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When are time series predictions causal? The potential system and dynamic causal effects

Author

Listed:
  • Jacob Carlson
  • Neil Shephard

Abstract

The potential system is a nonparametric time series model for assessing the causal impact of moving an assignment at time $t$ on an outcome at future time $t+h$, accounting for the presence of features. The potential system provides nonparametric content for, e.g., time series experiments, time series regression, local projection, impulse response functions and SVARs. It closes a gap between time series causality and nonparametric cross-sectional causal methods, and provides a foundation for many new methods which have causal content.

Suggested Citation

  • Jacob Carlson & Neil Shephard, 2026. "When are time series predictions causal? The potential system and dynamic causal effects," Papers 2603.20394, arXiv.org.
  • Handle: RePEc:arx:papers:2603.20394
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    References listed on IDEAS

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