章节

逻辑、想象和诠释:工具变量在社会科学因果推断中的应用

摘要

工具变量(instrumental variable)是社会科学定量分析中解决内生性问题的重要手段,是基于调查数据进行因果推断的前沿方法。本文在简要介绍工具变量的定义、原理及估算方法的基础上,对实证分析中较为常见的五类工具变量进行回顾梳理,为今后研究寻找工具变量提供了参考。同时,对工具变量估计量的权重性特征进行了阐述,并结合实例展示了使用工具变量进行因果推断的基本步骤和要点。最后,就工具变量方法的潜力和局限性进行了剖析。

作者

陈云松
杨典 ,中国社会科学院社会学研究所副所长,研究员,《社会学研究》编辑部主任;2019年人社部“百千万人才工程”国家级人选,国家有突出贡献中青年专家,享受国务院政府特殊津贴专家;主要研究领域为经济社会学和组织社会学;著有《公司的再造:金融市场与中国企业的现代转型》等多部著作;曾获2011年、2017年中国社会学会学术年会优秀论文一等奖、中国社会科学院2017年度优秀对策信息情况报告类特等奖、陆学艺社会学发展基金会第四届“社会学优秀成果奖”等奖项。

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逻辑、想象和诠释:工具变量在社会科学因果推断中的应用

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章节目录

  • 一 导言:因果推断的圣杯
  • 二 工具变量的原理:模型之外的力量
  • 三 工具变量的寻觅:逻辑和想象
    1. (一)来自“分析上层”的工具变量:集聚数据
    2. (二)来自“自然界”的工具变量:物候天象
    3. (三)来自“生理现象”的工具变量:生老病死
    4. (四)来自“社会空间”的工具变量:距离和价格
    5. (五)来自“实验”的工具变量:自然实验和虚拟实验
  • 四 工具变量估计量的诠释:局部干预效应问题
  • 五 工具变量分析实例:社会网、选择性交友与求职
    1. 1.第一步:建立模型
    2. 2.第二步:寻找工具变量
    3. 3.第三步:数据分析
    4. 4.第四步:机制诠释
  • 六 结语:局限抑或潜力?

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