Using a Sam-Based Model to Measure the Distributional Impacts of Government Policies
Susana Santos ()
No 2009/31, Working Papers Department of Economics from ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa
Abstract:
A Social Accounting Matrix (SAM) will be proposed as a working instrument for studying the (macro-)impacts of government policy on the distribution of income. A numerical version of the SAM, constructed from the System of National Accounts (SNA), will serve as the basis for the construction of an algebraic version of the same matrix for Portugal. To this end, a computable (numerically solvable) general (economy-wide) equilibrium (macroeconomic balance) approach will be adopted. A SAM-based model will be constructed, in which each cell is defined with a linear equation or system of equations, whose components are all the known and quantified transactions of the SNA, using parameters deduced from the numerical SAM that served as the basis for this model. A scenario will be defined and analysed from an experiment carried out in relation to the distributional impact of a reduction in the direct tax rate paid by households.
Date: 2009-09
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://pascal.iseg.utl.pt/~depeco/wp/wp312009.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:ise:isegwp:wp312009
Access Statistics for this paper
More papers in Working Papers Department of Economics from ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa Department of Economics, ISEG - Lisbon School of Economics and Management, Universidade de Lisboa, Rua do Quelhas 6, 1200-781 LISBON, PORTUGAL.
Bibliographic data for series maintained by Vitor Escaria ().