lorenz_gini_coefficent_aus_Italian_us_data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lorenz & Gini coefficent Aus, Italian & US data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will use australian, Italian and US household data on income and wealth to plot the lorenz curve and determine the Gini coefficent. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Australia"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can source Australian data from the Household, Income and Labour Dynamics in Australia (HILDA) data set. \n",
    "\n",
    "We will require the following imports."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import quantecon as qe\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we need to import the data from the HILDA.\n",
    "\n",
    "The data set has 18 waves each wave represents a finanical year. The 18th wave represents the 2017-18 financial year. In the data set the number wave is represented by the alphabet. Hence 'r' represents the fact the data is from the 18th wave."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Income"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "18"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "letter = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n','o', 'p', 'q', 'r']\n",
    "len(letter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "path1 = r'~/Documents/projects/lorenz_curve/Household_'+letter+'180c.dta'\n",
    "hilda_household = pd.read_stata(path1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I will determine fininacial year (2017-18) household disposable regular income. Disposable regular income is  all wages business income, investment income, regular private pensions, regular private transfers, other regular public income and foreign pensioins after tax. \n",
    "\n",
    "According to the [HILDA](https://melbourneinstitute.unimelb.edu.au/__data/assets/pdf_file/0008/3247289/HILDA-User-Manual-Release-18.0.pdf) data user manual (page 68), disposable regular income is the difference between the variables rhifdip and rhifdin. rhifdip represents the positive values while rhifdin represents the negative values. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "hifdip = np.array(hilda_household[letter+'hifdip'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "hifdin = np.array(hilda_household[letter+'hifdin'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "hh_disposable_regular_income = hifdip - hifdin"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now with this we can use the ``lorenz_curve`` function from quantecon to plot the lorenz curve for household disposable regular income. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "hh_disposable_regular_income.sort()\n",
    "x, y = qe.lorenz_curve(hh_disposable_regular_income)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "\n",
    "plt.plot(x, y, label='2017-18 Household disposable regular income')\n",
    "\n",
    "plt.plot(x, x, 'k--', label='equality')\n",
    "\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also determine the gini coefficient."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.3798976683281641"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qe.gini_coefficient(hh_disposable_regular_income)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is a little different to what has been recored by the [world bank](https://data.worldbank.org/indicator/SI.POV.GINI?locations=AU) who records australias income gini coefficient to be 0.344 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "letters = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n','o', 'p', 'q', 'r']\n",
    "year = ['2000-01', '2001-02', '2002-03','2003-04', '2004-05', '2005-06', '2006-07', '2007-08', '2008-09', '2009-10', '2010-11', '2011-12', '2012-13', '2013-14', '2014-15', '2015-16', '2016-17', '2017-18']\n",
    "gini = []\n",
    "for i, letter in enumerate(letters):\n",
    "    path1 = r'~/Documents/projects/lorenz_curve/Household_'+letter+'180c.dta'\n",
    "    hilda_household = pd.read_stata(path1)\n",
    "    hifdip = np.array(hilda_household[letter+'hifdip'])\n",
    "    hifdin = np.array(hilda_household[letter+'hifdin'])\n",
    "    hh_disposable_regular_income = hifdip - hifdin\n",
    "    hh_disposable_regular_income.sort()\n",
    "    x, y = qe.lorenz_curve(hh_disposable_regular_income)\n",
    "    plt.plot(x, y, label= year[i])\n",
    "    gini.append(qe.gini_coefficient(hh_disposable_regular_income))\n",
    "    \n",
    "plt.plot(x, x, 'k--', label='equality')\n",
    "plt.title('Australian Household Disposable Regular Income Lorenze Curve')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 8))\n",
    "\n",
    "plt.plot(year, gini, label = 'Gini coefficent over the years')\n",
    "plt.title('Australian Income Gini coefficent since 2000-01')\n",
    "plt.ylabel('Gini coefficent')\n",
    "plt.xlabel('year')\n",
    "plt.legend\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Wealth\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I will now determine the gini coefficent for household wealth. Te [HILDA](https://melbourneinstitute.unimelb.edu.au/__data/assets/pdf_file/0008/3247289/HILDA-User-Manual-Release-18.0.pdf) data user manual on page 84 explains how net worth is calculated. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "hwnwip = np.array(hilda_household['rhwnwip'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "hwnwin = np.array(hilda_household['rhwnwin'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "net_wealth = hwnwip - hwnwin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "net_wealth.sort()\n",
