From e72892c569ce42e85a2ca59da24cae2b96834080 Mon Sep 17 00:00:00 2001 From: Shu Date: Wed, 8 Feb 2023 10:31:55 +1100 Subject: [PATCH] Delete gini_lorenz_us.ipynb --- in-work/gini_lorenz_us.ipynb | 988 ----------------------------------- 1 file changed, 988 deletions(-) delete mode 100644 in-work/gini_lorenz_us.ipynb diff --git a/in-work/gini_lorenz_us.ipynb b/in-work/gini_lorenz_us.ipynb deleted file mode 100644 index c9a4d6b5f..000000000 --- a/in-work/gini_lorenz_us.ipynb +++ /dev/null @@ -1,988 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# gini_lorenz_us_v10" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "import numpy as np\n", - "from numba import njit, prange\n", - "import quantecon as qe\n", - "import matplotlib.pyplot as plt\n", - "from itertools import takewhile\n", - "from scipy.integrate import simps\n", - "from IPython.core.display import display, HTML\n", - "from mpl_toolkits.mplot3d import Axes3D\n", - "from matplotlib import cm\n", - "import itertools\n", - "from interpolation import interp\n", - "from scipy import interpolate\n", - "\n", - "%matplotlib inline" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# overview\n", - "\n", - "Using database ``SCF_plus``, which is constructed by [Kuhn, Schularick and Steins (2020)](https://www.journals.uchicago.edu/doi/10.1086/708815), this notebook plots\n", - "- transitional labor income, total income and net wealth ginis for US\n", - "- lorenz curves for US total income and net wealth in year 2016" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Def. (General Gini coefficients)\n", - "\n", - "For incomes/wealth of $x_i, \\forall i=1, \\cdots, n$ and them ranked in non-decreasing order, the covariance expression for the Gini, $G$, is ([Creedy 2015](https://www.wgtn.ac.nz/cpf/publications/pdfs/2015-pubs/WP03_2015_Gini_Inequality.pdf)):\n", - "$$\n", - "G = \\frac{2 Cov (x, F(x)) }{ \\bar x}\n", - "$$\n", - "where \n", - "- $F(x)$ is the distribution function,\n", - "- $\\bar x$ is the arithmetic mean of the $x_i$,\n", - "- $Cov (x, F(x))$ is the covariance." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## define some functions" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "def topshare(d, c=0.05, x='nw', fw='fw'):\n", - " \n", - " d = d[[x, fw]].sort_values(x, ascending=True).copy()\n", - " \n", - " d['xfw'] = d[x] * d[fw]\n", - " d['Fw'] = d[fw].cumsum()\n", - " \n", - " n = min([index for index,value in enumerate(d['Fw']) if value > (1-c)])\n", - " w = d['xfw']\n", - " wt = w[n:-1]\n", - " \n", - " \n", - " return np.sum(wt) / np.sum(w)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "def plot_ginis(x, y, \n", - " plotlabel=\"total income gini\", \n", - " ylabel=\"gini coefficient\", \n", - " path='wgini_us.pdf'):\n", - " \n", - " fig, ax = plt.subplots()\n", - " ax.plot(x, y, marker='o', label=plotlabel)\n", - "\n", - " ax.set_xlabel(\"year\", fontsize=12)\n", - " ax.set_ylabel(ylabel, fontsize=12)\n", - "\n", - " ax.legend(fontsize=12)\n", - " plt.savefig(path)\n", - " plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "# @njit(parallel=True)\n", - "def gini_coefficient(d, x='nw', aw='wgtI95W95'):\n", - " r\"\"\"\n", - " Implements the Gini inequality index with analytical weights\n", - "\n", - " References\n", - " ----------\n", - "\n", - " https://en.wikipedia.org/wiki/Gini_coefficient\n", - " \"\"\"\n", - " \n", - " d = d[[x, aw]].sort_values(x, ascending=True).copy()\n", - " \n", - " y = d[x]\n", - " \n", - " f_x = d[aw] / d[aw].sum()\n", - " F_x = f_x.cumsum()\n", - " \n", - " mu = np.sum(y * f_x)\n", - " \n", - " cov = np.cov(y, F_x, rowvar=False, aweights=f_x)[0,1]\n", - " \n", - " return 2 * cov / mu" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "def lorenz(d, x='nw', fw='fw'):\n", - " \n", - " d = d[[x, fw]].sort_values(x, ascending=True).copy()\n", - " \n", - " \n", - " d[x] = d[x] * d[fw]\n", - " \n", - " res = d.cumsum() / d.sum()\n", - " \n", - " return res[fw], res[x]" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "def