{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b371530c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from linearmodels import PooledOLS\n",
    "from linearmodels import PanelOLS\n",
    "import statsmodels.api as sm\n",
    "import numpy.linalg as la\n",
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0005395d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('taroutput.csv', \n",
    "                 usecols = ['Country','Countryid','Device','Delta','rho0','rho0se','rho1','rho1se','noobs','Threshold','Transactioncost'],\\\n",
    "                 index_col = ['Country'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "06511d20",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\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>Countryid</th>\n",
       "      <th>Device</th>\n",
       "      <th>Delta</th>\n",
       "      <th>rho0</th>\n",
       "      <th>rho0se</th>\n",
       "      <th>rho1</th>\n",
       "      <th>rho1se</th>\n",
       "      <th>noobs</th>\n",
       "      <th>Threshold</th>\n",
       "      <th>Transactioncost</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AE</th>\n",
       "      <td>1</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>0.947</td>\n",
       "      <td>0.145</td>\n",
       "      <td>-0.132</td>\n",
       "      <td>0.025</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0117</td>\n",
       "      <td>0.03328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AT</th>\n",
       "      <td>2</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.097</td>\n",
       "      <td>0.066</td>\n",
       "      <td>-0.423</td>\n",
       "      <td>0.050</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0476</td>\n",
       "      <td>0.20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AU</th>\n",
       "      <td>3</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>0.694</td>\n",
       "      <td>0.254</td>\n",
       "      <td>-0.437</td>\n",
       "      <td>0.046</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0281</td>\n",
       "      <td>0.10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BE</th>\n",
       "      <td>4</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.047</td>\n",
       "      <td>0.074</td>\n",
       "      <td>-0.429</td>\n",
       "      <td>0.049</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0442</td>\n",
       "      <td>0.21000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BR</th>\n",
       "      <td>5</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.042</td>\n",
       "      <td>0.055</td>\n",
       "      <td>-0.572</td>\n",
       "      <td>0.055</td>\n",
       "      <td>302</td>\n",
       "      <td>0.1449</td>\n",
       "      <td>0.29250</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SG</th>\n",
       "      <td>30</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>48</td>\n",
       "      <td>-1.037</td>\n",
       "      <td>0.061</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>266</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.07000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TH</th>\n",
       "      <td>31</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>48</td>\n",
       "      <td>-1.320</td>\n",
       "      <td>0.126</td>\n",
       "      <td>-0.888</td>\n",
       "      <td>0.093</td>\n",
       "      <td>266</td>\n",
       "      <td>0.0387</td>\n",
       "      <td>0.07000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TR</th>\n",
       "      <td>32</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>48</td>\n",
       "      <td>-1.976</td>\n",
       "      <td>0.125</td>\n",
       "      <td>-0.990</td>\n",
       "      <td>0.067</td>\n",
       "      <td>266</td>\n",
       "      <td>0.0909</td>\n",
       "      <td>0.18000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TW</th>\n",
       "      <td>33</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>48</td>\n",
       "      <td>0.287</td>\n",
       "      <td>0.106</td>\n",
       "      <td>-0.539</td>\n",
       "      <td>0.052</td>\n",
       "      <td>266</td>\n",
       "      <td>0.0332</td>\n",
       "      <td>0.05000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UK</th>\n",
       "      <td>34</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>48</td>\n",
       "      <td>-0.188</td>\n",
       "      <td>0.211</td>\n",
       "      <td>-1.325</td>\n",
       "      <td>0.058</td>\n",
       "      <td>266</td>\n",
       "      <td>0.0279</td>\n",
       "      <td>0.20000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>136 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Countryid          Device  Delta   rho0  rho0se   rho1  rho1se  noobs  \\\n",
       "Country                                                                         \n",
       "AE              1  iPad Pro Large     12  0.947   0.145 -0.132   0.025    302   \n",
       "AT              2  iPad Pro Large     12 -0.097   0.066 -0.423   0.050    302   \n",
       "AU              3  iPad Pro Large     12  0.694   0.254 -0.437   0.046    302   \n",
       "BE              4  iPad Pro Large     12 -0.047   0.074 -0.429   0.049    302   \n",
       "BR              5  iPad Pro Large     12 -0.042   0.055 -0.572   0.055    302   \n",
       "...           ...             ...    ...    ...     ...    ...     ...    ...   \n",
       "SG             30  iPad Pro Large     48 -1.037   0.061    NaN     NaN    266   \n",
       "TH             31  iPad Pro Large     48 -1.320   0.126 -0.888   0.093    266   \n",
       "TR             32  iPad Pro Large     48 -1.976   0.125 -0.990   0.067    266   \n",
       "TW             33  iPad Pro Large     48  0.287   0.106 -0.539   0.052    266   \n",
       "UK             34  iPad Pro Large     48 -0.188   0.211 -1.325   0.058    266   \n",
       "\n",
       "         Threshold  Transactioncost  \n",
       "Country                              \n",
       "AE          0.0117          0.03328  \n",
       "AT          0.0476          0.20000  \n",
       "AU          0.0281          0.10000  \n",
       "BE          0.0442          0.21000  \n",
       "BR          0.1449          0.29250  \n",
       "...            ...              ...  \n",
       "SG             NaN          0.07000  \n",
       "TH          0.0387          0.07000  \n",
       "TR          0.0909          0.18000  \n",
       "TW          0.0332          0.05000  \n",
       "UK          0.0279          0.20000  \n",
       "\n",
       "[136 rows x 10 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.reset_index()[df.reset_index()['Country'] != 'ALL'].set_index('Country')\n",
    "df[df['Device']=='iPad Pro Large']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "67a2e0d7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rickw\\AppData\\Local\\Temp\\ipykernel_6776\\631446254.py:11: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  dfrho = dfrho0.append(dfrho1)\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rho0</th>\n",
       "      <th>Rho</th>\n",
       "      <th>Device</th>\n",
       "      <th>Delta</th>\n",
       "      <th>rho1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AE</th>\n",
       "      <td>0.947</td>\n",
       "      <td>Inner</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AT</th>\n",
       "      <td>-0.097</td>\n",
       "      <td>Inner</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AU</th>\n",
       "      <td>0.694</td>\n",
       "      <td>Inner</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BE</th>\n",
       "      <td>-0.047</td>\n",
       "      <td>Inner</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BR</th>\n",
       "      <td>-0.042</td>\n",
       "      <td>Inner</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SG</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Outer</td>\n",
       "      <td>iPad Mini</td>\n",
       "      <td>48</td>\n",
       "      <td>-0.969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TH</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Outer</td>\n",
       "      <td>iPad Mini</td>\n",
       "      <td>48</td>\n",
       "      <td>-0.555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TR</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Outer</td>\n",
       "      <td>iPad Mini</td>\n",
       "      <td>48</td>\n",
       "      <td>-1.173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TW</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Outer</td>\n",
       "      <td>iPad Mini</td>\n",
       "      <td>48</td>\n",
       "      <td>-0.907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UK</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Outer</td>\n",
       "      <td>iPad Mini</td>\n",
       "      <td>48</td>\n",
       "      <td>-1.542</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1088 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          rho0    Rho          Device  Delta   rho1\n",
       "Country                                            \n",
       "AE       0.947  Inner  iPad Pro Large     12    NaN\n",
       "AT      -0.097  Inner  iPad Pro Large     12    NaN\n",
       "AU       0.694  Inner  iPad Pro Large     12    NaN\n",
       "BE      -0.047  Inner  iPad Pro Large     12    NaN\n",
       "BR      -0.042  Inner  iPad Pro Large     12    NaN\n",
       "...        ...    ...             ...    ...    ...\n",
       "SG         NaN  Outer       iPad Mini     48 -0.969\n",
       "TH         NaN  Outer       iPad Mini     48 -0.555\n",
       "TR         NaN  Outer       iPad Mini     48 -1.173\n",
       "TW         NaN  Outer       iPad Mini     48 -0.907\n",
       "UK         NaN  Outer       iPad Mini     48 -1.542\n",
       "\n",
       "[1088 rows x 5 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfrho0 = pd.DataFrame({'rho0':df['rho0']})\n",
    "dfrho0['Rho'] = 'Inner'\n",
    "dfrho0['Device'] = df['Device']\n",
    "dfrho0['Delta'] = df['Delta']\n",
    "\n",
    "dfrho1 = pd.DataFrame({'rho1':df['rho1']})\n",
    "dfrho1['Rho'] = 'Outer'\n",
    "dfrho1['Device'] = df['Device']\n",
    "dfrho1['Delta'] = df['Delta']\n",
    "\n",
    "dfrho = dfrho0.append(dfrho1)\n",
    "dfrho"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "3e16a115",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "d = 12\n",
    "plt.figure(figsize=(8,8))\n",
    "regdata = df[df['Delta'] == d]\n",
    "sns.regplot(data=regdata, x='Transactioncost', y='Threshold', robust=True, marker='o', scatter_kws={'s':40, \"color\": \"grey\"}, line_kws={\"color\": \"red\"})\n",
    "plt.xlabel(r'Transaction Cost',size=18)\n",
    "plt.ylabel(r'Threshold, $c^{iUS}_{d='+str(d)+'}$',size=18)\n",
    "plt.tick_params(labelsize=16)\n",
    "plt.ylim(0,0.18)\n",
    "plt.savefig('figregctc12.png',transparent=True, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d92bd69d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "d = 24\n",
    "plt.figure(figsize=(8,8))\n",
    "regdata = df[df['Delta'] == d]\n",
    "sns.regplot(data=regdata, x='Transactioncost', y='Threshold', robust=True, marker='o', scatter_kws={'s':40, \"color\": \"grey\"}, line_kws={\"color\": \"red\"})\n",
    "plt.xlabel(r'Transaction Cost',size=18)\n",
    "plt.ylabel(r'Threshold, $c^{iUS}_{d='+str(d)+'}$',size=18)\n",
    "plt.tick_params(labelsize=16)\n",
    "plt.ylim(0,0.18)\n",
    "plt.savefig('figregctc24.png',transparent=True, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "dd6c0f5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "d = 36\n",
    "plt.figure(figsize=(8,8))\n",
    "regdata = df[df['Delta'] == d]\n",
    "sns.regplot(data=regdata, x='Transactioncost', y='Threshold', robust=True, marker='o', scatter_kws={'s':40, \"color\": \"grey\"}, line_kws={\"color\": \"red\"})\n",
    "plt.xlabel(r'Transaction Cost',size=18)\n",
    "plt.ylabel(r'Threshold, $c^{iUS}_{d='+str(d)+'}$',size=18)\n",
    "plt.tick_params(labelsize=16)\n",
    "plt.ylim(0,0.18)\n",
    "plt.savefig('figregctc36.png',transparent=True, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c4c84d05",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "d = 48\n",
    "plt.figure(figsize=(8,8))\n",
    "regdata = df[df['Delta'] == d]\n",
    "sns.regplot(data=regdata, x='Transactioncost', y='Threshold', robust=True, marker='o', scatter_kws={'s':40, \"color\": \"grey\"}, line_kws={\"color\": \"red\"})\n",
    "plt.xlabel(r'Transaction Cost',size=18)\n",
    "plt.ylabel(r'Threshold, $c^{iUS}_{d='+str(d)+'}$',size=18)\n",
    "plt.tick_params(labelsize=16)\n",
    "plt.ylim(0,0.18)\n",
    "plt.savefig('figregctc48.png',transparent=True, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e370a59a",
   "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",
    "sns.boxplot(data=df, x='Delta', y='Threshold', hue='Device', showmeans=True, color='grey',\n",
    "            meanprops={\"marker\":\"o\",\n",
    "                       \"markerfacecolor\":\"white\", \n",
    "                       \"markeredgecolor\":\"black\",\n",
    "                       \"markersize\":\"8\"})\n",
    "\n",
    "plt.xlabel(r'Delta, $d$',size=18)\n",
    "plt.ylabel('Threshold, $c_i$',size=18)\n",
    "plt.ylim(0,0.20)\n",
    "plt.tick_params(labelsize=16)\n",
    "#plt.legend(fontsize='large')\n",
    "plt.legend(loc='upper right', fontsize=18)\n",
    "plt.savefig('figboxplotthreshold.png',transparent=True, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "66046704",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = pd.DataFrame(data=None, index=None, columns=None, dtype=None, copy=None)\n",
    "df2 = pd.DataFrame(data=None, index=None, columns=None, dtype=None, copy=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "3e39fbbb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1['Rho'] = df['rho0']\n",
    "df1['Threshold'] = 'Inner'\n",
    "df1['Delta'] = df['Delta']\n",
    "df1['Device'] = df['Device']\n",
    "\n",
    "df2['Rho'] = df['rho1']\n",
    "df2['Threshold'] = 'Outer'\n",
    "df2['Delta'] = df['Delta']\n",
    "df2['Device'] = df['Device']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "3ec3c8c1",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rickw\\AppData\\Local\\Temp\\ipykernel_6776\\3559124262.py:1: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df3 = df1.append(df2)\n"
     ]
    }
   ],
   "source": [
    "df3 = df1.append(df2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "28c6af6b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df3 = df3.reset_index()[df3.reset_index()['Country'] != 'ALL'].set_index('Country')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "d6c28617",
   "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>Rho</th>\n",
       "      <th>Threshold</th>\n",
       "      <th>Delta</th>\n",
       "      <th>Device</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AE</th>\n",
       "      <td>0.947</td>\n",
       "      <td>Inner</td>\n",
       "      <td>12</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AT</th>\n",
       "      <td>-0.097</td>\n",
       "      <td>Inner</td>\n",
       "      <td>12</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AU</th>\n",
       "      <td>0.694</td>\n",
       "      <td>Inner</td>\n",
       "      <td>12</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BE</th>\n",
       "      <td>-0.047</td>\n",
       "      <td>Inner</td>\n",
       "      <td>12</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BR</th>\n",
       "      <td>-0.042</td>\n",
       "      <td>Inner</td>\n",
       "      <td>12</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SG</th>\n",
       "      <td>-0.969</td>\n",
       "      <td>Outer</td>\n",
       "      <td>48</td>\n",
       "      <td>iPad Mini</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TH</th>\n",
       "      <td>-0.555</td>\n",
       "      <td>Outer</td>\n",
       "      <td>48</td>\n",
       "      <td>iPad Mini</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TR</th>\n",
       "      <td>-1.173</td>\n",
       "      <td>Outer</td>\n",
       "      <td>48</td>\n",
       "      <td>iPad Mini</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TW</th>\n",
       "      <td>-0.907</td>\n",
       "      <td>Outer</td>\n",
       "      <td>48</td>\n",
       "      <td>iPad Mini</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UK</th>\n",
       "      <td>-1.542</td>\n",
       "      <td>Outer</td>\n",
       "      <td>48</td>\n",
       "      <td>iPad Mini</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1088 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Rho Threshold  Delta          Device\n",
       "Country                                        \n",
       "AE       0.947     Inner     12  iPad Pro Large\n",
       "AT      -0.097     Inner     12  iPad Pro Large\n",
       "AU       0.694     Inner     12  iPad Pro Large\n",
       "BE      -0.047     Inner     12  iPad Pro Large\n",
       "BR      -0.042     Inner     12  iPad Pro Large\n",
       "...        ...       ...    ...             ...\n",
       "SG      -0.969     Outer     48       iPad Mini\n",
       "TH      -0.555     Outer     48       iPad Mini\n",
       "TR      -1.173     Outer     48       iPad Mini\n",
       "TW      -0.907     Outer     48       iPad Mini\n",
       "UK      -1.542     Outer     48       iPad Mini\n",
       "\n",
       "[1088 rows x 4 columns]"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "827e2465",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(rc={'figure.figsize':(16,8)})\n",
    "sns.set_theme(style=\"whitegrid\")\n",
    "\n",
    "# Draw a nested violinplot and split the violins for easier comparison\n",
    "sns.violinplot(data=df3, x='Delta', y='Rho', hue='Threshold',\n",
    "               split=True, inner='quart', linewidth=1.5,\n",
    "               palette={'Inner': '0.4', 'Outer': '.8'})\n",
    "plt.xlabel(r'delta, $d$', size=20)\n",
    "plt.ylabel(r'All iPads: $\\hat{\\rho}$', size=20)\n",
    "plt.tick_params(labelsize=16)\n",
    "plt.legend(fontsize='x-large', title_fontsize='40')\n",
    "plt.ylim([-2,1])\n",
    "plt.axhline(y=0, color='black', linestyle='solid')\n",
    "plt.axhline(y=-1, color='black', linestyle='dashed')\n",
    "\n",
    "sns.despine(left=True)\n",
