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dc.contributor.authorPosch, Olafen_US
dc.contributor.authorTrimborn, Timoen_US
dc.description.abstractWe propose a simple and powerful method for determining the transition process in continuous-time DSGE models under Poisson uncertainty numerically. The idea is to transform the system of stochastic differential equations into a system of functional differential equations of the retarded type. We then use the Waveform Relaxation algorithm to provide a guess of the policy function and solve the resulting system of ordinary differential equations by standard methods and fix-point iteration. Analytical solutions are provided as a benchmark from which our numerical method can be used to explore broader classes of models. We illustrate the algorithm simulating both the stochastic neoclassical growth model and the Lucas model under Poisson uncertainty which is motivated by the Barro-Rietz rare disaster hypothesis. We find that, even for non-linear policy functions, the maximum (absolute) error is very small.en_US
dc.publisherWirtschaftswiss. Fak., Leibniz Univ. Hannoveren_US
dc.relation.ispartofseriesDiskussionspapiere der Wirtschaftswissenschaftlichen Fakultät // Wirtschaftswissenschaftliche Fakultät, Leibniz Universität Hannover 450en_US
dc.subject.keywordContinuous-time DSGEen_US
dc.subject.keywordOptimal stochastic controlen_US
dc.subject.keywordWaveform Relaxationen_US
dc.subject.stwDynamisches Gleichgewichten_US
dc.subject.stwStochastischer Prozessen_US
dc.titleNumerical solution of continuous-time DSGE models under poisson uncertaintyen_US
dc.typeWorking Paperen_US
Appears in Collections:Diskussionspapiere, Wirtschaftswissenschaftliche Fakultät, Universität Hannover

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