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6 changes: 6 additions & 0 deletions .translate/state/cass_koopmans_1.md.yml
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@@ -0,0 +1,6 @@
source-sha: bce028b3121056e0bbb7b57e48b356aa8da050d2
synced-at: "2026-07-18"
model: claude-sonnet-5
mode: RESYNC
section-count: 9
tool-version: 0.17.0
29 changes: 23 additions & 6 deletions lectures/cass_koopmans_1.md
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Expand Up @@ -9,6 +9,23 @@ kernelspec:
display_name: Python 3 (ipykernel)
language: python
name: python3
translation:
title: Cass-Koopmans模型
headings:
Overview: 概述
The Model: 模型
'The Model::Digression: Aggregation Theory': 插话:聚合理论
'The Model::Digression: Aggregation Theory::An Economy': 一个经济体
Planning Problem: 规划问题
Planning Problem::Useful Properties of Linearly Homogeneous Production Function: 线性齐次生产函数的有用性质
Planning Problem::First-order necessary conditions: 一阶必要条件
Shooting Algorithm: 打靶算法
Setting Initial Capital to Steady State Capital: 将初始资本设定为稳态资本
A Turnpike Property: 收费公路性质(Turnpike property)
A Limiting Infinite Horizon Economy: 极限无限期经济
Stable Manifold and Phase Diagram: 稳定流形和相图
Concluding Remarks: 结论
Concluding Remarks::Exercise: 练习
---

(cass_koopmans_1)=
Expand Down Expand Up @@ -570,8 +587,8 @@ plt.show()
@jit
def bisection(pp, c0, k0, T=10, tol=1e-4, max_iter=500, k_ter=0, verbose=True):

# 设置初始边界
c0_upper = pp.f(k0)
# 猜测c0的初始边界
c0_upper = pp.f(k0) + (1 - pp.δ) * k0
Comment on lines +590 to +591
c0_lower = 0

i = 0
Expand Down Expand Up @@ -659,7 +676,7 @@ $$
1=\beta \frac{u'(\bar{C})}{u'(\bar{C})}[f'(\bar{K})+(1-\delta)]
$$

定义 $\beta = \frac{1}{1+\rho}$,得到
定义 $\beta = \frac{1}{1+\rho}$,并化简得到

$$
1+\rho = 1[f'(\bar{K}) + (1-\delta)]
Expand Down Expand Up @@ -842,7 +859,7 @@ plot_saving_rate(pp, 0.3, k_ss/3, [250, 150, 75, 50], k_ss=k_ss)
合适的做法是将终端条件{eq}`constraint4`替换为

$$
\lim_{T \rightarrow +\infty} \beta^T u'(C_T) K_{T+1} = 0
\lim_{T \rightarrow +\infty} \beta^T u'(C_T) K_{T+1} = 0 ,
$$
Comment on lines 861 to 863

收敛到最优稳态的路径将满足以上条件。
Expand Down Expand Up @@ -971,11 +988,11 @@ c_vec2, k_vec2 = bisection(pp, 1e-3, 1e-3, T=200, k_ter=Ks)

* 蓝线表示方程 {eq}`eq:tildeC` 所描述的不动点 $C = \tilde C (K)$ 的图像。
* 红线表示方程 {eq}`eq:tildeK` 所描述的不动点 $K = \tilde K(C)$ 的图像。
* 绿线表示从时间0时任意 $K_0$ 开始收敛到稳态的稳定流形
* 绿线表示从时间0时任意 $K_0$ 开始收敛到稳态所描绘出的稳定路径
* 对于给定的 $K_0$,射击算法将 $C_0$ 设置为绿线上的坐标,以启动一条收敛到最优稳态的路径。
Comment on lines 989 to 992
* 绿线上的箭头显示了动态方程{eq}`eq:systemdynamics`推动连续对 $(K_{t+1}, C_t)$ 的方向。

除了显示三条曲线外,图{numref}`stable_manifold`还绘制了箭头来指示当给定 $K_0$ 时,$C_0$不在绿线所示稳定流形上时,动态方程{eq}`eq:systemdynamics`驱动系统的方向
除了这三条曲线外,图{numref}`stable_manifold`还绘制了箭头,指示当给定 $K_0$ 时,$C_0$ 不在绿线所示的稳定流形上,动态方程{eq}`eq:systemdynamics`将把系统驱动向何处

* 如果对给定的$K_0$,$C_0$设置在绿线以下,则积累了过多的资本

Expand Down
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