Python implementation of the fixed effects estimator
Description
- Includes two methods, fit and predict. Computes and stores coefficients of regressors, intercept and unobserved heterogenity intercepts. Other stats like standard errors or p-values are not included
- Sklearn-based
- Uses sklearn BaseEstimator and RegressorMixin as base classes
- Compatibility with cross validation classes may not work (not tested)
- Implements FE à la Stata, basically ensuring that the sum of unobserved heterogeneity intercepts sum to 0, which eases interpretation. See details here