lorenzit():\n", - " return interp(x_s, y_s, x)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "def display_side_by_side(dfs:list, captions:list):\n", - " \"\"\"Display tables side by side to save vertical space\n", - " Input:\n", - " dfs: list of pandas.DataFrame\n", - " captions: list of table captions\n", - " \"\"\"\n", - " output = \"\"\n", - " combined = dict(zip(captions, dfs))\n", - " for caption, df in combined.items():\n", - " output += df.style.set_table_attributes(\"style='display:inline'\").set_caption(caption)._repr_html_()\n", - " output += \"\\xa0\\xa0\\xa0\"\n", - " display(HTML(output))" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "def get_lorenz(df, xname='nw'):\n", - " \n", - " f_vals, l_vals = [], []\n", - " for i in df.groupby('yearmerge').apply(lorenz, x=xname):\n", - " f_vals.append(np.asarray(i[0]))\n", - " l_vals.append(np.asarray(i[1]))\n", - " \n", - " return f_vals, l_vals" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "def lorenz2gini1(y, x):\n", - " \"\"\"\n", - " Measure the area using Trapezoidal rule \n", - " \n", - " Please find here: https://numpy.org/doc/stable/reference/generated/numpy.trapz.html\n", - " \"\"\"\n", - " return (0.5 - np.trapz(y, x=x)) / 0.5" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "def lorenz2gini2(y, x):\n", - " \"\"\"\n", - " Measure the area using simpsons rule\n", - " \n", - " https://scipy.github.io/devdocs/tutorial/integrate.html#integrating-using-samples\n", - " \"\"\"\n", - " return (0.5 - simps(y, x=x)) / 0.5" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## import and process the data\n", - "\n", - "The data is stored here: https://github.com/QuantEcon/high_dim_data/blob/main/SCF_plus/SCF_plus.dta?raw=true.\n", - "\n", - "We can cross-check the following table with [Kuhn, Schularick and Steins (2020)](https://www.journals.uchicago.edu/doi/10.1086/708815)'s." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - 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yearmergetinwlitopnwtoptitopli
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1520040.5275950.8086190.6126100.6930600.4100900.376192
1620070.5521790.8155200.6330410.7128250.4422940.400196
1720100.5442000.8455380.6502700.7436380.4373810.421030
1820130.5576670.8496680.6543720.7483880.4455100.409836
1920160.5814140.8602470.6799590.7708500.4752990.444579
\n", - "
" - ], - "text/plain": [ - " yearmerge ti nw li topnw topti topli\n", - "0 1950 0.442887 0.825467 0.537074 0.728481 0.344888 0.194463\n", - "1 1953 0.425954 0.805667 0.516405 0.716981 0.318291 0.208020\n", - "2 1956 0.452425 0.812515 0.541754 0.720734 0.342615 0.238985\n", - "3 1959 0.438263 0.796247 0.527094 0.699496 0.329404 0.242411\n", - "4 1962 0.444881 0.814602 0.534969 0.724429 0.334118 0.140910\n", - "5 1965 0.436888 0.788713 0.748102 0.688363 0.331124 0.140400\n", - "6 1968 0.428210 0.801978 0.536256 0.706939 0.318522 0.243205\n", - "7 1971 0.427249 0.791657 0.559171 0.688179 0.314425 0.215095\n", - "8 1977 0.461506 0.756274 0.569864 0.640513 0.350292 0.248622\n", - "9 1983 0.456792 0.775618 0.571856 0.662277 0.335159 0.263979\n", - "10 1989 0.527126 0.789176 0.604547 0.670077 0.400109 0.336962\n", - "11 1992 0.494583 0.784872 0.605767 0.667867 0.365408 0.325224\n", - "12 1995 0.521231 0.789405 0.606393 0.677522 0.382618 0.348431\n", - "13 1998 0.518514 0.799358 0.588948 0.685094 0.395004 0.339899\n", - "14 2001 0.540124 0.804660 0.610213 0.694177 0.423103 0.381357\n", - "15 2004 0.527595 0.808619 0.612610 0.693060 0.410090 0.376192\n", - "16 2007 0.552179 0.815520 0.633041 0.712825 0.442294 0.400196\n", - "17 2010 0.544200 0.845538 0.650270 0.743638 0.437381 0.421030\n", - "18 2013 0.557667 0.849668 0.654372 0.748388 0.445510 0.409836\n", - "19 2016 0.581414 0.860247 0.679959 0.770850 0.475299 0.444579" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df = pd.read_stata('https://github.com/QuantEcon/high_dim_data/blob/main/SCF_plus/SCF_plus.dta?raw=true')\n", - "df = df[['id', 'year', 