  This study simulates the evolution of artificial economies in order to
understand the tax relevance of administrative boundaries in the quality of
life of its citizens. The modeling involves the construction of a computational
algorithm, which includes citizens, bounded into families; firms and
governments; all of them interacting in markets for goods, labor and real
estate. The real estate market allows families to move to dwellings with higher
quality or lower price when the families capitalize property values. The goods
market allows consumers to search on a flexible number of firms choosing by
price and proximity. The labor market entails a matching process between firms
(location) and candidates (qualification). The government may be configured
into one, four or seven distinct sub-national governments. The role of
government is to collect taxes on the value added of firms in its territory and
invest the taxes into higher levels of quality of life for residents. The model
does not have a credit market. The results suggest that the configuration of
administrative boundaries is relevant to the levels of quality of life arising
from the reversal of taxes. The model with seven regions is more dynamic, with
higher GDP values, but more unequal and heterogeneous across regions. The
simulation with only one region is more homogeneously poor. The study seeks to
contribute to a theoretical and methodological framework as well as to
describe, operationalize and test computer models of public finance analysis,
with explicitly spatial and dynamic emphasis. Several alternatives of expansion
of the model for future research are described. Moreover, this study adds to
the existing literature in the realm of simple microeconomic computational
models, specifying structural relationships between local governments and
firms, consumers and dwellings mediated by distance.
