topics_causal_inf
Topics Course Causal Inference Summer 2024
Science Score: 31.0%
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Low similarity (12.2%) to scientific vocabulary
Repository
Topics Course Causal Inference Summer 2024
Basic Info
- Host: GitHub
- Owner: buddejul
- License: mit
- Language: Python
- Default Branch: main
- Size: 2.24 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Topics Causal Inference
Replication repository for Causal Inference Topics Course Summer Semester 2024.
The repository follows the src/bld structure. All input (source) files generating
outputs are stored in the src folder. All generated output (see below for
instructions) will be stored in the bld folder. The project is completely replicable
based on the provided repository, with the exemption of the generated WGAN files
(details see below).
Instructions
To run the replication, Python has to be installed on the system.
First, after cloning the repository, create the virtual environment by typing
shell
mamba env create
in the shell. Note the current path of the shell needs to be the cloned repository.
For building the project, I use a workflow management system called
pytask. pytask facilitates
reproducible analysis by automatically discovering tasks and evaluating tasks only when
the code or dependencies have changed.
To build the project, first activate the virtual environment and then run the build:
shell
conda activate topics_causal_inf
pytask
However, it is advised to run the tasks collected by pytask in parallel by specifying
```shell pytask -n [n_workers]
Alternative: Starts os.cpu_count() - 1 workers.
pytask -n auto ```
With 11 workers on my private computer, building the full project takes about 90
minutes. To reduce runtime, the simulation settings in config.py might be changed.
In particular,
python
N_SIM = 40
N_SPLITS = 10
control the number of total simulation runs as well as the number of splits for the generic ML procedure.
Note that I generated the inputs to the WGAN-based simulations externally on a Google
Colab server. The results have to be stored under
src\topics_causal_inf\wgan_generated\. Alternatively,
DG_TO_RUN = ["standard", "wgan"] in task_wa_replication.py has to be changed (i.e.
remove "wgan").
Note: Sometimes the compilation of the LaTeX document fails on the first try, but
rerunning pytask then usually works. Else, this step can just be ignored.
Owner
- Name: Julian Budde
- Login: buddejul
- Kind: user
- Location: Bonn, Germany
- Repositories: 2
- Profile: https://github.com/buddejul
Econ PhD, Uni Bonn
Citation (CITATION)
@Unpublished{budde2024,
Title = "Topics Causal Inference",
Author = "Julian Budde",
Year = "2024",
Url = "https://github.com/buddejul/topics_causal_inf",
}
GitHub Events
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Dependencies
- actions/checkout v4 composite
- codecov/codecov-action v3 composite
- mamba-org/setup-micromamba v1 composite
- r-lib/actions/setup-tinytex v2 composite
- conda-lock
- ipykernel
- jupyterlab
- numpy
- pandas >=2.2
- pdbpp
- pip >=21.1
- plotly >=5.2.0,<6
- pre-commit
- pyreadr
- pytask >=0.5.0
- pytask-latex >=0.4.2
- pytask-parallel >=0.5.0
- pytask-r >=0.4.1
- pytest
- pytest-cov
- pytest-xdist
- python 3.12
- r-forcats
- r-plyr
- r-precommit
- r-yaml
- statsmodels