Real-time forecast of DSGE models with time-varying volatility in GARCH form

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dc.authoridCekin, Semih Emre/0000-0003-4637-3112
dc.authoridLee, Chien-Chiang/0000-0003-0037-4347
dc.contributor.authorCekin, Semih Emre
dc.contributor.authorIvashchenko, Sergey
dc.contributor.authorGupta, Rangan
dc.contributor.authorLee, Chien-Chiang
dc.date.accessioned2025-02-20T08:42:19Z
dc.date.available2025-02-20T08:42:19Z
dc.date.issued2024
dc.departmentTürk-Alman Üniversitesien_US
dc.description.abstractRecent research shows that time -varying volatility plays a crucial role in non-linear modeling. Contributing to this literature, we suggest an approach that allows for straightforward computation of DSGE models with timevarying volatility, where the volatility component is formulated as a GARCH process. As an application of our approach, we examine the forecasting performance of this DSGE-GARCH model using euro area real-time data. Our findings suggest that the DSGE-GARCH approach is superior in out -of -sample forecasting performance in comparison to various other benchmarks for the forecast of inflation rates, output growth and interest rates, especially in the short term. Comparing our approach to the widely used stochastic volatility specification using in -sample forecasts, we also show that the DSGE-GARCH is superior in in -sample forecast quality and computational efficiency. In addition to these results, our approach reveals interesting properties and dynamics of time -varying correlations (conditional correlations).
dc.identifier.doi10.1016/j.irfa.2024.103175
dc.identifier.issn1057-5219
dc.identifier.issn1873-8079
dc.identifier.scopus2-s2.0-85188437829
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.irfa.2024.103175
dc.identifier.urihttps://hdl.handle.net/20.500.12846/1644
dc.identifier.volume93en_US
dc.identifier.wosWOS:001218037100001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Science Inc
dc.relation.ispartofInternational Review of Financial Analysis
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250220
dc.subjectDSGEen_US
dc.subjectForecastingen_US
dc.subjectGARCHen_US
dc.subjectStochastic volatilityen_US
dc.subjectConditional correlationsen_US
dc.titleReal-time forecast of DSGE models with time-varying volatility in GARCH form
dc.typeArticle

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