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🌐 [translation-sync] Read the six folded datasets from data-lectures, not high_dim_data #293

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mmcky merged 6 commits into from
Aug 11, 2026
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🌐 [translation-sync] Read the six folded datasets from data-lectures, not high_dim_data #293

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841d07d
Update translation: lectures/heavy_tails.md
mmcky Aug 11, 2026
665f298
Update translation: .translate/state/heavy_tails.md.yml
mmcky Aug 11, 2026
3ca6d1a
Update translation: lectures/inequality.md
mmcky Aug 11, 2026
2961160
Update translation: .translate/state/inequality.md.yml
mmcky Aug 11, 2026
57e9fa6
Update translation: lectures/mle.md
mmcky Aug 11, 2026
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Update translation: .translate/state/mle.md.yml
mmcky Aug 11, 2026
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4 changes: 2 additions & 2 deletions .translate/state/heavy_tails.md.yml
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synced-at: "2026-08-11"
model: claude-sonnet-5
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8 changes: 4 additions & 4 deletions .translate/state/inequality.md.yml
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synced-at: "2026-07-18"
source-sha: 0066783cc3c1a064c33b848236799b5b1f4ed564
synced-at: "2026-08-11"
model: claude-sonnet-5
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6 changes: 3 additions & 3 deletions .translate/state/mle.md.yml
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source-sha: a453cf5371b1fd8cf1388417ba702dab3f277961
synced-at: "2026-08-03"
source-sha: 0066783cc3c1a064c33b848236799b5b1f4ed564
synced-at: "2026-08-11"
model: claude-sonnet-5
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section-count: 5
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13 changes: 4 additions & 9 deletions lectures/inequality.md
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Expand Up @@ -4,7 +4,7 @@ jupytext:
extension: .md
format_name: myst
format_version: 0.13
jupytext_version: 1.16.1
jupytext_version: 1.17.2
kernelspec:
display_name: Python 3 (ipykernel)
language: python
Expand Down Expand Up @@ -61,7 +61,6 @@ translation:

我们首先探讨不平等的衡量标准，然后将其应用于美国和其他国家的财富和收入数据。


### 一些历史

许多历史学家认为，在罗马共和国衰落这一历史事件中，不平等这一问题起到了重要作用（参见{cite}`levitt2019did`等）。
Expand All @@ -80,7 +79,6 @@ translation:

基于这些原因，我们开始思考什么是不平等，以及如何量化和分析不平等。


### 测量

在政界和大众媒体中，“不平等 ”一词的使用往往相当宽泛，没有任何确切的定义。
Expand Down Expand Up @@ -119,7 +117,6 @@ plt.rcParams['font.family'] = ['Source Han Serif SC']

在本节中，我们将讨论洛伦兹曲线的定义和性质。


### 定义

洛伦兹曲线选取一个样本 $w_1，\ldots，w_n$，并生成一条曲线 $L$。
Expand Down Expand Up @@ -156,7 +153,6 @@ $$

在上面的讨论中，我们重点讨论了财富，但同样的观点也适用于收入、消费等。


### 洛伦兹曲线的模拟数据

让我们来看一些例子，并加强理解。
Expand Down Expand Up @@ -249,8 +245,8 @@ plt.show()
接下来，我们来看一看美国的收入数据和财富数据。

(data:survey-consumer-finance)=
下面的代码导入了2016年的`SCF_plus`数据集的一个子集，
该数据集来源于[消费者财务调查](https://en.wikipedia.org/wiki/Survey_of_Consumer_Finances)（SCF）。
下面的代码导入了 2016 年的 `SCF_plus` 数据集的一个子集，
该数据集来源于 [消费者财务调查](https://en.wikipedia.org/wiki/Survey_of_Consumer_Finances)（SCF）。

```{code-cell} ipython3
url = 'https://raw.githubusercontent.com/QuantEcon/data-lectures/main/lectures/SCF_plus_mini.csv'
Expand Down Expand Up @@ -422,7 +418,6 @@ plt.show()
在全球数据网站 (Our World in Data) 上有一个用图表阐述[洛伦兹曲线和基尼系数](https://ourworldindata.org/what-is-the-gini-coefficient)的网页
```


### 模拟数据的基尼系数

让我们通过一些模拟数据来研究基尼系数。
Expand Down Expand Up @@ -1104,4 +1099,4 @@ gini_coefficients
```

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