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Economic Modelling
Article . 2020 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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A stochastic estimated version of the Italian dynamic General Equilibrium Model

Authors: Nicola Acocella; Elton Beqiraj; Giovanni Di Bartolomeo; Marco Di Pietro; Francesco Felici; Giorgio Alleva; Fabio Di Dio; +1 Authors

A stochastic estimated version of the Italian dynamic General Equilibrium Model

Abstract

Abstract This paper aims at identifying the main drivers of the Italian economic cycle. To this end, we estimate a small-open economy model based on a dual labor market, which captures the main features of the Italian economy. Our results indicate that labor market rigidities are important structural features of the Italian economy, but they provide a limited contribution in explaining the business cycle fluctuations. Long-term dynamics are mostly driven by supply factors (productivity and markups). However, demand factors, including monetary and fiscal policies, play a sizeable role in the short run. Policy experiments show that expansionary fiscal policies crowd out private consumption and investment. The paper also contributes to the recent debate on fiscal consolidation. Estimated fiscal multipliers support the view that plans aimed at reducing the public debt should be based on tax increases rather than expenditure cuts.

Country
Italy
Keywords

Bayesian estimation; Medium scale; DSGE model; Fiscal tools

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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