Wa+//nr0VJLD4dDLL7+s9PR03Xbbbbr33nt19913a/Xq1dH9eDwebdq0SUePHlVxcbEWLFigqqoqVVVVRduMHTtWGzdu1GuvvaYpU6boe9/7np544gndc889V1U7k5YBALAWmzFxtyy+Tvl8Pnk8Hp05c0Yf/8EbCoWN3lxyh/I96ckuDQAAdCLSf3u93ujZoUR4llacYMgoFG7PgNyHBwAAayDwxImczpKkDObwAABgCQSeOC3B9iu0nHabXE7+PAAAWAE9epwLQR4rAQCA1RB44rRyhRYAAJZD4InTGuQePAAAWA2BJ06grf0KrXQngQcAAKsg8MRpbYuM8PCnAQDAKujV4wTa2h8c6maEBwAAyyDwxInM4XEzwgMAgGXQq8fxM8IDAIDlEHjiBNoY4QEAwGro1eO0dozwcJUWAADWQeCJEwi2X5bOCA8AANZBrx7HHzmlxXO0AACwDHr1ONFTWtxpGQAAyyDwxAkwwgMAgOXQq8dpDTLCAwCA1RB44jDCAwCA9dCrx/GHuPEgAABWQ+CJc/GUFn8aAACsgl49Dg8PBQDAegg8cfxtjPAAAGA19OpxLk5aZoQHAACrIPDEiT4tnREeAAAsg149TmuwfYSHh4cCAGAdBJ44AUZ4AACwHHr1ODw8FAAA66FXj+NvM5J4tAQAAFZC4IkTCrcHHkZ4AACwDnr1TjDCAwCAdRB4OuFy8KcBAMAq6NUTcDnsstttyS4DAAD0EgJPAlySDgCAtdCzJ8BjJQAAsBYCTwJcoQUAgLXQsydA4AEAwFro2RNI4wotAAAshZ49gTQnV2gBAGAlBJ4EuAcPAADWQs+eAKe0AACwFnr2BFxMWgYAwFLo2RNghAcAAGuhZ0+AOTwAAFgLPXsCaZzSAgDAUujZE0hzcFk6AABWQuBJgDstAwBgLfTsCTBpGQAAa6FnT4DAAwCAtdCzJ0DgAQDAWujZE+DGgwAAWAs9ewIurtICAMBSCDwJcEoLAABroWdPgFNaAABYCz17AozwAABgLf3Ss/v9fk2ZMkU2m027du2K2VZXV6dZs2YpMzNTubm5WrRokQKBQEybPXv2qLS0VBkZGRo5cqSWL18uY0xMm9dff11Tp05Venq6xo0bp7Vr1151vTxLCwAAa3H2x4c8/PDDKigo0FtvvRWzPhQKaebMmcrLy9PWrVt16tQpzZs3T8YYrVmzRpLk8/k0Y8YMTZ8+XTt27NDBgwdVUVGhzMxMPfTQQ5KkQ4cO6c4771RlZaWeeeYZvfHGG1qwYIHy8vJ0zz339LjeNCeTlgEAsJI+DzyvvPKKqqur9eKLL+qVV16J2VZdXa39+/ervr5eBQUFkqQf/ehHqqio0IoVK5SVlaVnn31Wra2t+vnPfy63263Jkyfr4MGDeuyxx1RVVSWbzaa1a9dq9OjRevzxxyVJEydOVE1NjVavXn1VgcflcFzz9wYAAANHn567+eCDD1RZWalf/epXGjRo0GXbt23bpsmTJ0fDjiSVl5fL7/dr586d0TalpaVyu90xbRoaGnT48OFom7Kysph9l5eXq6amRsFgMGFtfr9fPp8vZong4aEAAFhLnwUeY4wqKio0f/58FRcXJ2zT1NSk4cOHx6zLzs6Wy+VSU1NTp20i76/Upq2tTSdPnkz42atWrZLH44kuhYWF0W1pXKUFAICl9LhnX7ZsmWw2W5dLTU2N1qxZI5/PpyVLlnS5P5vt8tEUY0zM+vg2kQnLPW1zqSVLlsjr9UaX+vr66DY3k5YBALCUHs/hWbhwoWbPnt1lm6KiIn3/+9/Xm2++GXMqSpKKi4t133336Re/+IXy8/O1ffv2mO3Nzc0KBoPREZv8/PzoSE7E8ePHJemKbZxOp3JychLW6Ha7L6stghEeAACspceBJzc3V7m5uVds98QTT+j73/9+9H1DQ4PKy8v1/PPPa9q0aZKkkpISrVixQo2NjRoxYoSk9onMbrdbU6dOjbZZunSpAoGAXC5XtE1BQYGKioqibTZs2BDz+dXV1SouLlZaWlpPvyL34QEAwGL6rGcfPXq0Jk+eHF1uvPFGSdL48eM1atQoSVJZWZkmTZqkuXPnqra2Vps3b9bixYtVWVmprKwsSdKcOXPkdrtVUVGhvXv36qWXXtLKlSujV2hJ0vz583XkyBFVVVXpwIEDevrpp7Vu3TotXrz4qmpn0jIAANaS1KEMh8Ohl19+Wenp6brtttt077336u6779bq1aujbTwejzZt2qSjR4+quLhYCxYsUFVVlaqqqqJtxo4dq40bN+q1117TlClT9L3vfU9PPPHEVV2SLkluTmkBAGApNhN/y+LrlM/na79a659e0J++c6fG5GQmuyQAAHAFkf7b6/VGzw4lwlBGAszhAQDAWujZE+Bp6QAAWAs9ewKM8AAAYC307AnwtHQAAKyFnj0BLksHAMBaCDxx7DbJyQgPAACWQs8eh7ADAID10LvHcXE6CwAAyyHwxGHCMgAA1kPvHsfJCA8AAJZD4InDHB4AAKyH3j2O084IDwAAVkPgicMIDwAA1kPvHocRHgAArIfAE8dB4AEAwHIIPHEcdv4kAABYDb17nDRGeAAAsBwCTxxOaQEAYD0EnjhpXKUFAIDl0LvHYQoPAADWQ/ceJ41HSwAAYDkEnjjM4QEAwHoIPHGcnNMCAMBy6N3jMMIDAID1EHjiMMIDAID10LvH4VlaAABYD4EnjpOrtAAAsBwCTxxGeAAAsB4CTxwHd1oGAMBy6N3jMMIDAID1EHjiEHgAALAeAk8cB5elAwBgOfTucRjhAQDAegg8cRyOZFcAAAB6G4EnThqntAAAsBx69zg8SwsAAOsh8MRJ407LAABYDoEnjp1TWgAAWA69exyu0gIAwHoIPHEIPAAAWA+BJ46TZ2kBAGA59O5xGOEBAMB6CDxxuCwdAADrIfDEcXJZOgAAlkPgiePksnQAACyH3j2O08YIDwAAVkPgiePglBYAAJZD4InDpGUAAKyHwBOHZ2kBAGA9BJ44jPAAAGA9BJ44adxpGQAAy6F3j2NnhAcAAMsh8MRJ4z48AABYDr17HObwAABgPQSeOGkEHgAALIfAE4cRHgAArKdPA09RUZFsNlvM8u1vfzumTV1dnWbNmqXMzEzl5uZq0aJFCgQCMW327Nmj0tJSZWRkaOTIkVq+fLmMMTFtXn/9dU2dOlXp6ekaN26c1q5de1U1O7hKCwAAy3H29QcsX75clZWV0feDBw+Ovg6FQpo5c6by8vK0detWnTp1SvPmzZMxRmvWrJEk+Xw+zZgxQ9OnT9eOHTt08OBBVVRUKDMzUw899JAk6dChQ7rzzjtVWVmpZ555Rm+88YYWLFigvLw83XPPPT2q18kIDwAAltPngWfIkCHKz89PuK26ulr79+9XfX29CgoKJEk/+tGPVFFRoRUrVigrK0vPPvusWltb9fOf/1xut1uTJ0/WwYMH9dhjj6mqqko2m01r167V6NGj9fjjj0uSJk6cqJqaGq1evbrngYc7LQMAYDl9fv7mBz/4gXJycjRlyhStWLEi5nTVtm3bNHny5GjYkaTy8nL5/X7t3Lkz2qa0tFRutzumTUNDgw4fPhxtU1ZWFvO55eXlqqmpUTAYTFiX3++Xz+eLWSTJyWXpAABYTp/27t/4xjf03HPPacuWLVq4cKEef/xxLViwILq9qalJw4cPj/md7OxsuVwuNTU1ddom8v5Kbdra2nTy5MmEta1atUoejye6FBYWSmLSMgAAVtTjwLNs2bLLJiLHLzU1NZKkb37zmyotLdUtt9yiBx54QGvXrtW6det06tSp6P5stssDhjEmZn18m8iE5Z62udSSJUvk9XqjS319fU/+DAAAIIX0eA7PwoULNXv27C7bFBUVJVx/6623SpLeffdd5eTkKD8/X9u3b49p09zcrGAwGB2xyc/Pj47kRBw/flySrtjG6XQqJycnYS1utzvmNBkAALCuHgee3Nxc5ebmXtWH1dbWSpJGjBghSSopKdGKFSvU2NgYXVddXS23262pU6dG2yxdulSBQEAulyvapqCgIBqsSkpKtGHDhpjPqq6uVnFxsdLS0q6qVgAAYB19Nodn27Zt+vGPf6xdu3bp0KFDeuGFF/Tggw/qrrvu0ujRoyVJZWVlmjRpkubOnava2lpt3rxZixcvVmVlpbKysiRJc+bMkdvtVkVFhfbu3auXXnpJK1eujF6hJUnz58/XkSNHVFVVpQMHDujpp5/WunXrtHjx4r76egAAIJWYPrJz504zbdo04/F4THp6urnpppvMo48+as6fPx/T7siRI2bmzJkmIyPDDBs2zCxcuNC0trbGtNm9e7e5/fbbjdvtNvn5+WbZsmUmHA7HtHnttdfMxz72MeNyuUxRUZF56qmnelSv1+s1kozX6726LwwAAPpdd/tvmzFxtyy+Tvl8Pnk8Hnm93ujoEgAAGNi6239z0xkAAGB5BB4AAGB5BB4AAGB5BB4AAGB5BB4AAGB5BB4AAGB5BB4AAGB5BB4AAGB5BB4AAGB5BB4AAGB5BB4AAGB5BB4AAGB5BB4AAGB5BB4AAGB5BB4AAGB5zmQXMFAYYyRJPp8vyZUAAIDuivTbkX68MwSeDmfPnpUkFRYWJrkSAADQU2fPnpXH4+l0u81cKRJdJ8LhsBoaGjRkyBDZbLZr3p/P51NhYaHq6+uVlZXVCxXianEsBg6OxcDBsRg4OBbXxhijs2fPqqCgQHZ75zN1GOHpYLfbNWrUqF7fb1ZWFv+ABwiOxcDBsRg4OBYDB8fi6nU1shPBpGUAAGB5BB4AAGB5BJ4+4na79eijj8rtdie7lOsex2Lg4FgMHByLgYNj0T+YtAwAACyPER4AAGB5BB4AAGB5BB4AAGB5BB4AAGB5BJ5eVlRUJJvNFrN8+9vfjmlTV1enWbNmKTMzU7m5uVq0aJECgUCSKr4++P1+TZkyRTabTbt27YrZtmPHDt1xxx0aOnSosrOzVVZWdlkb9J6ujoUk/fznP9ctt9yi9PR05efna+HChf1f5HXiSsdCkk6dOqVRo0bJZrPpzJkz/Vrf9aSzY/HWW2/pK1/5igoLC5WRkaGJEyfq3/7t35JXaAoj8PSB5cuXq7GxMbp85zvfiW4LhUKaOXOmzp8/r61bt+q5557Tiy++qIceeiiJFVvfww8/rIKCgsvWnz17VuXl5Ro9erS2b9+urVu3KisrS+Xl5QoGg0mo1Po6OxaS9Nhjj+mRRx7Rt7/9be3bt0+bN29WeXl5P1d4/ejqWER8/etf1y233NJPFV2/OjsWO3fuVF5enp555hnt27dPjzzyiJYsWaKf/OQnSagyxRn0qjFjxpgf//jHnW7fuHGjsdvt5tixY9F169evN26323i93n6o8PqzceNGM2HCBLNv3z4jydTW1ka37dixw0gydXV10XW7d+82ksy7776bhGqtratjcfr0aZORkWFeffXV5BV4HenqWEQ8+eSTprS01GzevNlIMs3Nzf1e5/WgO8fiUgsWLDDTp0/vn+IshBGePvCDH/xAOTk5mjJlilasWBFzumrbtm2aPHlyTJIvLy+X3+/Xzp07k1GupX3wwQeqrKzUr371Kw0aNOiy7TfddJNyc3O1bt06BQIBtbS0aN26dbr55ps1ZsyYJFRsXVc6Fps2bVI4HNaxY8c0ceJEjRo1Svfee6/q6+uTUK21XelYSNL+/fu1fPly/fKXv+zygYy4Nt05FvG8Xq+GDRvWx5VZD/+Ke9k3vvENPffcc9qyZYsWLlyoxx9/XAsWLIhub2pq