Diff in diff.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.linear_model import LinearRegression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data link  - http://dss.princeton.edu/training/Panel101.dta"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Stata version of the codes below - http://www.princeton.edu/~otorres/DID101.pdf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Treatment introducted in 1994 to countries E, F, G. \n",
    "Control countries - A, B, C, D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Reading data\n",
    "df = pd.read_stata('Panel101.dta')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>year</th>\n",
       "      <th>y</th>\n",
       "      <th>y_bin</th>\n",
       "      <th>x1</th>\n",
       "      <th>x2</th>\n",
       "      <th>x3</th>\n",
       "      <th>opinion</th>\n",
       "      <th>op</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>1990</td>\n",
       "      <td>1.342788e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.277904</td>\n",
       "      <td>-1.107956</td>\n",
       "      <td>0.282554</td>\n",
       "      <td>Str agree</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A</td>\n",
       "      <td>1991</td>\n",
       "      <td>-1.899661e+09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.320685</td>\n",
       "      <td>-0.948720</td>\n",
       "      <td>0.492538</td>\n",
       "      <td>Disag</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A</td>\n",
       "      <td>1992</td>\n",
       "      <td>-1.123436e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.363466</td>\n",
       "      <td>-0.789484</td>\n",
       "      <td>0.702523</td>\n",
       "      <td>Disag</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A</td>\n",
       "      <td>1993</td>\n",
       "      <td>2.645775e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.246144</td>\n",
       "      <td>-0.885533</td>\n",
       "      <td>-0.094391</td>\n",
       "      <td>Disag</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A</td>\n",
       "      <td>1994</td>\n",
       "      <td>3.008335e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.424623</td>\n",
       "      <td>-0.729768</td>\n",
       "      <td>0.946131</td>\n",
       "      <td>Disag</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country  year             y  y_bin        x1        x2        x3    opinion  \\\n",
       "0       A  1990  1.342788e+09    1.0  0.277904 -1.107956  0.282554  Str agree   \n",
       "1       A  1991 -1.899661e+09    0.0  0.320685 -0.948720  0.492538      Disag   \n",
       "2       A  1992 -1.123436e+07    0.0  0.363466 -0.789484  0.702523      Disag   \n",
       "3       A  1993  2.645775e+09    1.0  0.246144 -0.885533 -0.094391      Disag   \n",
       "4       A  1994  3.008335e+09    1.0  0.424623 -0.729768  0.946131      Disag   \n",
       "\n",
       "    op  \n",
       "0  1.0  \n",
       "1  0.0  \n",
       "2  0.0  \n",
       "3  0.0  \n",
       "4  0.0  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sample data\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Adding time variable, treatment occured in 1994 ; segmenting anything before 1994 as pre-period (0) \n",
    "df['time'] = np.where(df['year'] >= 1994, 1,0 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>year</th>\n",
       "      <th>y</th>\n",
       "      <th>y_bin</th>\n",
       "      <th>x1</th>\n",
       "      <th>x2</th>\n",
       "      <th>x3</th>\n",
       "      <th>opinion</th>\n",
       "      <th>op</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>1990</td>\n",
       "      <td>1.342788e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.277904</td>\n",
       "      <td>-1.107956</td>\n",
       "      <td>0.282554</td>\n",
       "      <td>Str agree</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A</td>\n",
       "      <td>1991</td>\n",
       "      <td>-1.899661e+09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.320685</td>\n",
       "      <td>-0.948720</td>\n",
       "      <td>0.492538</td>\n",
       "      <td>Disag</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A</td>\n",
       "      <td>1992</td>\n",
       "      <td>-1.123436e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.363466</td>\n",
       "      <td>-0.789484</td>\n",
       "      <td>0.702523</td>\n",
       "      <td>Disag</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A</td>\n",
       "      <td>1993</td>\n",
       "      <td>2.645775e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.246144</td>\n",
       "      <td>-0.885533</td>\n",
       "      <td>-0.094391</td>\n",
       "      <td>Disag</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A</td>\n",
       "      <td>1994</td>\n",
       "      <td>3.008335e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.424623</td>\n",