'ffanw', 'impnum', 'tinc', 'incws', \n", - " 'yearmerge', 'wgtI95W95', 'ffanwgroups', 'tincgroups']]\n", - "df['nw'] = df['ffanw'] \n", - "df['ti'] = df['tinc']\n", - "df['li'] = df['incws']\n", - "df1=df.astype({'yearmerge': int, 'year': int}).dropna()\n", - "df2 = df1.groupby('yearmerge').sum().reset_index()\n", - "\n", - "# calculate variables with weights\n", - "\n", - "df3 = df2[['yearmerge', 'wgtI95W95']]\n", - "df3.columns = 'yearmerge', 'fw'\n", - "df4 = pd.merge(df3, df1, how=\"left\", on=[\"yearmerge\"])\n", - "df4['fw'] = df4['wgtI95W95'] / df4['fw']\n", - "df4['nwfw'] = df4['nw'] * df4['fw']\n", - "df4['tifw'] = df4['ti'] * df4['fw']\n", - "df4['lifw'] = df4['li'] * df4['fw']\n", - "\n", - "dfx_1 = df4.groupby('yearmerge').sum().reset_index()\n", - "df5 = df4[df4['ffanwgroups'] == 'Top 10%']\n", - "df6 = df4[df4['tincgroups'] == 'Top 10%']\n", - "\n", - "dfx_2 = df5.groupby('yearmerge').sum().reset_index()\n", - "dfx_3 = df6.groupby('yearmerge').sum().reset_index()\n", - "\n", - "dfx_1['nwfwtop10'] = dfx_2['nwfw']\n", - "dfx_1['tifwtop10'] = dfx_3['tifw']\n", - "dfx_1['lifwtop10'] = dfx_3['lifw']\n", - "\n", - "dfx_1['nwfw'] = dfx_1['nwfwtop10'] / dfx_1['nwfw']\n", - "dfx_1['tifw'] = dfx_1['tifwtop10'] / dfx_1['tifw']\n", - "dfx_1['lifw'] = dfx_1['lifwtop10'] / dfx_1['lifw']\n", - "dfx_4 = dfx_1[['yearmerge', 'nwfw', 'tifw', 'lifw']]\n", - "\n", - "df7 = df4.groupby('yearmerge').apply(gini_coefficient, x='nw').to_frame().reset_index()\n", - "df7.columns = 'yearmerge', 'nw'\n", - "\n", - "df8 = df4.groupby('yearmerge').apply(gini_coefficient, x='ti').to_frame().reset_index()\n", - "df8.columns = 'yearmerge', 'ti'\n", - "\n", - "df9 = df4.groupby('yearmerge').apply(gini_coefficient, x='li').to_frame().reset_index()\n", - "df9.columns = 'yearmerge', 'li'\n", - "\n", - "df8['nw'] = df7['nw']\n", - "df8['li'] = df9['li']\n", - "df8['topnw'] = dfx_4['nwfw']\n", - "df8['topti'] = dfx_4['tifw']\n", - "df8['topli'] = dfx_4['lifw']\n", - "\n", - "df8" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Dynamic Gini coefficients plots" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "wg = np.asarray(df8['nw'])\n", - "topwg = np.asarray(df8['topnw'])\n", - "it = np.asarray(df8['ti'])\n", - "topit = np.asarray(df8['topti'])\n", - "li = np.asarray(df8['li'])\n", - "topli = np.asarray(df8['topli'])\n", - "years = df8['yearmerge']" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## labor income ginis" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Since values in 1965 are abnormal, we are going to smooth the curves by taking the average of Ginis/top shares in 1962 and 1968 as the values in 1965." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "li_new = li\n", - "topli_new = topli # use the topli from interpolation in section 2.2.2 below\n", - "\n", - "# take the average of Ginis/topshares in 1962 and 1968 for 1965\n", - "\n", - "li_new[5] = (li[4] + li[6]) / 2\n", - "topli_new[5] = (topli[4] + topli[6]) / 2" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plot_ginis(years, topli_new,\n", - " plotlabel=\"top $10\\%$ labor income share\", \n", - " ylabel=\"top $10\\%$ share\",\n", - " path='figures/gini_lorenz_us_2.pdf') # 2.15" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## net wealth ginis" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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RtbZnXJ7nAhfW8x5fAl96IDxjjGmyjdlFlFVUBV3nNtgMbmOMaTarMwsAGBWEVxaWLIwxppmszDhISue2tGsdUf/OAcaShTHGNIOKyirW7j4UlLegwJKFMcY0i825hzlWVmnJwhhjTO1O9FdYsjDGGFOrVZkF9OgQTeeYSF+H4hGWLIwxpomqqpRvdhUE7VUFWLIwxpgm237gCEUl5UG3HpQrSxbGGNNEJ/orxtiVhTHGmNqsyiyga2wk3dpF+ToUj7FkYYwxTaCqrM4sYEzP9jhqtwUnt5KFiIyppX1084ZjjDGBZdfBY+QdOR7U/RXg/pXFf2tp/7i5AjHGmEC0OvMgELzzK06oc9VZEQnBUeVOnLWxXa+xzsBZI9sYY1qqVZkFdGgdwRnxrX0dikfVt0R5Bd+XP62eGKqAPzd7RMYYE0BWZzrmVwRzfwXUnyx64riaWAKc49KuQJ6qlngqMGOM8Xc5hSVkHyrh5rN6+joUj6szWajqbufTZC/EYowxAeWbIF8PypVblfJEpD3wa2Ao0MZ1m6qeU9MxxhgT7FZlFtA2Mox+XWJ8HYrHuVtW9TWgFTAPOOa5cHxrwfocZi9OJ7ewhIS4KGZOTOGKYYm+