A large number of microsimulation models have been developed in Italy over the past years. Only few of them have been created to study specific regional contexts. This paper illustrates the development and validation of TREMOD, a new “static” tax-benefit microsimulation model for the Italian province of Trento. TREMOD is based on the EUROMOD platform and is proposed as an ex-ante evaluation model applicable to local taxation and welfare policies. The main strength of TREMOD is the high quality of the data used. The input database has been obtained by matching data from a local representative survey on households' life conditions with administrative data on individual income tax returns. This aspect is one of the main strengths of TREMOD compared with other experiences in microsimulation modelling. As shown in this paper, the combination of survey and administrative data yields substantial gains in simulation precision.

Developing and validating regional microsimulation models. TREMOD: the tax-benefit model of the Italian province of Trento

Azzolini, Davide;Bazzoli, Martina;De Poli, Silvia;Fiorio, Carlo;
2017-01-01

Abstract

A large number of microsimulation models have been developed in Italy over the past years. Only few of them have been created to study specific regional contexts. This paper illustrates the development and validation of TREMOD, a new “static” tax-benefit microsimulation model for the Italian province of Trento. TREMOD is based on the EUROMOD platform and is proposed as an ex-ante evaluation model applicable to local taxation and welfare policies. The main strength of TREMOD is the high quality of the data used. The input database has been obtained by matching data from a local representative survey on households' life conditions with administrative data on individual income tax returns. This aspect is one of the main strengths of TREMOD compared with other experiences in microsimulation modelling. As shown in this paper, the combination of survey and administrative data yields substantial gains in simulation precision.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/308908
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