Risk Matters: Breaking Certainty Equivalence in Linear Approximations
58 Pages Posted: 18 May 2018 Last revised: 29 Oct 2020
Date Written: September 2020
In this paper we use the property that certainty equivalence, as implied by a first-order approximation to the solution of stochastic discrete-time models, breaks in its equivalent continuous-time version. We study the extent to which a first-order approximated solution built by perturbation methods accounts for risk. We show that risk matters economically in a real business cycle (RBC) model with habit formation, and capital adjustment costs and that neglecting risk leads to substantial pricing errors. A first-order approximation in continuous time reduces pricing errors by 90 percent relative to the certainty equivalent linear solution.
Keywords: Certainty equivalence, Perturbation methods, Pricing errors
JEL Classification: C02, C61, C63, E13, E32, G12
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