       "      <td>-0.729768</td>\n",
       "      <td>0.946131</td>\n",
       "      <td>Disag</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country  year             y  y_bin        x1        x2        x3    opinion  \\\n",
       "0       A  1990  1.342788e+09    1.0  0.277904 -1.107956  0.282554  Str agree   \n",
       "1       A  1991 -1.899661e+09    0.0  0.320685 -0.948720  0.492538      Disag   \n",
       "2       A  1992 -1.123436e+07    0.0  0.363466 -0.789484  0.702523      Disag   \n",
       "3       A  1993  2.645775e+09    1.0  0.246144 -0.885533 -0.094391      Disag   \n",
       "4       A  1994  3.008335e+09    1.0  0.424623 -0.729768  0.946131      Disag   \n",
       "\n",
       "    op  time  \n",
       "0  1.0     0  \n",
       "1  0.0     0  \n",
       "2  0.0     0  \n",
       "3  0.0     0  \n",
       "4  0.0     1  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[A, B, C, D, E, F, G]\n",
       "Categories (7, object): [A < B < C < D < E < F < G]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.country.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "#creating a treated variable to identify target (1) and the holdout (0) groups\n",
    "df['treated'] = np.where(df['country'] >= 'E' , 1,0 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>year</th>\n",
       "      <th>y</th>\n",
       "      <th>y_bin</th>\n",
       "      <th>x1</th>\n",
       "      <th>x2</th>\n",
       "      <th>x3</th>\n",
       "      <th>opinion</th>\n",
       "      <th>op</th>\n",
       "      <th>time</th>\n",
       "      <th>treated</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>G</td>\n",
       "      <td>1995</td>\n",
       "      <td>1.323696e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.087186</td>\n",
       "      <td>-1.409817</td>\n",
       "      <td>2.829808</td>\n",
       "      <td>Str disag</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>G</td>\n",
       "      <td>1996</td>\n",
       "      <td>2.545242e+08</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.781075</td>\n",
       "      <td>-1.328000</td>\n",
       "      <td>4.278224</td>\n",
       "      <td>Str agree</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>G</td>\n",
       "      <td>1997</td>\n",
       "      <td>3.297033e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.257879</td>\n",
       "      <td>-1.577367</td>\n",
       "      <td>4.587326</td>\n",
       "      <td>Disag</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>G</td>\n",
       "      <td>1998</td>\n",
       "      <td>3.011821e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.242777</td>\n",
       "      <td>-1.601218</td>\n",
       "      <td>6.113762</td>\n",
       "      <td>Disag</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>G</td>\n",
       "      <td>1999</td>\n",
       "      <td>3.296283e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.234200</td>\n",
       "      <td>-1.621761</td>\n",
       "      <td>7.168922</td>\n",
       "      <td>Disag</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   country  year             y  y_bin        x1        x2        x3  \\\n",
       "65       G  1995  1.323696e+09    1.0  1.087186 -1.409817  2.829808   \n",
       "66       G  1996  2.545242e+08    1.0  0.781075 -1.328000  4.278224   \n",
       "67       G  1997  3.297033e+09    1.0  1.257879 -1.577367  4.587326   \n",
       "68       G  1998  3.011821e+09    1.0  1.242777 -1.601218  6.113762   \n",
       "69       G  1999  3.296283e+09    1.0  1.234200 -1.621761  7.168922   \n",
       "\n",
       "      opinion   op  time  treated  \n",
       "65  Str disag  0.0     1        1  \n",
       "66  Str agree  1.0     1        1  \n",
       "67      Disag  0.0     1        1  \n",
       "68      Disag  0.0     1        1  \n",
       "69      Disag  0.0     1        1  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "#creating interaction variable\n",
    "df['did'] = df['time'] * df['treated']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
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       "      <th>country</th>\n",
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       "      <th>x1</th>\n",
       "      <th>x2</th>\n",
       "      <th>x3</th>\n",
       "      <th>opinion</th>\n",
       "      <th>op</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>1990</td>\n",
       "      <td>1.342788e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.277904</td>\n",
       "      <td>-1.107956</td>\n",
       "      <td>0.282554</td>\n",
       "      <td>Str agree</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A</td>\n",
       "      <td>1991</td>\n",
       "      <td>-1.899661e+09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.320685</td>\n",
       "      <td>-0.948720</td>\n",
       "      <td>0.492538</td>\n",
       "      <td>Disag</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A</td>\n",
       "      <td>1992</td>\n",
       "      <td>-1.123436e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.363466</td>\n",
       "      <td>-0.789484</td>\n",
       "      <td>0.702523</td>\n",
       "      <td>Disag</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A</td>\n",
       "      <td>1993</td>\n",
       "      <td>2.645775e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.246144</td>\n",
       "      <td>-0.885533</td>\n",
       "      <td>-0.094391</td>\n",
       "      <td>Disag</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A</td>\n",
       "      <td>1994</td>\n",
       "      <td>3.008335e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.424623</td>\n",
       "      <td>-0.729768</td>\n",
       "      <td>0.946131</td>\n",
       "      <td>Disag</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country  year             y  y_bin        x1        x2        x3    opinion  \\\n",
       "0       A  1990  1.342788e+09    1.0  0.277904 -1.107956  0.282554  Str agree   \n",
       "1       A  1991 -1.899661e+09    0.0  0.320685 -0.948720  0.492538      Disag   \n",
       "2       A  1992 -1.123436e+07    0.0  0.363466 -0.789484  0.702523      Disag   \n",
       "3       A  1993  2.645775e+09    1.0  0.246144 -0.885533 -0.094391      Disag   \n",
       "4       A  1994  3.008335e+09    1.0  0.424623 -0.729768  0.946131      Disag   \n",
       "\n",
       "    op  time  treated  did  \n",
       "0  1.0     0        0    0  \n",
       "1  0.0     0        0    0  \n",
       "2  0.0     0        0    0  \n",
       "3  0.0     0        0    0  \n",
       "4  0.0     1        0    0  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Splitting variables into dependent (x) and independent (y) variables\n",
    "x = df.iloc[:,9:12]\n",
    "y = df.iloc[:,2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = LinearRegression().fit(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 2.28945465e+09,  1.77596967e+09, -2.51951163e+09])"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.coef_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Model to get the summary statistics\n",
    "import statsmodels.api as sm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:                      y   R-squared:                       0.083\n",
      "Model:                            OLS   Adj. R-squared:                  0.041\n",
      "Method:                 Least Squares   F-statistic:                     1.984\n",
      "Date:                Tue, 06 Oct 2020   Prob (F-statistic):              0.125\n",
      "Time:                        21:54:12   Log-Likelihood:                -1623.7\n",
      "No. Observations:                  70   AIC:                             3255.\n",
      "Df Residuals:                      66   BIC:                             3264.\n",
      "Df Model:                           3                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==============================================================================\n",
      "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "const       3.581e+08   7.38e+08      0.485      0.629   -1.12e+09    1.83e+09\n",
      "time        2.289e+09   9.53e+08      2.402      0.019    3.87e+08    4.19e+09\n",
      "treated     1.776e+09   1.13e+09      1.575      0.120   -4.75e+08    4.03e+09\n",
      "did         -2.52e+09   1.46e+09     -1.731      0.088   -5.43e+09    3.87e+08\n",
      "==============================================================================\n",
      "Omnibus:                        6.182   Durbin-Watson:                   1.615\n",
      "Prob(Omnibus):                  0.045   Jarque-Bera (JB):                7.779\n",
      "Skew:                          -0.304   Prob(JB):                       0.0205\n",
      "Kurtosis:                       4.516   Cond. No.                         7.26\n",
      "==============================================================================\n",
      "\n",
      "Warnings:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\sadha\\Anaconda3\\lib\\site-packages\\numpy\\core\\fromnumeric.py:2389: FutureWarning: Method .ptp is deprecated and will be removed in a future version. Use numpy.ptp instead.\n",
      "  return ptp(axis=axis, out=out, **kwargs)\n"
     ]
    }
   ],
   "source": [
    "X2 = sm.add_constant(x)\n",
    "est = sm.OLS(y, X2)\n",
    "est2 = est.fit()\n",
    "print(est2.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Coefficients of the variable did provides the true lift of the treatment. In this case, the treatment has a negative performance on the outcome variable."
   ]
  }
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