    "plt.savefig('figviolinplotrho.png',transparent=True, bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "45d6bd4f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfrhopl = df3[df3['Device'] == 'iPad Pro Large']\n",
    "\n",
    "sns.set(rc={'figure.figsize':(8,8)})\n",
    "sns.set_theme(style=\"whitegrid\")\n",
    "\n",
    "# Draw a nested violinplot and split the violins for easier comparison\n",
    "sns.violinplot(data=dfrhopl, x='Delta', y='Rho', hue='Threshold',\n",
    "               split=True, inner='quart', linewidth=1.5,\n",
    "               palette={'Inner': '0.4', 'Outer': '.8'})\n",
    "plt.xlabel(r'delta, $d$', size=20)\n",
    "plt.ylabel(r'iPad Pro Large: $\\hat{\\rho}$', size=20)\n",
    "plt.tick_params(labelsize=16)\n",
    "plt.legend(fontsize='x-large', title_fontsize='40')\n",
    "plt.ylim([-2,1])\n",
    "plt.axhline(y=0, color='black', linestyle='solid')\n",
    "plt.axhline(y=-1, color='black', linestyle='dashed')\n",
    "\n",
    "sns.despine(left=True)\n",
    "plt.savefig('figviolinplotrhoprol.png',transparent=True, bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "de14e64f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfrhops = df3[df3['Device'] == 'iPad Pro Small']\n",
    "\n",
    "sns.set(rc={'figure.figsize':(8,8)})\n",
    "sns.set_theme(style=\"whitegrid\")\n",
    "\n",
    "# Draw a nested violinplot and split the violins for easier comparison\n",
    "sns.violinplot(data=dfrhops, x='Delta', y='Rho', hue='Threshold',\n",
    "               split=True, inner='quart', linewidth=1.5,\n",
    "               palette={'Inner': '0.4', 'Outer': '.8'})\n",
    "plt.xlabel(r'delta, $d$', size=20)\n",
    "plt.ylabel(r'iPad Pro Small: $\\hat{\\rho}$', size=20)\n",
    "plt.tick_params(labelsize=16)\n",
    "plt.legend(fontsize='x-large', title_fontsize='40')\n",
    "plt.ylim([-2,1])\n",
    "plt.axhline(y=0, color='black', linestyle='solid')\n",
    "plt.axhline(y=-1, color='black', linestyle='dashed')\n",
    "\n",
    "sns.despine(left=True)\n",
    "plt.savefig('figviolinplotrhopros.png',transparent=True, bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "f15746f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfrhoip = df3[df3['Device'] == 'iPad']\n",
    "\n",
    "sns.set(rc={'figure.figsize':(8,8)})\n",
    "sns.set_theme(style=\"whitegrid\")\n",
    "\n",
    "# Draw a nested violinplot and split the violins for easier comparison\n",
    "sns.violinplot(data=dfrhoip, x='Delta', y='Rho', hue='Threshold',\n",
    "               split=True, inner='quart', linewidth=1.5,\n",
    "               palette={'Inner': '0.4', 'Outer': '.8'})\n",
    "plt.xlabel(r'delta, $d$', size=20)\n",
    "plt.ylabel(r'iPad Air: $\\hat{\\rho}$', size=20)\n",
    "plt.tick_params(labelsize=16)\n",
    "plt.legend(fontsize='x-large', title_fontsize='40')\n",
    "plt.ylim([-2,1])\n",
    "plt.axhline(y=0, color='black', linestyle='solid')\n",
    "plt.axhline(y=-1, color='black', linestyle='dashed')\n",
    "\n",
    "sns.despine(left=True)\n",
    "plt.savefig('figviolinplotrhoip.png',transparent=True, bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "622b3eba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfrhoipm = df3[df3['Device'] == 'iPad Mini']\n",
    "\n",
    "sns.set(rc={'figure.figsize':(8,8)})\n",
    "sns.set_theme(style=\"whitegrid\")\n",
    "\n",
    "# Draw a nested violinplot and split the violins for easier comparison\n",
    "sns.violinplot(data=dfrhoipm, x='Delta', y='Rho', hue='Threshold',\n",
    "               split=True, inner='quart', linewidth=1.5,\n",
    "               palette={'Inner': '0.4', 'Outer': '.8'})\n",
    "plt.xlabel(r'delta, $d$', size=20)\n",
    "plt.ylabel(r'iPad Mini: $\\hat{\\rho}$', size=20)\n",
    "plt.tick_params(labelsize=16)\n",
    "plt.legend(fontsize='x-large', title_fontsize='40')\n",
    "plt.ylim([-2,1])\n",
    "plt.axhline(y=0, color='black', linestyle='solid')\n",
    "plt.axhline(y=-1, color='black', linestyle='dashed')\n",
    "\n",
    "sns.despine(left=True)\n",
    "plt.savefig('figviolinplotrhoipm.png',transparent=True, bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "7718e052",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,8))\n",
    "\n",
    "sns.boxplot(data=dfrho, x='Delta', y='rho0', hue='Device', showmeans=True, color='grey', showfliers = False,\n",
    "            meanprops={\"marker\":\"o\",\n",
    "                       \"markerfacecolor\":\"white\", \n",
    "                       \"markeredgecolor\":\"black\",\n",
    "                       \"markersize\":\"8\"})\n",
    "\n",
    "sns.boxplot(data=dfrho, x='Delta', y='rho1', hue='Device', showmeans=True, color='grey', showfliers = False,\n",
    "            meanprops={\"marker\":\"o\",\n",
    "                       \"markerfacecolor\":\"white\", \n",
    "                       \"markeredgecolor\":\"black\",\n",
    "                       \"markersize\":\"8\"})\n",
    "\n",
    "\n",
    "plt.xlabel(r'Delta, $d$',size=18)\n",
    "plt.ylabel('Threshold, $c_i$',size=18)\n",
    "#plt.ylim(0,0.20)\n",
    "plt.tick_params(labelsize=16)\n",
    "#plt.legend(fontsize='large')\n",
    "plt.legend(loc='upper right', fontsize=18)\n",
    "plt.savefig('figboxplotthreshold.png',transparent=True, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6f7d83cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.boxplot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1be1c57a",
   "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>Countryid</th>\n",
       "      <th>Device</th>\n",
       "      <th>Delta</th>\n",
       "      <th>rho0</th>\n",
       "      <th>rho0se</th>\n",
       "      <th>rho1</th>\n",
       "      <th>rho1se</th>\n",
       "      <th>noobs</th>\n",
       "      <th>Threshold</th>\n",
       "      <th>Transactioncost</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ALL</th>\n",
       "      <td>a</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.33185</td>\n",
       "      <td>0.00891</td>\n",
       "      <td>-0.642742</td>\n",
       "      <td>0.016837</td>\n",
       "      <td>10268</td>\n",
       "      <td>0.1235</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AE</th>\n",
       "      <td>1</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>0.94700</td>\n",
       "      <td>0.14500</td>\n",
       "      <td>-0.132000</td>\n",
       "      <td>0.025000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0117</td>\n",
       "      <td>0.033280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AT</th>\n",
       "      <td>2</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.09700</td>\n",
       "      <td>0.06600</td>\n",
       "      <td>-0.423000</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0476</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AU</th>\n",
       "      <td>3</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>0.69400</td>\n",
       "      <td>0.25400</td>\n",
       "      <td>-0.437000</td>\n",
       "      <td>0.046000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0281</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BE</th>\n",
       "      <td>4</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.04700</td>\n",
       "      <td>0.07400</td>\n",
       "      <td>-0.429000</td>\n",
       "      <td>0.049000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0442</td>\n",
       "      <td>0.210000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BR</th>\n",
       "      <td>5</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.04200</td>\n",
       "      <td>0.05500</td>\n",
       "      <td>-0.572000</td>\n",
       "      <td>0.055000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.1449</td>\n",
       "      <td>0.292500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA</th>\n",
       "      <td>6</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-1.32400</td>\n",
       "      <td>0.20700</td>\n",
       "      <td>-0.341000</td>\n",
       "      <td>0.043000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0247</td>\n",
       "      <td>0.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CZ</th>\n",
       "      <td>7</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>0.82100</td>\n",
       "      <td>0.21700</td>\n",
       "      <td>-0.348000</td>\n",
       "      <td>0.041000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0305</td>\n",
       "      <td>0.210000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td>8</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.13400</td>\n",
       "      <td>0.05900</td>\n",
       "      <td>-0.458000</td>\n",
       "      <td>0.056000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0543</td>\n",
       "      <td>0.190000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DK</th>\n",
       "      <td>9</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>0.17400</td>\n",
       "      <td>0.11200</td>\n",
       "      <td>-0.399000</td>\n",
       "      <td>0.046000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0346</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ES</th>\n",
       "      <td>10</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.09900</td>\n",
       "      <td>0.06700</td>\n",
       "      <td>-0.420000</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0477</td>\n",
       "      <td>0.210000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FI</th>\n",
       "      <td>11</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.08800</td>\n",
       "      <td>0.06900</td>\n",
       "      <td>-0.441000</td>\n",
       "      <td>0.051000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0479</td>\n",
       "      <td>0.240000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FR</th>\n",
       "      <td>12</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.04700</td>\n",
       "      <td>0.07400</td>\n",
       "      <td>-0.429000</td>\n",
       "      <td>0.049000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0442</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HK</th>\n",
       "      <td>13</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>0.01200</td>\n",
       "      <td>0.02200</td>\n",
       "      <td>-0.522000</td>\n",
       "      <td>0.047000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0306</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HU</th>\n",
       "      <td>14</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-1.26400</td>\n",
       "      <td>0.16700</td>\n",
       "      <td>-0.411000</td>\n",
       "      <td>0.051000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0311</td>\n",
       "      <td>0.270000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IE</th>\n",
       "      <td>15</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.08900</td>\n",
       "      <td>0.07000</td>\n",
       "      <td>-0.443000</td>\n",
       "      <td>0.051000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0455</td>\n",
       "      <td>0.230000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IT</th>\n",
       "      <td>16</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.05200</td>\n",
       "      <td>0.07300</td>\n",
       "      <td>-0.430000</td>\n",
       "      <td>0.049000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0451</td>\n",
       "      <td>0.220000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JP</th>\n",
       "      <td>17</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.31700</td>\n",
       "      <td>0.07300</td>\n",
       "      <td>-0.679000</td>\n",
       "      <td>0.067000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0845</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KR</th>\n",
       "      <td>18</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.49100</td>\n",
       "      <td>0.04700</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>302</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LU</th>\n",
       "      <td>19</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.04400</td>\n",
       "      <td>0.07300</td>\n",
       "      <td>-0.429000</td>\n",
       "      <td>0.049000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0441</td>\n",
       "      <td>0.170000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MX</th>\n",
       "      <td>20</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.27000</td>\n",
       "      <td>0.06600</td>\n",
       "      <td>-0.669000</td>\n",
       "      <td>0.065000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0881</td>\n",
       "      <td>0.160000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MY</th>\n",
       "      <td>21</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-1.22800</td>\n",
       "      <td>0.24700</td>\n",
       "      <td>-0.540000</td>\n",
       "      <td>0.052000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0185</td>\n",
       "      <td>0.082038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NL</th>\n",
       "      <td>22</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.04200</td>\n",
       "      <td>0.07300</td>\n",
       "      <td>-0.433000</td>\n",
       "      <td>0.049000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0446</td>\n",
       "      <td>0.210000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NO</th>\n",
       "      <td>23</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.16900</td>\n",
       "      <td>0.06600</td>\n",
       "      <td>-0.481000</td>\n",
       "      <td>0.058000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0845</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NZ</th>\n",
       "      <td>24</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.31600</td>\n",
       "      <td>0.08700</td>\n",
       "      <td>-0.622000</td>\n",
       "      <td>0.061000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0630</td>\n",
       "      <td>0.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PH</th>\n",
       "      <td>25</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>0.02200</td>\n",
       "      <td>0.04100</td>\n",
       "      <td>-0.668000</td>\n",
       "      <td>0.052000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0791</td>\n",
       "      <td>0.120000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PL</th>\n",
       "      <td>26</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.35700</td>\n",
       "      <td>0.04500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>302</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.230000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PT</th>\n",
       "      <td>27</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.08600</td>\n",
       "      <td>0.06700</td>\n",
       "      <td>-0.444000</td>\n",
       "      <td>0.052000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0494</td>\n",
       "      <td>0.230000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RU</th>\n",
       "      <td>28</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.22500</td>\n",
       "      <td>0.08200</td>\n",
       "      <td>-1.044000</td>\n",
       "      <td>0.056000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0738</td>\n",
       "      <td>0.190000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SE</th>\n",
       "      <td>29</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>1.66400</td>\n",
       "      <td>0.61400</td>\n",
       "      <td>-0.350000</td>\n",
       "      <td>0.043000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0172</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SG</th>\n",
       "      <td>30</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.54100</td>\n",
       "      <td>0.04700</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>302</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.070000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TH</th>\n",
       "      <td>31</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>0.25300</td>\n",
       "      <td>0.20000</td>\n",
       "      <td>-0.433000</td>\n",
       "      <td>0.053000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0220</td>\n",
       "      <td>0.070000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TR</th>\n",
       "      <td>32</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.48300</td>\n",
       "      <td>0.09600</td>\n",
       "      <td>-0.796000</td>\n",
       "      <td>0.073000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.1174</td>\n",
       "      <td>0.180000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TW</th>\n",
       "      <td>33</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>0.09100</td>\n",
       "      <td>0.12900</td>\n",
       "      <td>-0.255000</td>\n",
       "      <td>0.038000</td>\n",
       "      <td>302</td>\n",
       "      <td>0.0245</td>\n",
       "      <td>0.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UK</th>\n",
       "      <td>34</td>\n",
       "      <td>iPad Pro Large</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.36800</td>\n",
       "      <td>0.04500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>302</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Countryid          Device  Delta     rho0   rho0se      rho1  \\\n",
       "Country                                                                \n",
       "ALL             a  iPad Pro Large     12 -0.33185  0.00891 -0.642742   \n",
       "AE              1  iPad Pro Large     12  0.94700  0.14500 -0.132000   \n",
       "AT              2  iPad Pro Large     12 -0.09700  0.06600 -0.423000   \n",
       "AU              3  iPad Pro Large     12  0.69400  0.25400 -0.437000   \n",
       "BE              4  iPad Pro Large     12 -0.04700  0.07400 -0.429000   \n",
       "BR              5  iPad Pro Large     12 -0.04200  0.05500 -0.572000   \n",
       "CA              6  iPad Pro Large     12 -1.32400  0.20700 -0.341000   \n",
       "CZ              7  iPad Pro Large     12  0.82100  0.21700 -0.348000   \n",
       "DE              8  iPad Pro Large     12 -0.13400  0.05900 -0.458000   \n",
       "DK              9  iPad Pro Large     12  0.17400  0.11200 -0.399000   \n",
       "ES             10  iPad Pro Large     12 -0.09900  0.06700 -0.420000   \n",
