Decomposition Methods in the Social Sciences

Is the difference in wages between men and women (the gender wage gap) due to less labor market experience of women compared to men, or is it due to discrimination against women, for example because labor market experience of women is valued less than labor market experience of men? How much of the gender wage gap can be "explained" by differences in endowments such as education, skill, or experience? How much do changes in educational attainment and general trends in earnings inequality contribute to the change in the wage gap over time? How would test scores of pupils with and without migration background compare if there would be no differences in average socio-economic status? How much did de-unionization and the decline in real minimum wages contribute to rising wage inequality? How high would the mortality rate in country A be if it had the demographic composition of country B? Decomposition methods can help find answers to such and other questions by providing insights into the mechanics of group differentials (such as earnings differences between men and women). Based on methodological developments mostly in labor economics (and some parallel developments in demography), these methods are increasingly popular in various fields of the social sciences. The seminar introduces the statistical concepts of decomposition methods, provides an overview of various approaches, and makes students familiar with the application of the methods and the interpretation of their results. Theoretical inputs and practical exercises (using Stata) will be alternated throughout the course.

Course leader

Johannes Giesecke is professor of sociology at the Humboldt University in Berlin, Germany.
Ben Jann is professor of sociology at the University of Bern, Switzerland.

Target group

Participants will find the course useful if:

- they are applied quantitative social science researchers from universities, research units in government agencies, or other research institutions;
- they are PhD students or Postdocs in quantitative social sciences;
- they are advanced master students in quantitative social sciences.

Course aim

By the end of the course participants will:

- have an overview of the most common decomposition methods;
- know the strengths and weaknesses of the different approaches;
- can identify potential areas of application of the different approaches;
- have a good understanding of how the methods work;
- can apply the methods purposefully in the context of their own work;
- can interpret the results correctly.

Credits info

3 EC
Optional bookings:

- 3 ECTS credit points via the University of Cologne for enrolled PhD students (with proof of status) per Spring Seminar course for active participation (20 EUR administration fee).

Fee info

EUR 500: Student/PhD student rate

The rate includes the tuition fee, course materials, and coffee/tea breaks.
EUR 750: Academic/non-profit rate

The rate includes the tuition fee, course materials, and coffee/tea breaks.

Scholarships

None available