Causalforests and high volume panel data
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Description
I am wondering what is the correct approach when using DoWhy/EconML with Causal Forest on Panel data with Fixed time and firm effects or fixed time and industry effects after being sure that these effects exist (Hausman test et al). Can one just use time and firm/industry ID as covariates or would one need to include hot encodings / dummies, which would lead to many .... (3500 firms, 49 industries, 12 years in my case, 32000 "observations"). Please advise!
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Research direction
The issue names no file, test, or entry point to investigate. First clarify whether the expected outcome is documentation or a library change, then identify the relevant EconML causal-forest documentation and tests; done should explain the supported treatment of panel fixed effects and high-volume categorical features.
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Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100