On Granger causality and the effect of interventions in time series

DOI10.1007/s10985-009-9143-3zbMath1322.62063OpenAlexW2009420806WikidataQ46780571 ScholiaQ46780571MaRDI QIDQ746001

Vanessa Didelez, Michael Eichler

Publication date: 15 October 2015

Published in: Lifetime Data Analysis (Search for Journal in Brave)

Full work available at URL: https://cris.maastrichtuniversity.nl/en/publications/38480412-0c31-490b-b919-5bb7b6c2d74d

zbMATH Keywords

decision theorytime seriescausalitygraphical modelscausal inference

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian problems; characterization of Bayes procedures (62C10)

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Uses Software

• TETRAD

Cites Work

• Granger causality and path diagrams for multivariate time series
• Dynamic discrete choice and dynamic treatment effects
• Time-series estimation of the effects of natural experiments
• Bayesian inference for causal effects: The role of randomization
• Long memory continuous time models
• Identifying the consequences of dynamic treatment strategies: a decision-theoretic overview
• Dynamic modelling and causality
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• Graphical Models for Marked Point Processes Based on Local Independence
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• A Note on Noncausality
• Markov Properties for Acyclic Directed Mixed Graphs
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• Investigating Causal Relations by Econometric Models and Cross-spectral Methods
• What can Statistics Contribute to a Causal Understanding?
• Graphical Models for Composable Finite Markov Processes
• Composable Markov processes
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