DssY46dWZx5kVI/2hIYEd38FuJ8sxgPxqnrck8H40oL1Ocyav4mS8krAcS9y1vxNAJYwjDGnyT96nO/yirl6ZJKvQ/EKd+dZbAS6eTIQX5u9OP1kojihpLyS2YvTfRSRMcafBXv9iurcvbL4HPhYRP4F7HPdoKovNXtUPpBbWPPArtrajTEt2+rMAqLCQxmUEOvrULzC3WRxNpAN/LBauwJBkSwS4qLIqSExJMQF78JgxpjGW5VZwPDkOCLCWsYSe24lC1X9gacD8bWZE1NO6bMAiAoPZebEFB9GZYzxR0XHytm27zB3nd/X16F4jbtXFohIB+BioIuqzhaRBCBEVbM9Fp0XnejEnr14GzmFpUSEhfDIlMHWuW2MOc2a3QWotpz+CnB/1dlUIB24Hvi9s7kP8E8PxeUTVwxL5KsHzueeH/alrKKKkT3a+TokY4wfWp1ZQHioMKx7nK9D8Rp3b7b9DbhWVSfx/RpRq4CgXKL8SufVxHtpuT6OxBjjj1ZlFjCkWxyR4aG+DsVr3E0WPVT1M+fzEwsLltGA21iBJKl9NKN7tuedddmoav0HGGNajOLjFXybU9SibkGB+8lii4hMrNZ2AbCpmePxG1cNTyQjr5gN2UW+DsUY40fWZxVSUaWM6RXcxY6qczdZ3Au8KiKvAFEi8izwMjDT3ROJyCQRSReRnSLyQA3bY0VkoYhsEJHNInKTsz1JRL4Qka3O9jvdPWdTXDy4K63CQpi/Lij6740xzWR15kFCBEYkt6w+TbeShaquBIYAm3HMq8gERqvqN+4cLyKhwNPARcAAYJqIDKi2223AFlUdApwLPCEiETj6SO5V1f7AWOC2Go5tdm0jw5k4sAvvb8ilrKLK06czxgSIVZkFDEqMpU2roLwLXyu3Z5Ooao6qPqaqt6nqow0cMjsa2KmqGapaBrwBXF79FEBbZ0W+NkABUKGqe1V1nTOGI8BWwCvjWacMT6TwWDlfpB/wxumMMX7ueEUl6/cUMrpHy+qvgDo6qEXkOVW91fn8P3zfsX0KVf2xG+dJBPa4vM4GxlTbZw7wPpALtMUx+uqUX+lFpAcwDMdIrJpivhW4FaB79+5uhFW3s3p3JL5tK95Zm83EgV2a/H7GmMC2MbuIsoqqFte5DXVfWWS6PN8JfFfLwx01rd9bPflMBNKABBx1M+aIyMlF4kWkDfAOcJeqHq7pJKr6nKqOVNWR8fHxboZWu7DQEK4YmsAX6QcoKC5r8vsZYwLbicUDR9mVxfdU9RGX5w828TzZgOs6vt1wXEG4ugl4VB1jVXeKSCbQD1gtIuE4EsWrqjq/ibE0yJTh3Xh+WSYfbMzlx+N6ePPUxhg/syqzgJTObWnXOsLXoXiduzO4HxCRUdXaRovIfW6e5xugj4j0dHZaT8Vxy8lVFnC+8707AylAhrMP40Vgq6o+6eb5mk3/rjH07xrDO+tyvH1qY4wfqaisYu2ughZ5Cwrc7+C+E9hSrW0LcJc7B6tqBXA7sBhHB/U8Vd0sIjNEZIZzt4eA8SKyCfgMuF9V84EJwA3AeSKS5nxc7GbczeKq4Yls2FPIzgNHvXlaY4wf2bL3MMVllS02Wbg79isCKK/WVgZEunsiVV0ELKrW9ozL81zgwhqOW07NfR5ec9nQBB5etJV312czc2I/X4ZijPGBBetz+MP73wLw5w+3UlmlLW6RUXevLNYCv6zWNgNY17zh+KdObSM5p288767LoarKlv8wpiU5UXK5qMSxLN6+w6XMmr+JBetb1q1pd5PF3cB9IrJWROaJyDrgfuAOz4XmX6YM70ZuUSkrMw/6OpRGWbA+hwmPfk7PBz5kwqOft7gPujGNZSWXHdwtfrRZRPoCl+IY1TQf+EBVW8xN/AsHdKZtqzDmr8th/BkdfR1Og5z4zejEBz6nsIRZ8x3LerW0S2ljGspKLjs0ZAb3UVV9Q1VnO/9sMYkCIDI8lEvO7MpHm/ZyrKyi/gP8iP1mZEzjlJZX0qqWsqktreRyrclCRD52eb5MRJbW9PBOmP5hyvBuFJdV8snm/b4OpUHsNyNjGq74eAU/ffkbSiuqCA89dYxNSyy5XNdtqH+7PH/B04EEgpHJ7UhqH8U767KbfPtmwfocZi9OJ7ewhIS4KGZOTPHYLaGEuChyakgMLe03I2PcVXSsnJ+8vJqN2UX89dohCOK1/6/+qq5kcTnwmvN5iKr+ywvx+LWQEOHKYd34++c72FdUSpdYt0cOn8LbfQgzJ6Zw77w0Kl0GcrXE34yMccfBo8e54cXV7DhwhKevG86kQY514Vpacqiurj6LC52zpwGe8kYwgWDKsERUYUFa40cTebsP4ew+HVGgdStHCcgQgYevHNTiP/zGVLevqJRrnl1BRv5RXrhx1MlEYeq+slgOrBCR7UCkiPy7pp3cXHU2aPTo2JoRye14Z202Pz+nF9/nU/d5uw/hnXXZVCm8+8sJrNt9iAfmb2JgYqxHzmVMoMo6eIzrX1zJoeJyXrlpdIurhFefuq4srsaxbHg6jhVim7LqbFCZMjyRHQeOsjm3xsVv69W+lkXIPNGHoKq8sXoPI5Lb0bdzW87p61iNd0l6XrOfy5hAtfPAEa5+9muOlFbw6s/GWKKoQV1XFj9T1TkAIjKwGVaeDRqXDk7gwfe38M66bAY18Df0jzbt5dCxMoRT12gPDxWP9CGsyiwgI7+Yx3/QG3AkpL6d27Bkex63nNOr2c9nTKD5NqeIH7+0mhAR3rx1HCld2vo6JL9U15XFn12eX+rpQAJJbHQ4FwzoxPtpuZRXul9y9a01e7jttXUM696OP08ZRGJcFIIjUcRFhXPZkIRmj/WN1Vm0jQzjksFdT7al9o1ndWZBwM0XMaa5rd1dwLTnVxIVHspbMyxR1KWuK4vvROQJHHW3w0XkpzXtpKoveSQyPzdlWDcWbdrH0u15nN+/c737/+urTB5cuIWz+3Tk2RtGEB0RxnWjkwF4Ly2HO99I4/NtB7hgQP3v5a7CY2Us+nYfU0clERURerI9tW8nnl+WycqMg5zXr/nOZ4y/cx2y3r51BIdLyunWPpq5PxtDog0lr1NdVxZTgVhgGhCOY5nw6o/png7QX6WmxNOhdQTz66lzoar832c7eHDhFiYO7MwLN44kOuLUHH3x4K4kxEbywvKMZo1x/rocyiqqmDrq1BKzI3u0Iyo81PotTItyYsh6TmEJChwsLqOiSrlpQrIlCjfUmixUdbuq/kxVfwgsUdUf1PA4z4ux+pXw0BAuG5rAf7fup+hY9dXbHVSVhxdt5cn/bmfK8ESevm44rcJCT9svPDSEn0zowcqMAr7NKWqW+FSV11dnMSQpjgEJMadsiwwPZdwZHViy3ZKFaTlqGrKuwLNLMms+wJzCrbWhVPV8EQkXkbNF5FoAEWktIq09G55/u2p4N8oqqvhgU/UKsVBZpfzm3U08vyyTG8cl8/iPhhAWWvuPe+ro7rSOCOWFZc1zdbEu6xA7Dhxl2qikGren9o1n18Fj7MovbpbzGePvbNmbpnG3rOogYDvwPI4SpwCpQIvsrzhhYEIMfTu3Oe1WVHllFXe+sZ7XV+/h9h/05o+XDSQkpO75GDGR4Vw7qjsfbNzL3qKmf3hfW7WH1hGhTK6l0zzVOYR26Q67ujDBLevgMX71+npqq0Rjy964x91VZ58Bfq+q/fi+Yt4S4CyPRBUgRIQpw7uxdvehk7+hl5ZX8vP/rOWDjXuZdVE/fj0xxe2JezdN6EGVKi9/vatJcRWVlPPhplwuG5pI61Y1j2Ho0bE1yR2ird/CBK2C4jIeXLiZ85/8kv9u2ceFAzoRGX7qV54te+M+d8uqDgTmOp8rgKoWi0iLT8lXDE3k0Y+2MXnOco6WVhAeGkJZZRUPXzmY68Z0r/8NXCS1j+aiQV15bVUWvzqvD21q+aKvz3tpOZSWV3Hd6LrPn9o3nrfWZHO8orLGvhRjAlFJWSUvfZXJM19+R3FZBdeOSuKuC/rSOSbSqwt4