       "FI             11  iPad Pro Large     12 -0.08800  0.06900 -0.441000   \n",
       "FR             12  iPad Pro Large     12 -0.04700  0.07400 -0.429000   \n",
       "HK             13  iPad Pro Large     12  0.01200  0.02200 -0.522000   \n",
       "HU             14  iPad Pro Large     12 -1.26400  0.16700 -0.411000   \n",
       "IE             15  iPad Pro Large     12 -0.08900  0.07000 -0.443000   \n",
       "IT             16  iPad Pro Large     12 -0.05200  0.07300 -0.430000   \n",
       "JP             17  iPad Pro Large     12 -0.31700  0.07300 -0.679000   \n",
       "KR             18  iPad Pro Large     12 -0.49100  0.04700       NaN   \n",
       "LU             19  iPad Pro Large     12 -0.04400  0.07300 -0.429000   \n",
       "MX             20  iPad Pro Large     12 -0.27000  0.06600 -0.669000   \n",
       "MY             21  iPad Pro Large     12 -1.22800  0.24700 -0.540000   \n",
       "NL             22  iPad Pro Large     12 -0.04200  0.07300 -0.433000   \n",
       "NO             23  iPad Pro Large     12 -0.16900  0.06600 -0.481000   \n",
       "NZ             24  iPad Pro Large     12 -0.31600  0.08700 -0.622000   \n",
       "PH             25  iPad Pro Large     12  0.02200  0.04100 -0.668000   \n",
       "PL             26  iPad Pro Large     12 -0.35700  0.04500       NaN   \n",
       "PT             27  iPad Pro Large     12 -0.08600  0.06700 -0.444000   \n",
       "RU             28  iPad Pro Large     12 -0.22500  0.08200 -1.044000   \n",
       "SE             29  iPad Pro Large     12  1.66400  0.61400 -0.350000   \n",
       "SG             30  iPad Pro Large     12 -0.54100  0.04700       NaN   \n",
       "TH             31  iPad Pro Large     12  0.25300  0.20000 -0.433000   \n",
       "TR             32  iPad Pro Large     12 -0.48300  0.09600 -0.796000   \n",
       "TW             33  iPad Pro Large     12  0.09100  0.12900 -0.255000   \n",
       "UK             34  iPad Pro Large     12 -0.36800  0.04500       NaN   \n",
       "\n",
       "           rho1se  noobs  Threshold  Transactioncost  \n",
       "Country                                               \n",
       "ALL      0.016837  10268     0.1235              NaN  \n",
       "AE       0.025000    302     0.0117         0.033280  \n",
       "AT       0.050000    302     0.0476         0.200000  \n",
       "AU       0.046000    302     0.0281         0.100000  \n",
       "BE       0.049000    302     0.0442         0.210000  \n",
       "BR       0.055000    302     0.1449         0.292500  \n",
       "CA       0.043000    302     0.0247         0.050000  \n",
       "CZ       0.041000    302     0.0305         0.210000  \n",
       "DE       0.056000    302     0.0543         0.190000  \n",
       "DK       0.046000    302     0.0346         0.250000  \n",
       "ES       0.050000    302     0.0477         0.210000  \n",
       "FI       0.051000    302     0.0479         0.240000  \n",
       "FR       0.049000    302     0.0442         0.200000  \n",
       "HK       0.047000    302     0.0306         0.000000  \n",
       "HU       0.051000    302     0.0311         0.270000  \n",
       "IE       0.051000    302     0.0455         0.230000  \n",
       "IT       0.049000    302     0.0451         0.220000  \n",
       "JP       0.067000    302     0.0845         0.000000  \n",
       "KR            NaN    302        NaN         0.100000  \n",
       "LU       0.049000    302     0.0441         0.170000  \n",
       "MX       0.065000    302     0.0881         0.160000  \n",
       "MY       0.052000    302     0.0185         0.082038  \n",
       "NL       0.049000    302     0.0446         0.210000  \n",
       "NO       0.058000    302     0.0845         0.250000  \n",
       "NZ       0.061000    302     0.0630         0.150000  \n",
       "PH       0.052000    302     0.0791         0.120000  \n",
       "PL            NaN    302        NaN         0.230000  \n",
       "PT       0.052000    302     0.0494         0.230000  \n",
       "RU       0.056000    302     0.0738         0.190000  \n",
       "SE       0.043000    302     0.0172         0.250000  \n",
       "SG            NaN    302        NaN         0.070000  \n",
       "TH       0.053000    302     0.0220         0.070000  \n",
       "TR       0.073000    302     0.1174         0.180000  \n",
       "TW       0.038000    302     0.0245         0.050000  \n",
       "UK            NaN    302        NaN         0.200000  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dffilter1 = df[df['Delta'] == 12]\n",
    "dffilter2 = dffilter1[dffilter1['Device'] == 'iPad Pro Large']\n",
    "dffilter2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "02ad06c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'302'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "str(dffilter2['noobs']['AE'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7b117056",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{table}[ht]\\centering\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Pro Large Devices, $d = 24$}\\label{regTAR: iPad Pro Large Delta24}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad Pro Large, $d=24$, No. Observations: 290}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  1.893&  \\footnotesize{(0.182)***}&  -0.271&  \\footnotesize{(0.031)***}&  0.012&  $\\infty$  &  1.012  \\\\\n",
      "AT\n",
      "&  -0.262&  \\footnotesize{(0.090)***}&  -0.826&  \\footnotesize{(0.064)***}&  0.047&  1.053  &  0.183  \\\\\n",
      "AU\n",
      "&  -0.439&  \\footnotesize{(0.070)***}&  -1.189&  \\footnotesize{(0.079)***}&  0.086&  0.553  &  0  \\\\\n",
      "BE\n",
      "&  -0.196&  \\footnotesize{(0.094)**}&  -0.874&  \\footnotesize{(0.063)***}&  0.045&  1.466  &  0.154  \\\\\n",
      "BR\n",
      "&  -0.236&  \\footnotesize{(0.072)***}&  -0.751&  \\footnotesize{(0.067)***}&  0.140&  1.188  &  0.23  \\\\\n",
      "CA\n",
      "&  -1.925&  \\footnotesize{(0.245)***}&  -0.495&  \\footnotesize{(0.049)***}&  0.025&  0  &  0.468  \\\\\n",
      "CZ\n",
      "&  0.867&  \\footnotesize{(0.326)***}&  -0.580&  \\footnotesize{(0.051)***}&  0.028&  $\\infty$  &  0.369  \\\\\n",
      "DE\n",
      "&  -0.265&  \\footnotesize{(0.092)***}&  -0.839&  \\footnotesize{(0.065)***}&  0.047&  1.039  &  0.175  \\\\\n",
      "DK\n",
      "&  -0.193&  \\footnotesize{(0.099)*}&  -0.963&  \\footnotesize{(0.066)***}&  0.046&  1.492  &  0.097  \\\\\n",
      "ES\n",
      "&  -0.290&  \\footnotesize{(0.089)***}&  -0.809&  \\footnotesize{(0.065)***}&  0.048&  0.934  &  0.193  \\\\\n",
      "FI\n",
      "&  -0.393&  \\footnotesize{(0.080)***}&  -0.944&  \\footnotesize{(0.073)***}&  0.053&  0.641  &  0.111  \\\\\n",
      "FR\n",
      "&  -0.196&  \\footnotesize{(0.094)**}&  -0.874&  \\footnotesize{(0.063)***}&  0.045&  1.466  &  0.154  \\\\\n",
      "HK\n",
      "&  0.044&  \\footnotesize{(0.023)*}&  -1.076&  \\footnotesize{(0.047)***}&  0.031&  $\\infty$  &  0  \\\\\n",
      "HU\n",
      "&  -0.635&  \\footnotesize{(0.078)***}&  -0.965&  \\footnotesize{(0.087)***}&  0.075&  0.317  &  0.095  \\\\\n",
      "IE\n",
      "&  -0.304&  \\footnotesize{(0.090)***}&  -0.877&  \\footnotesize{(0.066)***}&  0.046&  0.883  &  0.153  \\\\\n",
      "IT\n",
      "&  -0.152&  \\footnotesize{(0.100)}&  -0.859&  \\footnotesize{(0.061)***}&  0.042&  1.94  &  0.163  \\\\\n",
      "JP\n",
      "&  -0.729&  \\footnotesize{(0.082)***}&  -1.285&  \\footnotesize{(0.076)***}&  0.093&  0.245  &  0  \\\\\n",
      "KR\n",
      "&  -1.479&  \\footnotesize{(0.179)***}&  -0.858&  \\footnotesize{(0.058)***}&  0.027&  0  &  0.164  \\\\\n",
      "LU\n",
      "&  -0.147&  \\footnotesize{(0.095)}&  -0.866&  \\footnotesize{(0.062)***}&  0.044&  2.012  &  0.159  \\\\\n",
      "MX\n",
      "&  -0.374&  \\footnotesize{(0.073)***}&  -1.018&  \\footnotesize{(0.074)***}&  0.093&  0.683  &  0  \\\\\n",
      "MY\n",
      "&  -1.454&  \\footnotesize{(0.083)***}&  -0.963&  \\footnotesize{(0.064)***}&  0.054&  0  &  0.097  \\\\\n",
      "NL\n",
      "&  -0.172&  \\footnotesize{(0.094)*}&  -0.879&  \\footnotesize{(0.063)***}&  0.045&  1.695  &  0.151  \\\\\n",
      "NO\n",
      "&  -0.245&  \\footnotesize{(0.100)**}&  -0.680&  \\footnotesize{(0.062)***}&  0.074&  1.138  &  0.281  \\\\\n",
      "NZ\n",
      "&  -0.481&  \\footnotesize{(0.100)***}&  -1.005&  \\footnotesize{(0.068)***}&  0.061&  0.488  &  0  \\\\\n",
      "PH\n",
      "&  0.517&  \\footnotesize{(0.094)***}&  -0.711&  \\footnotesize{(0.046)***}&  0.056&  $\\infty$  &  0.258  \\\\\n",
      "PL\n",
      "&  -0.392&  \\footnotesize{(0.076)***}&  -0.726&  \\footnotesize{(0.073)***}&  0.084&  0.643  &  0.247  \\\\\n",
      "PT\n",
      "&  -0.366&  \\footnotesize{(0.079)***}&  -0.943&  \\footnotesize{(0.072)***}&  0.053&  0.702  &  0.112  \\\\\n",
      "RU\n",
      "&  -0.741&  \\footnotesize{(0.090)***}&  -1.029&  \\footnotesize{(0.063)***}&  0.080&  0.237  &  0  \\\\\n",
      "SE\n",
      "&  -0.869&  \\footnotesize{(0.083)***}&  -0.484&  \\footnotesize{(0.071)***}&  0.072&  0.157  &  0.484  \\\\\n",
      "SG\n",
      "&  -1.493&  \\footnotesize{(0.171)***}&  -0.857&  \\footnotesize{(0.058)***}&  0.017&  0  &  0.164  \\\\\n",
      "TH\n",
      "&  0.236&  \\footnotesize{(0.212)}&  -0.919&  \\footnotesize{(0.071)***}&  0.024&  $\\infty$  &  0.127  \\\\\n",
      "TR\n",
      "&  2.681&  \\footnotesize{(1.031)***}&  -1.205&  \\footnotesize{(0.060)***}&  0.018&  $\\infty$  &  0  \\\\\n",
      "TW\n",
      "&  -0.117&  \\footnotesize{(0.126)}&  -0.486&  \\footnotesize{(0.054)***}&  0.033&  2.571  &  0.481  \\\\\n",
      "UK\n",
      "&  -0.191&  \\footnotesize{(0.126)}&  -0.856&  \\footnotesize{(0.060)***}&  0.046&  1.509  &  0.165  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  -0.250&  0.139&  -0.852&  0.063&  0.053&  1.112&  0.168\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -0.264&  0.094&  -0.870&  0.064&  0.046&  1.046&  0.157\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  0.838&  0.166&  0.210&  0.010&  0.026 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rickw\\AppData\\Local\\Temp\\ipykernel_18180\\3403052443.py:47: RuntimeWarning: invalid value encountered in log10\n",
      "  hl1 = np.log10(0.5) / np.log10(1+dffilter2['rho1'][c]) / (52 / Delta)\n",
      "C:\\Users\\rickw\\AppData\\Local\\Temp\\ipykernel_18180\\3403052443.py:46: RuntimeWarning: invalid value encountered in log10\n",
      "  hl0 = np.log10(0.5) / np.log10(1+dffilter2['rho0'][c]) / (52 / Delta)\n"
     ]
    }
   ],
   "source": [
    "Delta = 24\n",
    "Device = 'iPad Pro Large'\n",
    "\n",
    "dffilter1 = df[df['Delta'] == Delta]\n",
    "dffilter2 = dffilter1[dffilter1['Device'] == Device]\n",
    "dffilter2\n",
    "coeffinner = []\n",
    "coeffouter = []\n",
    "seinner = []\n",
    "seouter = []\n",
    "thold = []\n",
    "\n",
    "countrylist = ['AE','AT','AU','BE','BR','CA','CZ','DE','DK','ES','FI','FR','HK','HU','IE','IT',\n",
    "              'JP','KR','LU','MX','MY','NL','NO','NZ','PH','PL','PT','RU','SE','SG','TH','TR','TW','UK']\n",
    "\n",
    "print('\\\\begin{table}[ht]' + '\\\\centering')\n",
    "print(r'\\caption{Threshold Autogregression Persistence Estimates for '+ Device +' Devices, $d = '+ str(Delta) +'$}\\\\label{regTAR: '+ Device + ' Delta' + str(Delta) +'}')\n",
    "print('\\\\begin{tabular}{ c r l r l c c c } ')\n",
    "print('\\\\hline')\n",
    "print('\\\\hline')\n",
    "print(' ')\n",
    "print('& \\\\multicolumn{7}{c}{$i=$'+ Device +', $d='+ str(Delta) +'$, No. Observations: ' + str(dffilter2['noobs']['AE']) + '}' + '\\\\'+ '\\\\')\n",
    "print('\\\\cline{2-8}')\n",
    "print('\\\\'+ '\\\\'+'[-0.1ex]')\n",
    "print('Country')\n",
    "print('& \\\\multicolumn{1}{c}{ Inner} ')\n",
    "print('& \\\\multicolumn{1}{c}{ Inner} ')\n",
    "print('& \\\\multicolumn{1}{c}{ Outer} ')\n",
    "print('& \\\\multicolumn{1}{c}{ Outer} ')\n",
    "print('& \\\\multicolumn{1}{c}{ Threshold} ')\n",
    "print('& \\\\multicolumn{1}{c}{ Half-life} ')\n",
    "print('& \\\\multicolumn{1}{c}{ Half-life} '+ '\\\\'+ '\\\\')\n",
    "print('')\n",
    "print('& \\\\multicolumn{1}{c}{ $\\\\hat{\\\\rho}_{0}$ } ')\n",
    "print('& \\\\multicolumn{1}{c}{ SE} ')\n",
    "print('& \\\\multicolumn{1}{c}{ $\\\\hat{\\\\rho}_{1}$ } ')\n",
    "print('& \\\\multicolumn{1}{c}{ SE} ')\n",
    "print('& \\\\multicolumn{1}{c}{ $c_i$ } ')\n",
    "print('& \\\\multicolumn{1}{c}{ $\\\\hat{\\\\rho}_{0}$ } ')\n",
    "print('& \\\\multicolumn{1}{c}{ $\\\\hat{\\\\rho}_{1}$ } '+ '\\\\'+ '\\\\')\n",
    "print('\\\\hline'+ '\\\\'+ '\\\\'+'[-0.8ex] ')\n",
    "\n",
    "for c in countrylist:\n",
    "    print(c)\n",
    "    \n",
    "    hl0 = np.log10(0.5) / np.log10(1+dffilter2['rho0'][c]) / (52 / Delta)\n",
    "    hl1 = np.log10(0.5) / np.log10(1+dffilter2['rho1'][c]) / (52 / Delta)\n",
    "    \n",
    "    if hl0 < 0:\n",
    "        hl0 = '$\\infty$'\n",
    "    elif dffilter2['rho0'][c] < -1:\n",
    "        hl0 = str(0)\n",
    "    else:\n",
    "        hl0 = str(round(hl0,3))\n",
    "        \n",
    "    if hl1 < 0:\n",
    "        hl1 = '$\\infty$'\n",
    "    elif dffilter2['rho1'][c] < -1:\n",
    "        hl1 = str(0)    \n",
    "    else:\n",
    "        hl1 = str(round(hl1,3))\n",
    "        \n",
    "    # Statistical Significance Tests:\n",
    "    \n",
    "    if ((dffilter2['rho0'][c] / dffilter2['rho0se'][c]) > 2.576 or (dffilter2['rho0'][c] / dffilter2['rho0se'][c]) < -2.576):\n",
    "                          sig0 = '***'\n",
    "    elif ((dffilter2['rho0'][c] / dffilter2['rho0se'][c]) > 1.96 or (dffilter2['rho0'][c] / dffilter2['rho0se'][c]) < -1.96):\n",
    "                          sig0 = '**'\n",
    "    elif ((dffilter2['rho0'][c] / dffilter2['rho0se'][c]) > 1.645 or (dffilter2['rho0'][c] / dffilter2['rho0se'][c]) < -1.645):\n",
    "                          sig0 = '*'\n",
    "    else:\n",
    "        sig0 = ''\n",
    "     \n",
    "    \n",
    "    if ((dffilter2['rho1'][c] / dffilter2['rho1se'][c]) > 2.576 or (dffilter2['rho1'][c] / dffilter2['rho1se'][c]) < -2.576):\n",
    "                          sig1 = '***'\n",
    "    elif ((dffilter2['rho1'][c] / dffilter2['rho1se'][c]) > 1.96 or (dffilter2['rho1'][c] / dffilter2['rho1se'][c]) < -1.96):\n",
    "                          sig1 = '**'    \n",
    "    elif ((dffilter2['rho1'][c] / dffilter2['rho1se'][c]) > 1.645 or (dffilter2['rho1'][c] / dffilter2['rho1se'][c]) < -1.645):\n",
    "                          sig1 = '*'\n",
    "    else:\n",
    "        sig1 = ''\n",
    "    \n",
    "    # LaTex Output:\n",
    "    \n",
    "\n",
    "    \n",
    "    print('&  ' + str(\"%.3f\" % round(dffilter2['rho0'][c],3)) + \n",
    "          '&  \\\\footnotesize{(' + str(\"%.3f\" % round(dffilter2['rho0se'][c],3)) + ')' + sig0 + '}' +\n",
    "          '&  ' + str(\"%.3f\" % round(dffilter2['rho1'][c],3)) + \n",
    "          '&  \\\\footnotesize{(' + str(\"%.3f\" % round(dffilter2['rho1se'][c],3)) + ')' + sig1 + '}' +\n",
    "          '&  ' + str(\"%.3f\" % round(dffilter2['Threshold'][c],3)) + \n",
    "          '&  ' + hl0 + '  &  ' + hl1 + '  \\\\' + '\\\\')  \n",
    "        \n",
    "    coeffinner.append(dffilter2['rho0'][c])\n",
    "    coeffouter.append(dffilter2['rho1'][c])\n",
    "    seinner.append(dffilter2['rho0se'][c])\n",
    "    seouter.append(dffilter2['rho1se'][c])\n",
    "    thold.append(dffilter2['Threshold'][c])\n",
    "\n",
    "print('\\hline')\n",
    "print('\\multicolumn{1}{l}{ Average }' +\n",
    "          '&  ' + str(\"%.3f\" % round(np.nanmean(coeffinner),3)) + \n",
    "          '&  ' + str(\"%.3f\" % round(np.nanmean(seinner),3)) +    \n",
    "          '&  ' + str(\"%.3f\" % round(np.nanmean(coeffouter),3)) +  \n",
    "          '&  ' + str(\"%.3f\" % round(np.nanmean(seouter),3)) + \n",
    "          '&  ' + str(\"%.3f\" % round(np.nanmean(thold),3)) +         \n",
    "          '&  ' + str(\"%.3f\" % round(np.log10(0.5) / np.log10(1+np.nanmean(coeffinner)) / (52 / Delta),3)) +\n",
    "          '&  ' + str(\"%.3f\" % round(np.log10(0.5) / np.log10(1+np.nanmean(coeffouter)) / (52 / Delta),3)) +'\\\\' + '\\\\')\n",
    "\n",
    "print('\\multicolumn{1}{l}{ Median }' +\n",
    "          '&  ' + str(\"%.3f\" % round(np.nanmedian(coeffinner),3)) + \n",
    "          '&  ' + str(\"%.3f\" % round(np.nanmedian(seinner),3)) +    \n",
    "          '&  ' + str(\"%.3f\" % round(np.nanmedian(coeffouter),3)) +  \n",
    "          '&  ' + str(\"%.3f\" % round(np.nanmedian(seouter),3)) + \n",
    "          '&  ' + str(\"%.3f\" % round(np.nanmedian(thold),3)) +         \n",
    "          '&  ' + str(\"%.3f\" % round(np.log10(0.5) / np.log10(1+np.nanmedian(coeffinner)) / (52 / Delta),3)) +\n",
    "          '&  ' + str(\"%.3f\" % round(np.log10(0.5) / np.log10(1+np.nanmedian(coeffouter)) / (52 / Delta),3)) +'\\\\' + '\\\\')\n",
    "\n",
    "print('\\multicolumn{1}{l}{ Std Dev }' +\n",
    "          '&  ' + str(\"%.3f\" % round(np.nanstd(coeffinner),3)) + \n",
    "          '&  ' + str(\"%.3f\" % round(np.nanstd(seinner),3)) +    \n",
    "          '&  ' + str(\"%.3f\" % round(np.nanstd(coeffouter),3)) +  \n",
    "          '&  ' + str(\"%.3f\" % round(np.nanstd(seouter),3)) + \n",
    "          '&  ' + str(\"%.3f\" % round(np.nanstd(thold),3)) +         \n",
    "                      ' && \\\\' + '\\\\')\n",
    "\n",
    "print('\\\\hline')\n",
    "print('\\\\hline'+ '\\\\'+ '\\\\'+'[-0.8ex] ')\n",
    "print('\\\\multicolumn{4}{l}{ \\\\textit{Note: Standard Errors in Parenthesis} } &')\n",
    "print('\\\\multicolumn{4}{r}{ \\\\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } '+ '\\\\'+ '\\\\')\n",
    "print('\\\\multicolumn{8}{l}{ \\\\textit{Average and Median Half-Life calculated from Average and Median Estimates} } '+ '\\\\'+ '\\\\')\n",
    "print('\\\\end{tabular}')\n",
    "print('\\\\end{table}')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "a54d74f8",
   "metadata": {},
   "outputs": [],
   "source": [
    "def tarlatex(delta, device):    \n",
    "    Delta = delta\n",
    "    Device = device\n",
    "\n",
    "    dffilter1 = df[df['Delta'] == Delta]\n",
    "    dffilter2 = dffilter1[dffilter1['Device'] == Device]\n",
    "    dffilter2\n",
    "    coeffinner = []\n",
    "    coeffouter = []\n",
    "    seinner = []\n",
    "    seouter = []\n",
    "    thold = []\n",
    "\n",
