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Impulse response analysis for structural dynamic models with nonlinear regressors

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  • Gonçalves, Sílvia
  • Herrera, Ana María
  • Kilian, Lutz
  • Pesavento, Elena

Abstract

We study the construction of nonlinear impulse responses in linear structural dynamic models that include nonlinearly transformed regressors. We derive the closed-form solution for the population impulse responses to a given shock and propose a control function approach to estimating these responses without taking a stand on how the remainder of the model is identified. Our plug-in estimator dispenses with the need for simulations and, unlike conventional local projection (LP) estimators, is consistent. A modified LP estimator is shown to be consistent in special cases, but less accurate in finite samples than the plug-in estimator.

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  • Gonçalves, Sílvia & Herrera, Ana María & Kilian, Lutz & Pesavento, Elena, 2021. "Impulse response analysis for structural dynamic models with nonlinear regressors," Journal of Econometrics, Elsevier, vol. 225(1), pages 107-130.
    • Handle: RePEc:eee:econom:v:225:y:2021:i:1:p:107-130
    DOI: 10.1016/j.jeconom.2021.06.009
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    Cited by:

    1. Kilian, Lutz & Zhou, Xiaoqing, 2023. "Oil Price Shocks and Inflation," CEPR Discussion Papers 18416, C.E.P.R. Discussion Papers.
    2. Silvia Goncalves & Ana María Herrera & Lutz Kilian & Elena Pesavento, 2022. "When Do State-Dependent Local Projections Work?," Working Papers 2205, Federal Reserve Bank of Dallas.
    3. Lucidi, Francesco Simone & Pisa, Marta Maria & Tancioni, Massimiliano, 2024. "The effects of temperature shocks on energy prices and inflation in the Euro Area," European Economic Review, Elsevier, vol. 166(C).
    4. Pablo Guerrón-Quintana & Alexey Khazanov & Molin Zhong, 2023. "Financial and Macroeconomic Data Through the Lens of a Nonlinear Dynamic Factor Model," Finance and Economics Discussion Series 2023-027, Board of Governors of the Federal Reserve System (U.S.).
    5. Martin Bruns & Michele Piffer, 2021. "Monetary policy shocks over the business cycle: Extending the Smooth Transition framework," University of East Anglia School of Economics Working Paper Series 2021-07, School of Economics, University of East Anglia, Norwich, UK..
    6. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2023. "Shadow-rate VARs," Discussion Papers 14/2023, Deutsche Bundesbank.
    7. Eugene Dettaa & Endong Wang, 2024. "Inference in High-Dimensional Linear Projections: Multi-Horizon Granger Causality and Network Connectedness," Papers 2410.04330, arXiv.org.
    8. Silvia Goncalves & Ana María Herrera & Lutz Kilian & Elena Pesavento, 2024. "Nonparametric Local Projections," Working Papers 2414, Federal Reserve Bank of Dallas.
    9. Leonardo Nogueira Ferreira, 2023. "Monetary Policy Surprises, Financial Conditions, and the String Theory Revisited," Working Papers Series 573, Central Bank of Brazil, Research Department.
    10. Luca Eduardo Fierro & Mario Martinoli, 2024. "An Empirical Inquiry into the Distributional Consequences of Energy Price Shocks," LEM Papers Series 2024/30, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    11. Endong Wang, 2024. "Structural counterfactual analysis in macroeconomics: theory and inference," Papers 2409.09577, arXiv.org.
    12. Giovanni Ballarin, 2023. "Impulse Response Analysis of Structural Nonlinear Time Series Models," Papers 2305.19089, arXiv.org, revised Jun 2024.
    13. Dario Caldara & Chiara Scotti & Molin Zhong, 2021. "Macroeconomic and Financial Risks: A Tale of Mean and Volatility," International Finance Discussion Papers 1326, Board of Governors of the Federal Reserve System (U.S.).

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    More about this item

    Keywords

    Structural model; Censored regressor; Nonlinear transformation; Nonlinear responses; Partial identification; Control function; Block recursive model; Monte Carlo integration; Local projection;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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