Bht3v412ASOANScaRGQ0sNMDMQWUlRkHCRE4UuqYs1BW6VjOODqicV++Pzu7Jx9u2stba/Zw04SeDT5eVXltVRYDE2IY3K3uCYOpfeP594rdrNl1iAm9A6ugkzHVVVRW8fbabP766Xb2Hz7OBf07c/+kFPp0/n7uxBXDEi05NJK7yeJ/gA9F5BkgQkRm4ajBfYvHIgsQsxenU70sd3mlMntxeqM+lMO6t2NEcjte+iqTH4/rQWg9fR3VbcguYtu+I/zpikH17ju2VwciQkNYsj3PkoUJKKdeIUQyaVBXlm7PY8eBowzrHsec64Yzqkd7X4cZVNwdDfUBcBEQj6OvIhmYoqqfeDC2gOCJERa3nN2TPQUlfLJ5X4OPfWN1FlHhoVw+tP7Z4K1bhTGqZzuW2hBaE0Cqz5fIKSzlxeWZHDpWxj+vH878X4y3ROEBDSmruk5Vf6mql6jqDFVd68nAAkVtIymaMsLihwO60L19NM83cBjt0eMVvL8hl8lDutI2MtytY87pE8+2fUfYV1TamFCN8bqa5ksARISFcNHgro1aCdrUz92hs+Ei8qCIZIhIqfPPB0Wk5uVTW5CZE1OICj+1f6KpIyxCQ4SfTujBuqxC1u4+5PZx76flcqyskqn1dGy7Sk1xDqG1qwsTIGq7at9baL/weJK7VxaPARfg6KcY4vzzPOAvHoorYFwxLJFHpgw+uShgYlwUj0wZ3OROtKtHJhETGcaLDVgC5PXVWfTr0pZhSXFuH5PSuS2dY1rZbG7j96qqlH98udPmS/iIux3cVwNDVPWg83W6iKwDNgB3eySyAOKJERatW4Vx3Zhknlv6HXsKjpHUPrrO/b/NKWJTThF/nDygQZfhIkJq33g+/nYfFZVVdc4ybwgbomia04HDpdwzbwPLd+YztFss2/YfobT8+xWfbb6E57n7zVDbt4/dHPSgn4zvQYgIL31V/9o1r6/OolVYCFcO69bg86T27cTh0go2ZBc2IsrTnd4B6agxvmB940vRmpbri/QDXPTUMtbsLuDRKYN597YJPDrlzGa/mjd1c/fK4i1goYg8CGThGA31O2CepwIz0CU2kslDEpj3zR7uuqAvsVE1d1ofK6vgvbRcLhncldho9zq2XZ3VuyMh4qieNyK56aNI6qoxbv+hjbuOV1Ty2MfpvLg8k35d2vLmdWPp3ckxZ8LmS3ifu1cW9wGfAk8Da4G/A18A93soLuN081k9KS6r5I3VWbXu88GGvRw9XsG0Bs4YPyE2Opxh3ds1W7+FLdhmmioj7yhX/fNrXlzuWIhzwW0TTiYK4xvuzrMoU9Xfq2pvVY1W1T6q+j+qetzdE4nIJBFJF5GdIvJADdtjRWShiGwQkc0icpO7xwazQYmxjOvVgZe/3lVrVb7Xv8mid6c2jExu1+jzpPaNZ2NOEQePuv1PWquucZE1tlsHpKmPqvLO2mwu/ftysg+V8NwNI3jw8kFEhttyNL7m7tDZB0RkVLW20SJyn5vHh+K4KrkIGABME5EB1Xa7DdiiqkOAc4EnRCTCzWOD2i3n9GRvUSmLNu09bdu2fYdZn1XI1FFJTRpfnto3HlVYvjO/KaECML6GYvdhIZ6pMW4C24L1OUx49HN6PvAh4x75jB/982vufWsDgxNj+ejOs7lwYBdfh2ic3L0NdSewpVrbFuAuN48fDexU1QxVLQPeAC6vto8CbcXxjdcGKAAq3Dw2qJ3btxO94lvzwrJMVE8dOPjG6j1EhIYwZXjDO7ZdDU6MpX3riCavQnv0eAVfpOdxRsfWJMZFIkBkeAhVqvTu1KZJ722CS/WBEHuLSlmbVchFg7rw2i1j6RprV6L+xN1kEcH3S5OfUAbUfL/hdInAHpfX2c42V3OA/kAusAm4U1Wr3DwWABG5VUTWiMiavLzgmTcQEiL87KxebMopYnVmwcn20vJK5q/LZtKgLrRv3bT5kSEhwtl9OrJ0Rx5V1Re7aoBnl3zHweIynrx2KF89cD6Zj17CylnnE9+2FXe+sZ6SstNn3pqWqbaZ2Buzixq8JprxPHeTxVrgl9XaZgDr3Dy+pn/56t9IE4E0IAEYCswRkRg3j3U0qj6nqiNVdWR8fLyboQWGKcMTad86gueXfT+MdtGmvRwurWDq6Jqr4TVUat948o+WsWXv4UYdv/9wKc8vy2DykASGuEwMjIuO4Imrh/JdXjGPfLS1WWI1gc8GQgQWd5PF3cB9IrJWROY5J+TdD9zh5vHZgOs3WjccVxCubgLmq8NOIBPo5+axQS8yPJTpY5P5bNt+MvKOAo65FT06RDOuhj6Cxji7jyPBNnZU1JOfbKeySpl54el9E2f16cjPzurJv1fs5ottB5oUpwkOXWJtIEQgcXc01GagLzAb+AbH8h8pqlq9H6M23wB9RKSncz2pqcD71fbJAs4HEJHOQAqQ4eaxLcINY5MJDw3hpa8y2XngCN/sOsTU0d2bbeG0+LatGJQY06h+i/R9R3hr7R5+PK4H3TvUPNv81xNT6NelLTPf3kh+M4y6MoEtuYZVCWwmtv9qyKqzR1X1DVWd7fzzaAOOrQBuBxYDW4F5qrpZRGaIyAznbg8B40VkE/AZcL+q5td2rLvnDibxbVsxPCmOuSuzuODJpQC0btW8QwpT+8azNusQh0urd1HV7dGPttK6VRi3/6B3rftEhofyt6lDOVxazgPvbDyts960HAs35LIys4Af9u9kM7EDROPqdjaCqi4CFlVre8bleS5wobvHtkQL1uewfk/hKW0Pf7iNtq3Cm+0/WGrfTjz9xXd8vTOfSYO6unXM1zvz+SI9j1kX9aNdPR3t/brEcP+kfjz0wRZeX72nwaVnTeDbU3CM38zfxPDucfxj+gjCm2k9MuNZ9q8UQGYvTud4xakT804so9FchnWPo22rMLf7LaqqlIc/2kpiXBQ3ju/h1jE3je/BWb078tAHW072v5iWobyyittfXw8CT00dZokigNi/VADxxuiR8NAQJvTuyNLt+W7dJlq4MZdvcw5z74V93Z5lGxIiPHHNEFqFh3DXm2m1zkw3wefxT9LZsKeQv1x1Zr0rKRv/YskigHiiKl9NUlPiySks4bt6fusvLXcs9DagawxXDG3YbbDOMZE8cuVgNmYX8dSnO5oSrgkQS7fn8eySDKaN7s7Fg927xWn8R63JQkS2ujzfIyJZNT28E6YBz1Tlq8k5fR1DaL+sZ1TUf1bsJqewhN9c3J+QRkyiumhwV64e0Y1/fLmTb3YV1H+ACVh5R45zz7wN9O3cht9f2qJW6wkadXVw3+LyfLqnAzH1O9GJ7emiQolxUfTp1IYl2/P42dm9atyn8FgZf/98B6l94zmrT8dGn+sPlw1kVWYBd7+ZxqI7zybGzdrhJnBUVSn3zEvjSGk5r/5sDFERtihgIKo1WajqcpfnS7wTjqmPt9bxT+0bz79X7qakrLLG/9xPf7GTI8creOCifk06T5tWYfz12iFc/cwK/vj+Zp68ZmiT3s/4n+eXZbBsRz5/vnIQKV1smfFA5e6qsxHOdZf+ISL/dn14OkDjG6kp8ZRVVLEy8+Bp2/YUHOOVr3fzo+Hd6N81psnnGpHcntvP68P8dTl8sLHFTc4Paml7Cpm9OJ2LBnXhutE2TDqQuTvP4hVgCLAQ2O+5cIy/GNWjPZHhISxJz+MHKZ1O2fb4J+mIwD0X9m228/3qvN4s2Z7Hr+el8acPtrD/8HGr3R3gDpeW86vX19E5JpJHp5zZbCsNGN9wN1lMAnqqaqEHYzF+JDI8lHG9OrC02nyLTdlFvJeWyy/PPaNZl5AODw3h0sFd2bCnkH2HHUuBnKjdDVjCCDCqym/f/ZbcwlLm/Xxso8r9Gv/i7tDZLKCVJwMx/ie1bzwZ+cVkHTwGOL4AHl60lfatI5hx7hnNfr6Xv951WltzTzo03vHWmmwWbsjl7gv6NEtdd+N77iaLfwPvicg0ETnP9eHJ4IxvpTpvPy3Z4bi6+DI9jxUZB7njvN4eGbVkS1YHh50HjvCH9zcz/owO/OLc2tcKM4HF3dtQtzv/fLhauwI1j600Aa9Hh2i6t49mSXoe00Yl8chHW+nRIZrrxiR75HwJcVHk1JAYbMnqxlmwPsfjw6xrOldoiNAqLIS/XjvUihgFEXeXKO9Zy8MSRRATEZLaRfHZ1v30/u1HbN9/lHNT4okI88zEf29NOmwJqpcsPdH/s2B9jsfPVVGllFcqK747fSSdCVy23Iep1YL1OXyz69ApZQnf/GaPR75wwNGJ/ciUwSS6XEn8z6X9rXO7EWoqWeqp/p+azlVWWWV9TUHGlvswtZq9OJ2yyuqr3Hr2S+CKYYl89cB5LLrjbACOWc3uRvFm/4/1NbUMttyHqZUvvwQGJMQwvHscr63K4uazetoY/QYoq6giMjyEkvLTV/Pt0KbueiMNUVRSzuzF26htbWLrawoutV5ZVF/uo7aHd8I0vuCtVW5rM31sMhn5xXxt977dVlJWya3/WUNJeRVhNXQu5x8t4+430zhwuLTR51BVFm7I5YInl/DaqizO6dORyPBTv0qsryn4uDUaSkT+t5ZNx4Fs4GNVtZndQWbmxBRmzd90yv1ob34JXDy4Kw99sIX/rNjNhN6NX6ywpSgqKefml79hbdYhHp0ymMjw0FNGQ915fm+yCkp4bmkGn2zexx3n9+GmCT0bNGAh6+Ax/ue9b1myPY9BiTG8dOMoBneL9erIK+Mb4k6BGxF5A7gSWA3sAZKA0TiW/+gGDAauUtWPPRdqw4wcOVLXrFnj6zACnq+/BB5ZtJUXlmfy1f3n0SU20mvnDTR5R47z45dWs/PAEf527TAuObP2ehG78ot56IMtfLbtAL3iW/PHyQNPLktfm/LKKp5flsFTn+4gLES498IUfjwumTCrdBdURGStqo6scZubyWIe8LqqvuvSdjlwnapeKyI3Aner6tBmirnJLFkEh90Hi0md/SV3XdCHuy5ovrWogkn2oWNMf2EV+w8f55kbRpBazxf/CZ9v28//LtzCroPHmDiwM7+7ZECN1evW7CrgN+9uYvv+o0wc2Jk/XjawWZd6Mf6jOZJFEdBeVStd2kKBQ6oa43xeqKp+s/6wJYvgceNLq9m27zDL7z/PajZXs/PAEaa/sJpjZRX866ZRDV5a43hFJS8sy2TO5zupUuUHKfFszC5ib1EpXWIj6dEhmhUZBSTGRfHgZQO5YEBnD/1NjD+oK1m4+z/vO+AX1dpmONsBOgLFjQvPmLpNH5vM/sPH+WyrdYu52pRdxDXPrqSiSnnz5+MatQZTq7BQbvtBbz67N5X+Xdvy8eb95BaVosDeolJWZBTwg5SOfHL3OZYoWjh3k8XPgF8751usFJE9wEzgZuf2FOB/PBGgMef160RCbCRzV9q0nhNWfHeQac+vJCo8lLdnjGtyXZGEuCjyjpTVuG37/mJat3J3ZSATrNz6BKjqOhHpA4wFEoC9wApVLXduXwos9ViUpkULDRGuG9Odxz/ZTkbeUXrFt/F1SD716Zb9/PK1dXRvH83cm8c0W8e/Ta4zdXH7BrCqlqvqMlV9U1WXnkgUxnjDNaOSCAsRXl3Vsq8u3l2fzc/nrqV/l7bM+/m4Zh0h5ut5Nca/WW+hCQid2kYycVAX3l6bTUkLXQLk3yt2cfebGxjdoz2v3jKW9q2bbzY22EKOpm6WLEzAuGFsMkUl5SxsYXW6VZW/f7aD37+3mR8O6My/bhpFGw/0Ibgu5ChAYlwUj0wZbJPrDOB+PQtjfG5Mz/b06dSGV1fu5pqRSb4OxyuqqpQ/L9rKi8szmTI8kceuOtOjE+GuGJZoycHUyK4sTMAQEa4f050N2UVszC70dTgeV1FZxX3vbOTF5Zn8ZHwPHv/REJsxbXzGa588EZkkIukislNEHqhh+0wRSXM+vhWRShFp79x2t4hsdra/LiK27kMLNWVEN6LCQ5m7crevQ/Go4xWV3PbaOt5em81dF/ThD5MHEGJV54wPeSVZOGd4Pw1cBAwAponIANd9VHW2qg51LhkyC1iiqgUikgjcAYxU1UFAKDDVG3Eb/xMTGc4VwxJ4f0MuRceCc0Be8fEKfvryNyzevJ/fXzqAuy7oa0u0G5/z1pXFaGCnqmaoahnwBnB5HftPA153eR0GRIlIGBANtKweTnOK68ckU1pexTvrsn0dSrMrPFbG9S+sYmVGAU9cPYSfntXT1yEZA3gvWSTiWK32hGxn22lEJBqYBLwDoKo5wONAFo7JgEWq+kktx94qImtEZE1eXl4zhm/8yaDEWIYmxTF31W7cWdssUOw/XMo1z65gy97D/PP64Vw1opuvQzLmJG8li5quoWv7Xz4Z+EpVCwBEpB2Oq5CeOGaPtxaRGiv3qepzqjpSVUfGx7u38qYJTDeMTSYjr5gVQVIYKevgMX70zNfkHCrh5ZtGceHALr4OyZhTeCtZZOOogXFCN2q/lTSVU29BXQBkqmqec9b4fGC8R6I0AeOSM7sSFx3O3FWB39Gdvu8IP3rma46UVvDqLWMZf4YVejL+x1vJ4hugj4j0FJEIHAnh/eo7iUgskAq859KcBYwVkWhx9PKdD2z1QszGj0WGh3L1iG58snk/+5tQItTX1mUd4ppnVyACb/18HEOT4nwdkjE18kqyUNUK4HZgMY4v+nmqullEZojIDJddrwQ+UdVil2NXAW8D64BNzpif80bcxr9dPyaZiirljdV76t/ZDy3fkc/0F1YRFx3O2zPG06ez35SDMeY0bhU/CkRW/KhluOHFVezYf5Tl9//A7yesuZaobdc6nKJj5fTp3JZ/3zyaTm1t6pDxveYofmSMX5o+Npl9h0v5bNsBX4dSpwXrc5g1fxM5hSUoUFBcThXw43HJlihMQLBkYQLa+f060TU20u9ndM9enE5J+amr5arC0198V8sRxvgXSxYmoIWFhjBtdHeW7cgnM99/K/taYSET6CxZmIA31VkY6TU/HkbbOabmW01WWMgECksWJuB1iolk4sAuzFuTTWm5/xVGqqxS2kaGntZuhYVMILFkYYLC9WO7U1RSzgcb9/o6lNPM+XwnOw4Uc+2oblZYyAQsK35kgsK4Xh04I741c1fu5kd+tKbS1zvz+dtn25kyLJFHp5xpq8eagGVXFiYoOAojJZO2p5Bvc4p8HQ4AB46UcscbafTq2JqHrhhkicIENEsWJmhcNaIbkeEhfjGMtrJKufP1NI4eL+cf14+gtQdqZhvjTZYsTNCIjQrn8iGJvJeWy+FS3xZGeuqzHazIOMhDlw8ipYst42ECnyULE1Smj02mpLyS+Wt9Vxhp+Y58/v75Dq4a3o2rRybVf4AxAcCShQkqg7vFMiQpjrmrsnxSGOnA4VLuenM9vePb8NAVA71+fmM8xZKFCTrTx3Rn54GjrMwo8Op5Kyqr+NXr6yk+Xsk/rh9OdIT1U5jgYcnCBJ3JQxKIjfJ+YaSnPtvBqswC/nTFIFtu3AQdSxYm6JwojLT4230c8FJhpKXb85jzxU6uGdnNameboGTJwgSl68c6CiO9+Y3nCyPtKyrlrjfT6NupLQ9eNsjj5zPGFyxZmKDUs2NrzurdkddXZ1FRWeWx81RUVnHH6+spLa/k6euHExVx+hpQxgQDSxYmaE0fm0xuUSmfe7Aw0l8/3c7qXQX8+cpB9O7UxmPnMcbXLFmYoHVB/050iYlk7qosj7z/l+kHePqL75g6Kokrh1k/hQlulixM0AoLDWHq6CSWbs9j98HmLYy0t6iEu99Mo1+XtvzxMptPYYKfJQsT1KaN7k5oiPBqM15dVFRW8avX1lNWUcXT1w8nMtz6KUzws2RhglrnmEguHNCZt9bsabbCSI9/sp01uw/x8JTBnBFv/RSmZbBkYYLe9LHJHDpWzqJNTS+M9MW2Azyz5Dumje7O5UOtcJFpOSxZmKA3/owO9OrYmv80ceny3MIS7p6XRv+uMfxh8oBmis6YwGDJwgQ9EeH6scmszypkc27jCiOVV1Zx+2vrKK+o4