Job Mismatches: When People Don't Fit Their Jobs

Course content

What does it mean if a person works a job that does not fit her or him, and how does it come to that? The maybe best-known phenomenon in this regard is overqualification, which is widely accepted as costly challenge in Western countries.

Many highly qualified (immigrants) work at jobs that are far below their educational level. But the opposite phenomenon, underqualification, exists as well; a fair share of the less educated work at jobs that typically require more education than they have. Apart from education, there are further types of job mismatches. Some work at firms that have a work culture which is too competitive for their taste.

Others would like to work more or less hours a week than they are required to. The degree to which persons and fit may be unfitting is thus multi-dimensional. How do we measure job mismatches, how do they come about, and which socio-demographic groups are particularly likely to be mismatched? These and further questions will be tackled in this seminar.

Education

MA Research Methodology and Practice (MSc Curriculum 2015)

Course package:

Welfare, Inequality and Mobility
Culture, lifestyle and everyday life
Knowledge, organisation and politics
 

Creditstudents must be at master level

 

Learning outcome

Knowledge:

  • Overview of theoretical literature in the area of job mismatches, such as statistical discrimination theory or theory of non-cognitive skills.
  • Overview of methods used in the literature on job-mismatches, such as correspondence tests, meta-analysis, multilevel models, panel regression.

 

Skills:

  • Students will be able to read and comprehend advanced analyses of job mismatches.
  • Students will be able assess research designs and evaluate their pitfalls and strengths.

 

 Competences:

  • Students should be able to formulate own ideas about how job mismatches come about.
  • Students should be able to formulate own ideas about the consequences of job mismatches.
  • Students should be able to propose research designs to test their ideas and hypotheses about drivers of job mismatches.
  • Students should be able to write an empirical study.
  • Students should be able to give brief presentations of advanced research results.

Lectures, class discussions, student presentations, a final paper that consists of an empirical analysis of the (Danish) European Social Survey data. Students are expected to contribute actively to discussion of core theoretical-analytical tools as well as the more specific analytical examples and studies.

Readings are comprised primarily of peer-reviewed journal articles. The syllabus will consist of roughly 700 pages of reading.

Strong English skills and good comprehension of quantitative research methods, especially multiple regression. All lacks of skills can be compensated by hard work and interest. This course will not introduce students to quantitative methods in a formal sense, but discuss their applications in detail. This course also does not introduce students to the European Social Survey.

Individual

I give structured feedback to student presentations, drafts of the final paper and to the final paper. Moreover, students get informal feedback to their ideas and arguments during class discussions.

ECTS
7,5 ECTS
Type of assessment
Written assignment
Individual/group.
A written take-home essay is defined as an assignment that addresses one or more questions. The exam is based on the course syllabus, i.e. the literature set by the teacher. The written take-home essay must be no longer than 10 pages.
For group assignments, an extra 5 pages is added per additional student. Further details for this exam form can be found in the Curriculum and in the General Guide to Examinations at KUnet.
Marking scale
7-point grading scale
Censorship form
No external censorship
Criteria for exam assessment

Please see the learning outcome.

  • Category
  • Hours
  • Lectures
  • 28
  • Course Preparation
  • 75
  • Preparation
  • 16
  • Exam Preparation
  • 71
  • Exercises
  • 16
  • English
  • 206