Applied Statistics: Causal Inference in Economic Analysis and Machine Learning Methods
In this section you will find a repository of the Applied Statistics course I took as an undergraduate at PUCP. We develop a series of proyects and replications of papers in R, Julia and Phyton using Machine Learnign in Causal Inference. Click here to be redirected to my GitHub repository.
Here you can find a resume of the methods and models available:
Methods available:
- Data splitting
- Partialling out
- Cross validation
- Boostraping
Models available:
- OLS (with RCT data)
- IRA, CRA
- Lasso
- Dobble lasso
- Tree and Random Forest
- Causal Tree & Random Forest
- Debiased Machine Learning