Using Microsimulation to Optimize an Income Transfer System Towards Poverty Reduction
AbstractIn 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.
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Bibliographic InfoArticle provided by Journal of Artificial Societies and Social Simulation in its journal Journal of Artificial Societies and Social Simulation.
Volume (Year): 13 (2010)
Issue (Month): 1 ()
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Inequality; Optimization; Poverty; Public Policy; Simulation Methodology; Tax-Benefit System;
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- Sutherland Holly, 2002. "Indicators for Social Inclusion in the European Union: the Impact of Policy Changes and the Use of Microsimulation Models," Politica economica, Società editrice il Mulino, issue 1, pages 117-120.
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