Week7-2: explain week7_analysis.do

Week7/Week7_Stata代码详解.html

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+</style></head><body><a class="skip-link" href="#main">跳转到正文</a><div class="reading-progress" id="reading-progress" aria-hidden="true"></div><header id="top"><div class="hero"><div class="eyebrow">ECONOMETRICS / WEEK 07 / CODE READING</div><h1>读懂每一步，<span>从数据到回归</span></h1><p class="dek">week7_analysis.do 中文逐段详解。对照原文件行号，理解命令如何改变数据、保存结果，以及统计量的实际含义。</p><div class="meta"><span>165 行源代码</span><span>14 个执行步骤</span><span>98 条家庭记录</span><span>Stata 15 语法</span><span>2026-10-26 核对</span></div><div class="hero-bottom"><div class="flow" aria-label="分析流程"><span>Excel 与合计核对</span><b>→</b><span>宽表转长表</span><b>→</b><span>OLS 与残差</span><b>→</b><span>图形与稳健推断</span></div><button id="print-btn" class="print-btn" type="button">打印 / 保存 PDF</button></div></div></header><details class="mobile-nav"><summary>展开章节目录</summary><nav aria-label="移动端章节目录"><a href="#overview">阅读地图：这份 do 文件完成什么</a><a href="#syntax">语法预备：宏、变量、标量与返回值</a><a href="#setup">01 · 初始化环境与记录日志</a><a href="#import">02 · 读取 Excel 的指定数值区域</a><a href="#audit">03 · 逐列检查收入表头并核对合计</a><a href="#export-audit">04 · 临时切换数据并导出审计表</a><a href="#reshape">05 · 从宽表整理成 98 条家庭明细</a><a href="#ols">06 · OLS 回归、拟合值与模型统计量</a><a href="#coefficient-table">07 · 手工整理系数、t 检验与置信区间</a><a href="#residual">08 · 核对 OLS 残差的两个代数性质</a><a href="#group">09 · 按收入水平生成汇总表</a><a href="#plot">10 · 绘制散点与拟合直线，导出四种图形</a><a href="#robust">11 · 计算异方差稳健标准误并导出</a><a href="#hettest">12 · 恢复 OLS 并进行异方差检验</a><a href="#model-export">13 · 将模型汇总指标写成一行 CSV</a><a href="#finish">14 · 完成标记、关闭日志与退出</a><a href="#files">文件索引：每个输出保存了什么</a><a href="#checkpoints">理解与复现时最容易出错的地方</a><a href="#run">如何在给定路径下运行和查阅</a><a href="#sources">核对依据与文档范围</a></nav></details><div class="layout"><aside class="sidebar"><p class="nav-label">阅读目录</p><nav aria-label="章节目录"><a href="#overview">阅读地图：这份 do 文件完成什么</a><a href="#syntax">语法预备：宏、变量、标量与返回值</a><a href="#setup">01 · 初始化环境与记录日志</a><a href="#import">02 · 读取 Excel 的指定数值区域</a><a href="#audit">03 · 逐列检查收入表头并核对合计</a><a href="#export-audit">04 · 临时切换数据并导出审计表</a><a href="#reshape">05 · 从宽表整理成 98 条家庭明细</a><a href="#ols">06 · OLS 回归、拟合值与模型统计量</a><a href="#coefficient-table">07 · 手工整理系数、t 检验与置信区间</a><a href="#residual">08 · 核对 OLS 残差的两个代数性质</a><a href="#group">09 · 按收入水平生成汇总表</a><a href="#plot">10 · 绘制散点与拟合直线，导出四种图形</a><a href="#robust">11 · 计算异方差稳健标准误并导出</a><a href="#hettest">12 · 恢复 OLS 并进行异方差检验</a><a href="#model-export">13 · 将模型汇总指标写成一行 CSV</a><a href="#finish">14 · 完成标记、关闭日志与退出</a><a href="#files">文件索引：每个输出保存了什么</a><a href="#checkpoints">理解与复现时最容易出错的地方</a><a href="#run">如何在给定路径下运行和查阅</a><a href="#sources">核对依据与文档范围</a></nav><p class="nav-foot">代码逐段引用原文件<br>图片、样式与脚本内嵌<br>无网络依赖 · 支持打印</p></aside><main id="main"><section id="overview" aria-labelledby="heading-overview"><div class="section-heading"><h2 id="heading-overview">阅读地图：这份 do 文件完成什么</h2></div><p>这是一份从 Excel 家庭消费明细出发的完整 Stata 分析脚本：核对源表 → 转成长表 → 估计消费与收入的 OLS 关系 → 保存拟合值与残差 → 分组汇总与绘图 → 计算稳健标准误及异方差检验 → 导出结果。回归单位是 98 条家庭记录，收入有 10 个水平。</p><p>本文编写和独立核对日期为 <strong>2026 年 10 月 26 日</strong>；所引 Stata 数值来自工作目录内 <strong>2026 年 10 月 23 日</strong>的运行日志及 CSV。此次没有重跑或改动原 do 文件，也没有改写既有分析产物。我们从原 Excel 独立复算了主要统计量，确认它们与现有输出一致。下文代码块直接截取原文件，L 表示原文件物理行号。</p><div class="formula">拟合消费 = 22.930934 + 0.728798742 × 月收入；N = 98；R² = Line truncated
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