Examination of inequalities in Hungary by microsimulation in consistency with macro data

Effective decision making uses various databases including both micro and macro level datasets. In many cases it is a big challenge to ensure the consistency of the two levels. Different types of problems can occur and several methods can be used to solve them. The paper concentrates on the input al...

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Bibliographic Details
Published in:Society and economy 2016-12, Vol.38 (4), p.479-495
Main Authors: Cserhati, Ilona, Keresztely, Tibor, Takacs, Tibor
Format: Article
Language:English
Subjects:
Analysis
Consumption
Decision making
Economic growth
Equilibrium
Fiscal Politics / Budgeting
Households
Income distribution
Income inequality
Macroeconomics
Micro-Economics
Personal income
Population
Public administration
Society
Socio-Economic Research
Studies
Supranational / Global Economy
Tax reform
Taxation
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Summary:Effective decision making uses various databases including both micro and macro level datasets. In many cases it is a big challenge to ensure the consistency of the two levels. Different types of problems can occur and several methods can be used to solve them. The paper concentrates on the input alignment of the households’ income for microsimulation, which means refers to improving the elements of a micro data survey (EU-SILC) by using macro data from administrative sources. We use a combined micro-macro model called ECONS-TAX for this improvement. We also produced model projections until 2015 which is important because the official EU-SILC micro database will only be available in Hungary in the summer of 2017. The paper presents our estimations about the dynamics of income elements and the changes in income inequalities. Results show that the aligned data provides a different level of income inequality, but does not affect the direction of change from year to year. However, when we analyzed policy change, the use of aligned data caused larger differences both in income levels and in their dynamics.
ISSN:1588-9726
1588-970X
DOI:10.1556/204.2016.38.4.3