IDEAS home Printed from https://ideas.repec.org/p/hit/hituec/761.html
   My bibliography  Save this paper

Time-varying Local Projections with Stochastic Volatility

Author

Listed:
  • NAKAJIMA, Jouchi

Abstract

This study discusses a general approach to dynamic modeling using the local projection (LP) method. Previous studies have proposed time-varying (TV) parameters in LPs; however, they did not address possible variations in error variances. Overlooking this could introduce significant bias in the estimate of the TV parameter, and consequently, the estimated impulse response. We develop an estimation strategy for LPs with stochastic volatility (SV) and illustrate the importance of SV inclusion using simulated data. Application to a topical macroeconomic time-series analysis illustrates the benefits of the proposed approach in terms of improved predictions.

Suggested Citation

  • NAKAJIMA, Jouchi, 2025. "Time-varying Local Projections with Stochastic Volatility," Discussion Paper Series 761, Institute of Economic Research, Hitotsubashi University.
  • Handle: RePEc:hit:hituec:761
    as

    Download full text from publisher

    File URL: https://hermes-ir.lib.hit-u.ac.jp/hermes/ir/re/85120/DP761.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Silvia Miranda-Agrippino & Giovanni Ricco, 2021. "The Transmission of Monetary Policy Shocks," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(3), pages 74-107, July.
    2. 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.
    3. Joshua D. Angrist & Òscar Jordà & Guido M. Kuersteiner, 2018. "Semiparametric Estimates of Monetary Policy Effects: String Theory Revisited," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(3), pages 371-387, July.
    4. Inoue, Atsushi & Rossi, Barbara & Wang, Yiru, 2024. "Local projections in unstable environments," Journal of Econometrics, Elsevier, vol. 244(2).
    5. Silvia Miranda-Agrippino & Giovanni Ricco, 2021. "Bayesian local projections," Working Papers hal-03373574, HAL.
    6. 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.
    7. Òscar Jordà & Alan M. Taylor, 2016. "The Time for Austerity: Estimating the Average Treatment Effect of Fiscal Policy," Economic Journal, Royal Economic Society, vol. 126(590), pages 219-255, February.
    8. Germano Ruisi, 2019. "Time-Varying Local Projections," Working Papers 891, Queen Mary University of London, School of Economics and Finance.
    9. Aguilar, Omar & West, Mike, 2000. "Bayesian Dynamic Factor Models and Portfolio Allocation," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 338-357, July.
    10. Masahiro Tanaka, 2020. "Bayesian Inference of Local Projections with Roughness Penalty Priors," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 629-651, February.
    11. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2020. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1092-1110, July.
    12. Jouchi Nakajima & Mike West, 2013. "Bayesian Analysis of Latent Threshold Dynamic Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 151-164, April.
    13. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    14. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 361-393.
    15. Omori, Yasuhiro & Chib, Siddhartha & Shephard, Neil & Nakajima, Jouchi, 2007. "Stochastic volatility with leverage: Fast and efficient likelihood inference," Journal of Econometrics, Elsevier, vol. 140(2), pages 425-449, October.
    16. Mikkel Plagborg-Møller & Christian K. Wolf, 2020. "Local Projections and VARs Estimate the Same Impulse Responses," Working Papers 2020-16, Princeton University. Economics Department..
    17. James Cloyne & Òscar Jordà & Alan M. Taylor, 2023. "State-Dependent Local Projections: Understanding Impulse Response Heterogeneity," Working Paper Series 2023-05, Federal Reserve Bank of San Francisco.
    18. Harald Uhlig, 1997. "Bayesian Vector Autoregressions with Stochastic Volatility," Econometrica, Econometric Society, vol. 65(1), pages 59-74, January.
    19. Òscar Jordà, 2005. "Estimation and Inference of Impulse Responses by Local Projections," American Economic Review, American Economic Association, vol. 95(1), pages 161-182, March.
    20. Falk Bräuning & Viacheslav Sheremirov, 2023. "The Transmission Mechanisms of International Business Cycles: International Trade and the Foreign Effects of US Monetary Policy," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(1), pages 300-325, March.
    21. Dake Li & Mikkel Plagborg-Møller & Christian K. Wolf, 2021. "Local Projections vs. VARs: Lessons From Thousands of DGPs," Working Papers 2021-55, Princeton University. Economics Department..
    22. Regis Barnichon & Christian Brownlees, 2019. "Impulse Response Estimation by Smooth Local Projections," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 522-530, July.
    23. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    24. Ulrich K. Müller & Philippe-Emmanuel. Petalas, 2010. "Efficient Estimation of the Parameter Path in Unstable Time Series Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(4), pages 1508-1539.
    25. 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.
