Wage differentials over time among young adults educated in 2007
An important trend in the Norwegian labor market over the past two decades is the rising wage inequality, with particularly low wage growth in the lowest decile, see Greier and Grini (2018). Wage differences appear to occur at a "fertile" age.
In order to take a closer look at this, in this study, we are organizing a panel dataset that makes it possible to follow people over time with regard to (real) monthly salary and other characteristics related to the individual. The study is based on Statistics Norway's wage statistics and includes data for the years 2008 to 2018. Wages include cash benefits for work performed, and does not include overtime allowances, benefits in kind, insurance, board fees or the like. For the years 2015-2018, the data base is a total count of all employed persons, while for the years 2008-2014 there is a partial sample survey, with a total count for persons employed in the public sector and a sample survey for persons employed in the private sector.
In order to identify groups of "fertile age", we select people who completed their highest education in 2007 and who do not take further education of significance for the next ten years. In addition, the sample is constrained to include only persons who were less than 28 years in the year they completed their education. We then follow these people over time and observe wage developments and other characteristics of the persons, including occupation.
Based on a simple regression model for wage mobility from 2008 to 2018, we look at the correlation between how much one climbs in the wage distribution as a whole, and a number of characteristics of the individual. The characteristics include level of education, potential work experience, number of children in three different age groups, indicator variables that capture workplace centrality, marital status, immigrant background, number of jobs and dummy variables for occupation. The results show that people in the sample with particularly low wage growth are characterized by having a short education and working in specific occupations. The professions primarily include hairdressers, shop sellers, kindergarten and school assistants, nursing staff, security workers, car, taxi and van drivers, cleaners, and travel agency, reception and other information workers. Other calculations we carry out show that employees in these occupations in our sample also have low pay at the beginning of their professional career. The results thus indicate that persons in these occupations are particularly at risk of having persistently low wages.
Men with immigrant backgrounds climb somewhat less in the wage distribution than men with two Norwegian-born parents. For women, we find no significant difference in wage mobility between women with two Norwegian-born parents and others. People with many jobs climb somewhat less in the wage distribution than people with few working conditions. Here we have not made a distinction between whether one has several jobs at the same time or whether one has changed work place over time.
To get an indication of when wage differences occur during the ten-year follow-up period, we also make some illustrative and counterfactual calculations that illustrate the average real wage level in different occupations and years for a specific group of people, see Appendix B. The calculations illustrate that there are significant differences in wage levels and wage profiles for employees in various occupations.