    "x_1, y_1 = qe.lorenz_curve(net_wealth)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "\n",
    "plt.plot(x_1, y_1, label='Household net worth')\n",
    "plt.plot(x_1, x_1, 'k--', label='equality')\n",
    "\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6416459780522372"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qe.gini_coefficient(net_wealth)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Clearly we can see that the lorenze furve for welath is more scewed tot he right than for income. and as a result the gini coefficent for wealth is must higher. \n",
    "\n",
    "We can see this directly by ploting wealth and income on the same plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "\n",
    "plt.plot(x_1, y_1, label='Household net worth')\n",
    "plt.plot(x, y, label='Household disposable regular income')\n",
    "plt.plot(x_1, x_1, 'k--', label='equality')\n",
    "\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Italy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I will be checking natasha's work which can be found [here](https://github.com/jstac/nyu_lecture_notes/blob/master/figures_source/lorenz_curve_italy.ipynb).\n",
    "\n",
    "I have downloaded two file ``'rfam16.dta'`` and ``'ricfam16.dta'`` which have household net disposable income and household net wealth respectively. These files are sourced from [the bank of Italy](https://www.bancaditalia.it/statistiche/tematiche/indagini-famiglie-imprese/bilanci-famiglie/distribuzione-microdati/index.html) which you can find in a compressed folder called 'Shiw 2016 - STATA' which you can open [here](https://www.bancaditalia.it/statistiche/tematiche/indagini-famiglie-imprese/bilanci-famiglie/distribuzione-microdati/documenti/ind16_stata.zip?language_id=1)\n",
    "\n",
    "Once I have extracted and stored ``'rfam16.dta'`` and ``'ricfam16.dta'`` files I can begin."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Income"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nquest</th>\n",
       "      <th>y</th>\n",
       "      <th>yl</th>\n",
       "      <th>yl1</th>\n",
       "      <th>yl2</th>\n",
       "      <th>yt</th>\n",
       "      <th>ytp</th>\n",
       "      <th>ytp1</th>\n",
       "      <th>ytp2</th>\n",
       "      <th>yta</th>\n",
       "      <th>...</th>\n",
       "      <th>yca</th>\n",
       "      <th>yca1</th>\n",
       "      <th>yca2</th>\n",
       "      <th>ycf</th>\n",
       "      <th>ycf1</th>\n",
       "      <th>ycf2</th>\n",
       "      <th>ycf3</th>\n",
       "      <th>ycf4</th>\n",
       "      <th>cly</th>\n",
       "      <th>cly2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>173</td>\n",
       "      <td>16636.652344</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9400.0</td>\n",
       "      <td>23400.0</td>\n",
       "      <td>23400.0</td>\n",
       "      <td>0</td>\n",
       "      <td>-14000</td>\n",
       "      <td>...</td>\n",
       "      <td>7200.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7200.0</td>\n",
       "      <td>36.652817</td>\n",
       "      <td>36.652817</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>375</td>\n",
       "      <td>13939.661133</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9100.0</td>\n",
       "      <td>9100.0</td>\n",
       "      <td>9100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>4825.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4825.0</td>\n",
       "      <td>14.661126</td>\n",
       "      <td>14.661126</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>633</td>\n",
       "      <td>20305.498047</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14300.0</td>\n",
       "      <td>14300.0</td>\n",
       "      <td>14300.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>6000.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>5.497922</td>\n",
       "      <td>5.497922</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>923</td>\n",
       "      <td>13874.424805</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8450.0</td>\n",
       "      <td>8450.0</td>\n",
       "      <td>8450.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>5400.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5400.0</td>\n",
       "      <td>24.424614</td>\n",
       "      <td>24.424614</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1367</td>\n",
       "      <td>14155.201172</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10530.0</td>\n",
       "      <td>10530.0</td>\n",
       "      <td>10530.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>3600.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3600.0</td>\n",
       "      <td>25.201653</td>\n",
       "      <td>25.201653</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7415</th>\n",
       "      <td>928511</td>\n",
       "      <td>4400.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4400.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4400</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7416</th>\n",
