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DAG-Based Local Projections (Burkhard Raunig)

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Abstract

Directed acyclic graphs (DAGs) provide transparent framework for encoding causal structures and identifying causal effects. This paper demonstrates how DAGs help specify local projections (LPs) for estimating causal impulse responses. Examples illustrate how graphical rules can be used to select controls and instruments for identifying overall and path-specific effects. An empirical application to uncertainty shocks reveals substantial differences in the estimated responses of German industrial production across LP designs. The underlying DAGs help explain these differences and diagnose biases arising from violations of assumed causal structures. A DAG-based instrumental-variable LP reveals pronounced negative effects of U.S. uncertainty shocks.

Suggested Citation

  • Burkhard Raunig, 2026. "DAG-Based Local Projections (Burkhard Raunig)," Working Papers 271, Oesterreichische Nationalbank (Austrian Central Bank).
    • Handle: RePEc:onb:oenbwp:271
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    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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