    "    countrylist = ['AE','AT','AU','BE','BR','CA','CZ','DE','DK','ES','FI','FR','HK','HU','IE','IT',\n",
    "                  'JP','KR','LU','MX','MY','NL','NO','NZ','PH','PL','PT','RU','SE','SG','TH','TR','TW','UK']\n",
    "\n",
    "    print('\\\\begin{table}[ht]' + '\\\\centering')\n",
    "    print(r'\\caption{Threshold Autogregression Persistence Estimates for '+ Device +' Devices, $d = '+ str(Delta) +'$}\\\\label{regTAR: '+ Device + ' Delta' + str(Delta) +'}')\n",
    "    print('\\\\begin{tabular}{ c r l r l c c c } ')\n",
    "    print('\\\\hline')\n",
    "    print('\\\\hline')\n",
    "    print(' ')\n",
    "    print('& \\\\multicolumn{7}{c}{$i=$'+ Device +', $d='+ str(Delta) +'$, No. Observations: ' + str(dffilter2['noobs']['AE']) + '}' + '\\\\'+ '\\\\')\n",
    "    print('\\\\cline{2-8}')\n",
    "    print('\\\\'+ '\\\\'+'[-0.1ex]')\n",
    "    print('Country')\n",
    "    print('& \\\\multicolumn{1}{c}{ Inner} ')\n",
    "    print('& \\\\multicolumn{1}{c}{ Inner} ')\n",
    "    print('& \\\\multicolumn{1}{c}{ Outer} ')\n",
    "    print('& \\\\multicolumn{1}{c}{ Outer} ')\n",
    "    print('& \\\\multicolumn{1}{c}{ Threshold} ')\n",
    "    print('& \\\\multicolumn{1}{c}{ Half-life} ')\n",
    "    print('& \\\\multicolumn{1}{c}{ Half-life} '+ '\\\\'+ '\\\\')\n",
    "    print('')\n",
    "    print('& \\\\multicolumn{1}{c}{ $\\\\hat{\\\\rho}_{0}$ } ')\n",
    "    print('& \\\\multicolumn{1}{c}{ SE} ')\n",
    "    print('& \\\\multicolumn{1}{c}{ $\\\\hat{\\\\rho}_{1}$ } ')\n",
    "    print('& \\\\multicolumn{1}{c}{ SE} ')\n",
    "    print('& \\\\multicolumn{1}{c}{ $c_i$ } ')\n",
    "    print('& \\\\multicolumn{1}{c}{ $\\\\hat{\\\\rho}_{0}$ } ')\n",
    "    print('& \\\\multicolumn{1}{c}{ $\\\\hat{\\\\rho}_{1}$ } '+ '\\\\'+ '\\\\')\n",
    "    print('\\\\hline'+ '\\\\'+ '\\\\'+'[-0.8ex] ')\n",
    "\n",
    "    for c in countrylist:\n",
    "        print(c)\n",
    "\n",
    "        hl0 = np.log10(0.5) / np.log10(1+dffilter2['rho0'][c]) / (52 / Delta)\n",
    "        hl1 = np.log10(0.5) / np.log10(1+dffilter2['rho1'][c]) / (52 / Delta)\n",
    "\n",
    "        if hl0 < 0:\n",
    "            hl0 = '$\\infty$'\n",
    "        elif dffilter2['rho0'][c] < -1:\n",
    "            hl0 = str(0)\n",
    "        else:\n",
    "            hl0 = str(round(hl0,3))\n",
    "\n",
    "        if hl1 < 0:\n",
    "            hl1 = '$\\infty$'\n",
    "        elif dffilter2['rho1'][c] < -1:\n",
    "            hl1 = str(0)    \n",
    "        else:\n",
    "            hl1 = str(round(hl1,3))\n",
    "\n",
    "        # Statistical Significance Tests:\n",
    "\n",
    "        if ((dffilter2['rho0'][c] / dffilter2['rho0se'][c]) > 2.576 or (dffilter2['rho0'][c] / dffilter2['rho0se'][c]) < -2.576):\n",
    "                              sig0 = '***'\n",
    "        elif ((dffilter2['rho0'][c] / dffilter2['rho0se'][c]) > 1.96 or (dffilter2['rho0'][c] / dffilter2['rho0se'][c]) < -1.96):\n",
    "                              sig0 = '**'\n",
    "        elif ((dffilter2['rho0'][c] / dffilter2['rho0se'][c]) > 1.645 or (dffilter2['rho0'][c] / dffilter2['rho0se'][c]) < -1.645):\n",
    "                              sig0 = '*'\n",
    "        else:\n",
    "            sig0 = ''\n",
    "\n",
    "\n",
    "        if ((dffilter2['rho1'][c] / dffilter2['rho1se'][c]) > 2.576 or (dffilter2['rho1'][c] / dffilter2['rho1se'][c]) < -2.576):\n",
    "                              sig1 = '***'\n",
    "        elif ((dffilter2['rho1'][c] / dffilter2['rho1se'][c]) > 1.96 or (dffilter2['rho1'][c] / dffilter2['rho1se'][c]) < -1.96):\n",
    "                              sig1 = '**'    \n",
    "        elif ((dffilter2['rho1'][c] / dffilter2['rho1se'][c]) > 1.645 or (dffilter2['rho1'][c] / dffilter2['rho1se'][c]) < -1.645):\n",
    "                              sig1 = '*'\n",
    "        else:\n",
    "            sig1 = ''\n",
    "\n",
    "        # LaTex Output:\n",
    "\n",
    "\n",
    "\n",
    "        print('&  ' + str(\"%.3f\" % round(dffilter2['rho0'][c],3)) + \n",
    "              '&  \\\\footnotesize{(' + str(\"%.3f\" % round(dffilter2['rho0se'][c],3)) + ')' + sig0 + '}' +\n",
    "              '&  ' + str(\"%.3f\" % round(dffilter2['rho1'][c],3)) + \n",
    "              '&  \\\\footnotesize{(' + str(\"%.3f\" % round(dffilter2['rho1se'][c],3)) + ')' + sig1 + '}' +\n",
    "              '&  ' + str(\"%.3f\" % round(dffilter2['Threshold'][c],3)) + \n",
    "              '&  ' + hl0 + '  &  ' + hl1 + '  \\\\' + '\\\\')  \n",
    "\n",
    "        coeffinner.append(dffilter2['rho0'][c])\n",
    "        coeffouter.append(dffilter2['rho1'][c])\n",
    "        seinner.append(dffilter2['rho0se'][c])\n",
    "        seouter.append(dffilter2['rho1se'][c])\n",
    "        thold.append(dffilter2['Threshold'][c])\n",
    "\n",
    "    print('\\hline')\n",
    "    print('\\multicolumn{1}{l}{ Average }' +\n",
    "              '&  ' + str(\"%.3f\" % round(np.nanmean(coeffinner),3)) + \n",
    "              '&  ' + str(\"%.3f\" % round(np.nanmean(seinner),3)) +    \n",
    "              '&  ' + str(\"%.3f\" % round(np.nanmean(coeffouter),3)) +  \n",
    "              '&  ' + str(\"%.3f\" % round(np.nanmean(seouter),3)) + \n",
    "              '&  ' + str(\"%.3f\" % round(np.nanmean(thold),3)) +         \n",
    "              '&  ' + str(\"%.3f\" % round(np.log10(0.5) / np.log10(1+np.nanmean(coeffinner)) / (52 / Delta),3)) +\n",
    "              '&  ' + str(\"%.3f\" % round(np.log10(0.5) / np.log10(1+np.nanmean(coeffouter)) / (52 / Delta),3)) +'\\\\' + '\\\\')\n",
    "\n",
    "    print('\\multicolumn{1}{l}{ Median }' +\n",
    "              '&  ' + str(\"%.3f\" % round(np.nanmedian(coeffinner),3)) + \n",
    "              '&  ' + str(\"%.3f\" % round(np.nanmedian(seinner),3)) +    \n",
    "              '&  ' + str(\"%.3f\" % round(np.nanmedian(coeffouter),3)) +  \n",
    "              '&  ' + str(\"%.3f\" % round(np.nanmedian(seouter),3)) + \n",
    "              '&  ' + str(\"%.3f\" % round(np.nanmedian(thold),3)) +         \n",
    "              '&  ' + str(\"%.3f\" % round(np.log10(0.5) / np.log10(1+np.nanmedian(coeffinner)) / (52 / Delta),3)) +\n",
    "              '&  ' + str(\"%.3f\" % round(np.log10(0.5) / np.log10(1+np.nanmedian(coeffouter)) / (52 / Delta),3)) +'\\\\' + '\\\\')\n",
    "\n",
    "    print('\\multicolumn{1}{l}{ Std Dev }' +\n",
    "              '&  ' + str(\"%.3f\" % round(np.nanstd(coeffinner),3)) + \n",
    "              '&  ' + str(\"%.3f\" % round(np.nanstd(seinner),3)) +    \n",
    "              '&  ' + str(\"%.3f\" % round(np.nanstd(coeffouter),3)) +  \n",
    "              '&  ' + str(\"%.3f\" % round(np.nanstd(seouter),3)) + \n",
    "              '&  ' + str(\"%.3f\" % round(np.nanstd(thold),3)) +         \n",
    "                          ' && \\\\' + '\\\\')\n",
    "\n",
    "    print('\\\\hline')\n",
    "    print('\\\\hline'+ '\\\\'+ '\\\\'+'[-0.8ex] ')\n",
    "    print('\\\\multicolumn{4}{l}{ \\\\textit{Note: Standard Errors in Parenthesis} } &')\n",
    "    print('\\\\multicolumn{4}{r}{ \\\\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } '+ '\\\\'+ '\\\\')\n",
    "    print('\\\\multicolumn{8}{l}{ \\\\textit{Average and Median Half-Life calculated from Average and Median Estimates} } '+ '\\\\'+ '\\\\')\n",
    "    print('\\\\end{tabular}')\n",
    "    print('\\\\end{table}')\n",
    "    print('')\n",
    "    print('')\n",
    "    print('')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "00548c6b",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{table}[ht]\\centering\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Pro Large Devices, $d = 12$}\\label{regTAR: iPad Pro Large Delta12}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad Pro Large, $d=12$, No. Observations: 302}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  0.947&  \\footnotesize{(0.145)***}&  -0.132&  \\footnotesize{(0.025)***}&  0.012&  $\\infty$  &  1.13  \\\\\n",
      "AT\n",
      "&  -0.097&  \\footnotesize{(0.066)}&  -0.423&  \\footnotesize{(0.050)***}&  0.048&  1.568  &  0.291  \\\\\n",
      "AU\n",
      "&  0.694&  \\footnotesize{(0.254)***}&  -0.437&  \\footnotesize{(0.046)***}&  0.028&  $\\infty$  &  0.278  \\\\\n",
      "BE\n",
      "&  -0.047&  \\footnotesize{(0.074)}&  -0.429&  \\footnotesize{(0.049)***}&  0.044&  3.323  &  0.285  \\\\\n",
      "BR\n",
      "&  -0.042&  \\footnotesize{(0.055)}&  -0.572&  \\footnotesize{(0.055)***}&  0.145&  3.728  &  0.188  \\\\\n",
      "CA\n",
      "&  -1.324&  \\footnotesize{(0.207)***}&  -0.341&  \\footnotesize{(0.043)***}&  0.025&  0  &  0.384  \\\\\n",
      "CZ\n",
      "&  0.821&  \\footnotesize{(0.217)***}&  -0.348&  \\footnotesize{(0.041)***}&  0.030&  $\\infty$  &  0.374  \\\\\n",
      "DE\n",
      "&  -0.134&  \\footnotesize{(0.059)**}&  -0.458&  \\footnotesize{(0.056)***}&  0.054&  1.112  &  0.261  \\\\\n",
      "DK\n",
      "&  0.174&  \\footnotesize{(0.112)}&  -0.399&  \\footnotesize{(0.046)***}&  0.035&  $\\infty$  &  0.314  \\\\\n",
      "ES\n",
      "&  -0.099&  \\footnotesize{(0.067)}&  -0.420&  \\footnotesize{(0.050)***}&  0.048&  1.534  &  0.294  \\\\\n",
      "FI\n",
      "&  -0.088&  \\footnotesize{(0.069)}&  -0.441&  \\footnotesize{(0.051)***}&  0.048&  1.736  &  0.275  \\\\\n",
      "FR\n",
      "&  -0.047&  \\footnotesize{(0.074)}&  -0.429&  \\footnotesize{(0.049)***}&  0.044&  3.323  &  0.285  \\\\\n",
      "HK\n",
      "&  0.012&  \\footnotesize{(0.022)}&  -0.522&  \\footnotesize{(0.047)***}&  0.031&  $\\infty$  &  0.217  \\\\\n",
      "HU\n",
      "&  -1.264&  \\footnotesize{(0.167)***}&  -0.411&  \\footnotesize{(0.051)***}&  0.031&  0  &  0.302  \\\\\n",
      "IE\n",
      "&  -0.089&  \\footnotesize{(0.070)}&  -0.443&  \\footnotesize{(0.051)***}&  0.046&  1.716  &  0.273  \\\\\n",
      "IT\n",
      "&  -0.052&  \\footnotesize{(0.073)}&  -0.430&  \\footnotesize{(0.049)***}&  0.045&  2.995  &  0.285  \\\\\n",
      "JP\n",
      "&  -0.317&  \\footnotesize{(0.073)***}&  -0.679&  \\footnotesize{(0.067)***}&  0.084&  0.42  &  0.141  \\\\\n",
      "KR\n",
      "&  -0.491&  \\footnotesize{(0.047)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.237  &  nan  \\\\\n",
      "LU\n",
      "&  -0.044&  \\footnotesize{(0.073)}&  -0.429&  \\footnotesize{(0.049)***}&  0.044&  3.555  &  0.285  \\\\\n",
      "MX\n",
      "&  -0.270&  \\footnotesize{(0.066)***}&  -0.669&  \\footnotesize{(0.065)***}&  0.088&  0.508  &  0.145  \\\\\n",
      "MY\n",
      "&  -1.228&  \\footnotesize{(0.247)***}&  -0.540&  \\footnotesize{(0.052)***}&  0.018&  0  &  0.206  \\\\\n",
      "NL\n",
      "&  -0.042&  \\footnotesize{(0.073)}&  -0.433&  \\footnotesize{(0.049)***}&  0.045&  3.728  &  0.282  \\\\\n",
      "NO\n",
      "&  -0.169&  \\footnotesize{(0.066)**}&  -0.481&  \\footnotesize{(0.058)***}&  0.084&  0.864  &  0.244  \\\\\n",
      "NZ\n",
      "&  -0.316&  \\footnotesize{(0.087)***}&  -0.622&  \\footnotesize{(0.061)***}&  0.063&  0.421  &  0.164  \\\\\n",
      "PH\n",
      "&  0.022&  \\footnotesize{(0.041)}&  -0.668&  \\footnotesize{(0.052)***}&  0.079&  $\\infty$  &  0.145  \\\\\n",
      "PL\n",
      "&  -0.357&  \\footnotesize{(0.045)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.362  &  nan  \\\\\n",
      "PT\n",
      "&  -0.086&  \\footnotesize{(0.067)}&  -0.444&  \\footnotesize{(0.052)***}&  0.049&  1.779  &  0.273  \\\\\n",
      "RU\n",
      "&  -0.225&  \\footnotesize{(0.082)***}&  -1.044&  \\footnotesize{(0.056)***}&  0.074&  0.628  &  0  \\\\\n",
      "SE\n",
      "&  1.664&  \\footnotesize{(0.614)***}&  -0.350&  \\footnotesize{(0.043)***}&  0.017&  $\\infty$  &  0.371  \\\\\n",
      "SG\n",
      "&  -0.541&  \\footnotesize{(0.047)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.205  &  nan  \\\\\n",
      "TH\n",
      "&  0.253&  \\footnotesize{(0.200)}&  -0.433&  \\footnotesize{(0.053)***}&  0.022&  $\\infty$  &  0.282  \\\\\n",
      "TR\n",
      "&  -0.483&  \\footnotesize{(0.096)***}&  -0.796&  \\footnotesize{(0.073)***}&  0.117&  0.242  &  0.101  \\\\\n",
      "TW\n",
      "&  0.091&  \\footnotesize{(0.129)}&  -0.255&  \\footnotesize{(0.038)***}&  0.024&  $\\infty$  &  0.543  \\\\\n",
      "UK\n",
      "&  -0.368&  \\footnotesize{(0.045)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.349  &  nan  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  -0.104&  0.113&  -0.483&  0.051&  0.051&  1.454&  0.243\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -0.088&  0.073&  -0.435&  0.050&  0.045&  1.726&  0.280\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  0.565&  0.106&  0.166&  0.009&  0.030 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n",
      "\n",
      "\n",
      "\n",
      "\\begin{table}[ht]\\centering\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Pro Small Devices, $d = 12$}\\label{regTAR: iPad Pro Small Delta12}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad Pro Small, $d=12$, No. Observations: 290}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  -0.303&  \\footnotesize{(0.037)***}&  -0.020&  \\footnotesize{(0.037)}&  0.028&  0.443  &  7.918  \\\\\n",
      "AT\n",
      "&  -0.029&  \\footnotesize{(0.064)}&  -0.470&  \\footnotesize{(0.052)***}&  0.049&  5.435  &  0.252  \\\\\n",
      "AU\n",
      "&  -0.183&  \\footnotesize{(0.064)***}&  -0.636&  \\footnotesize{(0.065)***}&  0.082&  0.791  &  0.158  \\\\\n",
      "BE\n",
      "&  0.013&  \\footnotesize{(0.069)}&  -0.463&  \\footnotesize{(0.050)***}&  0.046&  $\\infty$  &  0.257  \\\\\n",
      "BR\n",
      "&  -0.016&  \\footnotesize{(0.055)}&  -0.497&  \\footnotesize{(0.049)***}&  0.140&  9.917  &  0.233  \\\\\n",
      "CA\n",
      "&  -1.036&  \\footnotesize{(0.134)***}&  -0.239&  \\footnotesize{(0.041)***}&  0.035&  0  &  0.586  \\\\\n",
      "CZ\n",
      "&  0.368&  \\footnotesize{(0.150)**}&  -0.359&  \\footnotesize{(0.043)***}&  0.041&  $\\infty$  &  0.36  \\\\\n",
      "DE\n",
      "&  -0.113&  \\footnotesize{(0.062)*}&  -0.435&  \\footnotesize{(0.054)***}&  0.050&  1.334  &  0.28  \\\\\n",
      "DK\n",
      "&  -0.110&  \\footnotesize{(0.048)**}&  -0.558&  \\footnotesize{(0.065)***}&  0.071&  1.373  &  0.196  \\\\\n",
      "ES\n",
      "&  -0.024&  \\footnotesize{(0.063)}&  -0.537&  \\footnotesize{(0.054)***}&  0.050&  6.585  &  0.208  \\\\\n",
      "FI\n",
      "&  -0.012&  \\footnotesize{(0.065)}&  -0.483&  \\footnotesize{(0.051)***}&  0.049&  13.25  &  0.242  \\\\\n",
      "FR\n",
      "&  -0.019&  \\footnotesize{(0.068)}&  -0.472&  \\footnotesize{(0.051)***}&  0.048&  8.339  &  0.25  \\\\\n",
      "HK\n",
      "&  0.032&  \\footnotesize{(0.033)}&  -0.436&  \\footnotesize{(0.046)***}&  0.031&  $\\infty$  &  0.279  \\\\\n",
      "HU\n",
      "&  -0.977&  \\footnotesize{(0.156)***}&  -0.356&  \\footnotesize{(0.052)***}&  0.036&  0.042  &  0.363  \\\\\n",
      "IE\n",
      "&  -0.040&  \\footnotesize{(0.066)}&  -0.485&  \\footnotesize{(0.052)***}&  0.047&  3.918  &  0.241  \\\\\n",
      "IT\n",
      "&  0.013&  \\footnotesize{(0.068)}&  -0.465&  \\footnotesize{(0.050)***}&  0.047&  $\\infty$  &  0.256  \\\\\n",
      "JP\n",
      "&  -0.445&  \\footnotesize{(0.050)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.272  &  nan  \\\\\n",
      "KR\n",
      "&  -1.742&  \\footnotesize{(0.267)***}&  -0.455&  \\footnotesize{(0.052)***}&  0.017&  0  &  0.264  \\\\\n",
      "LU\n",
      "&  0.013&  \\footnotesize{(0.069)}&  -0.463&  \\footnotesize{(0.050)***}&  0.046&  $\\infty$  &  0.257  \\\\\n",
      "MX\n",
      "&  -1.145&  \\footnotesize{(0.191)***}&  -0.490&  \\footnotesize{(0.053)***}&  0.042&  0  &  0.238  \\\\\n",
      "MY\n",
      "&  -0.436&  \\footnotesize{(0.046)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.279  &  nan  \\\\\n",
      "NL\n",
      "&  0.015&  \\footnotesize{(0.069)}&  -0.467&  \\footnotesize{(0.050)***}&  0.046&  $\\infty$  &  0.254  \\\\\n",
      "NO\n",
      "&  -0.254&  \\footnotesize{(0.059)***}&  -0.650&  \\footnotesize{(0.070)***}&  0.085&  0.546  &  0.152  \\\\\n",
      "NZ\n",
      "&  -0.258&  \\footnotesize{(0.108)**}&  -0.561&  \\footnotesize{(0.057)***}&  0.051&  0.536  &  0.194  \\\\\n",
      "PH\n",
      "&  0.034&  \\footnotesize{(0.041)}&  -0.745&  \\footnotesize{(0.054)***}&  0.082&  $\\infty$  &  0.117  \\\\\n",
      "PL\n",
      "&  -0.192&  \\footnotesize{(0.065)***}&  -0.492&  \\footnotesize{(0.065)***}&  0.079&  0.75  &  0.236  \\\\\n",
      "PT\n",
      "&  -0.012&  \\footnotesize{(0.065)}&  -0.483&  \\footnotesize{(0.051)***}&  0.049&  13.25  &  0.242  \\\\\n",
      "RU\n",
      "&  -0.385&  \\footnotesize{(0.068)***}&  -0.770&  \\footnotesize{(0.080)***}&  0.091&  0.329  &  0.109  \\\\\n",
      "SE\n",
      "&  0.290&  \\footnotesize{(0.190)}&  -0.383&  \\footnotesize{(0.045)***}&  0.034&  $\\infty$  &  0.331  \\\\\n",
      "SG\n",
      "&  -0.796&  \\footnotesize{(0.144)***}&  -0.406&  \\footnotesize{(0.052)***}&  0.018&  0.101  &  0.307  \\\\\n",
      "TH\n",
      "&  1.471&  \\footnotesize{(0.438)***}&  -0.389&  \\footnotesize{(0.049)***}&  0.012&  $\\infty$  &  0.325  \\\\\n",
      "TR\n",
      "&  3.175&  \\footnotesize{(1.518)**}&  -0.694&  \\footnotesize{(0.060)***}&  0.014&  $\\infty$  &  0.135  \\\\\n",
      "TW\n",
      "&  -0.243&  \\footnotesize{(0.063)***}&  -0.567&  \\footnotesize{(0.070)***}&  0.042&  0.575  &  0.191  \\\\\n",
      "UK\n",
      "&  -0.334&  \\footnotesize{(0.043)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.394  &  nan  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  -0.108&  0.138&  -0.481&  0.054&  0.050&  1.396&  0.244\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -0.075&  0.066&  -0.472&  0.052&  0.047&  2.052&  0.250\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  0.769&  0.253&  0.140&  0.009&  0.026 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n",
      "\n",
      "\n",
      "\n",
      "\\begin{table}[ht]\\centering\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Devices, $d = 12$}\\label{regTAR: iPad Delta12}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad, $d=12$, No. Observations: 302}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  -0.826&  \\footnotesize{(0.132)***}&  -0.091&  \\footnotesize{(0.023)***}&  0.017&  0.091  &  1.677  \\\\\n",
      "AT\n",
      "&  -0.041&  \\footnotesize{(0.042)}&  -0.762&  \\footnotesize{(0.046)***}&  0.115&  3.821  &  0.111  \\\\\n",