       "      <td>928512</td>\n",
       "      <td>18218.640625</td>\n",
       "      <td>19000.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>-5400.0</td>\n",
       "      <td>600.0</td>\n",
       "      <td>600.0</td>\n",
       "      <td>0</td>\n",
       "      <td>-6000</td>\n",
       "      <td>...</td>\n",
       "      <td>4600.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4600.0</td>\n",
       "      <td>18.640512</td>\n",
       "      <td>18.640512</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7417</th>\n",
       "      <td>928513</td>\n",
       "      <td>26900.000000</td>\n",
       "      <td>9000.0</td>\n",
       "      <td>9000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14300.0</td>\n",
       "      <td>14300.0</td>\n",
       "      <td>14300.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>3600.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3600.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7418</th>\n",
       "      <td>928514</td>\n",
       "      <td>14295.498047</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9490.0</td>\n",
       "      <td>9490.0</td>\n",
       "      <td>9490.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>4800.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4800.0</td>\n",
       "      <td>5.497922</td>\n",
       "      <td>5.497922</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7419</th>\n",
       "      <td>928515</td>\n",
       "      <td>50612.222656</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16800.0</td>\n",
       "      <td>16800.0</td>\n",
       "      <td>16800.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>33062.363281</td>\n",
       "      <td>22462.365234</td>\n",
       "      <td>10600.0</td>\n",
       "      <td>749.858765</td>\n",
       "      <td>203.035263</td>\n",
       "      <td>67.361481</td>\n",
       "      <td>479.462036</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7420 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      nquest             y       yl      yl1     yl2       yt      ytp  \\\n",
       "0        173  16636.652344      0.0      0.0     0.0   9400.0  23400.0   \n",
       "1        375  13939.661133      0.0      0.0     0.0   9100.0   9100.0   \n",
       "2        633  20305.498047      0.0      0.0     0.0  14300.0  14300.0   \n",
       "3        923  13874.424805      0.0      0.0     0.0   8450.0   8450.0   \n",
       "4       1367  14155.201172      0.0      0.0     0.0  10530.0  10530.0   \n",
       "...      ...           ...      ...      ...     ...      ...      ...   \n",
       "7415  928511   4400.000000      0.0      0.0     0.0   4400.0      0.0   \n",
       "7416  928512  18218.640625  19000.0  14000.0  5000.0  -5400.0    600.0   \n",
       "7417  928513  26900.000000   9000.0   9000.0     0.0  14300.0  14300.0   \n",
       "7418  928514  14295.498047      0.0      0.0     0.0   9490.0   9490.0   \n",
       "7419  928515  50612.222656      0.0      0.0     0.0  16800.0  16800.0   \n",
       "\n",
       "         ytp1  ytp2    yta  ...           yca          yca1     yca2  \\\n",
       "0     23400.0     0 -14000  ...   7200.000000      0.000000   7200.0   \n",
       "1      9100.0     0      0  ...   4825.000000      0.000000   4825.0   \n",
       "2     14300.0     0      0  ...   6000.000000      0.000000   6000.0   \n",
       "3      8450.0     0      0  ...   5400.000000      0.000000   5400.0   \n",
       "4     10530.0     0      0  ...   3600.000000      0.000000   3600.0   \n",
       "...       ...   ...    ...  ...           ...           ...      ...   \n",
       "7415      0.0     0   4400  ...      0.000000      0.000000      0.0   \n",
       "7416    600.0     0  -6000  ...   4600.000000      0.000000   4600.0   \n",
       "7417  14300.0     0      0  ...   3600.000000      0.000000   3600.0   \n",
       "7418   9490.0     0      0  ...   4800.000000      0.000000   4800.0   \n",
       "7419  16800.0     0      0  ...  33062.363281  22462.365234  10600.0   \n",
       "\n",
       "             ycf        ycf1       ycf2        ycf3  ycf4  cly  cly2  \n",
       "0      36.652817   36.652817   0.000000    0.000000   0.0    3     2  \n",
       "1      14.661126   14.661126   0.000000    0.000000   0.0    2     1  \n",
       "2       5.497922    5.497922   0.000000    0.000000   0.0    4     2  \n",
       "3      24.424614   24.424614   0.000000    0.000000   0.0    2     1  \n",
       "4      25.201653   25.201653   0.000000    0.000000   0.0    2     1  \n",
       "...          ...         ...        ...         ...   ...  ...   ...  \n",
       "7415    0.000000    0.000000   0.000000    0.000000   0.0    1     1  \n",
       "7416   18.640512   18.640512   0.000000    0.000000   0.0    4     2  \n",
       "7417    0.000000    0.000000   0.000000    0.000000   0.0    6     3  \n",
       "7418    5.497922    5.497922   0.000000    0.000000   0.0    2     1  \n",
       "7419  749.858765  203.035263  67.361481  479.462036   0.0    9     5  \n",
       "\n",
       "[7420 rows x 29 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path2 = r'C:\\Users\\harve\\Documents\\QuantEcon\\projects\\lorenz_curve\\rfam16.dta'\n",
    "income = pd.read_stata(path2)\n",