0vDhw2N+Jzs7Wy6XS01NTf1drqUZY1RRUaH58+eruLg4YZshQ4botdde0zPPPKOMjAwNHjxYf/zjH7Vx40Y5nTxbt7d051i8//77CofDWrlypR5//HH95je/0enTpzVjxgzmuPWi7hwLv9+vr3zlK/rXf/1XjR49up8rvH5051jE27Ztm1544QU9+OCDfVyd9RB4umHZsmWXTUSOX2pqaiRJ3/zmN1VaWqpbbrlFDzzwgNauXat169bp1KlT0f3ZbLbLPsMYk3A9Ltfd47FmzRr5fD4tWbKk0321tLTo/vvv12233aY333xTb7zxhm6++Wbdeeedamlp6cdvlZp681iEw2EFg0E98cQTKi8v16233qr169frb3/7m7Zs2dKP3yo19eaxWLJkiSZOnKivfvWr/fgNrKM3j8Wl9u3bpy9+8Yv67ne/qxkzZvTxt7AeHi3RDSdPntTJkye7bFNUVKT09PTL1h87dkyjRo3Sm2++qWnTpum73/2ufve73+mtt96KtmlubtawYcP0X//1X5o+fXqv12813T0es2fP1oYNG2KCZCgUksPh0H333adf/OIXWrdunZYuXarGxsbosH0gEFB2drbWrVun2bNn9+l3SXW9eSx+9rOf6f7771d9fb1GjRoVbTd8+HB9//vfV2VlZZ99DyvozWMxZcoU7dmzJ9rGGKNwOCyHw6FHHnlE//Iv/9Kn3yXV9eaxiNi/f7+mT5+uBx54QCtWrOiz2q2MwNPHfv/732vWrFk6cuSIRo8erVdeeUVf+MIXdPToUY0YMUKS9Pzzz2vevHk6fvy4srKyklyxddTV1cnn80XfNzQ0qLy8XL/5zW80bdo0jRo1SmvWrNHKlSvV0NAQ/Y9OW1ubhg4dqp/+9KeaM2dOssq3lO4ci4MHD+qmm27Sq6++qjvuuEOSdPr0aeXl5emVV15RWVlZssq3lO4ci/feey9mhHPHjh26//779ec//1njx4/XDTfckIzSLac7x0JqH9n57Gc/q3nz5umHP/xhsspNfcmaLW1Ff/7zn81jjz1mamtrzfvvv2+ef/55U1BQYO66665om7a2NjN58mRzxx13mL/+9a/m1VdfNaNGjTILFy5MYuXXh0OHDl12BcSBAweM2+02//AP/2D2799v9u7da7761a8aj8djGhoaklesxSU6FsYY88UvftHcfPPN5o033jB79uwxX/jCF8ykSZNMIBBITqHXgc6OxaW2bNnCVVr9INGx2Lt3r8nLyzP33XefaWxsjC7Hjx9PXqEpijk8vcjtduv555/XZz7zGU2aNEnf/e53VVlZqfXr10fbOBwOvfzyy0pPT9dtt92me++9V3fffbdWr16dxMqvXxMmTNCGDRu0e/dulZSU6Pbbb1dDQ4P+8Ic/REfg0H9++ctfatq0aZo5c6ZKS0uVlpamP/zhD0pLS0t2aUBS/PrXv9aJEyf07LPPasSIEdHlE5/4RLJLSzmc0gIAAJbHCA8AALA8Ag8AALA8Ag8AALA8Ag8AALA8Ag8AALA8Ag8AALA8Ag8AALA8Ag8AALA8Ag8AALA8Ag8AALA8Ag8AALA8Ag8AALC8/x8DIsVwlOn33AAAAABJRU5ErkJggg==", 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" ] @@ -314,14 +313,6 @@ } }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/hostedtoolcache/Python/3.10.12/x64/lib/python3.10/site-packages/HARK/metric.py:52: UserWarning: Arrays of different shapes. Returning differences in size.\n", - " warn(\"Arrays of different shapes. Returning differences in size.\")\n" - ] - }, { "name": "stdout", "output_type": "stream", @@ -331,7 +322,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -353,14 +344,12 @@ ] }, { - "cell_type": "code", - "execution_count": 9, + "cell_type": "markdown", "metadata": { "incorrectly_encoded_metadata": "pycharm= [markdown] {\"name\": \"#%% md\\n\"}" }, - "outputs": [], "source": [ - "# At this time, the value function for a perfect foresight consumer with an artificial borrowing constraint is not computed nor included as part of its $\\texttt{solution}$." + "At this time, the value function for a perfect foresight consumer with an artificial borrowing constraint is not computed nor included as part of its $\\texttt{solution}$." ] }, { @@ -369,7 +358,7 @@ "source": [ "## Simulating the perfect foresight consumer model\n", "\n", - "Suppose we wanted to simulate many consumers who share the parameter values that we passed to `PerfForesightConsumerType`-- an *ex ante* homogeneous *type* of consumers. To do this, our instance would have to know *how many* agents there are of this type, as well as their initial levels of assets $a_t$ and permanent income $P_t$.