      "AU\n",
      "&  -0.352&  \\footnotesize{(0.058)***}&  -0.809&  \\footnotesize{(0.060)***}&  0.090&  0.369  &  0.097  \\\\\n",
      "BE\n",
      "&  -0.025&  \\footnotesize{(0.041)}&  -0.759&  \\footnotesize{(0.045)***}&  0.115&  6.318  &  0.112  \\\\\n",
      "BR\n",
      "&  -0.225&  \\footnotesize{(0.063)***}&  -0.900&  \\footnotesize{(0.055)***}&  0.135&  0.628  &  0.069  \\\\\n",
      "CA\n",
      "&  -0.218&  \\footnotesize{(0.054)***}&  -0.764&  \\footnotesize{(0.037)***}&  0.084&  0.65  &  0.111  \\\\\n",
      "CZ\n",
      "&  -0.177&  \\footnotesize{(0.050)***}&  -0.705&  \\footnotesize{(0.059)***}&  0.156&  0.821  &  0.131  \\\\\n",
      "DE\n",
      "&  -0.022&  \\footnotesize{(0.045)}&  -0.789&  \\footnotesize{(0.047)***}&  0.114&  7.19  &  0.103  \\\\\n",
      "DK\n",
      "&  -0.237&  \\footnotesize{(0.060)***}&  -0.848&  \\footnotesize{(0.044)***}&  0.081&  0.591  &  0.085  \\\\\n",
      "ES\n",
      "&  0.295&  \\footnotesize{(0.120)**}&  -0.247&  \\footnotesize{(0.033)***}&  0.176&  $\\infty$  &  0.564  \\\\\n",
      "FI\n",
      "&  -0.033&  \\footnotesize{(0.039)}&  -0.785&  \\footnotesize{(0.045)***}&  0.121&  4.767  &  0.104  \\\\\n",
      "FR\n",
      "&  -0.025&  \\footnotesize{(0.041)}&  -0.759&  \\footnotesize{(0.045)***}&  0.115&  6.318  &  0.112  \\\\\n",
      "HK\n",
      "&  1.159&  \\footnotesize{(0.458)**}&  -0.154&  \\footnotesize{(0.026)***}&  0.002&  $\\infty$  &  0.956  \\\\\n",
      "HU\n",
      "&  -0.250&  \\footnotesize{(0.059)***}&  -0.759&  \\footnotesize{(0.060)***}&  0.141&  0.556  &  0.112  \\\\\n",
      "IE\n",
      "&  -0.020&  \\footnotesize{(0.042)}&  -0.748&  \\footnotesize{(0.044)***}&  0.116&  7.918  &  0.116  \\\\\n",
      "IT\n",
      "&  -0.024&  \\footnotesize{(0.041)}&  -0.759&  \\footnotesize{(0.044)***}&  0.115&  6.585  &  0.112  \\\\\n",
      "JP\n",
      "&  -0.493&  \\footnotesize{(0.083)***}&  -0.906&  \\footnotesize{(0.061)***}&  0.054&  0.235  &  0.068  \\\\\n",
      "KR\n",
      "&  -0.463&  \\footnotesize{(0.058)***}&  -0.747&  \\footnotesize{(0.048)***}&  0.062&  0.257  &  0.116  \\\\\n",
      "LU\n",
      "&  -0.024&  \\footnotesize{(0.041)}&  -0.759&  \\footnotesize{(0.044)***}&  0.115&  6.585  &  0.112  \\\\\n",
      "MX\n",
      "&  -0.277&  \\footnotesize{(0.066)***}&  -0.695&  \\footnotesize{(0.057)***}&  0.113&  0.493  &  0.135  \\\\\n",
      "MY\n",
      "&  -0.169&  \\footnotesize{(0.077)**}&  -0.857&  \\footnotesize{(0.053)***}&  0.087&  0.864  &  0.082  \\\\\n",
      "NL\n",
      "&  -0.027&  \\footnotesize{(0.041)}&  -0.757&  \\footnotesize{(0.045)***}&  0.115&  5.844  &  0.113  \\\\\n",
      "NO\n",
      "&  -0.241&  \\footnotesize{(0.063)***}&  -1.011&  \\footnotesize{(0.052)***}&  0.086&  0.58  &  0  \\\\\n",
      "NZ\n",
      "&  -1.252&  \\footnotesize{(0.203)***}&  -0.566&  \\footnotesize{(0.052)***}&  0.030&  0  &  0.192  \\\\\n",
      "PH\n",
      "&  -0.090&  \\footnotesize{(0.060)}&  -0.743&  \\footnotesize{(0.052)***}&  0.054&  1.696  &  0.118  \\\\\n",
      "PL\n",
      "&  -0.241&  \\footnotesize{(0.062)***}&  -0.720&  \\footnotesize{(0.051)***}&  0.151&  0.58  &  0.126  \\\\\n",
      "PT\n",
      "&  -0.033&  \\footnotesize{(0.039)}&  -0.784&  \\footnotesize{(0.046)***}&  0.121&  4.767  &  0.104  \\\\\n",
      "RU\n",
      "&  -0.417&  \\footnotesize{(0.058)***}&  -1.217&  \\footnotesize{(0.068)***}&  0.098&  0.296  &  0  \\\\\n",
      "SE\n",
      "&  0.209&  \\footnotesize{(0.071)***}&  -0.639&  \\footnotesize{(0.040)***}&  0.087&  $\\infty$  &  0.157  \\\\\n",
      "SG\n",
      "&  -0.076&  \\footnotesize{(0.046)*}&  -0.614&  \\footnotesize{(0.039)***}&  0.067&  2.024  &  0.168  \\\\\n",
      "TH\n",
      "&  -0.303&  \\footnotesize{(0.056)***}&  -0.585&  \\footnotesize{(0.052)***}&  0.072&  0.443  &  0.182  \\\\\n",
      "TR\n",
      "&  -0.412&  \\footnotesize{(0.081)***}&  -1.044&  \\footnotesize{(0.075)***}&  0.123&  0.301  &  0  \\\\\n",
      "TW\n",
      "&  -0.269&  \\footnotesize{(0.052)***}&  -0.675&  \\footnotesize{(0.039)***}&  0.041&  0.51  &  0.142  \\\\\n",
      "UK\n",
      "&  0.366&  \\footnotesize{(0.096)***}&  -0.638&  \\footnotesize{(0.041)***}&  0.053&  $\\infty$  &  0.157  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  -0.154&  0.076&  -0.723&  0.048&  0.095&  0.957&  0.124\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -0.173&  0.058&  -0.759&  0.046&  0.106&  0.842&  0.112\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  0.369&  0.074&  0.216&  0.011&  0.039 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n",
      "\n",
      "\n",
      "\n",
      "\\begin{table}[ht]\\centering\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Mini Devices, $d = 12$}\\label{regTAR: iPad Mini Delta12}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad Mini, $d=12$, No. Observations: 302}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  3.095&  \\footnotesize{(0.665)***}&  -0.184&  \\footnotesize{(0.030)***}&  0.003&  $\\infty$  &  0.787  \\\\\n",
      "AT\n",
      "&  -0.043&  \\footnotesize{(0.048)}&  -0.712&  \\footnotesize{(0.055)***}&  0.106&  3.639  &  0.129  \\\\\n",
      "AU\n",
      "&  0.249&  \\footnotesize{(0.102)**}&  -0.516&  \\footnotesize{(0.043)***}&  0.044&  $\\infty$  &  0.22  \\\\\n",
      "BE\n",
      "&  -0.085&  \\footnotesize{(0.049)*}&  -0.681&  \\footnotesize{(0.058)***}&  0.102&  1.801  &  0.14  \\\\\n",
      "BR\n",
      "&  0.495&  \\footnotesize{(0.132)***}&  -0.159&  \\footnotesize{(0.039)***}&  0.100&  $\\infty$  &  0.924  \\\\\n",
      "CA\n",
      "&  -0.112&  \\footnotesize{(0.053)**}&  -0.486&  \\footnotesize{(0.043)***}&  0.078&  1.347  &  0.24  \\\\\n",
      "CZ\n",
      "&  1.921&  \\footnotesize{(0.474)***}&  -0.381&  \\footnotesize{(0.042)***}&  0.024&  $\\infty$  &  0.333  \\\\\n",
      "DE\n",
      "&  0.249&  \\footnotesize{(0.078)***}&  -0.684&  \\footnotesize{(0.047)***}&  0.102&  $\\infty$  &  0.139  \\\\\n",
      "DK\n",
      "&  0.042&  \\footnotesize{(0.081)}&  -0.385&  \\footnotesize{(0.043)***}&  0.062&  $\\infty$  &  0.329  \\\\\n",
      "ES\n",
      "&  -0.067&  \\footnotesize{(0.048)}&  -0.679&  \\footnotesize{(0.056)***}&  0.112&  2.307  &  0.141  \\\\\n",
      "FI\n",
      "&  -0.132&  \\footnotesize{(0.055)**}&  -0.584&  \\footnotesize{(0.059)***}&  0.095&  1.13  &  0.182  \\\\\n",
      "FR\n",
      "&  -0.078&  \\footnotesize{(0.049)}&  -0.690&  \\footnotesize{(0.058)***}&  0.102&  1.97  &  0.137  \\\\\n",
      "HK\n",
      "&  0.084&  \\footnotesize{(0.032)***}&  -0.193&  \\footnotesize{(0.029)***}&  0.022&  $\\infty$  &  0.746  \\\\\n",
      "HU\n",
      "&  0.136&  \\footnotesize{(0.182)}&  -0.317&  \\footnotesize{(0.043)***}&  0.043&  $\\infty$  &  0.42  \\\\\n",
      "IE\n",
      "&  -0.060&  \\footnotesize{(0.073)}&  -0.486&  \\footnotesize{(0.050)***}&  0.066&  2.585  &  0.24  \\\\\n",
      "IT\n",
      "&  -0.085&  \\footnotesize{(0.049)*}&  -0.681&  \\footnotesize{(0.058)***}&  0.102&  1.801  &  0.14  \\\\\n",
      "JP\n",
      "&  -0.293&  \\footnotesize{(0.107)***}&  -0.638&  \\footnotesize{(0.056)***}&  0.044&  0.461  &  0.157  \\\\\n",
      "KR\n",
      "&  0.346&  \\footnotesize{(0.177)*}&  -0.263&  \\footnotesize{(0.038)***}&  0.027&  $\\infty$  &  0.524  \\\\\n",
      "LU\n",
      "&  -0.085&  \\footnotesize{(0.049)*}&  -0.681&  \\footnotesize{(0.058)***}&  0.102&  1.801  &  0.14  \\\\\n",
      "MX\n",
      "&  -0.064&  \\footnotesize{(0.160)}&  -0.473&  \\footnotesize{(0.042)***}&  0.057&  2.418  &  0.25  \\\\\n",
      "MY\n",
      "&  -0.020&  \\footnotesize{(0.052)}&  -0.751&  \\footnotesize{(0.053)***}&  0.141&  7.918  &  0.115  \\\\\n",
      "NL\n",
      "&  -0.087&  \\footnotesize{(0.049)*}&  -0.678&  \\footnotesize{(0.058)***}&  0.102&  1.757  &  0.141  \\\\\n",
      "NO\n",
      "&  -0.171&  \\footnotesize{(0.059)***}&  -0.639&  \\footnotesize{(0.061)***}&  0.094&  0.853  &  0.157  \\\\\n",
      "NZ\n",
      "&  -0.053&  \\footnotesize{(0.129)}&  -0.517&  \\footnotesize{(0.051)***}&  0.037&  2.937  &  0.22  \\\\\n",
      "PH\n",
      "&  -0.036&  \\footnotesize{(0.048)}&  -0.732&  \\footnotesize{(0.057)***}&  0.065&  4.363  &  0.121  \\\\\n",
      "PL\n",
      "&  0.701&  \\footnotesize{(0.296)**}&  -0.336&  \\footnotesize{(0.041)***}&  0.032&  $\\infty$  &  0.391  \\\\\n",
      "PT\n",
      "&  -0.132&  \\footnotesize{(0.055)**}&  -0.584&  \\footnotesize{(0.059)***}&  0.095&  1.13  &  0.182  \\\\\n",
      "RU\n",
      "&  0.293&  \\footnotesize{(0.144)**}&  -0.702&  \\footnotesize{(0.048)***}&  0.043&  $\\infty$  &  0.132  \\\\\n",
      "SE\n",
      "&  -0.096&  \\footnotesize{(0.045)**}&  -0.591&  \\footnotesize{(0.058)***}&  0.128&  1.585  &  0.179  \\\\\n",
      "SG\n",
      "&  -0.339&  \\footnotesize{(0.075)***}&  -0.600&  \\footnotesize{(0.057)***}&  0.035&  0.386  &  0.175  \\\\\n",
      "TH\n",
      "&  0.163&  \\footnotesize{(0.119)}&  -0.427&  \\footnotesize{(0.041)***}&  0.035&  $\\infty$  &  0.287  \\\\\n",
      "TR\n",
      "&  -0.435&  \\footnotesize{(0.077)***}&  -0.989&  \\footnotesize{(0.079)***}&  0.129&  0.28  &  0.035  \\\\\n",
      "TW\n",
      "&  -0.089&  \\footnotesize{(0.042)**}&  -0.425&  \\footnotesize{(0.043)***}&  0.072&  1.716  &  0.289  \\\\\n",
      "UK\n",
      "&  -0.049&  \\footnotesize{(0.047)}&  -0.622&  \\footnotesize{(0.053)***}&  0.121&  3.184  &  0.164  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  0.152&  0.115&  -0.543&  0.050&  0.074&  -1.131&  0.204\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -0.056&  0.066&  -0.587&  0.052&  0.075&  2.750&  0.181\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  0.645&  0.128&  0.185&  0.010&  0.036 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n",
      "\n",
      "\n",
      "\n",
      "\\begin{table}[ht]\\centering\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Pro Large Devices, $d = 24$}\\label{regTAR: iPad Pro Large Delta24}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad Pro Large, $d=24$, No. Observations: 290}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  1.893&  \\footnotesize{(0.182)***}&  -0.271&  \\footnotesize{(0.031)***}&  0.012&  $\\infty$  &  1.012  \\\\\n",
      "AT\n",
      "&  -0.262&  \\footnotesize{(0.090)***}&  -0.826&  \\footnotesize{(0.064)***}&  0.047&  1.053  &  0.183  \\\\\n",
      "AU\n",
      "&  -0.439&  \\footnotesize{(0.070)***}&  -1.189&  \\footnotesize{(0.079)***}&  0.086&  0.553  &  0  \\\\\n",
      "BE\n",
      "&  -0.196&  \\footnotesize{(0.094)**}&  -0.874&  \\footnotesize{(0.063)***}&  0.045&  1.466  &  0.154  \\\\\n",
      "BR\n",
      "&  -0.236&  \\footnotesize{(0.072)***}&  -0.751&  \\footnotesize{(0.067)***}&  0.140&  1.188  &  0.23  \\\\\n",
      "CA\n",
      "&  -1.925&  \\footnotesize{(0.245)***}&  -0.495&  \\footnotesize{(0.049)***}&  0.025&  0  &  0.468  \\\\\n",
      "CZ\n",
      "&  0.867&  \\footnotesize{(0.326)***}&  -0.580&  \\footnotesize{(0.051)***}&  0.028&  $\\infty$  &  0.369  \\\\\n",
      "DE\n",
      "&  -0.265&  \\footnotesize{(0.092)***}&  -0.839&  \\footnotesize{(0.065)***}&  0.047&  1.039  &  0.175  \\\\\n",
      "DK\n",
      "&  -0.193&  \\footnotesize{(0.099)*}&  -0.963&  \\footnotesize{(0.066)***}&  0.046&  1.492  &  0.097  \\\\\n",
      "ES\n",
      "&  -0.290&  \\footnotesize{(0.089)***}&  -0.809&  \\footnotesize{(0.065)***}&  0.048&  0.934  &  0.193  \\\\\n",
      "FI\n",
      "&  -0.393&  \\footnotesize{(0.080)***}&  -0.944&  \\footnotesize{(0.073)***}&  0.053&  0.641  &  0.111  \\\\\n",
      "FR\n",
      "&  -0.196&  \\footnotesize{(0.094)**}&  -0.874&  \\footnotesize{(0.063)***}&  0.045&  1.466  &  0.154  \\\\\n",
      "HK\n",
      "&  0.044&  \\footnotesize{(0.023)*}&  -1.076&  \\footnotesize{(0.047)***}&  0.031&  $\\infty$  &  0  \\\\\n",
      "HU\n",
      "&  -0.635&  \\footnotesize{(0.078)***}&  -0.965&  \\footnotesize{(0.087)***}&  0.075&  0.317  &  0.095  \\\\\n",
      "IE\n",
      "&  -0.304&  \\footnotesize{(0.090)***}&  -0.877&  \\footnotesize{(0.066)***}&  0.046&  0.883  &  0.153  \\\\\n",
      "IT\n",
      "&  -0.152&  \\footnotesize{(0.100)}&  -0.859&  \\footnotesize{(0.061)***}&  0.042&  1.94  &  0.163  \\\\\n",
      "JP\n",
      "&  -0.729&  \\footnotesize{(0.082)***}&  -1.285&  \\footnotesize{(0.076)***}&  0.093&  0.245  &  0  \\\\\n",
      "KR\n",
      "&  -1.479&  \\footnotesize{(0.179)***}&  -0.858&  \\footnotesize{(0.058)***}&  0.027&  0  &  0.164  \\\\\n",
      "LU\n",
      "&  -0.147&  \\footnotesize{(0.095)}&  -0.866&  \\footnotesize{(0.062)***}&  0.044&  2.012  &  0.159  \\\\\n",
      "MX\n",
      "&  -0.374&  \\footnotesize{(0.073)***}&  -1.018&  \\footnotesize{(0.074)***}&  0.093&  0.683  &  0  \\\\\n",
      "MY\n",
      "&  -1.454&  \\footnotesize{(0.083)***}&  -0.963&  \\footnotesize{(0.064)***}&  0.054&  0  &  0.097  \\\\\n",
      "NL\n",
      "&  -0.172&  \\footnotesize{(0.094)*}&  -0.879&  \\footnotesize{(0.063)***}&  0.045&  1.695  &  0.151  \\\\\n",
      "NO\n",
      "&  -0.245&  \\footnotesize{(0.100)**}&  -0.680&  \\footnotesize{(0.062)***}&  0.074&  1.138  &  0.281  \\\\\n",
      "NZ\n",
      "&  -0.481&  \\footnotesize{(0.100)***}&  -1.005&  \\footnotesize{(0.068)***}&  0.061&  0.488  &  0  \\\\\n",
      "PH\n",
      "&  0.517&  \\footnotesize{(0.094)***}&  -0.711&  \\footnotesize{(0.046)***}&  0.056&  $\\infty$  &  0.258  \\\\\n",
      "PL\n",
      "&  -0.392&  \\footnotesize{(0.076)***}&  -0.726&  \\footnotesize{(0.073)***}&  0.084&  0.643  &  0.247  \\\\\n",
      "PT\n",
      "&  -0.366&  \\footnotesize{(0.079)***}&  -0.943&  \\footnotesize{(0.072)***}&  0.053&  0.702  &  0.112  \\\\\n",
      "RU\n",
      "&  -0.741&  \\footnotesize{(0.090)***}&  -1.029&  \\footnotesize{(0.063)***}&  0.080&  0.237  &  0  \\\\\n",
      "SE\n",
      "&  -0.869&  \\footnotesize{(0.083)***}&  -0.484&  \\footnotesize{(0.071)***}&  0.072&  0.157  &  0.484  \\\\\n",
      "SG\n",
      "&  -1.493&  \\footnotesize{(0.171)***}&  -0.857&  \\footnotesize{(0.058)***}&  0.017&  0  &  0.164  \\\\\n",
      "TH\n",
      "&  0.236&  \\footnotesize{(0.212)}&  -0.919&  \\footnotesize{(0.071)***}&  0.024&  $\\infty$  &  0.127  \\\\\n",
      "TR\n",
      "&  2.681&  \\footnotesize{(1.031)***}&  -1.205&  \\footnotesize{(0.060)***}&  0.018&  $\\infty$  &  0  \\\\\n",
      "TW\n",
      "&  -0.117&  \\footnotesize{(0.126)}&  -0.486&  \\footnotesize{(0.054)***}&  0.033&  2.571  &  0.481  \\\\\n",
      "UK\n",
      "&  -0.191&  \\footnotesize{(0.126)}&  -0.856&  \\footnotesize{(0.060)***}&  0.046&  1.509  &  0.165  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  -0.250&  0.139&  -0.852&  0.063&  0.053&  1.112&  0.168\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -0.264&  0.094&  -0.870&  0.064&  0.046&  1.046&  0.157\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  0.838&  0.166&  0.210&  0.010&  0.026 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n",
      "\n",
      "\n",
      "\n",
      "\\begin{table}[ht]\\centering\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Pro Small Devices, $d = 24$}\\label{regTAR: iPad Pro Small Delta24}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad Pro Small, $d=24$, No. Observations: 278}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  -0.621&  \\footnotesize{(0.047)***}&  -0.040&  \\footnotesize{(0.047)}&  0.028&  0.33  &  7.837  \\\\\n",
      "AT\n",
      "&  -0.342&  \\footnotesize{(0.075)***}&  -0.914&  \\footnotesize{(0.076)***}&  0.053&  0.764  &  0.13  \\\\\n",
      "AU\n",
      "&  -0.373&  \\footnotesize{(0.079)***}&  -1.061&  \\footnotesize{(0.075)***}&  0.078&  0.685  &  0  \\\\\n",
      "BE\n",
      "&  -0.159&  \\footnotesize{(0.082)*}&  -0.934&  \\footnotesize{(0.066)***}&  0.050&  1.847  &  0.118  \\\\\n",
      "BR\n",
      "&  -0.206&  \\footnotesize{(0.069)***}&  -0.658&  \\footnotesize{(0.057)***}&  0.138&  1.387  &  0.298  \\\\\n",
      "CA\n",
      "&  -1.480&  \\footnotesize{(0.158)***}&  -0.409&  \\footnotesize{(0.050)***}&  0.036&  0  &  0.608  \\\\\n",
      "CZ\n",
      "&  0.134&  \\footnotesize{(0.166)}&  -0.586&  \\footnotesize{(0.054)***}&  0.044&  $\\infty$  &  0.363  \\\\\n",
      "DE\n",
      "&  -3.876&  \\footnotesize{(0.915)***}&  -0.623&  \\footnotesize{(0.055)***}&  0.011&  0  &  0.328  \\\\\n",
      "DK\n",
      "&  -0.415&  \\footnotesize{(0.070)***}&  -0.938&  \\footnotesize{(0.085)***}&  0.069&  0.597  &  0.115  \\\\\n",
      "ES\n",
      "&  -0.242&  \\footnotesize{(0.091)***}&  -0.820&  \\footnotesize{(0.066)***}&  0.048&  1.155  &  0.187  \\\\\n",
      "FI\n",
      "&  -0.190&  \\footnotesize{(0.081)**}&  -0.932&  \\footnotesize{(0.067)***}&  0.049&  1.518  &  0.119  \\\\\n",
      "FR\n",
      "&  -0.147&  \\footnotesize{(0.087)*}&  -0.926&  \\footnotesize{(0.065)***}&  0.048&  2.012  &  0.123  \\\\\n",
      "HK\n",
      "&  0.083&  \\footnotesize{(0.039)**}&  -0.895&  \\footnotesize{(0.054)***}&  0.031&  $\\infty$  &  0.142  \\\\\n",
      "HU\n",
      "&  -0.696&  \\footnotesize{(0.060)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.269  &  nan  \\\\\n",
      "IE\n",
      "&  -0.052&  \\footnotesize{(0.097)}&  -0.842&  \\footnotesize{(0.061)***}&  0.042&  5.991  &  0.173  \\\\\n",
      "IT\n",
      "&  -0.101&  \\footnotesize{(0.089)}&  -0.898&  \\footnotesize{(0.063)***}&  0.047&  3.005  &  0.14  \\\\\n",
      "JP\n",
      "&  -0.803&  \\footnotesize{(0.059)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.197  &  nan  \\\\\n",
      "KR\n",
      "&  -2.445&  \\footnotesize{(0.230)***}&  -0.820&  \\footnotesize{(0.059)***}&  0.021&  0  &  0.187  \\\\\n",
      "LU\n",
      "&  -0.159&  \\footnotesize{(0.082)*}&  -0.934&  \\footnotesize{(0.066)***}&  0.050&  1.847  &  0.118  \\\\\n",
      "MX\n",
      "&  -0.465&  \\footnotesize{(0.084)***}&  -1.074&  \\footnotesize{(0.074)***}&  0.084&  0.511  &  0  \\\\\n",
      "MY\n",
      "&  0.220&  \\footnotesize{(0.200)}&  -0.945&  \\footnotesize{(0.056)***}&  0.024&  $\\infty$  &  0.11  \\\\\n",
      "NL\n",
      "&  -0.161&  \\footnotesize{(0.083)*}&  -0.932&  \\footnotesize{(0.066)***}&  0.049&  1.822  &  0.119  \\\\\n",
      "NO\n",
      "&  -0.273&  \\footnotesize{(0.062)***}&  -1.047&  \\footnotesize{(0.073)***}&  0.085&  1.003  &  0  \\\\\n",
      "NZ\n",
      "&  -0.585&  \\footnotesize{(0.082)***}&  -1.038&  \\footnotesize{(0.080)***}&  0.081&  0.364  &  0  \\\\\n",
      "PH\n",
