Publications - Olaf Posch en-us PURE Extension (Web Department) 30 <![CDATA[Peso problems in the estimation of the C-CAPM]]> Parra-Alvarez, J. C., Posch, O., Schrimpf, A. This paper shows that the consumption-based capital asset pricing model (C-CAPM) with low-probability disaster risk rationalizes pricing errors. We find that implausible estimates of risk aversion and time preference are not puzzling if market participants expect a future catastrophic change in fundamentals, which just happens not to occur in the sample (a “peso problem”). A bias in structural parameter estimates emerges as a result of pricing errors in quiet times. While the bias essentially removes the pricing error in the simple models when risk-free rates are constant, time-variation may also generate large and persistent estimated pricing errors in simulated data. We also show analytically how the problem of biased estimates can be avoided in empirical research by resolving the misspecification in moment conditions.

Forskning Sat, 01 Jan 2022 14:34:43 +0100 179eeeea-26ee-4faf-adfc-9178b5e77172
<![CDATA[Risk matters]]> Parra-Alvarez, J. C., Polattimur, H., Posch, O. 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 derive a risk-sensitive first-order perturbation solution for a general class of rational expectations models. 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 perturbation provides a sensible approximation to the effects of risk in continuous-time models. It reduces pricing errors by around 90% relative to the certainty equivalent linear approximation.

Forskning Wed, 01 Dec 2021 14:34:43 +0100 89f45e86-0061-4578-8e65-6bfd39c1c1b8
<![CDATA[Estimating dynamic equilibrium models using mixed frequency macro and financial data]]> Christensen, B. J., Posch, O., Van Der Wel, M. We provide a framework for inference in dynamic equilibrium models including financial market data at daily frequency, along with macro series at standard lower frequency. Our formulation of the macro-finance model in continuous time conveniently accounts for the difference in observation frequency. We suggest the use of martingale estimating functions (MEF) to infer the structural parameters of the model directly through a nonlinear scheme. This method is compared to regression-based methods and the generalized method of moments (GMM). We illustrate our approaches by estimating various versions of the AK-Vasicek model with mean-reverting interest rates. We provide asymptotic theory and Monte Carlo evidence on the small sample behavior of the estimators and report empirical estimates using 30 years of US macro and financial data.

Forskning Thu, 01 Sep 2016 14:34:43 +0200 c31819ef-998c-4e01-8265-cedc61545bba
<![CDATA[Numerical solution of dynamic equilibrium models under Poisson uncertainty]]> Posch, O., Trimborn, T. Forskning Tue, 01 Jan 2013 14:34:43 +0100 cac4b902-a00c-44c2-bde9-bb364e9c9f8a <![CDATA[Explaining output volatility]]> Posch, O. Forskning Sat, 01 Jan 2011 14:34:43 +0100 f9cbe300-ee60-4a7d-b280-785fca6c3077 <![CDATA[On the link between volatility and growth]]> Posch, O., Wälde, K. Forskning Sat, 01 Jan 2011 14:34:43 +0100 471d15b1-82d4-4a6e-9565-8795eeb2a83b <![CDATA[Risk premia in general equilibrium]]> Posch, O. Forskning Sat, 01 Jan 2011 14:34:43 +0100 3025750a-84d2-4764-ab0a-2156a432945c <![CDATA[Structural estimation of jump-diffusion processes in macroeconomics]]> Posch, O. Forskning Thu, 01 Jan 2009 14:34:43 +0100 9f7ea400-a9c2-11de-a554-000ea68e967b