Wage Level as One of the Most Important Indicators of the Quantitative Aspect of the Standard of Living of the Population and Selected Indicators of Economic Maturity in OECD Member Countries

Abstract

The present paper focuses on the comparison of wage levels across OECD countries, the research data coming from an official OECD website. The following eight variables are employed in this study – the average wage, minimum wage, GDP per capita, tertiary education attainment, employment ratio, trade unions, labour productivity and inflation rate. The average wage represents the main explained variable in regression and correlation analysis, the remaining seven variables being used as potential explanatory ones. In order to compare living standards in different countries, average and minimum wages as well as per capita GDP data were adjusted to relative purchasing power parity. The principal objective was to identify which explanatory variables statistically significantly affect the average wage. The analysis showed that only three of them – namely the employment ratio, GDP per capita and labour productivity – have a significant effect at a 5% statistical level. The regression hyperplane with a forward stepwise selection was applied. Nine clusters of OECD countries were created based on both all the eight variables and four of them selected in regression analysis (the average wage and three explanatory ones) with the aim to identify the countries that coexist in the same cluster. Ward's method and Euclidean distance are utilized in cluster analysis, the number of clusters being determined with the use of the Dunn index. The study also aims at the prediction of the average wage by 2022, which was made via exponential smoothing of time series. (The greatest purchasing power is reported by Luxembourg, Switzerland, Iceland, the U.S., the Netherlands, Denmark, Norway and Austria, the highest average wage growth rate by 2022 being expected in the Baltic and some other post-communist countries.)