    26. Li, Dake & Plagborg-Møller, Mikkel & Wolf, Christian K., 2024. "Local projections vs. VARs: Lessons from thousands of DGPs," Journal of Econometrics, Elsevier, vol. 244(2).
    27. Mikkel Plagborg‐Møller & Christian K. Wolf, 2021. "Local Projections and VARs Estimate the Same Impulse Responses," Econometrica, Econometric Society, vol. 89(2), pages 955-980, March.
    28. Shephard, Neil (ed.), 2005. "Stochastic Volatility: Selected Readings," OUP Catalogue, Oxford University Press, number 9780199257201, Decembrie.
    29. José Luis Montiel Olea & Mikkel Plagborg‐Møller, 2021. "Local Projection Inference Is Simpler and More Robust Than You Think," Econometrica, Econometric Society, vol. 89(4), pages 1789-1823, July.
    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. Òscar Jordà & Alan M. Taylor, 2024. "Local Projections," NBER Working Papers 32822, National Bureau of Economic Research, Inc.
    2. Ho, Paul & Lubik, Thomas A. & Matthes, Christian, 2024. "Averaging impulse responses using prediction pools," Journal of Monetary Economics, Elsevier, vol. 146(C).
    3. Atsushi Inoue & `Oscar Jord`a & Guido M. Kuersteiner, 2023. "Inference for Local Projections," Papers 2306.03073, arXiv.org, revised Aug 2024.
    4. Cloyne, James & Jordà , Òscar & Taylor, Alan M., 2023. "State-Dependent Local Projections: Understanding Impulse Response Heterogeneity," CEPR Discussion Papers 17903, C.E.P.R. Discussion Papers.
    5. Francisco Serranito & Philipp RODERWEIS & Jamel Saadaoui, 2023. "Is Quantitative Easing Productive? The Role of Bank Lending in the Monetary Transmission Process," EconomiX Working Papers 2023-17, University of Paris Nanterre, EconomiX.
    6. Michael D. Bauer & Eric T. Swanson, 2023. "A Reassessment of Monetary Policy Surprises and High-Frequency Identification," NBER Macroeconomics Annual, University of Chicago Press, vol. 37(1), pages 87-155.
    7. Ferrara, Laurent & Metelli, Luca & Natoli, Filippo & Siena, Daniele, 2021. "Questioning the puzzle: Fiscal policy, real exchange rate and inflation," Journal of International Economics, Elsevier, vol. 133(C).
    8. Hauzenberger, Niko & Pfarrhofer, Michael & Stelzer, Anna, 2021. "On the effectiveness of the European Central Bank’s conventional and unconventional policies under uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 822-845.
    9. Philipp Roderweis & Jamel Saadaoui & Francisco Serranito, 2023. "The Unintended Consequences of ECB’s Asset Purchases. How Excess Reserves Shape Bank Lending," Working Papers of BETA 2023-34, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    10. De Santis, Roberto A. & Tornese, Tommaso, 2024. "US monetary policy is more powerful in low economic growth regimes," Working Paper Series 2919, European Central Bank.
    11. Bruns, Martin & Lütkepohl, Helmut, 2022. "Comparison of local projection estimators for proxy vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    12. Hernández, Juan R. & Ventosa-Santaulària, Daniel & Valencia, J. Eduardo, 2024. "Global supply chain inflationary pressures and monetary policy in Mexico," Emerging Markets Review, Elsevier, vol. 58(C).
    13. Masahiro Tanaka, 2025. "Quasi-Bayesian Local Projections: Simultaneous Inference and Extension to the Instrumental Variable Method," Papers 2503.20249, arXiv.org.
    14. Mario Di Serio & Matteo Fragetta & Emanuel Gasteiger & Giovanni Melina, 2024. "The Euro Area Government Spending Multiplier in Demand‐ and Supply‐Driven Recessions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(6), pages 1342-1372, December.
    15. Benatti, Nicola & Groiss, Martin & Kelly, Petra & Lopez-Garcia, Paloma, 2024. "Environmental regulation and productivity growth in the euro area: Testing the porter hypothesis," Journal of Environmental Economics and Management, Elsevier, vol. 126(C).
    16. Leonardo Nogueira Ferreira, 2023. "Monetary Policy Surprises, Financial Conditions, and the String Theory Revisited," Working Papers Series 573, Central Bank of Brazil, Research Department.
    17. Aruoba, S. Borağan & Drechsel, Thomas, 2024. "The long and variable lags of monetary policy: Evidence from disaggregated price indices," Journal of Monetary Economics, Elsevier, vol. 148(S).
    18. Ziwei Mei & Liugang Sheng & Zhentao Shi, 2023. "Nickell Bias in Panel Local Projection: Financial Crises Are Worse Than You Think," Papers 2302.13455, arXiv.org, revised Oct 2023.
    19. Robert Adamek & Stephan Smeekes & Ines Wilms, 2024. "Local projection inference in high dimensions," The Econometrics Journal, Royal Economic Society, vol. 27(3), pages 323-342.
    20. Robert Kirkby & Huong Ngoc Vu, 2024. "Impacts of Monetary Policy Shocks on Inflation and Output in New Zealand," The Economic Record, The Economic Society of Australia, vol. 100(329), pages 160-187, June.

    More about this item

    Keywords

    Local projections; Time-varying parameters; Stochastic volatility;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    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:hit:hituec:761. 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: Hiromichi Miyake (email available below). General contact details of provider: https://edirc.repec.org/data/iehitjp.html .

    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.