Causal inference with multiple time series: principles and problems

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Abstract

I review the use of the concept of Granger causality for causal inference from time-series data. First, I give a theoretical justification by relating the concept to other theoretical causality measures. Second, I outline possible problems with spurious causality and approaches to tackle these problems. Finally, I sketch an identification algorithm that learns causal time-series structures in the presence of latent variables. The description of the algorithm is non-technical and thus accessible to applied scientists who are interested in adopting the method.
Original languageEnglish
Article number20110613
Number of pages17
JournalPhilosophical Transactions of the Royal Society A: mathematical Physical and Engineering Sciences
Volume371
Issue number1997
DOIs
Publication statusPublished - 1 Jan 2013

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