\n", + "Suppose we wanted to simulate many consumers who share the parameter values that we passed to `PerfForesightConsumerType` -- an *ex ante* homogeneous *type* of consumers. To do this, our instance would have to know *how many* agents there are of this type, as well as their initial levels of assets $a_t$ and permanent income $P_t$.\n", "\n", "### Setting simulation parameters\n", "\n", @@ -378,26 +367,26 @@ "| Description | Code | Example value |\n", "| :---: | --- | --- |\n", "| Number of consumers of this type | $\\texttt{AgentCount}$ | $10000$ |\n", - "| Number of periods to simulate | $\\texttt{T_sim}$ | $120$ |\n", + "| Number of periods to simulate | $\\texttt{T\\_sim}$ | $120$ |\n", "| Mean of initial log (normalized) assets | $\\texttt{aNrmInitMean}$ | $-6.0$ |\n", "| Stdev of initial log (normalized) assets | $\\texttt{aNrmInitStd}$ | $1.0$ |\n", "| Mean of initial log permanent income | $\\texttt{pLvlInitMean}$ | $0.0$ |\n", "| Stdev of initial log permanent income | $\\texttt{pLvlInitStd}$ | $0.0$ |\n", "| Aggregrate productivity growth factor | $\\texttt{PermGroFacAgg}$ | $1.0$ |\n", - "| Age after which consumers are automatically killed | $\\texttt{T_age}$ | $None$ |\n", + "| Age after which consumers are automatically killed | $\\texttt{T\\_age}$ | $None$ |\n", "\n", "We have specified the model so that initial assets and permanent income are both distributed lognormally, with mean and standard deviation of the underlying normal distributions provided by the user.\n", "\n", "The parameter $\\texttt{PermGroFacAgg}$ exists for compatibility with more advanced models that employ aggregate productivity shocks; it can simply be set to 1.\n", "\n", - "In infinite horizon models, it might be useful to prevent agents from living extraordinarily long lives through a fortuitous sequence of mortality shocks. We have thus provided the option of setting $\\texttt{T_age}$ to specify the maximum number of periods that a consumer can live before they are automatically killed (and replaced with a new consumer with initial state drawn from the specified distributions). This can be turned off by setting it to `None`.\n", + "In infinite horizon models, it might be useful to prevent agents from living extraordinarily long lives through a fortuitous sequence of mortality shocks. We have thus provided the option of setting $\\texttt{T\\_age}$ to specify the maximum number of periods that a consumer can live before they are automatically killed (and replaced with a new consumer with initial state drawn from the specified distributions). This can be turned off by setting it to `None`.