Structural estimation of jump-diffusion processes in macroeconomics

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Structural estimation of jump-diffusion processes in macroeconomics. / Posch, Olaf.

I: Journal of Econometrics, Bind 153, Nr. 2, 2009, s. 196-210.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

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Posch, Olaf. / Structural estimation of jump-diffusion processes in macroeconomics. I: Journal of Econometrics. 2009 ; Bind 153, Nr. 2. s. 196-210.

Bibtex

@article{9f7ea400a9c211dea554000ea68e967b,
title = "Structural estimation of jump-diffusion processes in macroeconomics",
abstract = "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.",
author = "Olaf Posch",
year = "2009",
doi = "10.1016/j.jeconom.2009.06.003",
language = "English",
volume = "153",
pages = "196--210",
journal = "Journal of Econometrics",
issn = "0304-4076",
publisher = "Elsevier BV",
number = "2",

}

RIS

TY - JOUR

T1 - Structural estimation of jump-diffusion processes in macroeconomics

AU - Posch, Olaf

PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

U2 - 10.1016/j.jeconom.2009.06.003

DO - 10.1016/j.jeconom.2009.06.003

M3 - Journal article

VL - 153

SP - 196

EP - 210

JO - Journal of Econometrics

JF - Journal of Econometrics

SN - 0304-4076

IS - 2

ER -