PyFixest 0.10.7

Adds basic support for event study estimation via two-way fixed effects and Gardner's two-stage "Did2s" approach. This is a beta version and experimental. Further updates (i.e. proper event studies vs "only" ATTs) and a more flexible did2s front end will follow in a release in the near future =)

%load_ext autoreload
%autoreload 2

from pyfixest.experimental.did import event_study
from pyfixest.summarize import etable
import pandas as pd
df_het = pd.read_csv("pyfixest/experimental/data/df_het.csv")

fit_twfe = event_study(
    data = df_het,
    yname = "dep_var",
    idname= "state",
    tname = "year",
    gname = "g",
    estimator = "twfe"
)

fit_did2s = event_study(
    data = df_het,
    yname = "dep_var",
    idname= "state",
    tname = "year",
    gname = "g",
    estimator = "did2s"
)

etable([fit_twfe, fit_did2s])
# | Coefficient   | est1             | est2             |
# |:--------------|:-----------------|:-----------------|
# | ATT           | 2.135*** (0.044) | 2.152*** (0.048) |
# Significance levels: * p < 0.05, ** p < 0.01, *** p < 0.001