    "income"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "the variable ``y`` represents net disposible income and is what I will use to determine the lorenz curve and gini coefficent. More detail on the varibales in this file can be found [here](https://www.bancaditalia.it/statistiche/tematiche/indagini-famiglie-imprese/bilanci-famiglie/documentazione/documenti/2016/eng_Legen16.pdf?language_id=1)\n",
    "\n",
    "I'll use the quantecon library to determine the lorenz curve and gini coefficient. The documentation of these functions can be found [here](https://quanteconpy.readthedocs.io/en/latest/tools/inequality.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "l_vals, f_vals = qe.lorenz_curve(income.y.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "\n",
    "plt.plot(l_vals, f_vals, label='income')\n",
    "plt.plot(l_vals, l_vals, 'k--', label='equality')\n",
    "plt.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let look at what the gini coefficient of this lorenz curve is"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.3490282500006961"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qe.gini_coefficient(income.y.values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is pretty good. According to the [world bank](https://data.worldbank.org/indicator/SI.POV.GINI?locations=IT) the gini coefficient for Italy is 0.354 as of 2015."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nquest</th>\n",
       "      <th>ar2</th>\n",
       "      <th>ar3</th>\n",
       "      <th>bd1</th>\n",
       "      <th>bd2</th>\n",
       "      <th>bd</th>\n",
       "      <th>af1</th>\n",
       "      <th>af2</th>\n",
       "      <th>af3</th>\n",
       "      <th>af4</th>\n",
       "      <th>pf1</th>\n",
       "      <th>pf2</th>\n",
       "      <th>pf3</th>\n",
       "      <th>pf</th>\n",
       "      <th>ar1</th>\n",
       "      <th>ar</th>\n",
       "      <th>af</th>\n",
       "      <th>w</th>\n",
       "      <th>clw</th>\n",
       "      <th>clw2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>173</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000</td>\n",
       "      <td>6000</td>\n",
       "      <td>6000.000000</td>\n",
       "      <td>12000.000000</td>\n",
       "      <td>10000.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>120000.0</td>\n",
       "      <td>121000.0</td>\n",
       "      <td>10000.000000</td>\n",
       "      <td>1.310000e+05</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>375</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>500</td>\n",
       "      <td>9904.016602</td>\n",
       "      <td>10404.016602</td>\n",
       "      <td>4000.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>193000.0</td>\n",
       "      <td>193000.0</td>\n",
       "      <td>4000.000000</td>\n",
       "      <td>1.970000e+05</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>633</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3000</td>\n",
       "      <td>5000</td>\n",
       "      <td>10000.000000</td>\n",
       "      <td>15000.000000</td>\n",
       "      <td>1500.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>203000.0</td>\n",
       "      <td>1500.000000</td>\n",
       "      <td>2.045000e+05</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>923</td>\n",
       "      <td>0.0</td>\n",
       "      <td>400</td>\n",
       "      <td>0</td>\n",
       "      <td>5000.000000</td>\n",
       "      <td>5000.000000</td>\n",
       "      <td>6663.775391</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>270000.0</td>\n",
       "      <td>270400.0</td>\n",
       "      <td>6663.775391</td>\n",
       "      <td>2.770638e+05</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1367</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5000</td>\n",
       "      <td>0</td>\n",
       "      <td>10000.000000</td>\n",
       "      <td>10000.000000</td>\n",
       "      <td>6875.775391</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>65000.0</td>\n",
       "      <td>6875.775391</td>\n",
       "      <td>7.187577e+04</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7415</th>\n",
       "      <td>928511</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1500.000000</td>\n",
       "      <td>1500.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>3600</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>2800</td>\n",
       "      <td>2800.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3600.000000</td>\n",
       "      <td>8.000000e+02</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7416</th>\n",
       "      <td>928512</td>\n",
       "      <td>0.0</td>\n",
       "      <td>200</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5085.697754</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>7000.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7000.000000</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>20200.0</td>\n",
       "      <td>5085.697754</td>\n",
       "      <td>1.828570e+04</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7417</th>\n",
       "      <td>928513</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7418</th>\n",
       "      <td>928514</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>15000.000000</td>\n",
       "      <td>15000.000000</td>\n",
       "      <td>1500.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>180000.0</td>\n",
