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A Comparative Analysis of Household Incomes of People with Different Levels of Education in Poland and the USA

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  • Kamila Trzcińska
  • Elżbieta Zalewska

Abstract

Household income is one of the most important economic categories depending on various factors, in particular on the level of education of the head of the household. Salaries are treated as the market valuation of graduates made by employers. Hence, the question arises of how the education system affects the distribution of household income, in particular in the group of people with higher education. The aim of the article is to apply the Singh-Maddala model to describe the income distribution of people with primary, secondary and higher education in Poland and the USA. On the basis of numerical characteristics and measures of income inequality, the situation of education, in particular higher education, and its impact on household income in the analyzed countries were assessed. All analyzes were based on the Singh-Maddala model. The maximum likelihood method was used to estimate the model parameters. The analysis showed that the higher the level of education, the better the income situation of the household. In Poland, salaries in the group of people with higher education are the most unequal, while in the USA the greatest income inequalities occur in the group of people with primary education. The article describes the issue of household income distribution and income inequality, which is an important and current socio-economic problem. To describe and analyze the economic situation of household incomes of people with different levels of education in Poland and the USA statistical data from the Luxembourg Income Study Database (LIS) was used. Empirical studies conducted for different samples add significantly to existing knowledge on the topic.

Suggested Citation

  • Kamila Trzcińska & Elżbieta Zalewska, 2024. "A Comparative Analysis of Household Incomes of People with Different Levels of Education in Poland and the USA," LIS Working papers 877, LIS Cross-National Data Center in Luxembourg.
    • Handle: RePEc:lis:liswps:877
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    References listed on IDEAS

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    1. Francesca Greselin & Leo Pasquazzi & Ričardas Zitikis, 2013. "Contrasting the Gini and Zenga indices of economic inequality," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(2), pages 282-297, February.
    2. Craig C. Wu, 1977. "Education in Farm Production: The Case of Taiwan," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 59(4), pages 699-709.
    3. Singh, S K & Maddala, G S, 1976. "A Function for Size Distribution of Incomes," Econometrica, Econometric Society, vol. 44(5), pages 963-970, September.
    4. Jolliffe, Dean, 2002. "Whose Education Matters in the Determination of Household Income? Evidence from a Developing Country," Economic Development and Cultural Change, University of Chicago Press, vol. 50(2), pages 287-312, January.
    5. Fabio Clementi & Mauro Gallegati, 2005. "Pareto's Law of Income Distribution: Evidence for Grermany, the United Kingdom, and the United States," Microeconomics 0505006, University Library of Munich, Germany.
    6. Majumder, Amita & Chakravarty, Satya Ranjan, 1990. "Distribution of Personal Income: Development of a New Model and Its Application to U.S. Income Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(2), pages 189-196, April-Jun.
    7. Alberto Arcagni & Francesco Porro, 2013. "On the parameters of Zenga distribution," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(3), pages 285-303, August.
    8. Jamison, Dean T. & Moock, Peter R., 1984. "Farmer education and farm efficiency in Nepal: The role of schooling, extension services, and cognitive skills," World Development, Elsevier, vol. 12(1), pages 67-86, January.
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    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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