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We present a method for estimating causal effects in time series data when fine-grained information about the outcome of interest is available.
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[author] Pearl, JudeaJ. (2009). Causality. Cambridge University Press
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[author] Imbens, Guido WG. W. (2010). Better LATE than nothing. Journal of Economic Literature 48
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[author] Ricci, FrancescoF., Rokach, LiorL. and Shapira, BrachaB. (2011). Introduction to recommender systems handbook. Springer
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[author] Cattaneo, Matias DM. D., Frandsen, Brigham RB. R. and Titiunik, RocioR. (2015). Randomization inference in the regression discontinuity design: An application to party advantages in the US Senate. Journal of Causal Inference 3 1–24
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[author] Phan, Tuan QT. Q. and Airoldi, Edoardo ME. M. (2015). A natural experiment of social network formation and dynamics. Proceedings of the National Academy of Sciences 112 6595–6600
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[author] Carnegie, Nicole BohmeN. B., Harada, MasatakaM. and Hill, Jennifer L.J. L. (2016). Assessing Sensitivity to Unmeasured Confounding Using a Simulated Potential Confounder. Journal of Research on Educational Effectiveness 9 395-420
2016
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[author] Kang, HyunseungH., Zhang, AnruA., Cai, T TonyT. T. and Small, Dylan SD. S. (2016). Instrumental variables estimation with some invalid instruments and its application to Mendelian randomization. Journal of the American Statistical Association 111 132–144
2016
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