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Dynamic Identification Using System Projections and Instrumental Variables

Author

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  • Lewis, Daniel
  • Mertens, Karel

Abstract

We propose System Projections with Instrumental Variables (SP-IV) to estimate dynamic structural relationships. SP-IV replaces lag sequences of instruments in traditional IV with lead sequences of endogenous variables. SP-IV allows the inclusion of controls to weaken exogeneity requirements, can be more efficient than IV with lags, and allows identification over many time horizons without creating many-weak-instruments problems. SP-IV also enables the estimation of structural relationships across impulse responses obtained from local projections or vector autoregressions. We provide a bias-based test for instrument strength, and inference procedures under strong and weak identification. SP-IV outperforms competing estimators of the Phillips Curve parameters in simulations. We estimate the Phillips Curve implied by the main business cycle shock of Angeletos, Collard and Dellas (2020), and find evidence for forward-looking behavior. The data is consistent with weak but also relatively strong cyclical connections between inflation and unemployment.

Suggested Citation

  • Lewis, Daniel & Mertens, Karel, 2022. "Dynamic Identification Using System Projections and Instrumental Variables," CEPR Discussion Papers 17153, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:17153
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    Cited by:

    1. is not listed on IDEAS
    2. Andrew J. Fieldhouse & Karel Mertens, 2023. "The Returns to Government R&D: Evidence from U.S. Appropriations Shocks," Working Papers 2305, Federal Reserve Bank of Dallas, revised 21 Nov 2024.
    3. Andrew J. Fieldhouse & Karel Mertens, 2025. "The Social Returns to Public R&D," NBER Chapters, in: Entrepreneurship and Innovation Policy and the Economy, volume 5, National Bureau of Economic Research, Inc.

    More about this item

    Keywords

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    JEL classification:

    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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