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SSRN Electronic Journal
Article . 2024 . Peer-reviewed
Data sources: Crossref
EconStor
Research . 2023
Data sources: EconStor
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MaCGE-MOD: Malta’s Computable General Equilibrium Model

Authors: Ian P. Cassar; Nathaniel Debono; Stefano Deriu; Rosita Pretaroli; Noel Rapa; Francesca Severini; Claudio Socci;

MaCGE-MOD: Malta’s Computable General Equilibrium Model

Abstract

This paper introduces the latest addition to the modelling toolkit of the Central Bank of Malta: a static Computable General Equilibrium model for Malta named MaCGE-MOD. Developed through a collaboration with the University of Macerata, the model is a multiinput, multi-output and multi-sector model, calibrated on a Social Accounting Matrix which illustrates the income flows among production processes and institutional sectors in Malta. The model constitutes a set of equations which describe the circular flow of income in the economy and the behaviour of economic agents. It is a useful tool to determine ex ante the impacts of policy decisions or exogenous shocks once all the associated direct, indirect and induced effects have propagated through the economy. As it is based on a Social Accounting Matrix, the model can provide disaggregated sectoral analyses to complement analyses of the aggregate effects of policy-making scenarios or exogenous shocks. Thus, MaCGE-MOD can potentially be an important tool for policy makers to identify effects not easily discernible from the other aggregated models currently available.

Country
Italy
Keywords

Computable General Equilibrium, Social Accounting Matrix, Malta, simulations, sectoral analyses, ddc:330, Malta, E16, E17, Computable General Equilibrium, Social Accounting Matrix, C61, sectoral analyses, C68, H30, D58, simulations

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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!
0
Average
Average
Average
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