Analýza mezd a vybraných ukazatelů v zemích OECD

The research database consists of the OECD countries except Iceland, Latvia and Turkey, which were excluded because of insufficient data. The primary objective of the study is to group the countries according to their average wage, GDP per capita, minimum wage and unemployment rate. Another objectiv...

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Bibliographic Details
Main Author: Diana Bílková
Format: Article in Journal/Newspaper
Language:unknown
Subjects:
Online Access:http://polek.vse.cz/doi/10.18267/j.polek.1231.html
http://polek.vse.cz/doi/10.18267/j.polek.1231.pdf
Description
Summary:The research database consists of the OECD countries except Iceland, Latvia and Turkey, which were excluded because of insufficient data. The primary objective of the study is to group the countries according to their average wage, GDP per capita, minimum wage and unemployment rate. Another objective, of no less importance, is to determine which of the three remaining above variables significantly affect the average wage, while defining the type and strength of this relationship. Yet another important goal is to develop forecasts of the wage level and GDP per capita for each OECD country by 2020. In terms of clustering OECD countries by the four variables, the Czech Republic always ranks alongside Chile and three post-communist countries, Estonia, Hungary and Poland. GDP per capita is the only explanatory variable significantly affecting the average wage. The dependence of these two variables is represented by a second-order polynomial (concave parabola), the selected regression parabola explaining approximately 88 percent of the variability in the observed levels of the average annual wage. The conversion of the average wage, GDP per capita and minimum wage to purchasing power parity allows consideration of different price levels and thus comparison of purchasing power parity of the population in different countries. wages in OECD countries, GDP in OECD countries, cluster analysis, Ward's method, Euclidean distance, stepwise regression