IDEAS home Printed from https://ideas.repec.org/p/ecb/ecbwps/20141696.html
   My bibliography  Save this paper

A theory of pruning

Author

Listed:
  • Lombardo, Giovanni
  • Uhlig, Harald

Abstract

Often, numerical simulations for dynamic, stochastic models in economics are needed. Higher order methods can be attractive, but bear the danger of generating explosive solutions in originally stationary models. Kim-Kim-Schaumburg-Sims (2008) proposed pruning to deal with this challenge for second order approximations. In this paper, we provide a theory of pruning and formulas for pruning of any order. We relate it to results described by Judd (1998) on perturbing dynamical systems. JEL Classification: C63, C02, C62

Suggested Citation

  • Lombardo, Giovanni & Uhlig, Harald, 2014. "A theory of pruning," Working Paper Series 1696, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:20141696
    Note: 656519
    as

    Download full text from publisher

    File URL: https://www.ecb.europa.eu//pub/pdf/scpwps/ecbwp1696.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    • Giovanni Lombardo & Harald Uhlig, 2018. "A Theory Of Pruning," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(4), pages 1825-1836, November.

    References listed on IDEAS

    as
    1. Lan, Hong & Meyer-Gohde, Alexander, 2013. "Pruning in perturbation DSGE models: Guidance from nonlinear moving average approximations," SFB 649 Discussion Papers 2013-024, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, December.
    3. Lombardo, Giovanni, 2010. "On approximating DSGE models by series expansions," Working Paper Series 1264, European Central Bank.
    4. Den Haan, Wouter J. & De Wind, Joris, 2012. "Nonlinear and stable perturbation-based approximations," Journal of Economic Dynamics and Control, Elsevier, vol. 36(10), pages 1477-1497.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gambacorta, Leonardo & Agénor, Pierre-Richard & Kharroubi, Enisse & Lombardo, Giovanni & Pereira da Silva, Luiz A., 2017. "The International Dimensions of Macroprudential Policies," CEPR Discussion Papers 12108, C.E.P.R. Discussion Papers.
    2. Mutschler, Willi, 2015. "Note on Higher-Order Statistics for the Pruned-State-Space of nonlinear DSGE models," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113138, Verein für Socialpolitik / German Economic Association.
    3. Thierry Betti & Thomas Coudert, 2022. "How harmful are cuts in public employment and wage in times of high unemployment?," Bulletin of Economic Research, Wiley Blackwell, vol. 74(1), pages 247-277, January.
    4. Thierry BETTI & Thomas COUDERT, 2015. "How can the labor market accounts for the effectiveness of fiscal policy over the business cycle?," Working Papers of LaRGE Research Center 2015-06, Laboratoire de Recherche en Gestion et Economie (LaRGE), Université de Strasbourg.
    5. Levieuge, Grégory & Sahuc, Jean-Guillaume, 2021. "Downward interest rate rigidity," European Economic Review, Elsevier, vol. 137(C).
    6. Borovicka, J. & Hansen, L.P., 2016. "Term Structure of Uncertainty in the Macroeconomy," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1641-1696, Elsevier.
    7. Martin M. Andreasen & Anders Kronborg, 2017. "The Extended Perturbation Method: New Insights on the New Keynesian Model," CREATES Research Papers 2017-14, Department of Economics and Business Economics, Aarhus University.
    8. Mutschler, Willi, 2015. "Identification of DSGE models—The effect of higher-order approximation and pruning," Journal of Economic Dynamics and Control, Elsevier, vol. 56(C), pages 34-54.
    9. Mutschler, Willi, 2018. "Higher-order statistics for DSGE models," Econometrics and Statistics, Elsevier, vol. 6(C), pages 44-56.
    10. Ajevskis Viktors, 2017. "Semi-global solutions to DSGE models: perturbation around a deterministic path," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(2), pages 1-28, April.
    11. Viktors Ajevskis, 2019. "Generalised Impulse Response Function as a Perturbation of a Global Solution to DSGE Models," Working Papers 2019/04, Latvijas Banka.
    12. Yu-Ting Chiang, 2022. "Attention and Fluctuations in Macroeconomic Uncertainty," Working Papers 2022-004, Federal Reserve Bank of St. Louis, revised 09 Nov 2023.