\n", "\n", "The cell below puts these parameters into a dictionary, then gives them to `PFexample`. Note that all of these parameters *could* have been passed as part of the original dictionary; we omitted them above for simplicity." ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": { "pycharm": { "name": "#%%\n" @@ -431,14 +420,14 @@ "\n", "### Generating simulated data\n", "\n", - "Before simulating, the `initialize_sim` method must be invoked. This resets our instance back to its initial state, drawing a set of initial $\\texttt{aNrm}$ and $\\texttt{pLvl}$ values from the specified distributions and storing them in the attributes $\\texttt{aNrmNow_init}$ and $\\texttt{pLvlNow_init}$. It also resets this instance's internal random number generator, so that the same initial states will be set every time `initialize_sim` is called. In models with non-trivial shocks, this also ensures that the same sequence of shocks will be generated on every simulation run.\n", + "Before simulating, the `initialize_sim` method must be invoked. This resets our instance back to its initial state, drawing a set of initial $\\texttt{aNrm}$ and $\\texttt{pLvl}$ values from the specified distributions and storing them in the attributes $\\texttt{aNrmNow\\_init}$ and $\\texttt{pLvlNow\\_init}$. It also resets this instance's internal random number generator, so that the same initial states will be set every time `initialize_sim` is called. In models with non-trivial shocks, this also ensures that the same sequence of shocks will be generated on every simulation run.\n", "\n", "Finally, the `simulate` method can be called." ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": { "pycharm": { "name": "#%%\n" @@ -463,7 +452,7 @@ " -5.20458357, -46.23524203]])}" ] }, - "execution_count": 11, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -475,19 +464,17 @@ ] }, { - "cell_type": "code", - "execution_count": 12, + "cell_type": "markdown", "metadata": { "incorrectly_encoded_metadata": "pycharm= [markdown] {\"name\": \"#%% md\\n\"}" }, - "outputs": [], "source": [ - "# Each simulation variable $\\texttt{X}$ named in $\\texttt{track_vars}$ will have the *history* of that variable for each agent stored in the attribute $\\texttt{X_hist}$ as an array of shape $(\\texttt{T_sim},\\texttt{AgentCount})$. To see that the simulation worked as intended, we can plot the mean of $m_t$ in each simulated period:" + "Each simulation variable $\\texttt{X}$ named in $\\texttt{track\\_vars}$ will have the *history* of that variable for each agent stored in the attribute $\\texttt{X\\_hist}$ as an array of shape $(\\texttt{T\\_sim},\\texttt{AgentCount})$. To see that the simulation worked as intended, we can plot the mean of $m_t$ in each simulated period:" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 11, "metadata": { "pycharm": { "name": "#%%\n" @@ -496,7 +483,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -518,14 +505,14 @@ "incorrectly_encoded_metadata": "pycharm= [markdown] {\"name\": \"#%% md\\n\"}" }, "source": [ - "A perfect foresight consumer can borrow against the PDV of his future income-- his human wealth-- and thus as time goes on, our simulated agents approach the (very negative) steady state level of $m_t$ while being steadily replaced with consumers with roughly $m_t=1$.