  Bojinov & Shephard (2019) defined potential outcome time series to
nonparametrically measure dynamic causal effects in time series experiments.
Four innovations are developed in this paper: "instrumental paths," treatments
which are "shocks," "linear potential outcomes" and the "causal response
function." Potential outcome time series are then used to provide a
nonparametric causal interpretation of impulse response functions, generalized
impulse response functions, local projections and LP-IV.
