# Generate shocks if stochastic

if σ > 0:

np.random.seed(seed)

ϵ = np.random.normal(0, 1, n)

rng = np.random.default_rng(seed)

ϵ = rng.normal(0, 1, n)

# Simulate forward

for t in range(2, n):

sam_t = LinearStateSpace(A, C, G, mu_0=μ_0)

x, y = sam_t.simulate(ts_length=n)

rng = np.random.default_rng()

x, y = sam_t.simulate(ts_length=n, random_state=rng)

fig, axes = plt.subplots(3, 1, sharex=True, figsize=(12, 8))

titles = ["Output ($Y_t$)", "Consumption ($C_t$)", "Investment ($I_t$)"]

except ValueError:

print("Stationary distribution does not exist")

np.random.seed(seed)

x, y = self.simulate(ts_length)

rng = np.random.default_rng(seed)

x, y = self.simulate(ts_length, random_state=rng)

fig, axes = plt.subplots(3, 1, sharex=True, figsize=(12, 8))

titles = ["Output ($Y_t$)",