    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. Lan, Hong & Meyer-Gohde, Alexander, 2013. "Solving DSGE models with a nonlinear moving average," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2643-2667.
    2. Lan, Hong & Meyer-Gohde, Alexander, 2013. "Decomposing risk in dynamic stochastic general equilibrium," SFB 649 Discussion Papers 2013-022, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Ajevskis Viktors, 2017. "Semi-global solutions to DSGE models: perturbation around a deterministic path," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(2), pages 1-28, April.
    4. repec:hum:wpaper:sfb649dp2013-024 is not listed on IDEAS
    5. Brzoza-Brzezina, Michał & Kolasa, Marcin & Makarski, Krzysztof, 2015. "A penalty function approach to occasionally binding credit constraints," Economic Modelling, Elsevier, vol. 51(C), pages 315-327.
    6. Viktors Ajevskis, 2019. "Generalised Impulse Response Function as a Perturbation of a Global Solution to DSGE Models," Working Papers 2019/04, Latvijas Banka.
    7. Ajevskis, Viktors, 2019. "Nonlocal Solutions To Dynamic Equilibrium Models: The Approximate Stable Manifolds Approach," Macroeconomic Dynamics, Cambridge University Press, vol. 23(6), pages 2544-2571, September.
    8. Ajevskis, Viktors, 2014. "Global Solutions to DSGE Models as a Perturbation of a Deterministic Path," MPRA Paper 55145, University Library of Munich, Germany.
    9. Lilia Maliar & Serguei Maliar & Sébastien Villemot, 2013. "Taking Perturbation to the Accuracy Frontier: A Hybrid of Local and Global Solutions," Computational Economics, Springer;Society for Computational Economics, vol. 42(3), pages 307-325, October.
    10. repec:hum:wpaper:sfb649dp2013-022 is not listed on IDEAS
    11. Lan, Hong & Meyer-Gohde, Alexander, 2013. "Pruning in perturbation DSGE models: Guidance from nonlinear moving average approximations," SFB 649 Discussion Papers 2013-024, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Borovička, Jaroslav & Hansen, Lars Peter, 2014. "Examining macroeconomic models through the lens of asset pricing," Journal of Econometrics, Elsevier, vol. 183(1), pages 67-90.
    13. Andrew Foerster & Juan F. Rubio‐Ramírez & Daniel F. Waggoner & Tao Zha, 2016. "Perturbation methods for Markov‐switching dynamic stochastic general equilibrium models," Quantitative Economics, Econometric Society, vol. 7(2), pages 637-669, July.
    14. Den Haan, Wouter J. & De Wind, Joris, 2012. "Nonlinear and stable perturbation-based approximations," Journal of Economic Dynamics and Control, Elsevier, vol. 36(10), pages 1477-1497.
    15. Francisco Blasques, 2014. "Transformed Polynomials For Nonlinear Autoregressive Models Of The Conditional Mean," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(3), pages 218-238, May.
    16. Francisco (F.) Blasques & Marc Nientker, 2019. "Transformed Perturbation Solutions for Dynamic Stochastic General Equilibrium Models," Tinbergen Institute Discussion Papers 19-012/III, Tinbergen Institute, revised 09 Feb 2020.
    17. Balcilar, Mehmet & Gupta, Rangan & Kotzé, Kevin, 2015. "Forecasting macroeconomic data for an emerging market with a nonlinear DSGE model," Economic Modelling, Elsevier, vol. 44(C), pages 215-228.
    18. repec:hum:wpaper:sfb649dp2014-034 is not listed on IDEAS
    19. Meyer-Gohde, Alexander, 2014. "Risky linear approximations," SFB 649 Discussion Papers 2014-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    20. Meyer-Gohde, Alexander, 2015. "Risk-Sensitive Linear Approximations," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113057, Verein für Socialpolitik / German Economic Association.
    21. Rabitsch, Katrin & Stepanchuk, Serhiy & Tsyrennikov, Viktor, 2015. "International portfolios: A comparison of solution methods," Journal of International Economics, Elsevier, vol. 97(2), pages 404-422.
    22. Karmakar, Sudipto, 2016. "Macroprudential regulation and macroeconomic activity," Journal of Financial Stability, Elsevier, vol. 25(C), pages 166-178.
    23. Hong Lan, 2018. "Comparing Solution Methods for DSGE Models with Labor Market Search," Computational Economics, Springer;Society for Computational Economics, vol. 51(1), pages 1-34, January.

    More about this item

    Keywords

    numerical economics; numerical simulation; Perturbation Methods; pruning; Taylor expansion;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium

    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:ecb:ecbwps:20141696. 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: Official Publications (email available below). General contact details of provider: https://edirc.repec.org/data/emieude.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.