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  • This paper shows how to solve and estimate a continuous-time dynamic stochastic general equilibrium (DSGE) model with jumps. It also shows that a continuous-time formulation can make it simpler (relative to its discrete-time version) to compute and estimate the deep parameters using the likelihood function when non-linearities and/or non-normalities are considered. We illustrate our approach by solving and estimating the stochastic AK and the neoclassical growth models. Our Monte Carlo experiments demonstrate that non-normalities can be detected for this class of models. Moreover, we provide strong empirical evidence for jumps in aggregate US data. (xsd:string)
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?:dateModified
  • 2009 (xsd:gyear)
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  • 2009 (xsd:gyear)
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  • 10.1016/j.jeconom.2009.06.003 ()
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  • en (xsd:string)
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  • 2 (xsd:string)
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  • Structural estimation of jump-diffusion processes in macroeconomics (xsd:string)
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  • Zeitschriftenartikel (xsd:string)
  • journal_article (en)
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  • GESIS-SSOAR (xsd:string)
  • In: Journal of Econometrics, 153, 2009, 2, 196-210 (xsd:string)
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  • urn:nbn:de:0168-ssoar-255082 ()
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  • 153 (xsd:string)