difference-in-differences estimation and inference in Python
Project description
difference-in-differences estimation and inference for Python
For the following use cases
- Balanced panels, unbalanced panels & repeated cross-section
- Two + Multiple time periods
- Fixed + Staggered treatment timing
- Binary + Multi-Valued treatment
- Heterogeneous treatment effects & triple difference
see the Documentation for more details.
Installing
The latest release can be installed using pip
pip install differences
requires Python >= 3.9
Quick Start
ATTgt
the ATTgt class implements the estimation procedures suggested by Callaway and Sant'Anna (2021) , Sant'Anna and Zhao (2020) and the multi-valued treatment case discussed in Callaway, Goodman-Bacon & Sant'Anna (2021)
from differences import ATTgt, simulate_data
df = simulate_data()
att_gt = ATTgt(data=df, cohort_name='cohort')
att_gt.fit(formula='y')
att_gt.aggregate('event')
differences ATTgt benefited from
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file differences-0.2.0.tar.gz.
File metadata
- Download URL: differences-0.2.0.tar.gz
- Upload date:
- Size: 472.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
54390bfd3bb49a80154a47fe6932573e3ceb6924fc45f68fe5187c5cfede6cb6
|
|
| MD5 |
43ea46b43e28fd5f9cd2faa0eb886f84
|
|
| BLAKE2b-256 |
e2ea6edbc3ee817168ca2d7155811086c9e107eae03ec83d8f222bd52c93f278
|
File details
Details for the file differences-0.2.0-py3-none-any.whl.
File metadata
- Download URL: differences-0.2.0-py3-none-any.whl
- Upload date:
- Size: 383.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c83dca3359d5f599a8eac81199e987086d9466b8689bd3593f584b71c98f9e69
|
|
| MD5 |
ce931e80c06775446588a5bbcc5e1aca
|
|
| BLAKE2b-256 |
93c7f3e58610709703b416d2dbfe97e41e416a2141fb03a5453ee45a0723c44c
|
