[Feature Request]: Using different covariates

### Describe the feature you want to propose or implement

Hello, I’ve encountered a problem. The variable y is a firm-year indicator, and x is a region-year indicator. I want to control for region fixed effects and time fixed effects. However, if I use a nonlinear machine learning method such as random forests, the interaction between region and time may remove most of the information in x when predicting it, which is clearly unreasonable. Therefore, I’d like to ask whether it’s acceptable to use different covariates for the outcome equation and the treatment equation. Alternatively, do you have a more reasonable approach? I look forward to your response. Thank you!

### Propose a possible solution or implementation

_No response_

### Did you consider alternatives to the proposed solution. If yes, please describe

_No response_

### Comments, context or references

_No response_