Global stochastic properties of dynamic models and their linear approximations

Ana Babus; Casper G. de Vries

The dynamic properties of micro based stochastic macro models are often analyzed through a linearization around the associated deterministic steady state. Recent literature has investigated the error made by such a deterministic approximation. Complementary to this literature we investigate how the linearization affects the stochastic properties of the original model. We consider a simple real business cycle model with noisy learning by doing. The solution has a stationary distribution that exhibits moment failure and has an unbounded support. The linear approximation, however, yields a stationary distribution with possibly a bounded support and all momentsfinite.

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Year of publication:	2010
Authors:	Babus, Ana ; Vries, Casper G. de
Publisher:	Rotterdam [u.a.] : Tinbergen Inst.
Subject:	Linearization \| ARCH process \| Real business cycles model \| Stochastic difference equation \| Real-Business-Cycle-Theorie \| Real business cycle model \| Stochastischer Prozess \| Stochastic process \| Dynamische Wirtschaftstheorie \| Economic dynamics \| Schätztheorie \| Estimation theory \| Zeitreihenanalyse \| Time series analysis