In this paper business cycles are considered as a multivariate phenomenon and not as a univariate one determined e.g. by the GNP. The subject is to look for the number of phases of a business cycle, which can be motivated by the number of clusters in a given dataset of macro-economic variables....

Tourism seasonality is the major characteristic of tourism industry, a well know but less understood phenomenon. Seasonal fluctuations of tourism demand are implying numerous negative implications affecting tourist destination, tourist operators and tourist demand. Almost every tourist...

The gender pay gap is a complex issue caused by a number of interrelated factors and has inevitable impact on the status of women in their economic and social life. The objectives of this paper are concentrated in investigating the sex-segregation by economic activity in the labour market and...

Regardless Adult participation in learning (APinL) indicator was by European Commission (2010) in Europe 2020 Strategy targeted with 15% by 2020, for European Union (EU) countries the respective percentage in 2017 was 10.9% only, with coefficient of variation of 70.4%. Recently it has been...

In this paper, the profitability indicators are analysed for the first hundred companies of the Croatian market, which are classified according to the net profit. The profitability indicators included in the analysis are the following: EBIT margin, EBITDA margin, net profit margin, return on...

Building homogenous classes is one of the main goals in clustering. Homogeneity can be measured by the intra-class variance (Bock, 1998). Especially in erosion projects but in other applications as well the separation between the built classes is as important as the homogeneity of the classes....

When analyzing business cycle data, one observes that the relevant predictor variables are often highly correlated. This paper presents a method to obtain measures of importance for the classification of data in which such multicollinearity is present. In systems with highly correlated variables...

The optimization of the hyper-parameters of a statistical procedure or machine learning task is a crucial step for obtaining a minimal error. Unfortunately, the optimization of hyper-parameters usually requires many runs of the procedure and hence is very costly. A more detailed knowledge of the...

Linear Discriminant Analysis (LDA) performs well for classifica- tion of business phases even though the premises of an LDA are not met. As the variables are highly correlated there are numerical as well as interpretational shortcomings. By transforming the classification problem to a regression...