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Symbolic Stationarization of Dynamic Equilibrium Models

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  • 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
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    File URL: https://hdl.handle.net/11250/2835495
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    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. Diego Comin & Mark Gertler, 2006. "Medium-Term Business Cycles," American Economic Review, American Economic Association, vol. 96(3), pages 523-551, June.
    6. Canova, Fabio, 2014. "Bridging DSGE models and the raw data," Journal of Monetary Economics, Elsevier, vol. 67(C), pages 1-15.
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    Keywords

    DSGE models; unit roots; endogenous growth; symbolic computation;
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