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Computation of policy counterfactuals in sequence space

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  • Hebden, James
  • Winkler, Fabian

Abstract

We propose an efficient procedure to solve for policy counterfactuals in sequence space. Forecasts of the variables relevant for the policy problem, and their impulse responses to anticipated policy shocks, constitute sufficient information to construct valid counterfactuals. Knowledge of the structural model equations or filtering of structural shocks is not required. The underlying model has to be linear but occasionally binding constraints are allowed under quasi-perfect foresight. We solve for deterministic and stochastic paths under instrument rules as well as under optimal policy with commitment or subgame-perfect discretion. As an application, we compute counterfactuals of the U.S. economy after the pandemic shock of 2020 under several monetary policy regimes.

Suggested Citation

  • Hebden, James & Winkler, Fabian, 2026. "Computation of policy counterfactuals in sequence space," Journal of Economic Dynamics and Control, Elsevier, vol. 182(C).
    • Handle: RePEc:eee:dyncon:v:182:y:2026:i:c:s0165188925001940
    DOI: 10.1016/j.jedc.2025.105228
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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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