      "&  -0.028&  \\footnotesize{(0.055)}&  -1.106&  \\footnotesize{(0.063)***}&  0.075&  11.265  &  0  \\\\\n",
      "PL\n",
      "&  -0.350&  \\footnotesize{(0.083)***}&  -0.738&  \\footnotesize{(0.074)***}&  0.075&  0.743  &  0.239  \\\\\n",
      "PT\n",
      "&  -0.190&  \\footnotesize{(0.081)**}&  -0.932&  \\footnotesize{(0.067)***}&  0.049&  1.518  &  0.119  \\\\\n",
      "RU\n",
      "&  -8.639&  \\footnotesize{(2.600)***}&  -0.794&  \\footnotesize{(0.059)***}&  0.009&  0  &  0.202  \\\\\n",
      "SE\n",
      "&  0.313&  \\footnotesize{(0.397)}&  -0.700&  \\footnotesize{(0.057)***}&  0.025&  $\\infty$  &  0.266  \\\\\n",
      "SG\n",
      "&  -1.473&  \\footnotesize{(0.177)***}&  -0.815&  \\footnotesize{(0.062)***}&  0.018&  0  &  0.19  \\\\\n",
      "TH\n",
      "&  2.653&  \\footnotesize{(0.512)***}&  -0.783&  \\footnotesize{(0.062)***}&  0.012&  $\\infty$  &  0.209  \\\\\n",
      "TR\n",
      "&  1.147&  \\footnotesize{(0.723)}&  -1.220&  \\footnotesize{(0.062)***}&  0.023&  $\\infty$  &  0  \\\\\n",
      "TW\n",
      "&  -0.668&  \\footnotesize{(0.058)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.29  &  nan  \\\\\n",
      "UK\n",
      "&  -0.128&  \\footnotesize{(0.141)}&  -0.750&  \\footnotesize{(0.060)***}&  0.043&  2.336  &  0.231  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  -0.609&  0.233&  -0.842&  0.064&  0.048&  0.340&  0.173\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -0.224&  0.083&  -0.898&  0.063&  0.048&  1.261&  0.140\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  1.709&  0.455&  0.220&  0.009&  0.027 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n",
      "\n",
      "\n",
      "\n",
      "\\begin{table}[ht]\\centering\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Devices, $d = 24$}\\label{regTAR: iPad Delta24}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad, $d=24$, No. Observations: 290}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  -1.467&  \\footnotesize{(0.157)***}&  -0.194&  \\footnotesize{(0.029)***}&  0.017&  0  &  1.483  \\\\\n",
      "AT\n",
      "&  0.385&  \\footnotesize{(0.100)***}&  -0.831&  \\footnotesize{(0.044)***}&  0.066&  $\\infty$  &  0.18  \\\\\n",
      "AU\n",
      "&  -0.358&  \\footnotesize{(0.063)***}&  -0.933&  \\footnotesize{(0.060)***}&  0.084&  0.722  &  0.118  \\\\\n",
      "BE\n",
      "&  -0.128&  \\footnotesize{(0.067)*}&  -0.923&  \\footnotesize{(0.054)***}&  0.102&  2.336  &  0.125  \\\\\n",
      "BR\n",
      "&  -0.698&  \\footnotesize{(0.066)***}&  -1.135&  \\footnotesize{(0.074)***}&  0.151&  0.267  &  0  \\\\\n",
      "CA\n",
      "&  0.398&  \\footnotesize{(0.179)**}&  -0.785&  \\footnotesize{(0.038)***}&  0.035&  $\\infty$  &  0.208  \\\\\n",
      "CZ\n",
      "&  0.009&  \\footnotesize{(0.096)}&  -0.899&  \\footnotesize{(0.054)***}&  0.090&  $\\infty$  &  0.14  \\\\\n",
      "DE\n",
      "&  0.562&  \\footnotesize{(0.112)***}&  -0.865&  \\footnotesize{(0.045)***}&  0.066&  $\\infty$  &  0.16  \\\\\n",
      "DK\n",
      "&  0.083&  \\footnotesize{(0.164)}&  -0.856&  \\footnotesize{(0.043)***}&  0.037&  $\\infty$  &  0.165  \\\\\n",
      "ES\n",
      "&  0.630&  \\footnotesize{(0.150)***}&  -0.457&  \\footnotesize{(0.043)***}&  0.176&  $\\infty$  &  0.524  \\\\\n",
      "FI\n",
      "&  -0.159&  \\footnotesize{(0.064)**}&  -0.948&  \\footnotesize{(0.055)***}&  0.109&  1.847  &  0.108  \\\\\n",
      "FR\n",
      "&  0.302&  \\footnotesize{(0.105)***}&  -0.784&  \\footnotesize{(0.046)***}&  0.067&  $\\infty$  &  0.209  \\\\\n",
      "HK\n",
      "&  -0.384&  \\footnotesize{(0.047)***}&  -0.144&  \\footnotesize{(0.052)***}&  0.011&  0.66  &  2.058  \\\\\n",
      "HU\n",
      "&  -1.510&  \\footnotesize{(0.252)***}&  -0.720&  \\footnotesize{(0.052)***}&  0.042&  0  &  0.251  \\\\\n",
      "IE\n",
      "&  0.019&  \\footnotesize{(0.077)}&  -0.876&  \\footnotesize{(0.049)***}&  0.083&  $\\infty$  &  0.153  \\\\\n",
      "IT\n",
      "&  -0.129&  \\footnotesize{(0.067)*}&  -0.923&  \\footnotesize{(0.054)***}&  0.102&  2.316  &  0.125  \\\\\n",
      "JP\n",
      "&  -0.828&  \\footnotesize{(0.082)***}&  -1.447&  \\footnotesize{(0.063)***}&  0.058&  0.182  &  0  \\\\\n",
      "KR\n",
      "&  -1.821&  \\footnotesize{(0.252)***}&  -0.864&  \\footnotesize{(0.043)***}&  0.022&  0  &  0.16  \\\\\n",
      "LU\n",
      "&  -0.129&  \\footnotesize{(0.067)*}&  -0.923&  \\footnotesize{(0.054)***}&  0.102&  2.316  &  0.125  \\\\\n",
      "MX\n",
      "&  -0.422&  \\footnotesize{(0.081)***}&  -1.043&  \\footnotesize{(0.064)***}&  0.109&  0.584  &  0  \\\\\n",
      "MY\n",
      "&  -0.237&  \\footnotesize{(0.106)**}&  -1.179&  \\footnotesize{(0.054)***}&  0.061&  1.183  &  0  \\\\\n",
      "NL\n",
      "&  -0.128&  \\footnotesize{(0.067)*}&  -0.924&  \\footnotesize{(0.054)***}&  0.102&  2.336  &  0.124  \\\\\n",
      "NO\n",
      "&  -0.436&  \\footnotesize{(0.079)***}&  -0.968&  \\footnotesize{(0.057)***}&  0.082&  0.559  &  0.093  \\\\\n",
      "NZ\n",
      "&  -0.403&  \\footnotesize{(0.093)***}&  -0.935&  \\footnotesize{(0.065)***}&  0.057&  0.62  &  0.117  \\\\\n",
      "PH\n",
      "&  0.148&  \\footnotesize{(0.084)*}&  -0.769&  \\footnotesize{(0.048)***}&  0.041&  $\\infty$  &  0.218  \\\\\n",
      "PL\n",
      "&  -0.404&  \\footnotesize{(0.070)***}&  -0.911&  \\footnotesize{(0.060)***}&  0.152&  0.618  &  0.132  \\\\\n",
      "PT\n",
      "&  -0.159&  \\footnotesize{(0.064)**}&  -0.951&  \\footnotesize{(0.056)***}&  0.109&  1.847  &  0.106  \\\\\n",
      "RU\n",
      "&  0.106&  \\footnotesize{(0.295)}&  -0.929&  \\footnotesize{(0.049)***}&  0.033&  $\\infty$  &  0.121  \\\\\n",
      "SE\n",
      "&  0.612&  \\footnotesize{(0.122)***}&  -0.810&  \\footnotesize{(0.044)***}&  0.070&  $\\infty$  &  0.193  \\\\\n",
      "SG\n",
      "&  -0.038&  \\footnotesize{(0.072)}&  -0.806&  \\footnotesize{(0.044)***}&  0.046&  8.258  &  0.195  \\\\\n",
      "TH\n",
      "&  -0.516&  \\footnotesize{(0.070)***}&  -0.880&  \\footnotesize{(0.064)***}&  0.072&  0.441  &  0.151  \\\\\n",
      "TR\n",
      "&  -3.547&  \\footnotesize{(0.636)***}&  -1.160&  \\footnotesize{(0.059)***}&  0.023&  0  &  0  \\\\\n",
      "TW\n",
      "&  -0.088&  \\footnotesize{(0.096)}&  -0.805&  \\footnotesize{(0.041)***}&  0.027&  3.473  &  0.196  \\\\\n",
      "UK\n",
      "&  0.451&  \\footnotesize{(0.114)***}&  -0.959&  \\footnotesize{(0.047)***}&  0.051&  $\\infty$  &  0.1  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  -0.302&  0.124&  -0.869&  0.052&  0.072&  0.888&  0.158\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -0.129&  0.088&  -0.905&  0.053&  0.066&  2.316&  0.136\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  0.796&  0.107&  0.235&  0.009&  0.040 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n",
      "\n",
      "\n",
      "\n",
      "\\begin{table}[ht]\\centering\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Mini Devices, $d = 24$}\\label{regTAR: iPad Mini Delta24}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad Mini, $d=24$, No. Observations: 290}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  5.269&  \\footnotesize{(0.842)***}&  -0.380&  \\footnotesize{(0.038)***}&  0.003&  $\\infty$  &  0.669  \\\\\n",
      "AT\n",
      "&  -0.285&  \\footnotesize{(0.065)***}&  -1.150&  \\footnotesize{(0.069)***}&  0.105&  0.954  &  0  \\\\\n",
      "AU\n",
      "&  -0.059&  \\footnotesize{(0.104)}&  -0.744&  \\footnotesize{(0.054)***}&  0.052&  5.261  &  0.235  \\\\\n",
      "BE\n",
      "&  -0.240&  \\footnotesize{(0.080)***}&  -0.985&  \\footnotesize{(0.064)***}&  0.082&  1.166  &  0.076  \\\\\n",
      "BR\n",
      "&  -0.005&  \\footnotesize{(0.085)}&  -0.408&  \\footnotesize{(0.062)***}&  0.204&  63.823  &  0.61  \\\\\n",
      "CA\n",
      "&  -0.194&  \\footnotesize{(0.088)**}&  -0.730&  \\footnotesize{(0.051)***}&  0.070&  1.483  &  0.244  \\\\\n",
      "CZ\n",
      "&  -0.048&  \\footnotesize{(0.110)}&  -0.870&  \\footnotesize{(0.058)***}&  0.080&  6.504  &  0.157  \\\\\n",
      "DE\n",
      "&  0.084&  \\footnotesize{(0.091)}&  -1.217&  \\footnotesize{(0.063)***}&  0.102&  $\\infty$  &  0  \\\\\n",
      "DK\n",
      "&  0.096&  \\footnotesize{(0.118)}&  -0.760&  \\footnotesize{(0.055)***}&  0.056&  $\\infty$  &  0.224  \\\\\n",
      "ES\n",
      "&  -0.176&  \\footnotesize{(0.077)**}&  -0.996&  \\footnotesize{(0.062)***}&  0.094&  1.653  &  0.058  \\\\\n",
      "FI\n",
      "&  -0.290&  \\footnotesize{(0.083)***}&  -0.974&  \\footnotesize{(0.066)***}&  0.076&  0.934  &  0.088  \\\\\n",
      "FR\n",
      "&  -0.236&  \\footnotesize{(0.077)***}&  -1.011&  \\footnotesize{(0.065)***}&  0.090&  1.188  &  0  \\\\\n",
      "HK\n",
      "&  0.263&  \\footnotesize{(0.061)***}&  -0.276&  \\footnotesize{(0.035)***}&  0.020&  $\\infty$  &  0.991  \\\\\n",
      "HU\n",
      "&  0.115&  \\footnotesize{(0.225)}&  -0.595&  \\footnotesize{(0.054)***}&  0.044&  $\\infty$  &  0.354  \\\\\n",
      "IE\n",
      "&  -0.144&  \\footnotesize{(0.100)}&  -0.922&  \\footnotesize{(0.060)***}&  0.057&  2.058  &  0.125  \\\\\n",
      "IT\n",
      "&  -0.240&  \\footnotesize{(0.080)***}&  -0.985&  \\footnotesize{(0.064)***}&  0.082&  1.166  &  0.076  \\\\\n",
      "JP\n",
      "&  -0.394&  \\footnotesize{(0.106)***}&  -1.203&  \\footnotesize{(0.066)***}&  0.048&  0.639  &  0  \\\\\n",
      "KR\n",
      "&  -0.200&  \\footnotesize{(0.070)***}&  -0.613&  \\footnotesize{(0.064)***}&  0.071&  1.434  &  0.337  \\\\\n",
      "LU\n",
      "&  -0.240&  \\footnotesize{(0.080)***}&  -0.985&  \\footnotesize{(0.064)***}&  0.082&  1.166  &  0.076  \\\\\n",
      "MX\n",
      "&  -0.718&  \\footnotesize{(0.048)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.253  &  nan  \\\\\n",
      "MY\n",
      "&  0.328&  \\footnotesize{(0.074)***}&  -1.035&  \\footnotesize{(0.045)***}&  0.093&  $\\infty$  &  0  \\\\\n",
      "NL\n",
      "&  -0.239&  \\footnotesize{(0.080)***}&  -0.986&  \\footnotesize{(0.064)***}&  0.081&  1.171  &  0.075  \\\\\n",
      "NO\n",
      "&  -0.103&  \\footnotesize{(0.074)}&  -0.863&  \\footnotesize{(0.062)***}&  0.085&  2.943  &  0.161  \\\\\n",
      "NZ\n",
      "&  -0.619&  \\footnotesize{(0.055)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.332  &  nan  \\\\\n",
      "PH\n",
      "&  -0.254&  \\footnotesize{(0.061)***}&  -1.033&  \\footnotesize{(0.075)***}&  0.065&  1.092  &  0  \\\\\n",
      "PL\n",
      "&  0.136&  \\footnotesize{(0.171)}&  -0.640&  \\footnotesize{(0.054)***}&  0.062&  $\\infty$  &  0.313  \\\\\n",
      "PT\n",
      "&  -0.290&  \\footnotesize{(0.083)***}&  -0.974&  \\footnotesize{(0.066)***}&  0.076&  0.934  &  0.088  \\\\\n",
      "RU\n",
      "&  -0.431&  \\footnotesize{(0.133)***}&  -1.006&  \\footnotesize{(0.059)***}&  0.053&  0.567  &  0  \\\\\n",
      "SE\n",
      "&  -0.235&  \\footnotesize{(0.060)***}&  -1.111&  \\footnotesize{(0.072)***}&  0.128&  1.194  &  0  \\\\\n",
      "SG\n",
      "&  6.698&  \\footnotesize{(2.708)**}&  -0.866&  \\footnotesize{(0.054)***}&  0.002&  $\\infty$  &  0.159  \\\\\n",
      "TH\n",
      "&  0.646&  \\footnotesize{(0.296)**}&  -0.599&  \\footnotesize{(0.047)***}&  0.019&  $\\infty$  &  0.35  \\\\\n",
      "TR\n",
      "&  -0.934&  \\footnotesize{(0.087)***}&  -1.412&  \\footnotesize{(0.078)***}&  0.125&  0.118  &  0  \\\\\n",
      "TW\n",
      "&  0.270&  \\footnotesize{(0.139)*}&  -0.489&  \\footnotesize{(0.044)***}&  0.025&  $\\infty$  &  0.476  \\\\\n",
      "UK\n",
      "&  -0.069&  \\footnotesize{(0.051)}&  -1.212&  \\footnotesize{(0.055)***}&  0.118&  4.475  &  0  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  0.214&  0.196&  -0.876&  0.059&  0.073&  -1.653&  0.153\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -0.185&  0.083&  -0.974&  0.062&  0.076&  1.564&  0.088\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  1.482&  0.458&  0.264&  0.010&  0.039 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n",
      "\n",
      "\n",
      "\n",
      "\\begin{table}[ht]\\centering\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Pro Large Devices, $d = 36$}\\label{regTAR: iPad Pro Large Delta36}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad Pro Large, $d=36$, No. Observations: 278}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  2.840&  \\footnotesize{(0.186)***}&  -0.416&  \\footnotesize{(0.032)***}&  0.012&  $\\infty$  &  0.892  \\\\\n",
      "AT\n",
      "&  -0.663&  \\footnotesize{(0.100)***}&  -1.233&  \\footnotesize{(0.072)***}&  0.047&  0.441  &  0  \\\\\n",
      "AU\n",
      "&  0.525&  \\footnotesize{(0.361)}&  -1.194&  \\footnotesize{(0.057)***}&  0.027&  $\\infty$  &  0  \\\\\n",
      "BE\n",
      "&  -0.659&  \\footnotesize{(0.116)***}&  -1.235&  \\footnotesize{(0.069)***}&  0.042&  0.446  &  0  \\\\\n",
      "BR\n",
      "&  -0.395&  \\footnotesize{(0.086)***}&  -0.785&  \\footnotesize{(0.065)***}&  0.126&  0.955  &  0.312  \\\\\n",
      "CA\n",
      "&  -2.149&  \\footnotesize{(0.202)***}&  -0.712&  \\footnotesize{(0.057)***}&  0.031&  0  &  0.386  \\\\\n",
      "CZ\n",
      "&  -0.155&  \\footnotesize{(0.166)}&  -1.010&  \\footnotesize{(0.062)***}&  0.054&  2.849  &  0  \\\\\n",
      "DE\n",
      "&  -0.677&  \\footnotesize{(0.106)***}&  -1.239&  \\footnotesize{(0.071)***}&  0.046&  0.425  &  0  \\\\\n",
      "DK\n",
      "&  -0.113&  \\footnotesize{(0.317)}&  -1.242&  \\footnotesize{(0.061)***}&  0.024&  4.002  &  0  \\\\\n",
      "ES\n",
      "&  0.131&  \\footnotesize{(0.249)}&  -1.100&  \\footnotesize{(0.060)***}&  0.025&  $\\infty$  &  0  \\\\\n",
      "FI\n",
      "&  -0.875&  \\footnotesize{(0.089)***}&  -1.320&  \\footnotesize{(0.079)***}&  0.053&  0.231  &  0  \\\\\n",
      "FR\n",
      "&  -0.658&  \\footnotesize{(0.116)***}&  -1.236&  \\footnotesize{(0.069)***}&  0.042&  0.447  &  0  \\\\\n",
      "HK\n",
      "&  0.069&  \\footnotesize{(0.016)***}&  -1.534&  \\footnotesize{(0.032)***}&  0.030&  $\\infty$  &  0  \\\\\n",
      "HU\n",
      "&  -1.251&  \\footnotesize{(0.107)***}&  -0.929&  \\footnotesize{(0.077)***}&  0.058&  0  &  0.181  \\\\\n",
      "IE\n",
      "&  -0.865&  \\footnotesize{(0.091)***}&  -1.279&  \\footnotesize{(0.079)***}&  0.054&  0.24  &  0  \\\\\n",
      "IT\n",
      "&  -0.654&  \\footnotesize{(0.114)***}&  -1.243&  \\footnotesize{(0.069)***}&  0.042&  0.452  &  0  \\\\\n",
      "JP\n",
      "&  -1.271&  \\footnotesize{(0.048)***}&  nan&  \\footnotesize{(nan)}&  nan&  0  &  nan  \\\\\n",
      "KR\n",
      "&  -1.136&  \\footnotesize{(0.056)***}&  nan&  \\footnotesize{(nan)}&  nan&  0  &  nan  \\\\\n",
      "LU\n",
      "&  -0.628&  \\footnotesize{(0.115)***}&  -1.232&  \\footnotesize{(0.068)***}&  0.042&  0.485  &  0  \\\\\n",
      "MX\n",
      "&  -0.656&  \\footnotesize{(0.074)***}&  -1.464&  \\footnotesize{(0.080)***}&  0.096&  0.45  &  0  \\\\\n",
      "MY\n",
      "&  -1.796&  \\footnotesize{(0.077)***}&  -1.245&  \\footnotesize{(0.051)***}&  0.046&  0  &  0  \\\\\n",
      "NL\n",
      "&  -0.752&  \\footnotesize{(0.096)***}&  -1.285&  \\footnotesize{(0.075)***}&  0.051&  0.344  &  0  \\\\\n",
      "NO\n",
      "&  -0.532&  \\footnotesize{(0.092)***}&  -1.136&  \\footnotesize{(0.075)***}&  0.083&  0.632  &  0  \\\\\n",
      "NZ\n",
      "&  -1.041&  \\footnotesize{(0.059)***}&  nan&  \\footnotesize{(nan)}&  nan&  0  &  nan  \\\\\n",
      "PH\n",
      "&  1.234&  \\footnotesize{(0.168)***}&  -0.802&  \\footnotesize{(0.048)***}&  0.045&  $\\infty$  &  0.296  \\\\\n",
      "PL\n",
      "&  -0.586&  \\footnotesize{(0.097)***}&  -1.019&  \\footnotesize{(0.075)***}&  0.074&  0.544  &  0  \\\\\n",
      "PT\n",
      "&  -0.852&  \\footnotesize{(0.089)***}&  -1.319&  \\footnotesize{(0.079)***}&  0.053&  0.251  &  0  \\\\\n",
      "RU\n",
      "&  -8.189&  \\footnotesize{(1.966)***}&  -1.241&  \\footnotesize{(0.050)***}&  0.009&  0  &  0  \\\\\n",
      "SE\n",
      "&  -1.384&  \\footnotesize{(0.100)***}&  -0.836&  \\footnotesize{(0.074)***}&  0.066&  0  &  0.265  \\\\\n",
      "SG\n",
      "&  -2.991&  \\footnotesize{(0.694)***}&  -1.088&  \\footnotesize{(0.058)***}&  0.006&  0  &  0  \\\\\n",
      "TH\n",
      "&  0.026&  \\footnotesize{(0.217)}&  -1.324&  \\footnotesize{(0.073)***}&  0.024&  $\\infty$  &  0  \\\\\n",
      "TR\n",
      "&  -1.867&  \\footnotesize{(0.119)***}&  -1.141&  \\footnotesize{(0.067)***}&  0.091&  0  &  0  \\\\\n",
      "TW\n",
      "&  0.078&  \\footnotesize{(0.119)}&  -0.498&  \\footnotesize{(0.053)***}&  0.033&  $\\infty$  &  0.696  \\\\\n",
      "UK\n",
      "&  -0.237&  \\footnotesize{(0.129)*}&  -1.163&  \\footnotesize{(0.062)***}&  0.048&  1.774  &  0  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  -0.827&  0.198&  -1.113&  0.064&  0.048&  0.273&  nan\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -0.659&  0.110&  -1.232&  0.068&  0.046&  0.447&  nan\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  1.610&  0.330&  0.254&  0.012&  0.026 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n",
      "\n",
      "\n",
      "\n",
      "\\begin{table}[ht]\\centering\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Pro Small Devices, $d = 36$}\\label{regTAR: iPad Pro Small Delta36}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad Pro Small, $d=36$, No. Observations: 266}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  -0.817&  \\footnotesize{(0.057)***}&  -0.210&  \\footnotesize{(0.056)***}&  0.028&  0.283  &  2.036  \\\\\n",
      "AT\n",
      "&  -0.669&  \\footnotesize{(0.103)***}&  -1.226&  \\footnotesize{(0.075)***}&  0.047&  0.434  &  0  \\\\\n",
      "AU\n",
      "&  -0.285&  \\footnotesize{(0.214)}&  -1.237&  \\footnotesize{(0.061)***}&  0.038&  1.43  &  0  \\\\\n",
      "BE\n",
      "&  -0.665&  \\footnotesize{(0.096)***}&  -1.290&  \\footnotesize{(0.077)***}&  0.050&  0.439  &  0  \\\\\n",
      "BR\n",
      "&  -0.334&  \\footnotesize{(0.094)***}&  -0.710&  \\footnotesize{(0.060)***}&  0.124&  1.181  &  0.388  \\\\\n",
      "CA\n",
      "&  -1.869&  \\footnotesize{(0.183)***}&  -0.666&  \\footnotesize{(0.058)***}&  0.036&  0  &  0.438  \\\\\n",
      "CZ\n",
      "&  0.077&  \\footnotesize{(0.213)}&  -0.952&  \\footnotesize{(0.062)***}&  0.043&  $\\infty$  &  0.158  \\\\\n",
      "DE\n",
      "&  -3.436&  \\footnotesize{(0.735)***}&  -1.031&  \\footnotesize{(0.061)***}&  0.014&  0  &  0  \\\\\n",
      "DK\n",
      "&  -0.686&  \\footnotesize{(0.097)***}&  -1.302&  \\footnotesize{(0.075)***}&  0.054&  0.414  &  0  \\\\\n",
