Clar, M., Duque, J.C. and Moreno, R. (2007), "Forecasting business and consumer surveys indicators. A time series models competition", Applied Economics, 39, 20: 2565 - 2580.
Abstract: The objective of this article is to compare different time-series methods for
the short-run forecasting of Business and Consumer Survey Indicators. We
consider all available data taken from the Business and Consumer Survey
Indicators for the Euro area between 1985 and 2002. The main results of the
forecast competition are offered not only for raw data but we also consider
the effects of seasonality and removing outliers on forecast accuracy. In most
cases, the univariate autoregressions were not outperformed by the other
methods. As for the effect of seasonal adjustment methods and the use of data
from which outliers have been removed, we obtain that the use of raw data has
little effect on forecast accuracy. The forecasting performance of qualitative
indicators is important since enlarging the observed time series of these
indicators with forecast intervals may help in interpreting and assessing the
implications of the current situation and can be used as an input in
quantitative forecast models.
