ABSTRAKThe thesis is a continuing forecast stiy of the two biggest taxes managed by
Indonesian?s Directorate General of Tax (Ditjen Paak)--lncome Taxes (PPh) and
Value Added Tax (PPN). In addition, the respond hopes to assist any revenue forecaster
on forecast analysis by introducing new conventional and unconventional ways.
Currently, the Ministry of Finance (DepKeu), in this case represented by
Ditjen Pajak and Agency for Fiscal Analysis (BAF) is responsible for revenue
forecasting in Indonesia. The existing forecasting practices used by Ditjen Pajak and
BAF based on a linear relationship between tax revenue and the macroeconomic
aggregates such as GDP, inflation rate, exchange rate, and others. This approach
seems to lack the fundamental economic relation that needs to show in any fiscal
forecasting. The best alternative and common international practice is to relate tax
revenue with its proxy base. For example, logically national consumption can act as a
reliable PPN?s base. As people increasingly consume goods and services, then PPN,
which is a tax on final domestic consumptiOn, will also increase. The economic theory
behind the movement can also assist any forecaster. For example, an increase in say
PPN rate will definitely affect the revenue. However, questions such as, the
eflèctivenesS of the rate change needs to be addressed. A good revenue forecaster
should take into account any changes in economic behavior.
The thesis employs the most commOn method of revenue forecasting
technique--Baseline forecasting, which is estimating of future revenues based on
current laws andlor decrees. The two types of baseline forecasting are macro models
(aggregate models) and micro models. For PPh, the report will only forecast macro
models, because of lack of ?good and unbiased micro database (i.e., a clean and
sufficient tax return database). On the other hand, PPN?s forecast analysis will have
both micro model and macro model, because of its sufficient micro and macro
databases.
The macro methodologies for PPh are elasticity, time-series model, and
monitoring, whereas the macro models for PPN are only time-series model and
monitoring. A regression analysis between tax receipt and GDP is practiced to find
the elasticity. The elasticity model will employ a stable relationship between the
growth of tax receipts and tir growth in the tax base. In addition, a dummy variable is
used to discover whether a tax reform has any impact on revenue collection. By using
the estimated of tax elasticity and forecasted growth rate of the tax base, a forecast of
the change in tax revenue can be obtained by simply multiplying the growth rate in
the tax base by the elasticity. The elasticity approach is feasible if there have been no
changes in the tax system (in rates, exemptions, and compliance) during a sufficiently
long period to permit estimation of its value. An alternative way is to discard the
concepts of tax elasticity and buoyancy and the economic basis of the revenue
equations in general. The new method is a time series analysis that will use a
regression analysis to exploit trends and correlations in the series of data for revenue
and the proxy base, including the autocorrelation in the tax revenue series. It does not
involve the assumption of an absence of tax changes, and it requires modest types and
qualities of data. The monitoring system works as a measurement of administrative
efficiency.
Estimating the PPh?s elasticity, the writer employs annual PPh?s data from
1984 to 1997, by taking into account the 1994 as the tax reform year. The results on
the pPh?s elasticity, the multiple regression analysis shows a linear relationship
between independent variables in the modeI?multicollinearity problem. This is
indicated by a relatively high R2 in the regression equation with few significant t
statistics. The presence of multicollinearity implies that there is no effect of 1994 tax
refbrm in PPh collection. The new estimated PPh elasticity of tax revenue with its
proxy base will not take into account the 1994 tax reform (i.e. GDP).
The time series model for both PPh and PPN will be a regression time series
model, which will utilize a quarterly data from 1989 to 2000. The model provides a
more sophisticated description of cause-and-effect relationship between the taxes and
their proxy bases (i.e. GDP for PPh and national consumption for PPN) and the
random matute of the process that generated the sample observations of the two taxes.
The result for PPh shows a significant relationship between PPh and GÐP. However,
the PPN?s result looks logically inconsistent with no significant relationship between
PPN and national consumption.. PPN?s regression time series model is not a fit model.
The monitoring analysis for both PPh and PPN serves as a management tool
that Ditjen Pajak can employ. It provides a flmdarnental inputs to both short- and
Long-term Ditjen Pajak planning.
PPN is the only tax that can accommodate micro model. The writer employs a
micro data that is input-output table, a statistical framework of indonesian economic
activities in a given period. Later, the writer will estimate the PPNs base before
estimating future revenue.
me shortcomings are lack of in depth economic study, statisticai problems
(e.g. multicollinearity, simultaneous equation problem, low confidence interval, and
fimited number of observations), and lack of scenario adjustments (e.g. impact of
WTC incident on the tax revenue).
The recommendations to counter these shortcomings are:
1. Setup the economic framework that accompanies any revenue forecasting
analysis.
2. Expand the number observations to stabilize the elasticity3s multiple regression
model and regression time series model.
3. Setup a clean and reliable tax revenue database, which includes discretionary
changes eflèct for tax revenue.
4. Setup a statistics of income database, a database of sample of tax return. This is
important for niicrosiniulation modeling.
5. Includes performance targeting measurement, such as audit rate, percentage of
collection, and others as a monitoring tool.
6. Setup a sepaiate database for personal and corporate income taxes. These two
taxes have very different characters.
7. Take into account any endogenous and exogenous adjustments.
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