      "ES\n",
      "&  -0.638&  \\footnotesize{(0.104)***}&  -1.259&  \\footnotesize{(0.073)***}&  0.047&  0.472  &  0  \\\\\n",
      "FI\n",
      "&  -0.684&  \\footnotesize{(0.094)***}&  -1.286&  \\footnotesize{(0.078)***}&  0.049&  0.417  &  0  \\\\\n",
      "FR\n",
      "&  -0.690&  \\footnotesize{(0.101)***}&  -1.282&  \\footnotesize{(0.075)***}&  0.048&  0.41  &  0  \\\\\n",
      "HK\n",
      "&  0.115&  \\footnotesize{(0.040)***}&  -1.274&  \\footnotesize{(0.053)***}&  0.030&  $\\infty$  &  0  \\\\\n",
      "HU\n",
      "&  -0.948&  \\footnotesize{(0.064)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.162  &  nan  \\\\\n",
      "IE\n",
      "&  -0.604&  \\footnotesize{(0.107)***}&  -1.220&  \\footnotesize{(0.074)***}&  0.043&  0.518  &  0  \\\\\n",
      "IT\n",
      "&  -0.621&  \\footnotesize{(0.103)***}&  -1.263&  \\footnotesize{(0.074)***}&  0.047&  0.495  &  0  \\\\\n",
      "JP\n",
      "&  -3.121&  \\footnotesize{(0.920)***}&  -0.895&  \\footnotesize{(0.064)***}&  0.012&  0  &  0.213  \\\\\n",
      "KR\n",
      "&  -3.159&  \\footnotesize{(0.549)***}&  -1.113&  \\footnotesize{(0.061)***}&  0.011&  0  &  0  \\\\\n",
      "LU\n",
      "&  -0.665&  \\footnotesize{(0.096)***}&  -1.290&  \\footnotesize{(0.077)***}&  0.050&  0.439  &  0  \\\\\n",
      "MX\n",
      "&  -0.785&  \\footnotesize{(0.085)***}&  -1.447&  \\footnotesize{(0.071)***}&  0.085&  0.312  &  0  \\\\\n",
      "MY\n",
      "&  0.115&  \\footnotesize{(0.189)}&  -1.279&  \\footnotesize{(0.054)***}&  0.028&  $\\infty$  &  0  \\\\\n",
      "NL\n",
      "&  -0.663&  \\footnotesize{(0.096)***}&  -1.290&  \\footnotesize{(0.077)***}&  0.049&  0.441  &  0  \\\\\n",
      "NO\n",
      "&  -0.523&  \\footnotesize{(0.082)***}&  -1.244&  \\footnotesize{(0.069)***}&  0.075&  0.648  &  0  \\\\\n",
      "NZ\n",
      "&  -0.398&  \\footnotesize{(0.244)}&  -1.138&  \\footnotesize{(0.062)***}&  0.030&  0.946  &  0  \\\\\n",
      "PH\n",
      "&  -0.210&  \\footnotesize{(0.074)***}&  -1.118&  \\footnotesize{(0.071)***}&  0.069&  2.036  &  0  \\\\\n",
      "PL\n",
      "&  -0.549&  \\footnotesize{(0.104)***}&  -1.029&  \\footnotesize{(0.076)***}&  0.066&  0.603  &  0  \\\\\n",
      "PT\n",
      "&  -0.684&  \\footnotesize{(0.094)***}&  -1.286&  \\footnotesize{(0.078)***}&  0.049&  0.417  &  0  \\\\\n",
      "RU\n",
      "&  -0.168&  \\footnotesize{(0.213)}&  -1.283&  \\footnotesize{(0.061)***}&  0.043&  2.609  &  0  \\\\\n",
      "SE\n",
      "&  -1.110&  \\footnotesize{(0.061)***}&  nan&  \\footnotesize{(nan)}&  nan&  0  &  nan  \\\\\n",
      "SG\n",
      "&  -1.197&  \\footnotesize{(0.061)***}&  nan&  \\footnotesize{(nan)}&  nan&  0  &  nan  \\\\\n",
      "TH\n",
      "&  2.504&  \\footnotesize{(0.636)***}&  -1.157&  \\footnotesize{(0.065)***}&  0.011&  $\\infty$  &  0  \\\\\n",
      "TR\n",
      "&  -1.786&  \\footnotesize{(0.120)***}&  -1.130&  \\footnotesize{(0.070)***}&  0.090&  0  &  0  \\\\\n",
      "TW\n",
      "&  -0.548&  \\footnotesize{(0.055)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.604  &  nan  \\\\\n",
      "UK\n",
      "&  -0.077&  \\footnotesize{(0.179)}&  -0.998&  \\footnotesize{(0.060)***}&  0.036&  5.989  &  0.077  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  -0.758&  0.184&  -1.130&  0.068&  0.047&  0.338&  nan\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -0.664&  0.102&  -1.232&  0.070&  0.047&  0.440&  nan\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  1.028&  0.204&  0.244&  0.008&  0.024 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n",
      "\n",
      "\n",
      "\n",
      "\\begin{table}[ht]\\centering"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rickw\\AppData\\Local\\Temp\\ipykernel_25180\\2733580979.py:47: RuntimeWarning: invalid value encountered in log10\n",
      "  hl0 = np.log10(0.5) / np.log10(1+dffilter2['rho0'][c]) / (52 / Delta)\n",
      "C:\\Users\\rickw\\AppData\\Local\\Temp\\ipykernel_25180\\2733580979.py:48: RuntimeWarning: invalid value encountered in log10\n",
      "  hl1 = np.log10(0.5) / np.log10(1+dffilter2['rho1'][c]) / (52 / Delta)\n",
      "C:\\Users\\rickw\\AppData\\Local\\Temp\\ipykernel_25180\\2733580979.py:110: RuntimeWarning: invalid value encountered in log10\n",
      "  '&  ' + str(\"%.3f\" % round(np.log10(0.5) / np.log10(1+np.nanmean(coeffouter)) / (52 / Delta),3)) +'\\\\' + '\\\\')\n",
      "C:\\Users\\rickw\\AppData\\Local\\Temp\\ipykernel_25180\\2733580979.py:119: RuntimeWarning: invalid value encountered in log10\n",
      "  '&  ' + str(\"%.3f\" % round(np.log10(0.5) / np.log10(1+np.nanmedian(coeffouter)) / (52 / Delta),3)) +'\\\\' + '\\\\')\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Devices, $d = 36$}\\label{regTAR: iPad Delta36}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad, $d=36$, No. Observations: 278}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  -2.106&  \\footnotesize{(0.159)***}&  -0.306&  \\footnotesize{(0.029)***}&  0.017&  0  &  1.314  \\\\\n",
      "AT\n",
      "&  0.098&  \\footnotesize{(0.124)}&  -1.068&  \\footnotesize{(0.052)***}&  0.065&  $\\infty$  &  0  \\\\\n",
      "AU\n",
      "&  -0.686&  \\footnotesize{(0.072)***}&  -0.927&  \\footnotesize{(0.071)***}&  0.092&  0.414  &  0.183  \\\\\n",
      "BE\n",
      "&  -0.087&  \\footnotesize{(0.107)}&  -1.089&  \\footnotesize{(0.054)***}&  0.072&  5.272  &  0  \\\\\n",
      "BR\n",
      "&  -0.776&  \\footnotesize{(0.064)***}&  -1.097&  \\footnotesize{(0.071)***}&  0.151&  0.321  &  0  \\\\\n",
      "CA\n",
      "&  -1.278&  \\footnotesize{(0.093)***}&  -0.814&  \\footnotesize{(0.047)***}&  0.070&  0  &  0.285  \\\\\n",
      "CZ\n",
      "&  -0.304&  \\footnotesize{(0.109)***}&  -1.186&  \\footnotesize{(0.060)***}&  0.089&  1.324  &  0  \\\\\n",
      "DE\n",
      "&  0.162&  \\footnotesize{(0.139)}&  -1.106&  \\footnotesize{(0.054)***}&  0.064&  $\\infty$  &  0  \\\\\n",
      "DK\n",
      "&  -0.116&  \\footnotesize{(0.221)}&  -1.021&  \\footnotesize{(0.046)***}&  0.032&  3.892  &  0  \\\\\n",
      "ES\n",
      "&  0.799&  \\footnotesize{(0.153)***}&  -0.552&  \\footnotesize{(0.045)***}&  0.176&  $\\infty$  &  0.598  \\\\\n",
      "FI\n",
      "&  -0.152&  \\footnotesize{(0.101)}&  -1.098&  \\footnotesize{(0.055)***}&  0.075&  2.911  &  0  \\\\\n",
      "FR\n",
      "&  -0.066&  \\footnotesize{(0.108)}&  -1.091&  \\footnotesize{(0.054)***}&  0.072&  7.028  &  0  \\\\\n",
      "HK\n",
      "&  -0.656&  \\footnotesize{(0.063)***}&  -0.226&  \\footnotesize{(0.056)***}&  0.010&  0.45  &  1.873  \\\\\n",
      "HU\n",
      "&  -0.574&  \\footnotesize{(0.094)***}&  -1.163&  \\footnotesize{(0.064)***}&  0.112&  0.562  &  0  \\\\\n",
      "IE\n",
      "&  -0.234&  \\footnotesize{(0.088)***}&  -1.161&  \\footnotesize{(0.057)***}&  0.083&  1.8  &  0  \\\\\n",
      "IT\n",
      "&  -0.109&  \\footnotesize{(0.106)}&  -1.092&  \\footnotesize{(0.054)***}&  0.072&  4.158  &  0  \\\\\n",
      "JP\n",
      "&  -2.429&  \\footnotesize{(0.331)***}&  -1.074&  \\footnotesize{(0.052)***}&  0.020&  0  &  0  \\\\\n",
      "KR\n",
      "&  -1.482&  \\footnotesize{(0.161)***}&  -0.927&  \\footnotesize{(0.046)***}&  0.036&  0  &  0.183  \\\\\n",
      "LU\n",
      "&  -0.109&  \\footnotesize{(0.106)}&  -1.092&  \\footnotesize{(0.054)***}&  0.072&  4.158  &  0  \\\\\n",
      "MX\n",
      "&  -0.713&  \\footnotesize{(0.093)***}&  -1.171&  \\footnotesize{(0.067)***}&  0.108&  0.384  &  0  \\\\\n",
      "MY\n",
      "&  -0.258&  \\footnotesize{(0.166)}&  -1.130&  \\footnotesize{(0.054)***}&  0.041&  1.608  &  0  \\\\\n",
      "NL\n",
      "&  -0.099&  \\footnotesize{(0.106)}&  -1.091&  \\footnotesize{(0.054)***}&  0.072&  4.603  &  0  \\\\\n",
      "NO\n",
      "&  -0.658&  \\footnotesize{(0.087)***}&  -1.100&  \\footnotesize{(0.064)***}&  0.081&  0.447  &  0  \\\\\n",
      "NZ\n",
      "&  -0.725&  \\footnotesize{(0.057)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.372  &  nan  \\\\\n",
      "PH\n",
      "&  1.206&  \\footnotesize{(0.201)***}&  -0.607&  \\footnotesize{(0.043)***}&  0.020&  $\\infty$  &  0.514  \\\\\n",
      "PL\n",
      "&  -0.905&  \\footnotesize{(0.051)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.204  &  nan  \\\\\n",
      "PT\n",
      "&  0.204&  \\footnotesize{(0.139)}&  -1.034&  \\footnotesize{(0.052)***}&  0.063&  $\\infty$  &  0  \\\\\n",
      "RU\n",
      "&  0.394&  \\footnotesize{(0.295)}&  -1.059&  \\footnotesize{(0.048)***}&  0.033&  $\\infty$  &  0  \\\\\n",
      "SE\n",
      "&  0.648&  \\footnotesize{(0.167)***}&  -1.025&  \\footnotesize{(0.050)***}&  0.059&  $\\infty$  &  0  \\\\\n",
      "SG\n",
      "&  -0.375&  \\footnotesize{(0.072)***}&  -0.856&  \\footnotesize{(0.054)***}&  0.058&  1.021  &  0.248  \\\\\n",
      "TH\n",
      "&  -0.991&  \\footnotesize{(0.051)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.102  &  nan  \\\\\n",
      "TR\n",
      "&  -1.165&  \\footnotesize{(0.061)***}&  nan&  \\footnotesize{(nan)}&  nan&  0  &  nan  \\\\\n",
      "TW\n",
      "&  -0.306&  \\footnotesize{(0.110)***}&  -0.974&  \\footnotesize{(0.048)***}&  0.026&  1.314  &  0.131  \\\\\n",
      "UK\n",
      "&  -0.014&  \\footnotesize{(0.159)}&  -0.955&  \\footnotesize{(0.056)***}&  0.046&  34.036  &  0.155  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  -0.408&  0.124&  -0.970&  0.054&  0.066&  0.916&  0.137\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -0.281&  0.106&  -1.071&  0.054&  0.068&  1.455&  nan\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  0.733&  0.063&  0.239&  0.008&  0.037 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n",
      "\n",
      "\n",
      "\n",
      "\\begin{table}[ht]\\centering\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Mini Devices, $d = 36$}\\label{regTAR: iPad Mini Delta36}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad Mini, $d=36$, No. Observations: 278}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  7.221&  \\footnotesize{(0.921)***}&  -0.569&  \\footnotesize{(0.040)***}&  0.003&  $\\infty$  &  0.57  \\\\\n",
      "AT\n",
      "&  -0.482&  \\footnotesize{(0.082)***}&  -1.410&  \\footnotesize{(0.066)***}&  0.094&  0.73  &  0  \\\\\n",
      "AU\n",
      "&  1.194&  \\footnotesize{(0.523)**}&  -0.967&  \\footnotesize{(0.058)***}&  0.018&  $\\infty$  &  0.141  \\\\\n",
      "BE\n",
      "&  -0.508&  \\footnotesize{(0.086)***}&  -1.399&  \\footnotesize{(0.066)***}&  0.082&  0.677  &  0  \\\\\n",
      "BR\n",
      "&  -1.015&  \\footnotesize{(0.173)***}&  -0.346&  \\footnotesize{(0.057)***}&  0.116&  0  &  1.13  \\\\\n",
      "CA\n",
      "&  -0.427&  \\footnotesize{(0.149)***}&  -0.966&  \\footnotesize{(0.055)***}&  0.057&  0.862  &  0.142  \\\\\n",
      "CZ\n",
      "&  -0.203&  \\footnotesize{(0.118)*}&  -1.292&  \\footnotesize{(0.060)***}&  0.080&  2.115  &  0  \\\\\n",
      "DE\n",
      "&  -0.167&  \\footnotesize{(0.140)}&  -1.421&  \\footnotesize{(0.089)***}&  0.072&  2.626  &  0  \\\\\n",
      "DK\n",
      "&  0.043&  \\footnotesize{(0.170)}&  -1.074&  \\footnotesize{(0.058)***}&  0.046&  $\\infty$  &  0  \\\\\n",
      "ES\n",
      "&  -0.465&  \\footnotesize{(0.084)***}&  -1.400&  \\footnotesize{(0.064)***}&  0.094&  0.767  &  0  \\\\\n",
      "FI\n",
      "&  -0.553&  \\footnotesize{(0.090)***}&  -1.405&  \\footnotesize{(0.068)***}&  0.076&  0.596  &  0  \\\\\n",
      "FR\n",
      "&  -0.504&  \\footnotesize{(0.087)***}&  -1.394&  \\footnotesize{(0.066)***}&  0.082&  0.684  &  0  \\\\\n",
      "HK\n",
      "&  0.399&  \\footnotesize{(0.072)***}&  -0.445&  \\footnotesize{(0.043)***}&  0.020&  $\\infty$  &  0.815  \\\\\n",
      "HU\n",
      "&  -0.574&  \\footnotesize{(0.102)***}&  -0.975&  \\footnotesize{(0.073)***}&  0.126&  0.562  &  0.13  \\\\\n",
      "IE\n",
      "&  -0.490&  \\footnotesize{(0.094)***}&  -1.393&  \\footnotesize{(0.066)***}&  0.077&  0.713  &  0  \\\\\n",
      "IT\n",
      "&  -0.508&  \\footnotesize{(0.086)***}&  -1.399&  \\footnotesize{(0.066)***}&  0.082&  0.677  &  0  \\\\\n",
      "JP\n",
      "&  -0.469&  \\footnotesize{(0.122)***}&  -1.006&  \\footnotesize{(0.069)***}&  0.042&  0.758  &  0  \\\\\n",
      "KR\n",
      "&  -0.420&  \\footnotesize{(0.076)***}&  -0.730&  \\footnotesize{(0.073)***}&  0.072&  0.881  &  0.367  \\\\\n",
      "LU\n",
      "&  -0.508&  \\footnotesize{(0.086)***}&  -1.399&  \\footnotesize{(0.066)***}&  0.082&  0.677  &  0  \\\\\n",
      "MX\n",
      "&  -0.918&  \\footnotesize{(0.050)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.192  &  nan  \\\\\n",
      "MY\n",
      "&  0.001&  \\footnotesize{(0.102)}&  -1.040&  \\footnotesize{(0.055)***}&  0.086&  $\\infty$  &  0  \\\\\n",
      "NL\n",
      "&  -0.510&  \\footnotesize{(0.086)***}&  -1.400&  \\footnotesize{(0.066)***}&  0.081&  0.673  &  0  \\\\\n",
      "NO\n",
      "&  -0.271&  \\footnotesize{(0.137)**}&  -1.046&  \\footnotesize{(0.067)***}&  0.062&  1.518  &  0  \\\\\n",
      "NZ\n",
      "&  -0.697&  \\footnotesize{(0.080)***}&  -1.116&  \\footnotesize{(0.090)***}&  0.062&  0.402  &  0  \\\\\n",
      "PH\n",
      "&  3.274&  \\footnotesize{(0.715)***}&  -0.684&  \\footnotesize{(0.057)***}&  0.011&  $\\infty$  &  0.417  \\\\\n",
      "PL\n",
      "&  -0.382&  \\footnotesize{(0.157)**}&  -0.915&  \\footnotesize{(0.062)***}&  0.077&  0.997  &  0.195  \\\\\n",
      "PT\n",
      "&  -0.553&  \\footnotesize{(0.090)***}&  -1.405&  \\footnotesize{(0.068)***}&  0.076&  0.596  &  0  \\\\\n",
      "RU\n",
      "&  0.013&  \\footnotesize{(0.303)}&  -1.263&  \\footnotesize{(0.055)***}&  0.032&  $\\infty$  &  0  \\\\\n",
      "SE\n",
      "&  0.042&  \\footnotesize{(0.140)}&  -1.144&  \\footnotesize{(0.058)***}&  0.078&  $\\infty$  &  0  \\\\\n",
      "SG\n",
      "&  0.167&  \\footnotesize{(0.467)}&  -1.051&  \\footnotesize{(0.058)***}&  0.009&  $\\infty$  &  0  \\\\\n",
      "TH\n",
      "&  -1.157&  \\footnotesize{(0.087)***}&  -0.530&  \\footnotesize{(0.057)***}&  0.050&  0  &  0.636  \\\\\n",
      "TR\n",
      "&  -0.640&  \\footnotesize{(0.200)***}&  -1.206&  \\footnotesize{(0.064)***}&  0.066&  0.47  &  0  \\\\\n",
      "TW\n",
      "&  -0.005&  \\footnotesize{(0.164)}&  -0.662&  \\footnotesize{(0.058)***}&  0.025&  95.734  &  0.442  \\\\\n",
      "UK\n",
      "&  -0.334&  \\footnotesize{(0.065)***}&  -1.315&  \\footnotesize{(0.067)***}&  0.118&  1.181  &  0  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  -0.012&  0.180&  -1.084&  0.063&  0.065&  39.946&  nan\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -0.446&  0.102&  -1.116&  0.064&  0.076&  0.813&  nan\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  1.460&  0.191&  0.318&  0.010&  0.031 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n",
      "\n",
      "\n",
      "\n",
      "\\begin{table}[ht]\\centering\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Pro Large Devices, $d = 48$}\\label{regTAR: iPad Pro Large Delta48}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad Pro Large, $d=48$, No. Observations: 266}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  2.923&  \\footnotesize{(0.200)***}&  -0.588&  \\footnotesize{(0.035)***}&  0.012&  $\\infty$  &  0.722  \\\\\n",
      "AT\n",
      "&  -0.663&  \\footnotesize{(0.166)***}&  -1.435&  \\footnotesize{(0.061)***}&  0.033&  0.588  &  0  \\\\\n",
      "AU\n",
      "&  -1.000&  \\footnotesize{(0.102)***}&  -1.627&  \\footnotesize{(0.072)***}&  0.059&  0.0  &  0  \\\\\n",
      "BE\n",
      "&  -0.726&  \\footnotesize{(0.157)***}&  -1.488&  \\footnotesize{(0.060)***}&  0.032&  0.494  &  0  \\\\\n",
      "BR\n",
      "&  -0.538&  \\footnotesize{(0.087)***}&  -0.993&  \\footnotesize{(0.070)***}&  0.128&  0.829  &  0.129  \\\\\n",
      "CA\n",
      "&  -1.711&  \\footnotesize{(0.168)***}&  -0.916&  \\footnotesize{(0.065)***}&  0.035&  0  &  0.258  \\\\\n",
      "CZ\n",
      "&  -0.248&  \\footnotesize{(0.206)}&  -1.242&  \\footnotesize{(0.061)***}&  0.041&  2.245  &  0  \\\\\n",
      "DE\n",
      "&  -0.743&  \\footnotesize{(0.155)***}&  -1.468&  \\footnotesize{(0.061)***}&  0.034&  0.471  &  0  \\\\\n",
      "DK\n",
      "&  -1.460&  \\footnotesize{(0.059)***}&  nan&  \\footnotesize{(nan)}&  nan&  0  &  nan  \\\\\n",
      "ES\n",
      "&  -0.684&  \\footnotesize{(0.165)***}&  -1.429&  \\footnotesize{(0.061)***}&  0.033&  0.555  &  0  \\\\\n",
      "FI\n",
      "&  -0.935&  \\footnotesize{(0.152)***}&  -1.497&  \\footnotesize{(0.060)***}&  0.033&  0.234  &  0  \\\\\n",
      "FR\n",
      "&  -0.725&  \\footnotesize{(0.157)***}&  -1.489&  \\footnotesize{(0.060)***}&  0.032&  0.496  &  0  \\\\\n",
      "HK\n",
      "&  0.095&  \\footnotesize{(0.030)***}&  -1.380&  \\footnotesize{(0.045)***}&  0.029&  $\\infty$  &  0  \\\\\n",
      "HU\n",
      "&  -1.633&  \\footnotesize{(0.104)***}&  -0.953&  \\footnotesize{(0.074)***}&  0.058&  0  &  0.209  \\\\\n",
      "IE\n",
      "&  -0.944&  \\footnotesize{(0.170)***}&  -1.455&  \\footnotesize{(0.060)***}&  0.031&  0.222  &  0  \\\\\n",
      "IT\n",
      "&  -0.729&  \\footnotesize{(0.158)***}&  -1.489&  \\footnotesize{(0.060)***}&  0.032&  0.49  &  0  \\\\\n",
      "JP\n",
      "&  -1.431&  \\footnotesize{(0.086)***}&  -1.057&  \\footnotesize{(0.063)***}&  0.083&  0  &  0  \\\\\n",
      "KR\n",
      "&  -1.630&  \\footnotesize{(0.117)***}&  -1.020&  \\footnotesize{(0.066)***}&  0.038&  0  &  0  \\\\\n",
      "LU\n",
      "&  -0.743&  \\footnotesize{(0.158)***}&  -1.486&  \\footnotesize{(0.060)***}&  0.031&  0.471  &  0  \\\\\n",
      "MX\n",
      "&  -4.013&  \\footnotesize{(1.032)***}&  -1.092&  \\footnotesize{(0.056)***}&  0.013&  0  &  0  \\\\\n",
      "MY\n",
      "&  -0.613&  \\footnotesize{(0.221)***}&  -1.417&  \\footnotesize{(0.047)***}&  0.020&  0.674  &  0  \\\\\n",
      "NL\n",
      "&  -0.755&  \\footnotesize{(0.159)***}&  -1.486&  \\footnotesize{(0.060)***}&  0.031&  0.455  &  0  \\\\\n",
      "NO\n",
      "&  -0.306&  \\footnotesize{(0.128)**}&  -1.346&  \\footnotesize{(0.066)***}&  0.057&  1.752  &  0  \\\\\n",
      "NZ\n",
      "&  -1.427&  \\footnotesize{(0.096)***}&  -0.968&  \\footnotesize{(0.093)***}&  0.072&  0  &  0.186  \\\\\n",
      "PH\n",
      "&  0.393&  \\footnotesize{(0.145)***}&  -0.851&  \\footnotesize{(0.057)***}&  0.052&  $\\infty$  &  0.336  \\\\\n",
      "PL\n",
      "&  -0.060&  \\footnotesize{(0.367)}&  -1.149&  \\footnotesize{(0.062)***}&  0.024&  10.341  &  0  \\\\\n",
      "PT\n",
