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Merged
mmcky merged 1 commit into from
Jul 22, 2026
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[action-translation] resync: wealth_dynamics.md #193

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6 changes: 3 additions & 3 deletions .translate/state/wealth_dynamics.md.yml
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
source-sha: 39b39c9bcb4363353b27e2180f12551fbd3a6e9f
synced-at: "2026-07-18"
source-sha: fccf5a9fd50129b3b03a4fd7b5d04976ac51e3a5
synced-at: "2026-07-21"
model: claude-sonnet-5
mode: RESYNC
section-count: 6
tool-version: 0.17.0
tool-version: 0.20.0
16 changes: 10 additions & 6 deletions lectures/wealth_dynamics.md
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Expand Up @@ -109,13 +109,16 @@ from numba.experimental import jitclass

上面已经导入的[QuantEcon.py](https://github.com/QuantEcon/QuantEcon.py)包含了计算洛伦兹曲线的函数。

举例说明，假设以下数据代表了10,000个家庭的财富分布
举例说明，假设

```{code-cell} ipython3
rng = np.random.default_rng()
n = 10_000 # 样本大小
w = np.exp(np.random.randn(n)) # 生成对数正态分布的随机样本
w = np.exp(rng.standard_normal(n)) # 生成对数正态分布的随机样本
```

是代表10,000个家庭财富的数据。

我们可以按如下方式计算并绘制洛伦兹曲线：

```{code-cell} ipython3
Expand Down Expand Up @@ -147,7 +150,7 @@ a_vals = (1, 2, 5) # 帕累托分布的尾部指数
n = 10_000 # 每个样本的大小
fig, ax = plt.subplots()
for a in a_vals:
u = np.random.uniform(size=n)
u = rng.uniform(size=n)
y = u**(-1/a) # 服从尾部指数为a的帕累托分布
f_vals, l_vals = qe.lorenz_curve(y)
ax.plot(f_vals, l_vals, label=f'$a = {a}$')
Expand Down Expand Up @@ -184,7 +187,7 @@ n = 100

fig, ax = plt.subplots()
for a in a_vals:
y = np.random.weibull(a, size=n)
y = rng.weibull(a, size=n)
ginis.append(qe.gini_coefficient(y))
ginis_theoretical.append(1 - 2**(-1/a))
ax.plot(a_vals, ginis, label='基尼系数估值')
Expand Down Expand Up @@ -543,13 +546,14 @@ plt.show()
这是一个解法，它在理论和模拟之间产生了很好的匹配。

```{code-cell} ipython3
rng = np.random.default_rng()
a_vals = np.linspace(1, 10, 25) # 帕累托尾部指数
ginis = np.empty_like(a_vals)

n = 1000 # 每个样本的大小
fig, ax = plt.subplots()
for i, a in enumerate(a_vals):
y = np.random.uniform(size=n)**(-1/a)
y = rng.uniform(size=n)**(-1/a)
ginis[i] = qe.gini_coefficient(y)
ax.plot(a_vals, ginis, label='抽样值')
ax.plot(a_vals, 1/(2*a_vals - 1), label='理论值')
Expand Down Expand Up @@ -630,4 +634,4 @@ plt.show()
```

```{solution-end}
```
```
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