IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2606.13519.html

Semiparametric Local Projections

Author

Listed:
  • Silvia Goncalves
  • Ana Maria Herrera
  • Lutz Kilian
  • Elena Peavento
  • Iones Kelanemer Holban

Abstract

We propose a semiparametric local projection estimator of nonlinear impulse response functions for a broad class of structural dynamic models relevant for applied macroeconomics, including models with nonlinearly transformed regressors, state dependent coefficients, and nonlinear interactions between shocks and state variables. The estimator is based on a doubly robust moment condition that identifies the average response function as a linear functional of a nonparametric conditional mean, augmented by a density ratio that captures the effect of shifting the shock of interest. We combine this moment condition with cross-fitting that handles serial dependence. The resulting estimator is $\sqrt{T}$-consistent and asymptotically normal. We examine the finite-sample performance of the estimator across a range of nonlinear data generating processes and illustrate its use in two empirical examples.

Suggested Citation

  • Silvia Goncalves & Ana Maria Herrera & Lutz Kilian & Elena Peavento & Iones Kelanemer Holban, 2026. "Semiparametric Local Projections," Papers 2606.13519, arXiv.org.
  • Handle: RePEc:arx:papers:2606.13519
    as

    Download full text from publisher

    File URL: https://arxiv.org/pdf/2606.13519
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Cloyne, James & Jordà , Òscar & Taylor, Alan M., 2023. "State-Dependent Local Projections: Understanding Impulse Response Heterogeneity," CEPR Discussion Papers 17903, Centre for Economic Policy Research.
    2. Lutz Kilian & Robert J. Vigfusson, 2011. "Are the responses of the U.S. economy asymmetric in energy price increases and decreases?," Quantitative Economics, Econometric Society, vol. 2(3), pages 419-453, November.
    3. Silvana Tenreyro & Gregory Thwaites, 2016. "Pushing on a String: US Monetary Policy Is Less Powerful in Recessions," American Economic Journal: Macroeconomics, American Economic Association, vol. 8(4), pages 43-74, October.
    4. Valerie A. Ramey & Sarah Zubairy, 2018. "Government Spending Multipliers in Good Times and in Bad: Evidence from US Historical Data," Journal of Political Economy, University of Chicago Press, vol. 126(2), pages 850-901.
    5. Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037.
    6. Giorgi Nikolaishvili, 2026. "Doubly Robust Nonparametric Local Projections," Working Papers 135, Wake Forest University, Economics Department.
    7. Alexander Chudik & Georgios Georgiadis, 2022. "Estimation of Impulse Response Functions When Shocks Are Observed at a Higher Frequency Than Outcome Variables," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 965-979, June.
    8. Mario Forni & Luca Gambetti & Nicolò Maffei‐Faccioli & Luca Sala, 2024. "Nonlinear Transmission of Financial Shocks: Some New Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 56(1), pages 5-33, February.
    9. 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.
    10. Victor Chernozhukov & Whitney K. Newey & Rahul Singh, 2022. "Automatic Debiased Machine Learning of Causal and Structural Effects," Econometrica, Econometric Society, vol. 90(3), pages 967-1027, May.
    11. Daniele Ballinari & Alexander Wehrli, 2024. "Semiparametric inference for impulse response functions using double/debiased machine learning," Papers 2411.10009, arXiv.org, revised Dec 2025.
    12. Herrera, Ana María & Lagalo, Latika Gupta & Wada, Tatsuma, 2015. "Asymmetries in the response of economic activity to oil price increases and decreases?," Journal of International Money and Finance, Elsevier, vol. 50(C), pages 108-133.
    13. Valerie A. Ramey & Daniel J. Vine, 2011. "Oil, Automobiles, and the US Economy: How Much Have Things Really Changed?," NBER Chapters, in: NBER Macroeconomics Annual 2010, volume 25, pages 333-367, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Goncalves, Silvia & Herrera, Ana Maria & Kilian, Lutz & Pesavento, Elena, 2024. "Nonparametric Local Projections," CEPR Discussion Papers 19684, Centre for Economic Policy Research.
    2. Gonçalves, Sílvia & Herrera, Ana María & Kilian, Lutz & Pesavento, Elena, 2024. "State-dependent local projections," Journal of Econometrics, Elsevier, vol. 244(2).
    3. Alessandri, Piergiorgio & Jordà, Òscar & Venditti, Fabrizio, 2025. "Decomposing the monetary policy multiplier," Journal of Monetary Economics, Elsevier, vol. 152(C).
    4. 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.
    5. Giovanni Ballarin, 2023. "Impulse Response Analysis of Structural Nonlinear Time Series Models," Papers 2305.19089, arXiv.org, revised Jun 2025.
    6. Nadav Ben Zeev, 2019. "Identification of Sign-Dependency of Impulse Responses," Working Papers 1907, Ben-Gurion University of the Negev, Department of Economics.
    7. Ramey, V.A., 2016. "Macroeconomic Shocks and Their Propagation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 71-162, Elsevier.
    8. Valentin Winkler, 2026. "When and Why State-Dependent Local Projections Work," Papers 2601.01622, arXiv.org.
    9. De Santis, Roberto A. & Tornese, Tommaso, 2023. "Energy supply shocks’ nonlinearities on output and prices," Working Paper Series 2834, European Central Bank.
    10. Fabrizio Renzi, 2025. "New evidence on state-dependent fiscal multipliers," Temi di discussione (Economic working papers) 1512, Bank of Italy, Economic Research and International Relations Area.
    11. Bunce, Alan & Carrillo-Maldonado, Paul, 2023. "Asymmetric effect of the oil price in the ecuadorian economy," Energy Economics, Elsevier, vol. 124(C).
    12. Klieber, Karin & Coulombe, Philippe Goulet, 2025. "Opening the black box of local projections," Working Paper Series 3105, European Central Bank.
    13. Omotosho, Babatunde S. & Yang, Bo, 2024. "Oil price shocks and macroeconomic dynamics in resource-rich emerging economies under regime shifts," Journal of International Money and Finance, Elsevier, vol. 144(C).
    14. NAKAJIMA, Jouchi, 2025. "Time-varying Local Projections with Stochastic Volatility," Discussion Paper Series 761, Institute of Economic Research, Hitotsubashi University.
    15. Òscar Jordà & Alan M. Taylor, 2024. "Local Projections," NBER Working Papers 32822, National Bureau of Economic Research, Inc.
    16. Dennis Bonam & Paul Konietschke, 2020. "Tax multipliers across the business cycle," Working Papers 699, DNB.
    17. Nicolas Caramp & Ethan Feilich, 2026. "Monetary Policy and Government Debt," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 58(2), pages 389-420, March.
    18. Sokbae Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2018. "Factor-Driven Two-Regime Regression," Papers 1810.11109, arXiv.org, revised Sep 2020.
    19. Giovanni Pellegrino, 2021. "Uncertainty and monetary policy in the US: A journey into nonlinear territory," Economic Inquiry, Western Economic Association International, vol. 59(3), pages 1106-1128, July.
    20. Philippe Goulet Coulombe & Karin Klieber, 2025. "Opening the Black Box of Local Projections," Papers 2505.12422, arXiv.org, revised Jul 2025.

    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • 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
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2606.13519. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: https://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.