How to code half-life for higher order AP(p) model in python?

Question

I want to calculate the half-life for an higher order AR(4) model. Basically, I want to know the pace of mean reversion of Dutch GDP growth.

I have half-life python code for an AR(1) model

For your information: grw is a dataframe with index=dates and GDP Growth for the Dutch economy

# Halflife calculation
gdp_lags = np.roll(grw['Growth_yoy'],1)

gdp_lags[0] = 0

gdp_rets = grw['Growth_yoy'] - gdp_lags

gdp_rets[0] = 0

#adds intercept terms to X variable for regression
gdp_lags2 = sm.add_constant(gdp_lags)

model = sm.OLS(gdp_rets,gdp_lags2)
results = model.fit()

halflife = -np.log(2) / results.params[1]
print(halflife)

I would like to have python code for an AR(4) model.

Answer 1

Since you're already using statsmodels you may want to take a look at statsmodels - ARIMA, i.e.:

from statsmodels.tsa.arima_model import ARIMA

model = ARIMA(endog=grw['Growth_yoy'], order=(4, 0, 0))  # p=4, d=0, q=0 for AR(4)
fit = model.fit()
fit.summary()