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update captions for graphs in lectures
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lectures/laffer_adaptive.md

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@@ -445,6 +445,15 @@ def draw_iterations(π0s, model, line_params, π_bars, num_steps):
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Let's simulate the result generated by varying the initial $\pi_{-1}$ and corresponding $p_{-1}$
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```{code-cell} ipython3
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---
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mystnb:
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figure:
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caption: Starting from different initial values of $\pi_0$, paths of $m_t$ (top
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panel, log scale for $m$), $p_t$ (second panel, log scale for $p$), $\pi_t$ (third panel), and $\mu_t$ (bottom
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panel)
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name: pi0_path
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width: 500px
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---
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πs = np.linspace(π_l, π_u, 10)
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line_params = {'lw': 1.5,

lectures/money_inflation_nonlinear.md

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@@ -402,6 +402,16 @@ def draw_iterations(p0s, model, line_params, p0_bars, num_steps):
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```
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```{code-cell} ipython3
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---
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mystnb:
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figure:
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caption: Starting from different initial values of $p_0$, paths of $m_t$ (top
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panel, log scale for $m$), $p_t$ (second panel, log scale for $p$), $\pi_t$ (third panel), and $\mu_t$ (bottom
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panel)
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name: p0_path_nonlin
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width: 500px
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---
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# Generate a sequence from p0_l to p0_u
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p0s = np.arange(p0_l, p0_u, 0.1)
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@@ -419,7 +429,7 @@ THE LECTURE MONEY_INFLATION.MD
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IF WE ZOOM, I CAN EXPLAIN QUICKLY.
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Staring at the paths of price levels in {numref}`p0_pathnonlin` show indicate that almost all paths converge to the **higher** inflation tax rate displayed in the stationary state Laffer curve. %displayed in figure {numref}`infl_tax`.
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Staring at the paths of price levels in {numref}`p0_path_nonlin` show indicate that almost all paths converge to the **higher** inflation tax rate displayed in the stationary state Laffer curve. %displayed in figure {numref}`infl_tax`.
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Thus, we have indeed discovered what we earlier called "perverse" dynamics under rational expectations in which the system converges to the higher of two possible stationary inflation tax rates.
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