@@ -303,24 +303,6 @@ The next figure plots the supply of capital, as in [](saving_log_2_olg), as well
303303
304304(For the special case of log utility, supply does not depend on the interest rate, so we have a constant function.)
305305
306- ``` {code-cell} ipython3
307- R_vals = np.linspace(0.3, 1)
308- α, β = 0.5, 0.9
309- w = 2.0
310-
311- fig, ax = plt.subplots()
312-
313- ax.plot(R_vals, capital_demand(R_vals, α),
314- label="aggregate demand")
315- ax.plot(R_vals, capital_supply(R_vals, β, w),
316- label="aggregate supply")
317-
318- ax.set_xlabel("$R_{t+1}$")
319- ax.set_ylabel("$k_{t+1}$")
320- ax.legend()
321- plt.show()
322- ```
323-
324306## Equilibrium
325307
326308In this section we derive equilibrium conditions and investigate an example.
@@ -409,15 +391,7 @@ ax.plot(R_vals, capital_supply(R_vals, β, w),
409391R_e = equilibrium_R_log_utility(α, β, w)
410392k_e = (β / (1 + β)) * w
411393
412- ax.plot(R_e, k_e, 'go', ms=6, alpha=0.6)
413-
414- ax.annotate(r'equilibrium',
415- xy=(R_e, k_e),
416- xycoords='data',
417- xytext=(0, 60),
418- textcoords='offset points',
419- fontsize=12,
420- arrowprops=dict(arrowstyle="->"))
394+ ax.plot(R_e, k_e, 'o',label='equilibrium')
421395
422396ax.set_xlabel("$R_{t+1}$")
423397ax.set_ylabel("$k_{t+1}$")
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