Python 中的虚拟变量回归

Question

I would like to run create a dummy variable regression in Python. So, I have a list of rates from 2000 to 2020 and I want to estimate the non-crisis (NC) and crisis (C) period alphas and betas from the following model incorporating dummy variables with respect to alphas and the coefficients of the risk factors:

Model

where Dnc,t is a dummy variable that takes a value of 1 for non-crisis periods and 0 otherwise and Dc,t is a dummy variable that takes a value of 1 for crisis periods and 0 otherwise. Now, I would like to run this regression in python.

Answer 1

Assuming that you're looking for Logistic Regression and you already have your X and Y variables in Pandas dataframes

from sklearn.linear_model import LogisticRegression
X, y = Your_Predictor_Variables, Your_Target_Variable
clf = LogisticRegression(random_state=0).fit(X, y)

print(clf.coef_, clf.intercept_)