\n", + "A perfect foresight consumer can borrow against the PDV of his future income -- his human wealth -- and thus as time goes on, our simulated agents approach the (very negative) steady state level of $m_t$ while being steadily replaced with consumers with roughly $m_t=1$.\n", "\n", - "The slight wiggles in the plotted curve are due to consumers randomly dying and being replaced; their replacement will have an initial state drawn from the distributions specified by the user. To see the current distribution of ages, we can look at the attribute $\\texttt{t_age}$." + "The slight wiggles in the plotted curve are due to consumers randomly dying and being replaced; their replacement will have an initial state drawn from the distributions specified by the user. To see the current distribution of ages, we can look at the attribute $\\texttt{t\\_age}$." ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 12, "metadata": { "pycharm": { "name": "#%%\n" @@ -534,7 +521,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -562,7 +549,7 @@ "\n", "One might wonder why HARK requires users to call `initialize_sim` before calling `simulate`: Why doesn't `simulate` just call `initialize_sim` as its first step? We have broken up these two steps so that users can simulate some number of periods, change something in the environment, and then resume the simulation.\n", "\n", - "When called with no argument, `simulate` will simulate the model for $\\texttt{T_sim}$ periods. The user can optionally pass an integer specifying the number of periods to simulate (which should not exceed $\\texttt{T_sim}$).\n", + "When called with no argument, `simulate` will simulate the model for $\\texttt{T\\_sim}$ periods. The user can optionally pass an integer specifying the number of periods to simulate (which should not exceed $\\texttt{T\\_sim}$).\n", "\n", "In the cell below, we simulate our perfect foresight consumers for 80 periods, then seize a bunch of their assets (dragging their wealth even more negative), then simulate for the remaining 40 periods.\n", "\n", @@ -571,7 +558,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 13, "metadata": { "pycharm": { "name": "#%%\n" @@ -580,7 +567,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -602,13 +589,6 @@ "plt.ylabel(\"Mean normalized market resources\")\n", "plt.show()" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -632,7 +612,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.12" + "version": "3.9.18" } }, "nbformat": 4,