Using Microsimulation to Optimize an Income Transfer System Towards Poverty Reduction

Seppo Sallila ()

Journal of Artificial Societies and Social Simulation, 2010, vol. 13, issue 1, 1

Abstract: In this study, a static microsimulation model SOMA is used to optimize Finland's tax-benefit legislation to alleviate poverty or at least to reduce it significantly. The method is a classical optimization method using a greed optimization strategy. This means an iterative process, where only one poverty diminishing parameter is changed by 10% from its earlier value at each iteration. Expenses are also optimized to reduce inequality as measured by the Gini-coefficient. Revenues and expenses are balanced at every iteration. Certain parameters of social assistance were found to be the most effective in reducing poverty. However by raising substantially the basic unemployment benefit, basic pensions, housing benefits and study grants - leaving social assistance untouched - poverty was reduced by under 50 percent. This means that social assistance is still required to reduce poverty further. Costs are most effectively financed by raising capital income tax.

Keywords: Inequality; Optimization; Poverty; Public Policy; Simulation Methodology; Tax-Benefit System (search for similar items in EconPapers)
Date: 2010-01-31
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.jasss.org/13/1/1/1.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:jas:jasssj:2008-2-3

Access Statistics for this article

More articles in Journal of Artificial Societies and Social Simulation from Journal of Artificial Societies and Social Simulation
Bibliographic data for series maintained by Francesco Renzini ().