       "      <td>181000.0</td>\n",
       "      <td>1500.000000</td>\n",
       "      <td>1.825000e+05</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7419</th>\n",
       "      <td>928515</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5000</td>\n",
       "      <td>15050</td>\n",
       "      <td>10000.000000</td>\n",
       "      <td>25050.000000</td>\n",
       "      <td>55394.179688</td>\n",
       "      <td>17000.0</td>\n",
       "      <td>66224.71875</td>\n",
       "      <td>0</td>\n",
       "      <td>1560.300415</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1560.300415</td>\n",
       "      <td>961000.0</td>\n",
       "      <td>966000.0</td>\n",
       "      <td>138618.890625</td>\n",
       "      <td>1.103059e+06</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7420 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      nquest  ar2   ar3    bd1           bd2            bd           af1  \\\n",
       "0        173  0.0  1000   6000   6000.000000  12000.000000  10000.000000   \n",
       "1        375  0.0     0    500   9904.016602  10404.016602   4000.000000   \n",
       "2        633  0.0  3000   5000  10000.000000  15000.000000   1500.000000   \n",
       "3        923  0.0   400      0   5000.000000   5000.000000   6663.775391   \n",
       "4       1367  0.0  5000      0  10000.000000  10000.000000   6875.775391   \n",
       "...      ...  ...   ...    ...           ...           ...           ...   \n",
       "7415  928511  0.0     0      0   1500.000000   1500.000000      0.000000   \n",
       "7416  928512  0.0   200      0      0.000000      0.000000   5085.697754   \n",
       "7417  928513  0.0     0      0      0.000000      0.000000      0.000000   \n",
       "7418  928514  0.0  1000      0  15000.000000  15000.000000   1500.000000   \n",
       "7419  928515  0.0  5000  15050  10000.000000  25050.000000  55394.179688   \n",
       "\n",
       "          af2          af3   af4          pf1  pf2   pf3           pf  \\\n",
       "0         0.0      0.00000     0     0.000000    0     0     0.000000   \n",
       "1         0.0      0.00000     0     0.000000    0     0     0.000000   \n",
       "2         0.0      0.00000     0     0.000000    0     0     0.000000   \n",
       "3         0.0      0.00000     0     0.000000    0     0     0.000000   \n",
       "4         0.0      0.00000     0     0.000000    0     0     0.000000   \n",
       "...       ...          ...   ...          ...  ...   ...          ...   \n",
       "7415      0.0      0.00000  3600     0.000000    0  2800  2800.000000   \n",
       "7416      0.0      0.00000     0  7000.000000    0     0  7000.000000   \n",
       "7417      0.0      0.00000     0     0.000000    0     0     0.000000   \n",
       "7418      0.0      0.00000     0     0.000000    0     0     0.000000   \n",
       "7419  17000.0  66224.71875     0  1560.300415    0     0  1560.300415   \n",
       "\n",
       "           ar1        ar             af             w  clw  clw2  \n",
       "0     120000.0  121000.0   10000.000000  1.310000e+05    6     3  \n",
       "1     193000.0  193000.0    4000.000000  1.970000e+05    7     4  \n",
       "2     200000.0  203000.0    1500.000000  2.045000e+05    7     4  \n",
       "3     270000.0  270400.0    6663.775391  2.770638e+05    8     4  \n",
       "4      60000.0   65000.0    6875.775391  7.187577e+04    4     2  \n",
       "...        ...       ...            ...           ...  ...   ...  \n",
       "7415       0.0       0.0    3600.000000  8.000000e+02    1     1  \n",
       "7416   20000.0   20200.0    5085.697754  1.828570e+04    3     2  \n",
       "7417       0.0       0.0       0.000000  0.000000e+00    1     1  \n",
       "7418  180000.0  181000.0    1500.000000  1.825000e+05    7     4  \n",
       "7419  961000.0  966000.0  138618.890625  1.103059e+06   10     5  \n",
       "\n",
       "[7420 rows x 20 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path3 = r'C:\\Users\\harve\\Documents\\QuantEcon\\projects\\lorenz_curve\\ricfam16.dta'\n",
    "wealth = pd.read_stata(path3)\n",
    "wealth"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The varibale ``w`` represents household net wealth and is what I will use to determine the lorenze curve and gini coefficent for household wealth."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "l_vals2, f_vals2 = qe.lorenz_curve(wealth.w.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "\n",
    "plt.plot(l_vals2, f_vals2, label='wealth')\n",
    "plt.plot(l_vals, l_vals, 'k--', label='equality')\n",
    "plt.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5886418992931254"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qe.gini_coefficient(wealth.w.values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets plot both lorenz curves for income and wealth on the same plot to clearly see which is has the largest inequality."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "\n",
    "plt.plot(l_vals2, f_vals2, label='wealth')\n",
    "plt.plot(l_vals, f_vals, label='income')\n",
    "plt.plot(l_vals, l_vals, 'k--', label='equality')\n",
    "plt.legend()\n",
    "\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": "3.8.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}