2018
DOI: 10.1016/j.econlet.2018.07.023
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DSGE Models with observation-driven time-varying volatility

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Cited by 6 publications
(6 citation statements)
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“…The heteroskedastic t-ABCD representation is a generalization of the homoskedastic Gaussian-ABCD representation of Fernández-Villaverde et al (2007) and the heteroskedastic score-driven Gaussian-ABCD representation of Angelini and Gorgi (2018). By assuming that t = and ν → ∞, we get the homoskedastic Gaussian-ABCD representation [Fernández-Villaverde et al (2007)].…”
Section: Heteroskedastic T-abcd Representationmentioning
confidence: 99%
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“…The heteroskedastic t-ABCD representation is a generalization of the homoskedastic Gaussian-ABCD representation of Fernández-Villaverde et al (2007) and the heteroskedastic score-driven Gaussian-ABCD representation of Angelini and Gorgi (2018). By assuming that t = and ν → ∞, we get the homoskedastic Gaussian-ABCD representation [Fernández-Villaverde et al (2007)].…”
Section: Heteroskedastic T-abcd Representationmentioning
confidence: 99%
“…Moreover, by assuming that t = , we get the new homoskedastic t-ABCD representation. In addition, we note that we provide the following contributions to the work of Angelini and Gorgi ( 2018): (i) Angelini and Gorgi (2018) assume that only the scale filter is score-driven. We use score-driven transition equation and scale filters.…”
Section: Heteroskedastic T-abcd Representationmentioning
confidence: 99%
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“…Hence, with respect to competitor PD models, the SD approach will benefit from the ease of estimation of the low dimensional vector of fix parameters. Due to these computational advantages, SD dynamics has been already employed in macroe- 2021), Angelini and Gorgi (2018), Blazsek et al (2019), Gorgi et al (2021). However, none of these works considers the problem of the identification of structural shocks and the theoretical properties of the OD models in relation to the Lucas Critique.…”
Section: Introductionmentioning
confidence: 99%