def get_table3(df):
### regressions:
rslt = smf.ols(formula="stdgrade ~ treat + pol1+ pol1t",
data=df,
weights=df["kwgt"]).fit(
cov_type='cluster',
cov_kwds={'groups': df["studentid"]})
rslt1 = rslt
formula2 = "stdgrade ~ treat + treatmentvol + treatmentfor + volcourse + forcourse + pol1 + pol1t + pol1vol + pol1tvol + pol1for + pol1tfor"
rslt = smf.ols(formula=formula2, data=df, weights=df["kwgt"]).fit(
cov_type='cluster', cov_kwds={'groups': df["studentid"]})
rslt2 = rslt
### Table stargazer:
stargazer = Stargazer([rslt1, rslt2])
stargazer.custom_columns(["column 1", "column 4"], [1, 1])
stargazer.title("Table 3 - Effects on standardized grades")
stargazer.show_model_numbers(False)
stargazer.significant_digits(2)
stargazer.covariate_order(["treat", "treatmentvol", "treatmentfor"])
stargazer.rename_covariates({
"treat":
"1st-year GPA is below 7",
"treatmentvol":
"Attendance is voluntary x treatment",
"treatmentfor":
"Absence is penalized x treatment"
})
stargazer.show_degrees_of_freedom(False)
stargazer.add_line('Fixed Effects', ['No', 'No'])
return stargazer
x_withfemale = sm.add_constant(x2)
model1 = sm.OLS(y, x).fit()
model2 = sm.OLS(y, x_withfemale).fit()
model1.summary()
model2.summary()
# =============================================================================
# STARGAZER MODEL OUTPUTS
# =============================================================================
from stargazer.stargazer import Stargazer
stargazer = Stargazer([model1, model2])
stargazer.custom_columns(['Base Model', 'Spesified Model'], [1, 1])
stargazer.significant_digits(2)
stargazer.covariate_order([
'const', 'propwomen', 'oppospower', 'gdpcap', 'sepowerdist', 'youthunemp'
])
stargazer.rename_covariates({
'const': 'Constant',
'oppospower': 'Opposition Power',
'gdpcap': 'GDP($)',
'sepowerdist': 'Class Political Power',
'youthunemp': 'Unemployed Youth %',
'propwomen': 'Female Property Rights'
})
stargazer.cov_spacing = 3
print(stargazer.render_latex())
