Fuzzy Approach to Short-Term Youth Unemployment Forecast

Abstract

The practical output of the paper is the prediction of the percentage of the short-term youth unemployment in the following two consecutive years. For this purpose, the non-traditional fuzzy model of the relevant prediction task is formulated in its theoretical-methodological part, which is subsequently applied in the application part. By means of the exact tools of the fuzzy approach (fuzzy sets and inference rules for manipulation with them), the synergy, uncertainty and complexity of the values (terms) of vaguely defined linguistic variables of an economic-psychological nature represented by sets of selected macroeconomic indicators is reflected. Despite the fact that the results of the fuzzy prediction are not significantly different from the results of conventional statistical prediction, the demonstration of the approach of the case of knowledgeable expertise to the choice of the relevant fuzzy sets and the formulation of the set of inference rules can be considered as a secondary benefit.

Fuzzy-based non-bankruptcy trend forecast

“…Its prediction is justified by the development of the historical part of influencing input values on which a target output vaguely depends -under these circumstances the fuzzy procedure was succesfully applied e.g. in [8]. − Under extreme conditions and/or the high uncertainty of input data the prognosis relies on the possible values of input variables specified by intervals; from this it is obvious that the prediction outcome is presented in the form of the interval of possible values.…”

“…It is clear that crisis impact, and the way the individual EU states get over, is going to be very uneven. How well and quickly the countries will pull together relies upon external and internal factors that individual economies face ( [12] [8]). The pandemic spread and the strictness of containment measures affects the future situation to a certain extend; nevertheless, a great role belongs to economic exposures, preexisting conditions and the policy responses [11].…”