A stochastic estimated version of the Italian dynamic General Equilibrium Model (IGEM)

Nicola Acocella (), Giorgio Alleva, Elton Beqiraj, Giovanni Di Bartolomeo (), Fabio Di Dio (), Marco Di Pietro (), Francesco Felici and Brunero Liseo

No 3, Working Papers from Department of the Treasury, Ministry of the Economy and of Finance

Abstract: We estimate with Bayesian techniques the Italian dynamic General Equilibrium Model (IGEM), which has been developed at the Italian Treasury Department, Ministry of Economy and Finance, to assess the effects of alter-native policy interventions. We analyze and discuss the estimated effects of various shocks on the Italian economy. Compared to the calibrated version used for policy analysis, we find a lower wage rigidity and higher adjustment costs. The degree of prices and wages indexation to past inflation is much smaller than the indexation level assumed in the calibrated model. No substantial difference is found in the estimated monetary parameters. Estimated fiscal multipliers are slightly smaller than those obtained from the calibrated version of the model.

Keywords: Dynamic General equilibrium model; Bayesian estimation; simulation analysis; Italy (search for similar items in EconPapers)
JEL-codes: E27 E30 E60 (search for similar items in EconPapers)
Pages: 42
Date: 2018-04
New Economics Papers: this item is included in nep-dge, nep-eec and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.dt.mef.gov.it/export/sites/sitodt/modul ... x_3_-_APRIL_2018.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:itt:wpaper:2018-3

Access Statistics for this paper

More papers in Working Papers from Department of the Treasury, Ministry of the Economy and of Finance Contact information at EDIRC.
Bibliographic data for series maintained by Michele Petrocelli ( this e-mail address is bad, please contact ).