h/WT2FaIEsWpkX40fAThZEa19H9+OJ01mUV8uhVZ9KzY+tmjs4Y/2fJwrQIsdHhTD4zgffSchpcGOmzrft5dmkG08d2Z/KQBA9FaIx/s2RhWowbxiVzrKySd9fluH1MTmEJ98zbwMCEGH53ifVTmJbLkoVpMc7sFseZ3WKZu3K3W4WRyioc/RSVVcrT11k/hWnZvJYsRGSSiKSLyE4ReaCG7TNFJM35+FZEKkWkvXNbnIi8LSLbRGSriIzzVtwmuEwfk8yOA0dZnVl/YaTHPt7G+qxC/nLVmfSwfgrTwnklWYhIKPA0cBEwAJgmIqdc06vqbFUdqqpDgVnAElU98T/6KeBjVe0HDAG2eiNuE3wmD0kgJjKs3mG0n2zexwvLM/nxuGQuObOrl6Izxn9568piNLBTVTNUtQx4A7i8jv2nAa8DiEgMcA7wIoCqlqlqoWfDNcEqKiKUH41IYvHmfeQdOV7jPnsKjvHrtzYwODGW317S38sRGuOfvJUsEgHXKjTZzrbTiEg0MAl4x9nUC8gD/iUi60XkBRGp8Z6AiNwqImtEZE1eXl7zRW+CyvVju1Neqcxbc3phpLKKKm5/fT2q8PR1w2kVZv0UxoD3koXU0FZbD+Nk4CuXW1BhwHDgn6o6DCgGTuvzAFDV51R1pKqOjI+Pb2rMJkidEd+GCb078NqqLCqrTv0YPvrRNjbsKeSxH51J9w7RPorQGP/jrWSRDSS5vO4G5Nay71Sct6Bcjs1W1VXO12/jSB7GNNr0McnkFJbwhUthpI+/3cdLX2Xyk/E9uGiw9VMY48pbyeIboI+I9BSRCBwJ4f3qO4lILJAKvHeiTVX3AXtEJMXZdD6wxfMhm2B2wYDOdGrbirmrHB3dewqOMfPtDQzpFsusi/v5ODpj/E+YN06iqhUicjuwGAgFXlLVzSIyw7n9GeeuVwKfqGr1SjW/Al51JpoM4CZvxG2CV3hoCMOS4li8ZT89H/iQsFAhVGCO9VMYUyOvJAsAVV0ELKrW9ky11y8DL9dwbBow0nPRmZZmwfoclmx3DIJQoLxSkVBh7e5DJLW3vgpjqrMZ3KZFmr04ndKKqlPayiqV2YvTfRSRMf7NkoVpkXILSxrUbkxLZ8nCtEgJcVENajempbNkYVqkmRNTiKq2MGBUeCgzJ6bUcoQxLZvXOriN8SdXDHMsIDB7cTq5hSUkxEUxc2LKyXZjzKksWZgW64phiZYcjHGT3YYyxhhTL0sWxhhj6mXJwhhjTL0sWRhjjKmXJQtjjDH1EncK1wciEckD6q6dWbuOQH4zhuMtFrd3WdzeZXF7XrKq1lgMKGiTRVOIyBpVDbiFCy1u77K4vcvi9i27DWWMMaZeliyMMcbUy5JFzZ7zdQCNZHF7l8XtXRa3D1mfhTHGmHrZlYUxxph6WbIwxhhTrxaRLETkJRE5ICLfurQNEZEVIrJJRBaKSIyzvYeIlIhImvPxjMsxI5z77xSR/xMR8Ze4ndvOdG7b7Nwe6e9xi8j1Lj/rNBGpEpGhvoi7EbGHi8grzvatIjLL5Rh//plHiMi/nO0bRORcX8QtIkki8oXzZ7dZRO50trcXkf+KyA7nn+1cjpnljC1dRCYGQtwi0sG5/1ERmVPtvbz+GW80VQ36B3AOMBz41qXtGyDV+fynwEPO5z1c96v2PquBcYAAHwEX+VHcYcBGYIjzdQcg1N/jrnbcYCDDVz/vRvzMrwPecD6PBnYBPfz9Zw7cBvzL+bwTsBYI8XbcQFdguPN5W2A7MAB4DHjA2f4A8Bfn8wHABqAV0BP4zhef8UbE3Ro4C5gBzKn2Xl7/jDf20SKuLFR1KVBQrTkFWOp8/l/gqrreQ0S6AjGqukId/8r/Bq5o5lBP0cC4LwQ2quoG57EHVbUyAOJ2NQ14HXzz84YGx65AaxEJA6KAMuBwAPzMBwCfOY87ABQCI70dt6ruVdV1zudHgK1AInA58Ipzt1dcYrgcR3I+rqqZwE5gtL/HrarFqrocKHV9H199xhurRSSLWnwLXOZ8fjWQ5LKtp4isF5ElInK2sy0RyHbZJ9vZ5m21xd0XUBFZLCLrROQ+Z7u/x+3qWpzJAv+JG2qP/W2gGNgLZAGPq2oB/hN7bXFvAC4XkTAR6QmMcG7zWdwi0gMYBqwCOqvqXnB8MeO4+sEZy54a4vP3uGvjL58Tt7TkZPFT4DYRWYvjUrLM2b4X6K6qw4B7gNec93prupfoi3HHtcUdhuNS93rnn1eKyPn4f9wAiMgY4Jiqnrjn7i9xQ+2xjwYqgQQct0XuFZFe+E/stcX9Eo4vpjXA34CvgQp8FLeItAHeAe5S1cN17VpDm9bR7lENiLvWt6ihzW/nMrTYsqqqug3HrRtEpC9wibP9OHDc+XytiHyH47f2bKCby1t0A3K9GbMzphrjxhHfElXNd25bhOMe9lz8O+4TpvL9VQX4yc8b6oz9OuBjVS0HDojIV8BIYBl+EHsdn/EK4O4T+4nI18AO4BBejltEwnF84b6qqvOdzftFpKuq7nXeqjngbM/m1CvSE/F5/bPSwLhr4zefcXe02CsLEenk/DME+B3wjPN1vIiEOp/3Avrg6HTdCxwRkbHOEQs/Bt7zl7iBxcCZIhLtvIeeCmwJgLhPtF0NvHGizV/idsZXW+xZwHni0BoYC2zzl9jr+IxHO+NFRH4IVKiq1z8rznO8CGxV1SddNr0P3Oh8fqNLDO8DU0WklfP2WR9gdQDEXSN/+Zy4zdc97N544PiNdS9QjiOb3wzciWMUw3bgUb6fzX4VsBnHfd11wGSX9xmJ4z7wd8CcE8f4Q9zO/ac7Y/8WeCyA4j4XWFnD+3g17kZ8VtoAbzl/5luAmYHwM8cx4i8dR8fspziWpfZ63DhulyqOUXxpzsfFOEbyfYbjauczoL3LMb91xpaOy8ihAIh7F44BCEed/z4DfPUZb+zDlvswxhhTrxZ7G8oYY4z7LFkYY4yplyULY4wx9bJkYYwxpl6WLIwxxtTLkoUxxph6WbIwxhhTL0sWxvg554x8Y3zKkoUxTSAiM0XknWptfxeRv4lIrIi8KCJ7RSRHRP7kspTMGSLyuYgcFJF8EXlVROJc3mOXiNwvIhuBYksYxtcsWRjTNHOBSSe+6J1f6tcC/8FR06AC6I1jGesLgZ85jxPgERwr1vbHsUDeH6u99zQci//FqWPxP2N8xpKFMU2gjsXgluJYCBFgEpCPY/2fi3AsX12sjiJDf8Wxui6qulNV/6uOQj55wJM4Fn909X+qukdVS7zxdzGmLnZpa0zTvQL8Angex2KO/wGSgXBgr0tZ5RCcxXucK8L+H3A2jloTITiWCHe1B2P8hF1ZGNN0C3AsDz8IuBR4FccX/XGgo6rGOR8xqjrQecwjOFYuPVNVY3AkmerFcGyVT+M3LFkY00SqWoqjxOprOOorZDlvT30CPCEiMSIS4uzUPnGrqS2O5aoLRSQRmOmT4I1xkyULY5rHK8BgHLegTvgxEIGj1sUhHAmlq3PbgzgqGRYBHwLzMcaPWT0LY5qBiHQHtgFdtHH1mI3xa3ZlYUwTOcuW3gO8YYnCBCsbDWVMEzhrWe8HduMYNmtMULLbUMYYY+plt6GMMcbUy5KFMcaYelmyMMYYUy9LFsYYY+plycIYY0y9/h+1dAkzo4lXVAAAAABJRU5ErkJggg==\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plot_ginis(years, wg,\n", - " plotlabel=\"net wealth gini\", \n", - " ylabel=\"gini coefficient\", \n", - " path='figures/gini_lorenz_us_3.pdf') # 2.12" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plot_ginis(years, topwg,\n", - " plotlabel=\"top $10\\%$ net