Main tax credits of PIT are related to housing: 15% tax credit on the interest mortgage
and capital (with a maximum of 9, 000 e). Other tax credits are applied to business activities.
From January 2008, 10.05% of the rent paid on the main home can be deducted, provided
that the taxable income is less than 24, 020e per year. Tax liabilities and tax credits are
shared by the central government and the regional-level administration at percentages of
67% and 33% respectively. Finally, although PIT has an individual nature, joint-returns are
also permitted by aggregating the incomes of each member in the family.
5.2 Data and the micro-simulation model
The empirical analysis is based on a very large data set of a million of tax payers containing
fiscal information from the 2004 Spanish Income Tax File-Return. The database is supplied
by the I.E.F. ‘Instituto de Estudios Fiscales’ to researchers. The sample contains almost 200
variables related to fiscal information of tax-payers and their relatives.
Stratitification of the sample (1176 stratas) has been carried out by province, income base
and the type of tax-return (individual and joint tax returns). Richest recipients have been
oversampled in order to get a better description of the highest part of income distribution.
Grossing-up factors are derived from the stratification scheme and they are used to estimate
population totals and other statistics from the sample (see Picos et al., 2007).
SIMESP is a static micro-simulation model for modeling reforms on PIT. As a static
model, it does not simulate behavior responses to changes in tax policies. Its output is
interpreted as short-term of first-round effect of the policy changes, but by using the large
data set mentioned before on administrative records, SIMESP takes advantage of the huge
heterogeneity regarding personal and demographic characteristics of the tax-payer popula-
tion. The model is able to providee some dynamic analysis projecting the monetary variable
of the models. Computation of variables, tax and income distributions and statistical indices
are grossed-up by means of the sampling weights in order to obtain population aggregates.
To interpret the empirical section we should first point out the following issues. Our
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