GRA 6650 Incentives, Wages and Labor Markets

GRA 6650 Incentives, Wages and Labor Markets

Course code: 
GRA 6650
Department: 
Economics
Credits: 
6
Program of study: 
Master of Science in Applied Economics
Course coordinator: 
Plamen Toshkov Nenov
Product category: 
Master
Portfolio: 
MSc in Applied Economics
Semester: 
2020 Spring
Active status: 
Active
Teaching language: 
English
Course type: 
One semester
Introduction

The labor market is probably the most important market in the economy, and a thorough understanding of how it works is important for an applied economist. This course will give students the knowledge and skills necessary to quantitatively analyze labor markets, wage determination, and human resource management. It will introduce students to recent trends in labor markets related to technological innovation (digitalization and automation) and globalization and the distributional and ethical challenges arising from those. It will cover topics related to personnel economics (recruiting and motivating workers and managers), discrimination, and theories of unemployment. It will cover examples of empirical data analysis associated with measuring wage discrimination and analyzing the productivity effects of changes in compensation schemes. We will also study numerical simulations of the aggregate labor market and conduct policy analysis using those.  

Learning outcomes - Knowledge

The course will provide students with comprehensive understanding of the labor market, wage determination, labor market incentives, and labor market policies. More specifically, students will gain knowledge about:

  • Labor supply, schooling decisions, and equilibrium wage determination;
  • Theories of labor market discrimination;
  • Personnel economics, incentives and contracts.
  • Theories of unemployment;
  • Recent trends in wage inequality;
  • Labor market policies and their effects on economic efficiency and equity. 
Learning outcomes - Skills

The course will provide skills necessary for conducting proper quantitative analysis of labor markets: These include:

  • Analytical skills: At the end of the course the students will be able to use economic analysis to study practical problems in wage formation, human resource management and labor market incentives, discrimination, and unemployment.
  • Data analysis using Stata: At the end of the course the students will know how to use Stata to empirically measure wage discrimination.
  • Simulations using Matlab: At the end of the course, the students will know how to use Matlab to simulate an aggregate labor market and study the unemployment effects of different public policies.
  • Presentation skills: The course will improve the presentation skills of the students.
General Competence
  • Students should develop an understanding of the main mechanisms that describe interactions in the labor market.
  • Students should be able to critically assess the underlying assumptions of the methods used.
  • Students should be able to evaluate the ethical challenges associated with labor market policies that have distributional effects.
Course content
  • Wage formation: labor supply, labor demand, and the theory of human capital;
  • Personnel economics and human resource management: incentives and compensation for workers and managers; analyzing the effects of changes in compensation schemes.
  • Discrimination: understanding and measuring discrimination in the labor market;
  • Wage inequality, employment, and the role of technology, computerization, and international trade;
  • Unemployment and public policy;
  • Labor market institutions, sustainability, and the distributional consequences of technology, gobalization, and labor market policies.
Teaching and learning activities

A course of 6 ECTS credits corresponds to a workload of 160-180 hours. 

Teaching activities include:

  • formal lectures;
  • practical exercises on the computer;
  • out-of-the-classroom discussions and consultations.
  • exercise sessions.

Learning activities include:

  • preparing with assigned readings and instructional content through other media (e.g. online videos) ahead of classroom sessions;
  • active participation in classroom discussions;
  • work on several voluntary problem sets, including computer exercises;
  • work on and delivery of an in-class presentation;
  • preparing for and taking the final written assessment.

Specific information regarding student assessment beyond the information given in the course description will be provided in class.

Software tools
Matlab
Stata
Additional information

Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class.

This is a course with continuous assessment (several exam components) and one final exam code. Each exam component is graded by using points on a scale from 0-100. The components will be weighted together according to the information in the course description in order to calculate the final letter grade for the examination code (course). Students who fail to participate in one/some/all exam elements will get a lower grade or may fail the course. You will find detailed information about the point system and the cut off points with reference to the letter grades when the course starts.

At resit, all exam components must, as a main rule, be retaken during the next scheduled course.

Required prerequisite knowledge

GRA 6626 and GRA 6039, or equivalent.

Exam categoryWeightInvigilationDurationSupport materialsGroupingComment exam
Exam category:
Activity
Form of assessment:
Presentation
Exam code:
GRA66501
Grading scale:
Point scale
Grading rules:
Internal examiner
Resit:
All components must, as a main rule, be retaken during next scheduled course
20No 1 Semester(s)Group ( 2 - 4)Presentations during the course. The presentation topics will be assigned in the beginning of the course. These will be based on current research and further discussions of the topics listed in the course content. Group size may vary depending on class size.
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
GRA66501
Grading scale:
Point scale
Grading rules:
Internal and external examiner
Resit:
All components must, as a main rule, be retaken during next scheduled course
80Yes3 Hour(s)
  • BI-approved exam calculator
  • Simple calculator
  • Bilingual dictionary
Individual Written examination under supervision. The written examination will include exercises and discussion questions covering the main topics from the course content.
Exams:
Exam category:Activity
Form of assessment:Presentation
Weight:20
Invigilation:No
Grouping (size):Group (2-4)
Support materials:
Duration: 1 Semester(s)
Comment:Presentations during the course. The presentation topics will be assigned in the beginning of the course. These will be based on current research and further discussions of the topics listed in the course content. Group size may vary depending on class size.
Exam code:GRA66501
Grading scale:Point scale
Resit:All components must, as a main rule, be retaken during next scheduled course
Exam category:Submission
Form of assessment:Written submission
Weight:80
Invigilation:Yes
Grouping (size):Individual
Support materials:
  • BI-approved exam calculator
  • Simple calculator
  • Bilingual dictionary
Duration:3 Hour(s)
Comment:Written examination under supervision. The written examination will include exercises and discussion questions covering the main topics from the course content.
Exam code:GRA66501
Grading scale:Point scale
Resit:All components must, as a main rule, be retaken during next scheduled course
Type of Assessment: 
Continuous assessment
Grading scale: 
ECTS
Total weight: 
100
Sum workload: 
0

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.