# Ceteris Lab downloadable Python script
# Course: Fundamentals of Python for Financial Econometrics

import numpy as np, statsmodels.api as sm
rng=np.random.default_rng(19)
ability=rng.normal(size=300)
educ=.7*ability+rng.normal(size=300)
wage=2+1.2*educ+1.5*ability+rng.normal(size=300)
naive=sm.OLS(wage,sm.add_constant(educ)).fit()
controlled=sm.OLS(wage,sm.add_constant(np.c_[educ,ability])).fit()
print('naive',naive.params[1],'controlled',controlled.params[1])