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  "Title": "Donor-Adjusted Post-Shock Forecasting",
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  "Description": "Implements donor-adjusted methods for forecasting\nconditional means and variances after structural shocks.\nHistorical donor episodes are weighted using covariates\nobserved before each shock, and their estimated post-shock\neffects are combined with forecasts from a target-series model.\nThe methods build on Lin and Eck (2021)\n<doi:10.1016/j.ijforecast.2021.03.010>. The package supports\ndonor balancing weights, structured donor pools, autoregressive\nintegrated moving average models, and generalized\nautoregressive conditional heteroscedasticity models with\nexternal regressors.",
  "License": "MIT + file LICENSE",
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      "headings": [
        "Overview",
        "Package data structure",
        "Donor balancing weights with dbw()",
        "Mean forecasting with SynthPrediction()",
        "ConocoPhillips example",
        "Fit a one-step post-shock forecast",
        "Inspect forecasts",
        "Compare the forecasts",
        "Inspect donor weights and the combined adjustment",
        "Structured donor pools",
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        "Interpret empirical variance forecasts carefully",
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        "References"
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