IDEAS home Printed from https://ideas.repec.org/p/bno/worpap/2021_18.html
   My bibliography  Save this paper

Symbolic Stationarization of Dynamic Equilibrium Models

Author

Listed:
  • Fabio Canova
  • Kenneth Sæterhagen Paulsen

Abstract

Dynamic equilibrium models are specified to track time series with unit root-like behavior. Thus, unit roots are typically introduced and the optimality conditions adjusted. This step requires tedious algebra and often leads to algebraic mistakes, especially in models with several unit roots. We propose a symbolic algorithm that simplies the step of rendering non-stationary models stationary. It is easy to implement and works when trends are stochastic or deterministic, exogenous or endogenous. Three examples illustrate the mechanics and the properties of the approach. A comparison with existing methods is provided.

Suggested Citation

  • Fabio Canova & Kenneth Sæterhagen Paulsen, 2021. "Symbolic Stationarization of Dynamic Equilibrium Models," Working Paper 2021/18, Norges Bank.
  • Handle: RePEc:bno:worpap:2021_18
    as

    Download full text from publisher

    File URL: https://hdl.handle.net/11250/2835495
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Diego Comin & Mark Gertler, 2006. "Medium-Term Business Cycles," American Economic Review, American Economic Association, vol. 96(3), pages 523-551, June.
    2. Klein, Paul, 2000. "Using the generalized Schur form to solve a multivariate linear rational expectations model," Journal of Economic Dynamics and Control, Elsevier, vol. 24(10), pages 1405-1423, September.
    3. Alejandro Justiniano & Giorgio Primiceri & Andrea Tambalotti, 2011. "Investment Shocks and the Relative Price of Investment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(1), pages 101-121, January.
    4. Fabio Canova & Christian Matthes, 2021. "A Composite Likelihood Approach for Dynamic Structural Models," The Economic Journal, Royal Economic Society, vol. 131(638), pages 2447-2477.
    5. Pierre Lafourcade & Joris de Wind, 2012. "Taking Trends Seriously in DSGE Models: An Application to the Dutch Economy," DNB Working Papers 345, Netherlands Central Bank, Research Department.
    6. Canova, Fabio, 2014. "Bridging DSGE models and the raw data," Journal of Monetary Economics, Elsevier, vol. 67(C), pages 1-15.
    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. Canova, Fabio & Sæterhagen Paulsen, Kenneth, 2023. "Symbolic stationarization of dynamic equilibrium models," Journal of Economic Dynamics and Control, Elsevier, vol. 154(C).
    2. Albonico, Alice & Paccagnini, Alessia & Tirelli, Patrizio, 2017. "Great recession, slow recovery and muted fiscal policies in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 81(C), pages 140-161.
    3. Albonico, Alice & Tirelli, Patrizio, 2020. "Financial crises and sudden stops: Was the European monetary union crisis different?," Economic Modelling, Elsevier, vol. 93(C), pages 13-26.
    4. Gregor Boehl & Gavin Goy & Felix Strobel, 2020. "A Structural Investigation of Quantitative Easing," CRC TR 224 Discussion Paper Series crctr224_2020_193, University of Bonn and University of Mannheim, Germany.
    5. Andrei Polbin & Sergey Drobyshevsky, 2014. "Developing a Dynamic Stochastic Model of General Equilibrium for the Russian Economy," Research Paper Series, Gaidar Institute for Economic Policy, issue 166P, pages 156-156.
    6. Cristiano Cantore & Vasco J. Gabriel & Paul Levine & Joseph Pearlman & Bo Yang, 2013. "The science and art of DSGE modelling: II – model comparisons, model validation, policy analysis and general discussion," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 19, pages 441-463, Edward Elgar Publishing.
    7. Hürtgen, Patrick, 2014. "Consumer misperceptions, uncertain fundamentals, and the business cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 279-292.
    8. Adrien Auclert & Bence Bardóczy & Matthew Rognlie & Ludwig Straub, 2021. "Using the Sequence‐Space Jacobian to Solve and Estimate Heterogeneous‐Agent Models," Econometrica, Econometric Society, vol. 89(5), pages 2375-2408, September.
    9. Bianchi, Francesco & Kung, Howard & Morales, Gonzalo, 2019. "Growth, slowdowns, and recoveries," Journal of Monetary Economics, Elsevier, vol. 101(C), pages 47-63.
    10. Peter N. Ireland, 2009. "On the Welfare Cost of Inflation and the Recent Behavior of Money Demand," American Economic Review, American Economic Association, vol. 99(3), pages 1040-1052, June.
    11. Konstantinos Theodoridis & Francesco Zanetti, 2016. "News shocks and labour market dynamics in matching models," Canadian Journal of Economics, Canadian Economics Association, vol. 49(3), pages 906-930, August.
    12. Normann Rion, 2020. "Fluctuations in a Dual Labor Market," PSE Working Papers halshs-02570540, HAL.
    13. Kolasa, Marcin & Rubaszek, Michał, 2015. "Forecasting using DSGE models with financial frictions," International Journal of Forecasting, Elsevier, vol. 31(1), pages 1-19.
    14. Loria, Francesca & Matthes, Christian & Wang, Mu-Chun, 2022. "Economic theories and macroeconomic reality," Journal of Monetary Economics, Elsevier, vol. 126(C), pages 105-117.
    15. Christian Bayer & Ralph Luetticke, 2019. "Shocks, Frictions, and Inequality in US Business Cycles," 2019 Meeting Papers 256, Society for Economic Dynamics.
    16. Copaciu, Mihai & Nalban, Valeriu & Bulete, Cristian, 2015. "R.E.M. 2.0, An estimated DSGE model for Romania," Dynare Working Papers 48, CEPREMAP.
    17. Mumtaz, Haroon & Zanetti, Francesco, 2012. "Neutral technology shocks and employment dynamics: results based on an RBC identification scheme," Bank of England working papers 453, Bank of England.
    18. Böhl, Gregor & Strobel, Felix, 2020. "US business cycle dynamics at the zero lower bound," IMFS Working Paper Series 143, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    19. Mertens, Elmar, 2023. "Precision-based sampling for state space models that have no measurement error," Journal of Economic Dynamics and Control, Elsevier, vol. 154(C).
    20. Giovanni Ganelli & Juha Tervala, 2020. "Welfare Multiplier of Public Investment," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 68(2), pages 390-420, June.

    More about this item

    Keywords

    DSGE models; unit roots; endogenous growth; symbolic computation;
    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:bno:worpap:2021_18. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nbgovno.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.