Graphical methods, inductive causal inference, and econometrics: a literature review

DOI10.1007/s10614-010-9236-9zbMath1214.62118OpenAlexW1967411360WikidataQ59362820 ScholiaQ59362820MaRDI QIDQ540664

Dae-Heum Kwon, David A. Bessler

Publication date: 3 June 2011

Published in: Computational Economics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10614-010-9236-9

zbMATH Keywords

causalitymachine learningdirected acyclic graphsMarkov condition

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Applications of graph theory (05C90) Directed graphs (digraphs), tournaments (05C20) General reference works (handbooks, dictionaries, bibliographies, etc.) pertaining to statistics (62-00)

Related Items (1)

An efficient algorithm for counting Markov equivalent DAGs

Uses Software

• FastICA
• TETRAD

Cites Work

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• General-to-specific or specific-to-general modelling? An opinion on current econometric terminology
• Finding a causal ordering via independent component analysis
• Causation, prediction, and search
• Probabilistic grammars for natural languages
• Statistics and Causal Inference
• Impulse Response Functions Based on a Causal Approach to Residual Orthogonalization in Vector Autoregressions
• 10.1162/153244303321897717
• Investigating Causal Relations by Econometric Models and Cross-spectral Methods
• The Probability Approach in Econometrics

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