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

被引：0
|
作者：
Dae-Heum Kwon
David A. Bessler
机构：
[1] Korean Rural Economic Institute (KREI),
[2] Texas A&M University,undefined
来源：
Computational Economics | 2011年 / 38卷
关键词：
Machine learning; Directed acyclic graphs; Markov condition; Causality; Econometrics; C10; C20; C30; C40;
D O I：
暂无
中图分类号：
学科分类号：
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：21
相关论文
共 50 条
  • [21] Equivalence model: a new graphical model for causal inference
    Poorolajal, Jalal
    EPIDEMIOLOGY AND HEALTH, 2020, 42
  • [22] Methods for Causal Inference in Marketing
    He, Zezhen
    Rao, Vithala R.
    FOUNDATIONS AND TRENDS IN MARKETING, 2024, 18 (3-4): : 176 - 309
  • [23] CAUSAL INFERENCE AND COMPARATIVE METHODS
    DEFELICE, EG
    COMPARATIVE POLITICAL STUDIES, 1986, 19 (03) : 415 - 437
  • [24] Methods for causal inference in epidemiology
    Richiardi, Lorenzo
    Bellocco, Rino
    EPIDEMIOLOGIA & PREVENZIONE, 2010, 34 (1-2): : 5 - 6
  • [25] Validating Causal Inference Methods
    Parikh, Harsh
    Vajao, Carlos
    Xu, Louise
    Tchetgen, Eric Tchetgen
    INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 162, 2022,
  • [26] The econometrics of Bayesian graphical models: a review with financial application
    Ahelegbey, Daniel Felix
    JOURNAL OF NETWORK THEORY IN FINANCE, 2016, 2 (02): : 1 - 33
  • [27] DoWhy-GCM: An Extension of DoWhy for Causal Inference in Graphical Causal Models
    Blobaum, Patrick
    Gotz, Peter
    Budhathoki, Kailash
    Mastakouri, Atalanti A.
    Janzing, Dominik
    JOURNAL OF MACHINE LEARNING RESEARCH, 2024, 25
  • [28] Simulation-based inference in econometrics: Methods and applications
    van Soest, A
    ECONOMIST-NETHERLANDS, 2002, 150 (01): : 123 - 125
  • [29] Causal Inference Methods for Combining Randomized Trials and Observational Studies: A Review
    Colnet, Benedicte
    Mayer, Imke
    Chen, Guanhua
    Dieng, Awa
    Li, Ruohong
    Varoquaux, Gael
    Vert, Jean -Philippe
    Josse, Julie
    Yang, Shu
    STATISTICAL SCIENCE, 2024, 39 (01) : 165 - 191
  • [30] The need for causal inference methods to answer causal questions
    McInerney, C. D.
    Kotze, A.
    Howell, S. J.
    ANAESTHESIA, 2022, 77 (03) : 355 - 356
12345