wealth share\", \n", - " ylabel=\"top $10\\%$ share\", \n", - " path='figures/gini_lorenz_us_4.pdf') # 2.14" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## total income ginis" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plot_ginis(years, \n", - " topit, \n", - " plotlabel=\"top $10\\%$ total income share\", \n", - " ylabel=\"top $10\\%$ share\", \n", - " path='figures/gini_lorenz_us_7.pdf')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can cross-check plots of total income and net wealth with [Kuhn, Schularick and Steins (2020)](https://www.journals.uchicago.edu/doi/10.1086/708815)'s Figure 4 & 5." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# US lorenz curves: net wealth vs total income" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## get lorenz curve data" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [], - "source": [ - "xnames = ['nw', 'ti', 'li']\n", - "F = []\n", - "L = []\n", - "for xn in xnames:\n", - " f_vals, l_vals = get_lorenz(df4, xname=xn)\n", - " F.append(f_vals)\n", - " L.append(l_vals)\n", - "\n", - "f_val1, l_val1 = F[0][-1], L[0][-1]\n", - "f_val2, l_val2 = F[1][-1], L[1][-1]\n", - "f_val3, l_val3 = F[2][-1], L[2][-1]\n", - "\n", - "fw = lambda x: interp(f_val1, l_val1, x)\n", - "fi = lambda x: interp(f_val2, l_val2, x)\n", - "fl = lambda x: interp(f_val3, l_val3, x)\n", - "x = np.linspace(0, 1, 100)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## plots\n", - "\n", - "Then plot US Lorenz curves for net wealth and total income in year 2016." - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots()\n", - "\n", - "ax.plot(f_val1, l_val1, label=f'net wealth')\n", - "# ax.plot(f_val3, l_val3, label=f'labor income')\n", - "ax.plot(f_val2, l_val2, label=f'total income')\n", - "ax.plot(f_val1, f_val1, label='equality')\n", - "\n", - "ax.legend(fontsize=12)\n", - "plt.savefig('figures/gini_lorenz_us_5.pdf')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## further cross-checking" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Given [the following relationship between Lorenz curves and Gini index](https://en.wikipedia.org/wiki/Lorenz_curve#:~:text=This%20curve%20is%20called%20the,more%20unequal%20the%20distribution%20is.), we can also verify the US Lorenz curves with our estimated Gini coefficients above:\n", - "- The Gini coefficient is the ratio of the area between the line of perfect equality and the observed Lorenz curve to the area between the line of perfect equality and the line of perfect inequality." - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [], - "source": [ - "wgini = []\n", - "igini = []\n", - "for f_val, l_val in zip(F[0], L[0]):\n", - " wgini.append(lorenz2gini1(l_val, f_val))\n", - "\n", - "for f_val, l_val in zip(F[1], L[1]):\n", - " igini.append(lorenz2gini1(l_val, f_val))\n", - "\n", - "df_lc = pd.DataFrame(list(zip(df8['yearmerge'], igini, wgini)), columns=['yearmerge', 'ti', 'nw'])\n", - "#display_side_by_side([df_lc, df8], ['Ginis From Lorenz', 'Ginis From Data'])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We cross-check our estimations again with the following 2 plots:\n", - "- we observed that the gini coefficients estimated from the Lorenz curves match perfectly with those estimated directly from data." - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots()\n", - "ax.plot('yearmerge', 'ti', data=df_lc, marker='o', alpha=0.5, label=f'income gini from lorenz')\n", - "ax.plot('yearmerge', 'ti', data=df8, marker='o', alpha=0.5, label=f'income gini from data')\n", - "\n", - "ax.legend(fontsize=12)\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots()\n", - "ax.plot('yearmerge', 'nw', data=df_lc, marker='o', alpha=0.5, label=f'wealth gini from lorenz')\n", - "ax.plot('yearmerge', 'nw', data=df8, marker='o', alpha=0.5, label=f'wealth gini from data')\n", - "\n", - "ax.legend(fontsize=12)\n", - "plt.show()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.8" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -}