castle_2.py

import numpy as np 
import pandas as pd 
import statsmodels.api as sm 
import statsmodels.formula.api as smf 
from itertools import combinations 
import plotnine as p

# read data
import ssl
ssl._create_default_https_context = ssl._create_unverified_context
def read_data(file): 
	return pd.read_stata("https://github.com/scunning1975/mixtape/raw/master/" + file)


castle['time_til'] = castle['year'] - castle['treatment_date']

castle['lead1'] = castle['time_til'] == -1
castle['lead2'] = castle['time_til'] == -2
castle['lead3'] = castle['time_til'] == -3
castle['lead4'] = castle['time_til'] == -4
castle['lead5'] = castle['time_til'] == -5
castle['lead6'] = castle['time_til'] == -6
castle['lead7'] = castle['time_til'] == -7
castle['lead8'] = castle['time_til'] == -8
castle['lead9'] = castle['time_til'] == -9
castle['lag0'] = castle['time_til'] == 0 
castle['lag1'] = castle['time_til'] == 1 
castle['lag2'] = castle['time_til'] == 2 
castle['lag3'] = castle['time_til'] == 3 
castle['lag4'] = castle['time_til'] == 4 
castle['lag5'] = castle['time_til'] == 5 

formula = "l_homicide ~ r20001 + r20002 + r20003 + r20011 + r20012 + r20013 + r20021 + r20022 + r20023 + r20031 + r20032 + r20033 + r20041 + r20042 + r20043 + r20051 + r20052 + r20053 + r20061 + r20062 + r20063 + r20071 + r20072 + r20073 + r20081 + r20082 + r20083 + r20091 + r20092 + r20093 + lead1 + lead2 + lead3 + lead4 + lead5 + lead6 + lead7 + lead8 + lead9 + lag1 + lag2 + lag3 + lag4 + lag5 + C(year) + C(state)"

event_study_formula = smf.wls(formula,
            data = castle, weights = castle['popwt']).fit(cov_type='cluster', cov_kwds={'groups':castle['sid']})
event_study_formula.summary()