Graphical Methods, Inductive Causal Inference, and Econometrics: A Literature Review

被引：9
|
作者：
Kwon, Dae-Heum [2 ]
Bessler, David A. [1 ]
机构：
[1] Texas A&M Univ, College Stn, TX 77843 USA
[2] KREI, Seoul, South Korea
来源：
COMPUTATIONAL ECONOMICS | 2011年 / 38卷 / 01期
关键词：
Machine learning; Directed acyclic graphs; Markov condition; Causality; Econometrics; MODELS;
D O I：
10.1007/s10614-010-9236-9
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
Recent work with graphical methods for inductive causal inference with observational econometric data is reviewed and compared with earlier work. Two alternative algorithms are described. Caveats on applications are discussed.
引用
收藏
页码：85 / 106
页数：22
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