@@ -225,7 +225,7 @@ First, we store parameters in a `namedtuple`:
225225
226226```{code-cell} ipython3
227227# Create the rational expectation version of Cagan model in finite time
228- CaganREE = namedtuple("ConsumptionSmoothing ",
228+ CaganREE = namedtuple("CaganREE ",
229229 ["m0", "T", "μ_seq", "α", "δ", "π_end"])
230230
231231def create_cagan_model(m0, α, T, μ_seq):
@@ -255,8 +255,8 @@ Now we can solve the model to compute $\pi_t$, $m_t$ and $p_t$ for $t =1, \ldots
255255
256256```{code-cell} ipython3
257257def solve(model):
258- m0, T, π_end, μ_seq, α, δ = model.m0, model.T, model.π_end, model.μ_seq, model.α, model.δ
259-
258+ model_params = model.m0, model.T, model.π_end, model.μ_seq, model.α, model.δ
259+ m0, T, π_end, μ_seq, α, δ = model_params
260260 A1 = np.eye(T+1, T+1) - δ * np.eye(T+1, T+1, k=1)
261261 A2 = np.eye(T+1, T+1) - np.eye(T+1, T+1, k=-1)
262262
@@ -451,22 +451,24 @@ T_seq = range(T+2)
451451fig, ax = plt.subplots(2, 3, figsize=[10,5], dpi=200)
452452
453453ax[0,0].plot(T_seq[:-1], μ_seq_2)
454+ ax[0,0].set_ylabel(r'$\mu$')
455+
454456ax[0,1].plot(T_seq, π_seq_2)
457+ ax[0,1].set_ylabel(r'$\pi$')
458+
455459ax[0,2].plot(T_seq, m_seq_2_regime1 - p_seq_2_regime1)
460+ ax[0,2].set_ylabel(r'$m - p$')
461+
456462ax[1,0].plot(T_seq, m_seq_2_regime1,
457463 label='Smooth $m_{T_1}$')
458464ax[1,0].plot(T_seq, m_seq_2_regime2,
459465 label='Jumpy $m_{T_1}$')
466+ ax[1,0].set_ylabel(r'$m$')
467+
460468ax[1,1].plot(T_seq, p_seq_2_regime1,
461469 label='Smooth $m_{T_1}$')
462470ax[1,1].plot(T_seq, p_seq_2_regime2,
463471 label='Jumpy $m_{T_1}$')
464-
465-
466- ax[0,0].set_ylabel(r'$\mu$')
467- ax[0,1].set_ylabel(r'$\pi$')
468- ax[0,2].set_ylabel(r'$m - p$')
469- ax[1,0].set_ylabel(r'$m$')
470472ax[1,1].set_ylabel(r'$p$')
471473
472474for i in range(2):
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