      "&  -0.946&  \\footnotesize{(0.154)***}&  -1.499&  \\footnotesize{(0.060)***}&  0.032&  0.219  &  0  \\\\\n",
      "RU\n",
      "&  -1.947&  \\footnotesize{(0.140)***}&  -1.210&  \\footnotesize{(0.053)***}&  0.052&  0  &  0  \\\\\n",
      "SE\n",
      "&  -1.568&  \\footnotesize{(0.087)***}&  -0.899&  \\footnotesize{(0.091)***}&  0.072&  0  &  0.279  \\\\\n",
      "SG\n",
      "&  -1.037&  \\footnotesize{(0.061)***}&  nan&  \\footnotesize{(nan)}&  nan&  0  &  nan  \\\\\n",
      "TH\n",
      "&  -1.320&  \\footnotesize{(0.126)***}&  -0.888&  \\footnotesize{(0.093)***}&  0.039&  0  &  0.292  \\\\\n",
      "TR\n",
      "&  -1.976&  \\footnotesize{(0.125)***}&  -0.990&  \\footnotesize{(0.067)***}&  0.091&  0  &  0.139  \\\\\n",
      "TW\n",
      "&  0.287&  \\footnotesize{(0.106)***}&  -0.539&  \\footnotesize{(0.052)***}&  0.033&  $\\infty$  &  0.826  \\\\\n",
      "UK\n",
      "&  -0.188&  \\footnotesize{(0.211)}&  -1.325&  \\footnotesize{(0.058)***}&  0.028&  3.072  &  0  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  -0.853&  0.169&  -1.208&  0.063&  0.043&  0.334&  nan\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -0.749&  0.153&  -1.284&  0.060&  0.033&  0.463&  nan\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  1.033&  0.161&  0.285&  0.012&  0.024 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n",
      "\n",
      "\n",
      "\n",
      "\\begin{table}[ht]\\centering\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Pro Small Devices, $d = 48$}\\label{regTAR: iPad Pro Small Delta48}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad Pro Small, $d=48$, No. Observations: 254}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  -0.260&  \\footnotesize{(0.081)***}&  -0.854&  \\footnotesize{(0.052)***}&  0.021&  2.125  &  0.333  \\\\\n",
      "AT\n",
      "&  -0.924&  \\footnotesize{(0.118)***}&  -1.503&  \\footnotesize{(0.063)***}&  0.041&  0.248  &  0  \\\\\n",
      "AU\n",
      "&  0.329&  \\footnotesize{(0.319)}&  -1.543&  \\footnotesize{(0.058)***}&  0.028&  $\\infty$  &  0  \\\\\n",
      "BE\n",
      "&  -0.826&  \\footnotesize{(0.144)***}&  -1.500&  \\footnotesize{(0.059)***}&  0.032&  0.366  &  0  \\\\\n",
      "BR\n",
      "&  -0.481&  \\footnotesize{(0.097)***}&  -0.930&  \\footnotesize{(0.065)***}&  0.126&  0.976  &  0.241  \\\\\n",
      "CA\n",
      "&  -1.392&  \\footnotesize{(0.140)***}&  -0.861&  \\footnotesize{(0.069)***}&  0.047&  0  &  0.324  \\\\\n",
      "CZ\n",
      "&  -0.193&  \\footnotesize{(0.219)}&  -1.228&  \\footnotesize{(0.061)***}&  0.043&  2.984  &  0  \\\\\n",
      "DE\n",
      "&  -1.076&  \\footnotesize{(0.106)***}&  -1.466&  \\footnotesize{(0.068)***}&  0.044&  0  &  0  \\\\\n",
      "DK\n",
      "&  -1.067&  \\footnotesize{(0.092)***}&  -1.630&  \\footnotesize{(0.072)***}&  0.053&  0  &  0  \\\\\n",
      "ES\n",
      "&  -0.674&  \\footnotesize{(0.202)***}&  -1.430&  \\footnotesize{(0.059)***}&  0.028&  0.571  &  0  \\\\\n",
      "FI\n",
      "&  -0.962&  \\footnotesize{(0.120)***}&  -1.513&  \\footnotesize{(0.063)***}&  0.038&  0.196  &  0  \\\\\n",
      "FR\n",
      "&  -0.901&  \\footnotesize{(0.141)***}&  -1.505&  \\footnotesize{(0.059)***}&  0.033&  0.277  &  0  \\\\\n",
      "HK\n",
      "&  0.176&  \\footnotesize{(0.067)***}&  -1.124&  \\footnotesize{(0.060)***}&  0.029&  $\\infty$  &  0  \\\\\n",
      "HU\n",
      "&  -1.756&  \\footnotesize{(0.112)***}&  -0.909&  \\footnotesize{(0.069)***}&  0.057&  0  &  0.267  \\\\\n",
      "IE\n",
      "&  -1.010&  \\footnotesize{(0.114)***}&  -1.485&  \\footnotesize{(0.065)***}&  0.040&  0  &  0  \\\\\n",
      "IT\n",
      "&  -0.845&  \\footnotesize{(0.138)***}&  -1.510&  \\footnotesize{(0.060)***}&  0.033&  0.343  &  0  \\\\\n",
      "JP\n",
      "&  -1.301&  \\footnotesize{(0.133)***}&  -0.866&  \\footnotesize{(0.066)***}&  0.043&  0  &  0.318  \\\\\n",
      "KR\n",
      "&  -5.847&  \\footnotesize{(1.405)***}&  -1.250&  \\footnotesize{(0.062)***}&  0.006&  0  &  0  \\\\\n",
      "LU\n",
      "&  -0.826&  \\footnotesize{(0.144)***}&  -1.500&  \\footnotesize{(0.059)***}&  0.032&  0.366  &  0  \\\\\n",
      "MX\n",
      "&  -1.205&  \\footnotesize{(0.048)***}&  nan&  \\footnotesize{(nan)}&  nan&  0  &  nan  \\\\\n",
      "MY\n",
      "&  -0.076&  \\footnotesize{(0.184)}&  -1.340&  \\footnotesize{(0.052)***}&  0.028&  8.095  &  0  \\\\\n",
      "NL\n",
      "&  -0.835&  \\footnotesize{(0.142)***}&  -1.502&  \\footnotesize{(0.060)***}&  0.033&  0.355  &  0  \\\\\n",
      "NO\n",
      "&  0.262&  \\footnotesize{(0.207)}&  -1.228&  \\footnotesize{(0.057)***}&  0.034&  $\\infty$  &  0  \\\\\n",
      "NZ\n",
      "&  -0.143&  \\footnotesize{(0.333)}&  -1.374&  \\footnotesize{(0.069)***}&  0.025&  4.146  &  0  \\\\\n",
      "PH\n",
      "&  -0.314&  \\footnotesize{(0.084)***}&  -1.115&  \\footnotesize{(0.075)***}&  0.068&  1.698  &  0  \\\\\n",
      "PL\n",
      "&  -1.138&  \\footnotesize{(0.063)***}&  nan&  \\footnotesize{(nan)}&  nan&  0  &  nan  \\\\\n",
      "PT\n",
      "&  -0.962&  \\footnotesize{(0.120)***}&  -1.513&  \\footnotesize{(0.063)***}&  0.038&  0.196  &  0  \\\\\n",
      "RU\n",
      "&  2.683&  \\footnotesize{(1.575)*}&  -1.280&  \\footnotesize{(0.062)***}&  0.012&  $\\infty$  &  0  \\\\\n",
      "SE\n",
      "&  -1.490&  \\footnotesize{(0.075)***}&  -1.178&  \\footnotesize{(0.099)***}&  0.083&  0  &  0  \\\\\n",
      "SG\n",
      "&  -1.296&  \\footnotesize{(0.052)***}&  nan&  \\footnotesize{(nan)}&  nan&  0  &  nan  \\\\\n",
      "TH\n",
      "&  2.059&  \\footnotesize{(0.825)**}&  -1.092&  \\footnotesize{(0.067)***}&  0.010&  $\\infty$  &  0  \\\\\n",
      "TR\n",
      "&  -2.101&  \\footnotesize{(0.172)***}&  -1.050&  \\footnotesize{(0.064)***}&  0.065&  0  &  0  \\\\\n",
      "TW\n",
      "&  -0.088&  \\footnotesize{(0.091)}&  -0.553&  \\footnotesize{(0.063)***}&  0.032&  6.946  &  0.795  \\\\\n",
      "UK\n",
      "&  -0.617&  \\footnotesize{(0.166)***}&  -1.296&  \\footnotesize{(0.060)***}&  0.036&  0.667  &  0  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  -0.738&  0.236&  -1.262&  0.064&  0.040&  0.477&  nan\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -0.840&  0.136&  -1.296&  0.063&  0.034&  0.349&  nan\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  1.283&  0.341&  0.265&  0.008&  0.022 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n",
      "\n",
      "\n",
      "\n",
      "\\begin{table}[ht]\\centering\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Devices, $d = 48$}\\label{regTAR: iPad Delta48}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad, $d=48$, No. Observations: 266}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  -2.263&  \\footnotesize{(0.183)***}&  -0.484&  \\footnotesize{(0.034)***}&  0.017&  0  &  0.967  \\\\\n",
      "AT\n",
      "&  -1.316&  \\footnotesize{(0.069)***}&  -0.857&  \\footnotesize{(0.084)***}&  0.125&  0  &  0.329  \\\\\n",
      "AU\n",
      "&  -0.813&  \\footnotesize{(0.081)***}&  -1.152&  \\footnotesize{(0.073)***}&  0.090&  0.382  &  0  \\\\\n",
      "BE\n",
      "&  -1.315&  \\footnotesize{(0.068)***}&  -0.853&  \\footnotesize{(0.084)***}&  0.125&  0  &  0.334  \\\\\n",
      "BR\n",
      "&  4.292&  \\footnotesize{(2.015)**}&  -0.988&  \\footnotesize{(0.047)***}&  0.013&  $\\infty$  &  0.145  \\\\\n",
      "CA\n",
      "&  -1.782&  \\footnotesize{(0.093)***}&  -0.877&  \\footnotesize{(0.043)***}&  0.069&  0  &  0.305  \\\\\n",
      "CZ\n",
      "&  0.800&  \\footnotesize{(0.564)}&  -1.242&  \\footnotesize{(0.056)***}&  0.039&  $\\infty$  &  0  \\\\\n",
      "DE\n",
      "&  -0.002&  \\footnotesize{(0.273)}&  -1.225&  \\footnotesize{(0.056)***}&  0.040&  319.594  &  0  \\\\\n",
      "DK\n",
      "&  -1.646&  \\footnotesize{(0.085)***}&  -0.893&  \\footnotesize{(0.049)***}&  0.076&  0  &  0.286  \\\\\n",
      "ES\n",
      "&  0.380&  \\footnotesize{(0.142)***}&  -0.590&  \\footnotesize{(0.051)***}&  0.233&  $\\infty$  &  0.718  \\\\\n",
      "FI\n",
      "&  -1.319&  \\footnotesize{(0.068)***}&  -0.837&  \\footnotesize{(0.083)***}&  0.126&  0  &  0.353  \\\\\n",
      "FR\n",
      "&  -1.313&  \\footnotesize{(0.068)***}&  -0.857&  \\footnotesize{(0.084)***}&  0.125&  0  &  0.329  \\\\\n",
      "HK\n",
      "&  -1.392&  \\footnotesize{(0.144)***}&  -0.492&  \\footnotesize{(0.051)***}&  0.006&  0  &  0.945  \\\\\n",
      "HU\n",
      "&  0.335&  \\footnotesize{(0.511)}&  -1.138&  \\footnotesize{(0.056)***}&  0.027&  $\\infty$  &  0  \\\\\n",
      "IE\n",
      "&  -1.345&  \\footnotesize{(0.068)***}&  -0.842&  \\footnotesize{(0.081)***}&  0.125&  0  &  0.347  \\\\\n",
      "IT\n",
      "&  -1.316&  \\footnotesize{(0.068)***}&  -0.852&  \\footnotesize{(0.084)***}&  0.124&  0  &  0.335  \\\\\n",
      "JP\n",
      "&  -1.195&  \\footnotesize{(0.115)***}&  -0.715&  \\footnotesize{(0.058)***}&  0.047&  0  &  0.51  \\\\\n",
      "KR\n",
      "&  -1.503&  \\footnotesize{(0.145)***}&  -0.867&  \\footnotesize{(0.048)***}&  0.038&  0  &  0.317  \\\\\n",
      "LU\n",
      "&  -1.316&  \\footnotesize{(0.068)***}&  -0.852&  \\footnotesize{(0.084)***}&  0.124&  0  &  0.335  \\\\\n",
      "MX\n",
      "&  -1.235&  \\footnotesize{(0.080)***}&  -0.895&  \\footnotesize{(0.075)***}&  0.146&  0  &  0.284  \\\\\n",
      "MY\n",
      "&  -1.044&  \\footnotesize{(0.053)***}&  nan&  \\footnotesize{(nan)}&  nan&  0  &  nan  \\\\\n",
      "NL\n",
      "&  -1.314&  \\footnotesize{(0.068)***}&  -0.849&  \\footnotesize{(0.084)***}&  0.125&  0  &  0.338  \\\\\n",
      "NO\n",
      "&  -0.776&  \\footnotesize{(0.088)***}&  -1.197&  \\footnotesize{(0.068)***}&  0.086&  0.428  &  0  \\\\\n",
      "NZ\n",
      "&  -0.840&  \\footnotesize{(0.063)***}&  nan&  \\footnotesize{(nan)}&  nan&  0.349  &  nan  \\\\\n",
      "PH\n",
      "&  0.017&  \\footnotesize{(0.174)}&  -0.565&  \\footnotesize{(0.047)***}&  0.023&  $\\infty$  &  0.769  \\\\\n",
      "PL\n",
      "&  -1.645&  \\footnotesize{(0.119)***}&  -0.922&  \\footnotesize{(0.055)***}&  0.101&  0  &  0.251  \\\\\n",
      "PT\n",
      "&  -1.320&  \\footnotesize{(0.068)***}&  -0.843&  \\footnotesize{(0.084)***}&  0.127&  0  &  0.346  \\\\\n",
      "RU\n",
      "&  -0.545&  \\footnotesize{(0.177)***}&  -1.170&  \\footnotesize{(0.051)***}&  0.048&  0.813  &  0  \\\\\n",
      "SE\n",
      "&  2.087&  \\footnotesize{(0.574)***}&  -1.112&  \\footnotesize{(0.053)***}&  0.027&  $\\infty$  &  0  \\\\\n",
      "SG\n",
      "&  -2.277&  \\footnotesize{(0.583)***}&  -0.752&  \\footnotesize{(0.045)***}&  0.012&  0  &  0.459  \\\\\n",
      "TH\n",
      "&  -1.378&  \\footnotesize{(0.070)***}&  -0.718&  \\footnotesize{(0.066)***}&  0.082&  0  &  0.505  \\\\\n",
      "TR\n",
      "&  -1.508&  \\footnotesize{(0.135)***}&  -0.968&  \\footnotesize{(0.070)***}&  0.091&  0  &  0.186  \\\\\n",
      "TW\n",
      "&  -0.411&  \\footnotesize{(0.117)***}&  -1.019&  \\footnotesize{(0.051)***}&  0.026&  1.209  &  0  \\\\\n",
      "UK\n",
      "&  -0.293&  \\footnotesize{(0.308)}&  -1.092&  \\footnotesize{(0.056)***}&  0.028&  1.845  &  0  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  -0.780&  0.221&  -0.897&  0.063&  0.078&  0.423&  0.281\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -1.314&  0.104&  -0.862&  0.056&  0.079&  nan&  0.323\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  1.243&  0.348&  0.200&  0.015&  0.052 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n",
      "\n",
      "\n",
      "\n",
      "\\begin{table}[ht]\\centering\n",
      "\\caption{Threshold Autogregression Persistence Estimates for iPad Mini Devices, $d = 48$}\\label{regTAR: iPad Mini Delta48}\n",
      "\\begin{tabular}{ c r l r l c c c } \n",
      "\\hline\n",
      "\\hline\n",
      " \n",
      "& \\multicolumn{7}{c}{$i=$iPad Mini, $d=48$, No. Observations: 266}\\\\\n",
      "\\cline{2-8}\n",
      "\\\\[-0.1ex]\n",
      "Country\n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Inner} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Outer} \n",
      "& \\multicolumn{1}{c}{ Threshold} \n",
      "& \\multicolumn{1}{c}{ Half-life} \n",
      "& \\multicolumn{1}{c}{ Half-life} \\\\\n",
      "\n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \n",
      "& \\multicolumn{1}{c}{ SE} \n",
      "& \\multicolumn{1}{c}{ $c_i$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{0}$ } \n",
      "& \\multicolumn{1}{c}{ $\\hat{\\rho}_{1}$ } \\\\\n",
      "\\hline\\\\[-0.8ex] \n",
      "AE\n",
      "&  8.546&  \\footnotesize{(0.971)***}&  -0.808&  \\footnotesize{(0.040)***}&  0.003&  $\\infty$  &  0.388  \\\\\n",
      "AT\n",
      "&  -1.061&  \\footnotesize{(0.082)***}&  -1.546&  \\footnotesize{(0.068)***}&  0.100&  0  &  0  \\\\\n",
      "AU\n",
      "&  -1.204&  \\footnotesize{(0.063)***}&  nan&  \\footnotesize{(nan)}&  nan&  0  &  nan  \\\\\n",
      "BE\n",
      "&  -1.095&  \\footnotesize{(0.090)***}&  -1.528&  \\footnotesize{(0.066)***}&  0.082&  0  &  0  \\\\\n",
      "BR\n",
      "&  -1.098&  \\footnotesize{(0.181)***}&  -0.489&  \\footnotesize{(0.061)***}&  0.116&  0  &  0.953  \\\\\n",
      "CA\n",
      "&  -1.387&  \\footnotesize{(0.073)***}&  -0.923&  \\footnotesize{(0.067)***}&  0.086&  0  &  0.25  \\\\\n",
      "CZ\n",
      "&  0.374&  \\footnotesize{(0.363)}&  -1.392&  \\footnotesize{(0.055)***}&  0.033&  $\\infty$  &  0  \\\\\n",
      "DE\n",
      "&  -1.035&  \\footnotesize{(0.135)***}&  -1.624&  \\footnotesize{(0.098)***}&  0.078&  0  &  0  \\\\\n",
      "DK\n",
      "&  0.809&  \\footnotesize{(0.424)*}&  -1.273&  \\footnotesize{(0.056)***}&  0.028&  $\\infty$  &  0  \\\\\n",
      "ES\n",
      "&  -1.071&  \\footnotesize{(0.088)***}&  -1.515&  \\footnotesize{(0.065)***}&  0.094&  0  &  0  \\\\\n",
      "FI\n",
      "&  -1.119&  \\footnotesize{(0.094)***}&  -1.538&  \\footnotesize{(0.066)***}&  0.072&  0  &  0  \\\\\n",
      "FR\n",
      "&  -1.113&  \\footnotesize{(0.088)***}&  -1.524&  \\footnotesize{(0.067)***}&  0.090&  0  &  0  \\\\\n",
      "HK\n",
      "&  -0.074&  \\footnotesize{(0.045)}&  -1.461&  \\footnotesize{(0.091)***}&  0.024&  8.322  &  0  \\\\\n",
      "HU\n",
      "&  -1.052&  \\footnotesize{(0.063)***}&  nan&  \\footnotesize{(nan)}&  nan&  0  &  nan  \\\\\n",
      "IE\n",
      "&  -1.101&  \\footnotesize{(0.097)***}&  -1.527&  \\footnotesize{(0.065)***}&  0.077&  0  &  0  \\\\\n",
      "IT\n",
      "&  -1.095&  \\footnotesize{(0.090)***}&  -1.528&  \\footnotesize{(0.066)***}&  0.082&  0  &  0  \\\\\n",
      "JP\n",
      "&  1.340&  \\footnotesize{(0.600)**}&  -0.735&  \\footnotesize{(0.062)***}&  0.012&  $\\infty$  &  0.482  \\\\\n",
      "KR\n",
      "&  0.757&  \\footnotesize{(0.450)*}&  -0.689&  \\footnotesize{(0.055)***}&  0.021&  $\\infty$  &  0.548  \\\\\n",
      "LU\n",
      "&  -1.095&  \\footnotesize{(0.090)***}&  -1.528&  \\footnotesize{(0.066)***}&  0.082&  0  &  0  \\\\\n",
      "MX\n",
      "&  -1.244&  \\footnotesize{(0.069)***}&  -0.839&  \\footnotesize{(0.070)***}&  0.163&  0  &  0.35  \\\\\n",
      "MY\n",
      "&  -0.711&  \\footnotesize{(0.069)***}&  -1.350&  \\footnotesize{(0.077)***}&  0.151&  0.515  &  0  \\\\\n",
      "NL\n",
      "&  -1.095&  \\footnotesize{(0.090)***}&  -1.529&  \\footnotesize{(0.066)***}&  0.081&  0  &  0  \\\\\n",
      "NO\n",
      "&  -0.457&  \\footnotesize{(0.239)*}&  -1.277&  \\footnotesize{(0.068)***}&  0.038&  1.048  &  0  \\\\\n",
      "NZ\n",
      "&  -0.759&  \\footnotesize{(0.082)***}&  -1.352&  \\footnotesize{(0.093)***}&  0.062&  0.45  &  0  \\\\\n",
      "PH\n",
      "&  2.836&  \\footnotesize{(0.736)***}&  -0.846&  \\footnotesize{(0.061)***}&  0.011&  $\\infty$  &  0.342  \\\\\n",
      "PL\n",
      "&  -1.099&  \\footnotesize{(0.060)***}&  nan&  \\footnotesize{(nan)}&  nan&  0  &  nan  \\\\\n",
      "PT\n",
      "&  -1.119&  \\footnotesize{(0.094)***}&  -1.538&  \\footnotesize{(0.066)***}&  0.072&  0  &  0  \\\\\n",
      "RU\n",
      "&  -2.779&  \\footnotesize{(0.400)***}&  -1.326&  \\footnotesize{(0.053)***}&  0.026&  0  &  0  \\\\\n",
      "SE\n",
      "&  -1.052&  \\footnotesize{(0.073)***}&  -1.548&  \\footnotesize{(0.084)***}&  0.128&  0  &  0  \\\\\n",
      "SG\n",
      "&  -1.361&  \\footnotesize{(0.137)***}&  -0.969&  \\footnotesize{(0.064)***}&  0.028&  0  &  0.184  \\\\\n",
      "TH\n",
      "&  -1.038&  \\footnotesize{(0.074)***}&  -0.555&  \\footnotesize{(0.066)***}&  0.057&  0  &  0.79  \\\\\n",
      "TR\n",
      "&  0.281&  \\footnotesize{(0.320)}&  -1.173&  \\footnotesize{(0.062)***}&  0.045&  $\\infty$  &  0  \\\\\n",
      "TW\n",
      "&  -0.262&  \\footnotesize{(0.167)}&  -0.907&  \\footnotesize{(0.071)***}&  0.026&  2.106  &  0.269  \\\\\n",
      "UK\n",
      "&  -0.793&  \\footnotesize{(0.064)***}&  -1.542&  \\footnotesize{(0.073)***}&  0.130&  0.406  &  0  \\\\\n",
      "\\hline\n",
      "\\multicolumn{1}{l}{ Average }&  -0.395&  0.199&  -1.238&  0.067&  0.068&  1.274&  nan\\\\\n",
      "\\multicolumn{1}{l}{ Median }&  -1.056&  0.090&  -1.352&  0.066&  0.072&  nan&  nan\\\\\n",
      "\\multicolumn{1}{l}{ Std Dev }&  1.834&  0.214&  0.344&  0.012&  0.041 && \\\\\n",
      "\\hline\n",
      "\\hline\\\\[-0.8ex] \n",
      "\\multicolumn{4}{l}{ \\textit{Note: Standard Errors in Parenthesis} } &\n",
      "\\multicolumn{4}{r}{ \\textit{$^{*}$p$<$0.10; $^{**}$p$<$0.05; $^{***}$p$<$0.01} } \\\\\n",
      "\\multicolumn{8}{l}{ \\textit{Average and Median Half-Life calculated from Average and Median Estimates} } \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n",
      "\n",
      "\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rickw\\AppData\\Local\\Temp\\ipykernel_25180\\2733580979.py:47: RuntimeWarning: divide by zero encountered in log10\n",
      "  hl0 = np.log10(0.5) / np.log10(1+dffilter2['rho0'][c]) / (52 / Delta)\n",
      "C:\\Users\\rickw\\AppData\\Local\\Temp\\ipykernel_25180\\2733580979.py:118: RuntimeWarning: invalid value encountered in log10\n",
      "  '&  ' + str(\"%.3f\" % round(np.log10(0.5) / np.log10(1+np.nanmedian(coeffinner)) / (52 / Delta),3)) +\n"
     ]
    }
   ],
   "source": [
    "for i in [12, 24, 36, 48]:     \n",
    "    for j in ['iPad Pro Large','iPad Pro Small','iPad','iPad Mini']:\n",
    "        tarlatex(i, j)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "754f9f8f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4af27b5a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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