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来源类型 | Working Paper |
规范类型 | 报告 |
DOI | 10.3386/w19614 |
来源ID | Working Paper 19614 |
Why ask Why? Forward Causal Inference and Reverse Causal Questions | |
Andrew Gelman; Guido Imbens | |
发表日期 | 2013-11-07 |
出版年 | 2013 |
语种 | 英语 |
摘要 | The statistical and econometrics literature on causality is more focused on "effects of causes" than on "causes of effects." That is, in the standard approach it is natural to study the effect of a treatment, but it is not in general possible to define the causes of any particular outcome. This has led some researchers to dismiss the search for causes as "cocktail party chatter" that is outside the realm of science. We argue here that the search for causes can be understood within traditional statistical frameworks as a part of model checking and hypothesis generation. We argue that it can make sense to ask questions about the causes of effects, but the answers to these questions will be in terms of effects of causes. |
主题 | Econometrics |
URL | https://www.nber.org/papers/w19614 |
来源智库 | National Bureau of Economic Research (United States) |
引用统计 | |
资源类型 | 智库出版物 |
条目标识符 | http://119.78.100.153/handle/2XGU8XDN/577289 |
推荐引用方式 GB/T 7714 | Andrew Gelman,Guido Imbens. Why ask Why? Forward Causal Inference and Reverse Causal Questions. 2013. |
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