IDEAS home Printed from https://ideas.repec.org/p/pen/papers/18-011.html
   My bibliography  Save this paper

Perturbations in DSGE Models: Odd Derivatives Theorem

Author

Listed:
  • Sherwin Lott

    (Department of Economics, University of Pennsylvania)

Abstract

When testing a theory, we should ask not just whether its predictions match what we see in the data, but also about its “completeness†: how much of the predictable variation in the data does the theory capture? Deï¬ ning completeness is conceptually challenging, but we show how methods based on machine learning can provide tractable measures of completeness. We also identify a model domain—the human perception and generation of randomness—where measures of completeness can be feasibly analyzed; from these measures we discover there is signiï¬ cant structure in the problem that existing theories have yet to capture.

Suggested Citation

  • Sherwin Lott, 2018. "Perturbations in DSGE Models: Odd Derivatives Theorem," PIER Working Paper Archive 18-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 21 May 2018.
    • Handle: RePEc:pen:papers:18-011
    as

    Download full text from publisher

    File URL: https://economics.sas.upenn.edu/system/files/working-papers/18-011%20PIER%20Paper%20Submission.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jesus Fernandez-Villaverde & Pablo Guerron-Quintana & Juan F. Rubio-Ramirez & Martin Uribe, 2011. "Risk Matters: The Real Effects of Volatility Shocks," American Economic Review, American Economic Association, vol. 101(6), pages 2530-2561, October.
    2. Lan, Hong & Meyer-Gohde, Alexander, 2014. "Solvability of perturbation solutions in DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 45(C), pages 366-388.
    3. Martin Andreasen, 2012. "On the Effects of Rare Disasters and Uncertainty Shocks for Risk Premia in Non-Linear DSGE Models," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 15(3), pages 295-316, July.
    4. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Solving dynamic general equilibrium models using a second-order approximation to the policy function," Journal of Economic Dynamics and Control, Elsevier, vol. 28(4), pages 755-775, January.
    5. Sy-Ming Guu & Kenneth L. Judd, 2001. "Asymptotic methods for asset market equilibrium analysis," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 18(1), pages 127-157.
    6. Levintal, Oren, 2017. "Fifth-order perturbation solution to DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 80(C), pages 1-16.
    7. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, December.
    8. Dario Caldara & Jesus Fernandez-Villaverde & Juan Rubio-Ramirez & Wen Yao, 2012. "Computing DSGE Models with Recursive Preferences and Stochastic Volatility," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 15(2), pages 188-206, April.
    9. Gary S. Anderson & Andrew T. Levin & Eric T. Swanson, 2006. "Higher-order perturbation solutions to dynamic, discrete-time rational expectations models," Working Paper Series 2006-01, Federal Reserve Bank of San Francisco.
    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. Lott, Sherwin, 2019. "Perturbations in DSGE models: An odd derivatives theorem," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.
    2. repec:hum:wpaper:sfb649dp2013-022 is not listed on IDEAS
    3. 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.
    4. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    5. repec:hum:wpaper:sfb649dp2013-024 is not listed on IDEAS
    6. 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.
    7. Parra-Alvarez, Juan Carlos & Polattimur, Hamza & Posch, Olaf, 2021. "Risk matters: Breaking certainty equivalence in linear approximations," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    8. Dlugoszek, Grzegorz R., 2016. "Solving DSGE portfolio choice models with asymmetric countries," SFB 649 Discussion Papers 2016-009, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. Meyer-Gohde, Alexander, 2014. "Risky linear approximations," SFB 649 Discussion Papers 2014-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. 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.
    11. Lan, Hong & Meyer-Gohde, Alexander, 2012. "Existence and Uniqueness of Perturbation Solutions in DSGE Models," Dynare Working Papers 14, CEPREMAP.
    12. Ruge-Murcia, Francisco, 2024. "Asset prices in a production network," European Economic Review, Elsevier, vol. 166(C).
    13. Lorenzo Bretscher & Alex Hsu & Andrea Tamoni, 2019. "Response of the Macroeconomy to Uncertainty Shocks:the Risk Premium Channel," 2019 Meeting Papers 1567, Society for Economic Dynamics.
    14. repec:hum:wpaper:sfb649dp2014-034 is not listed on IDEAS
    15. Lan, Hong & Meyer-Gohde, Alexander, 2014. "Solvability of perturbation solutions in DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 45(C), pages 366-388.
    16. Fernández-Villaverde, Jesús & Guerrón-Quintana, Pablo & Rubio-Ramírez, Juan F., 2015. "Estimating dynamic equilibrium models with stochastic volatility," Journal of Econometrics, Elsevier, vol. 185(1), pages 216-229.
    17. Levintal, Oren, 2017. "Fifth-order perturbation solution to DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 80(C), pages 1-16.
    18. Juan Carlos Parra-Alvarez & Hamza Polattimur & Olaf Posch, 2020. "Risk Matters: Breaking Certainty Equivalence," CESifo Working Paper Series 8250, CESifo.
    19. Giovanni Pellegrino & Efrem Castelnuovo & Giovanni Caggiano, 2023. "Uncertainty And Monetary Policy During The Great Recession," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(2), pages 577-606, May.
    20. 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.
    21. Ruge-Murcia, Francisco, 2020. "Estimating nonlinear dynamic equilibrium models by matching impulse responses," Economics Letters, Elsevier, vol. 197(C).
    22. repec:hum:wpaper:sfb649dp2016-009 is not listed on IDEAS
    23. repec:hum:wpaper:sfb649dp2012-015 is not listed on IDEAS
    24. Malkhozov, Aytek, 2014. "Asset prices in affine real business cycle models," Journal of Economic Dynamics and Control, Elsevier, vol. 45(C), pages 180-193.
    25. Gleb Kurovskiy, 2017. "Modelling terms of trade volatility impact on output dynamics in Russia," EcoMod2017 10361, EcoMod.

    More about this item

    Keywords

    Perturbation methods; DSGE models; odd derivatives; computational macroeconomics;
    All these keywords.

    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:pen:papers:18-011. 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: Administrator (email available below). General contact details of provider: https://edirc.repec.org/data/deupaus.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.