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Analýza mezd a vybraných ukazatelů v zemích OECD
[Analysis of Wages and Selected Indicators in OECD Countries]

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  • Diana Bílková

Abstract

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.

Suggested Citation

  • Diana Bílková, 2019. "Analýza mezd a vybraných ukazatelů v zemích OECD [Analysis of Wages and Selected Indicators in OECD Countries]," Politická ekonomie, Prague University of Economics and Business, vol. 2019(2), pages 133-156.
  • Handle: RePEc:prg:jnlpol:v:2019:y:2019:i:2:id:1231:p:133-156
    DOI: 10.18267/j.polek.1231
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    References listed on IDEAS

    as
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    7. Angeles, Luis, 2008. "GDP per capita or real wages? Making sense of conflicting views on pre-industrial Europe," Explorations in Economic History, Elsevier, vol. 45(2), pages 147-163, April.
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    More about this item

    Keywords

    wages in OECD countries; GDP in OECD countries; cluster analysis; Ward's method; Euclidean distance; stepwise regression;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E25 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Aggregate Factor Income Distribution

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