A STUDY OF THE EFFECT OF DATA TRANSFORMATION AND «LINEARIZATION» ON TIME SERIES
FORECASTS. A PRACTICAL APPROACH
Alexandros E. Milionis
Bank of Greece and University
of the Aegean
Nikolaos G. Galanopoulos
Bank of Greece (Trainee) and University
of the Aegean
ABSTRACT
Very often in actual macroeconomic time series there are causes that
disrupt the underlying stochastic process and their treatment is known as
«linearization». In addition, variance non-stationarity is in many cases also
present in such series and is removed by proper data transformation. The impact
of either (data transformation - linearization) on the quality of forecasts has
not been adequately studied to date. This work examines their effect on
univariate forecasting considering each one separately, as well as in
combination, using twenty of the most important time series for the Greek
economy. Empirical findings show a significant improvement in forecasts’ confidence
intervals, but no substantial improvement in point forecasts. Furthermore, the combined
transformation-linearization procedure improves substantially the non-normality
problem encountered in many macroeconomic time series.
JEL Classification: C22, C51,
C53, C87
Keywords: applied time series analysis, time series
«linearization», time series transformation, outliers, forecasting of
macroeconomic time series.
Ackowledgements: The authors are grateful to H. Gibson and the referee for helpful comments. The views expressed in the paper are those of the
authors and do not necessarily reflect those of the Bank of Greec
Correspondence:
Alexandros
E. Milionis
Bank
of Greece,
Directorate
of Statistics
21 E.
Venizelos Avenue,
Athens
GR 102 50
e-mail:
amilionis@bankofgreece.gr