Global stochastic properties of dynamic models and their linear approximations

A Babus; Casper de Vries

doi:10.1016/j.jedc.2010.02.001

Global stochastic properties of dynamic models and their linear approximations

A Babus
, Casper de Vries

Economics

Research output: Contribution to journal › Article › Academic › peer-review

1 Citation (Scopus)

Abstract

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 errors 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 moments finite. (C) 2010 Elsevier B.V. All rights reserved.

Original language	Undefined/Unknown
Pages (from-to)	817-824
Number of pages	8
Journal	Journal of Economic Dynamics and Control
Volume	34
Issue number	5
DOIs	https://doi.org/10.1016/j.jedc.2010.02.001
Publication status	Published - 2010

Bibliographical note

babus10

Research programs

EUR ESE 01

Access to Document

10.1016/j.jedc.2010.02.001

http://hdl.handle.net/1765/18600

Cite this

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AB - 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 errors 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 moments finite. (C) 2010 Elsevier B.V. All rights reserved.

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