Browsing by Subject "wage inequality"

The returns to human capital has been in the core of research in labor economics. Education and particularly years of schooling as a measurement of human capital has gained established status among researchers. Cognitive skills as a measurement of human capital is a rather rare variable in research. The absence of relevant, valid and comparable data concerning skills and cognitive proficiency has reduced the amount of research concerning the relationship between earnings and cognitive proficiency. Thanks to the OECD, a new survey of adults’ skills, PIAAC, is publicly available and includes data on surveyed individuals’ cognitive skills, education and earnings among other things in more than 40 countries representing the whole population of the countries. This enables extensive analysis on the relationship between earnings and cognitive skills. In this thesis the relationship between cognitive skills and earnings inequality is analyzed using a decomposition method on the dataset of PIAAC. The implementation of this thesis is sort of a replication of a study by Blau and Kahn (2005). The core of their study was to investigate if cognitive skills explain the higher wage inequality in the US compared to other countries. This thesis studies the relationship between earnings and skills inequality and analyzes if cognitive skills explain higher wage inequality in the UK compared to other countries. Due to country specific restrictions in the earning variables, some of the countries could not be included into my sample, for instance the US is missing. The UK is thus set as the base country in the country-specific comparisons of differences in wage inequality. The model used for these comparisons is a full distributional accounting method, also known as a decomposition method, which was originally created by Juhn, Murphy and Pierce (1993). The advantage of the decomposition method is that it enables the differences in wage inequality to be decomposed into different components at any desired point of the wage distribution. Under examination in this thesis are the 90-10, 90-50 and 50-10 wage gaps across countries by gender. The final sample comprises 21 countries and includes part- and full-time workers aged 16 to 65. The main question in this thesis is partly to replicate the study of Blau and Kahn (2005) and to see if the results on returns to skills and the decomposition model are similar to the results of Blau and Kahn (2005). Based on the results, some of the findings are surprisingly close to the findings of Blau and Kahn and some of the results quite different. The regression results prove a remarkable heterogeneity in estimated returns to skills and estimated returns to education across countries. A one standard deviation increase in numeracy test scores is associated with approximately a 4.8 to 15.3 percent wage rise for men across countries when education is controlled in the regression, while the corresponding associated return for women is approximately a 4.9 to 13.8 percent wage rise across countries. The estimated return to skills for men is surprisingly close to results of Blau and Kahn (2005), as they found the corresponding associated wage rise to vary from 5.3 to 15.9 percent, using a different dataset, IALS, which is a previous version of PIAAC. Estimated returns to education are remarkably high compared to estimated returns to numeracy test scores. Across countries, a one standard deviation increase in years of schooling is associated approximately with a 8.7 to 25.0 percent increase in wages for men, while for women the associated returns are between an 11.7 and 34.7 percent increase in wages. The corresponding findings of Blau and Kahn (2005) are a 4.8 to 16.8 percent wage rise for men and a 6.8 to 26.6 percent wage rise for women. Opposite to the results found in this thesis, Blau and Kahn found almost similar associated returns on wages for both education and IALS test scores, however this was only for men. For women, they found that the difference between the returns to education and returns to IALS test scores is notable. Based on the results in this thesis, there is a striking difference between the returns to education and the returns to skills, for both women and men. There is also a notable difference between women and men in returns to education. Education plays a more important role in explaining wages compared to cognitive skills, and women have even higher returns to education than men have. Based on the results of the decomposition model, in most occasions the unobservable characteristics and prices i.e. the residual inequality, explains most of the higher wage inequality between the UK and the other countries (or the lower inequality between the UK and the other country). This finding is partly in line with the findings of Blau and Kahn (2005), as they concluded that along with prices of characteristics i.e. returns to skills and education, the residual inequality weighs more in explaining the higher wage inequality in the US compared to other countries. Opposite to the findings of Blau and Kahn (2005), my results point out that the differences in observed prices of characteristics i.e. returns to observed skills and education does not play that big of a role in explaining the differences in wage inequality between the UK and other countries. Instead of prices, the second largest factor explaining wage inequality is the observed characteristics. Based on the decomposition results, distribution of skills does matter more than the prices of skills. Obviously Blau and Kahn (2005) did not have the same collection of countries in their dataset and the US was their base country, not the UK, hence the comparison must be done with caution. Nevertheless, based on the decomposition results in this thesis, the distribution of skills and residual inequality matters more than the prices of skills and education in explaining the higher inequality in the UK (or the lower inequality of the UK in some cases), though residual inequality plays the most important role in explaining the differences in wage inequality.