We present the postshock R package, which implements and extends a donor-based framework for forecasting when a structural shock is known and the target response of interest is not yet observed. The package estimates shock effects from historical donor episodes, balances donors using specified matching features, and transfers the resulting adjustment to a target-series forecast. It provides integrated workflows for conditional mean forecasting through ARIMA and ARIMAX models and conditional variance forecasting through GARCH-X models. Additional functionality includes structured donor pools, control-shock regressors, automated GARCH-X order selection, processed data objects, and reproducible empirical workflows.
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