| 来源类型 | Working Paper
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| 规范类型 | 报告
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| DOI | 10.3386/w24833
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| 来源ID | Working Paper 24833
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| A Causal Bootstrap |
| Guido Imbens; Konrad Menzel
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| 发表日期 | 2018-07-16
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| 出版年 | 2018
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| 语种 | 英语
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| 摘要 | The bootstrap, introduced by Efron (1982), has become a very popular method for estimating variances and constructing confidence intervals. A key insight is that one can approximate the properties of estimators by using the empirical distribution function of the sample as an approximation for the true distribution function. This approach views the uncertainty in the estimator as coming exclusively from sampling uncertainty. We argue that for causal estimands the uncertainty arises entirely, or partially, from a different source, corresponding to the stochastic nature of the treatment received. We develop a bootstrap procedure that accounts for this uncertainty, and compare its properties to that of the classical bootstrap. |
| 主题 | Econometrics
; Estimation Methods
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| URL | https://www.nber.org/papers/w24833
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| 来源智库 | National Bureau of Economic Research (United States)
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| 引用统计 |
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| 资源类型 | 智库出版物
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| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/582507
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推荐引用方式
GB/T 7714 |
Guido Imbens,Konrad Menzel. A Causal Bootstrap. 2018.
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文件名：
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w24833.pdf
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格式：
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Adobe PDF
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