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Risky Linear Approximations

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  • Alexander Meyer-Gohde

Abstract

I construct risk-corrected approximations of the policy functions of DSGEmodels around the stochastic steady state and ergodic mean that are linear in the state variables. The resulting approximations are uniformly more accurate than standard linear approximations and capture the dynamics of asset pricing variables such as the expected risk premium missed by standard linear approximations. The algorithm is fast and reliable, requiring only the solution of linear equations using standard perturbation output. I examine the joint macroeconomic and asset pricing implications of a real business cycle model with stochastic trends and recursive preferences. The method is able to estimate risk aversion under these preferences using the Kalman filter, where a standard linear approximation provides no information and alternative methods require computationally intensive particle filters subject to sampling variation.

Suggested Citation

  • Alexander Meyer-Gohde, 2014. "Risky Linear Approximations," SFB 649 Discussion Papers SFB649DP2014-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  • Handle: RePEc:hum:wpaper:sfb649dp2014-034
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    Cited by:

    1. Matthias Meier & Timo Reinelt, 2020. "Monetary Policy,Markup Dispersion, and Aggregate TFP," CRC TR 224 Discussion Paper Series crctr224_2020_161, University of Bonn and University of Mannheim, Germany.
    2. Grzegorz R. Dlugoszek, 2016. "Solving DSGE Portfolio Choice Models with Asymmetric Countries," SFB 649 Discussion Papers SFB649DP2016-009, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Jump, Robert Calvert & Levine, Paul, 2019. "Behavioural New Keynesian models," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 59-77.
    4. Walter Pohl & Karl Schmedders & Ole Wilms, 2018. "Higher Order Effects in Asset Pricing Models with Long‐Run Risks," Journal of Finance, American Finance Association, vol. 73(3), pages 1061-1111, June.

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    More about this item

    Keywords

    DSGE; Solution methods; Ergodic mean; Stochastic steady state; Perturbation;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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