On Granger causality and the effect of interventions in time series

Aalen OO. (1987) Dynamic modeling and causality. Scand Actuar J: 177–190

Aalen OO, Frigessi A (2007) What can statistics contribute to a causal understanding. Scand J Stat 34: 155–168

Box GEP, Jenkins GM, Reinsel GC (1994) Time series analysis, forecasting and control. Prentice Hall, Englewood Cliffs

Commenges D, Gegout-Petit A (2007) A general dynamical statistical model with possible causal interpretation

Comte F, Renault E (1996) Noncausality in continuous time models. Econometr Theory 12: 215–256

Cox DR, Wermuth N (1996) Multivariate dependencies—models analysis and interpretation. Chapman & Hall, London

Dawid AP (1979) Conditional independence in statistical theory (with discussion). J R Stat Soc B 41: 1–31

Dawid AP (2000) Causal inference without counterfactuals. J Am Stat Assoc 86: 9–26

Dawid AP (2002) Influence diagrams for causal modelling and inference. Int Stat Rev 70: 161–189

Dawid AP, Didelez V (2005) Identifying the consequences of dynamic treatment strategies, Technical report 262. Department of Statistical Science, University College London

Didelez V (2007) Graphical models for composable finite markov processes. Scand J Stat 34: 169–185

Didelez V (2008) Graphical models for marked point processes based on local independence. J R Stat Soc B 70: 245–264

Eichler M (2001) Graphical modelling of multivariate time series, Technical report. Universität Heidelberg

Eichler M (2006) Graphical modelling of dynamic relationships in multivariate time series. In: Winterhalder M, Schelter B, Timmer J (eds) Handbook of time series analysis. Wiley-VCH, pp 335–372

Eichler M (2007) Granger causality and path diagrams for multivariate time series. J Econometr 137: 334–353

Eichler M (2009) Causal inference from multivariate time series: what can be learned from granger causality. In: Glymour C, Wang W, Westerståhl D (eds) Proceedings from the 13th international congress of logic, methodology and philosophy of science. King’s College Publications, London

Eichler M, Didelez V (2007) Causal reasoning in graphical time series models. Proceedings of the 23rd conference on uncertainty in artificial intelligence

Comte F, Renault E (1996) Noncausality in continuous time models. Econometr Theory 12:215–256

Florens JP, Mouchart M (1982) A note on noncausality. Econometrica 50: 583–591

Florens JP, Mouchart M, Rolin JM (1990) Elements of Bayesian statistics. Marcel Dekker, New York

Granger CWJ (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37: 424–438

Granger CWJ (1980) Testing for causality, a personal viewpoint. J Econ Dyn Control 2: 329–352

Granger CWJ (1986) Comment on Statistics and causal inference by P. Holland. J Am Stat Assoc 81: 967–968

Granger CWJ (1988) Some recent developments in a concept of causality. J Econometr 39: 199–211

Heckman JJ (2008) Econometric causality. Int Stat Rev 76: 1–27

Heckman JJ, Navarro S (2007) Dynamic discrete choice and dynamic treatments effect. J Econon 136: 341–396

Hernán MA, Hernández-Díaz S, Robins JM (2004) A structural approach to selection bias. Epidemiology 15: 615–625

Hernán MA, Taubman SL (2008) Does obesity shorten life? the importance of well defined interventions to answer causal questions. Int J Obes 32: 8–14

Hsiao C (1982) Autoregressive modeling and causal ordering of econometric variables. J Econ Dyn Control 4: 243–259

Kallenberg O (2001) Foundations of modern probability. 2nd edn. Springer, New York

Lauritzen SL (1996) Graphical models. Oxford University Press, Oxford

Lauritzen SL (2001) Causal inference from graphical models. In: Barndorff-Nielsen OE, Cox DR, Klüppelberg C (eds) Complex stochastic systems. CRC Press, London, pp 63–107

Pearl J (1993) Graphical models, causality and interventions. Stat Sci 8: 266–269

Pearl J (1995) Causal diagrams for empirical research (with discussion). Biometrika 82: 669–710

Pearl J (2000) Causality. Cambridge University Press, Cambridge, UK

Richardson T (2003) Markov properties for acyclic directed mixed graphs. Scand J Stat 30: 145–157

Robins JM (1986) A new approach to causal inference in mortality studies with sustained exposure periods—application to control for the healthy worker survivor effect. Math Model 7: 1393–1512

Robins JM, Hernán MA, Siebert U (2004) Effects of multiple interventions. In: Ezzati M, Lopez AD, Rodgers A, Murray CJL (eds) Comparative quantification of health risks: global and regional burden of disease attributable to selected major risk factors, vol 1. World Health Organization, Geneva

Rubin DB (1974) Estimating causal effects of treatments in randomized and nonrandomized studies. J Edu Psychol 66: 688–701

Rubin DB (1978) Bayesian inference for causal effects: the role of randomization. Ann Stat 6: 34–68

Schweder T (1970) Composable markov processes. J Appl Prob 7: 400–410

Spirtes P, Glymour C, Scheines R (2001) Causation, prediction, and search, 2nd edn. [MIT Press, Cambridge, MA. With additional material by David Heckerman, Christopher Meek, Gregory F Cooper and Thomas Richardson]

White H (2006) Time series estimation of the effects of natural experiments. J Econometr 135: 527–566