DRE 7050 Topics in Empirical Microeconomics I

DRE 7050 Topics in Empirical Microeconomics I

Course code: 
DRE 7050
Department: 
Economics
Credits: 
3
Course coordinator: 
Vasilis Sarafidis
Course name in Norwegian: 
Topics in Empirical Microeconomics I
Product category: 
PhD
Portfolio: 
PhD Economics courses
Semester: 
2023 Spring
Active status: 
Active
Level of study: 
PhD
Teaching language: 
English
Course type: 
One semester
Introduction

The aim of the course is to give the students a thorough understanding of selected topics in empirical microeconomics. Selection of topics will depend on the instructor of the course. In Spring 2023 we will cover topics in panel data analysis, other than those studied in DRE 7006, such as dynamic panel data analysis and common factor models.

Learning outcomes - Knowledge

After having completed this course, students should be able to have an understanding of how panel data can be used to analyse complex problems and control for unobserved heterogeneity. In addition, students will have knowledge on how modern software can be used to analyse big data and turn the results into an easily interpretable format.

Learning outcomes - Skills

After having completed this course, students should be able to undertake rigorous panel data analysis and critically evaluate different estimation approaches in the context of the model at hand. Furthermore, students will develop skills on how to communicate these results to a broader audience.

General Competence

Panel data modelling is a broad area that combines economic theory, mathematics and statistical inference. Being a statistical tool, it relies on a set of assumptions that are not always met in some real-world settings. Upon completion of this course, students will be aware of the limitations of panel data analysis and how these can influence the final results in a research project.

Course content
  1. Introduction to panel data analysis
  2. Dynamic models
  3. Heterogeneous panels
  4. Mixed models
  5. Cross-sectional dependence
  6. Limited dependent variable models

 

Teaching and learning activities

Lectures, in-class applications, computer exercises, problem sets.

Software tools
Matlab
Stata
Qualifications

Admission to a PhD Programme is a general requirement for participation in PhD courses at BI Norwegian Business School.

External candidates are kindly asked to attach confirmation of admission to a PhD programme when signing up for a course with the doctoral administration. Other candidates may be allowed to sit in on courses by approval of the course leader. Sitting in on courses does not permit registration for courses, handing in exams or gaining credits for the course. Course certificates or conformation letters will not be issued for sitting in on courses

Exam categoryWeightInvigilationDurationGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
DRE 70501
Grading scale:
Pass/fail
Grading rules:
Internal examiner
Resit:
Examination when next scheduled course
100No1 Week(s)Individual
Exams:
Exam category:Submission
Form of assessment:Written submission
Weight:100
Invigilation:No
Grouping (size):Individual
Duration:1 Week(s)
Comment:
Exam code:DRE 70501
Grading scale:Pass/fail
Resit:Examination when next scheduled course
Type of Assessment: 
Ordinary examination
Total weight: 
100
Student workload
ActivityDurationComment
Teaching
15 Hour(s)
Feedback activities and counselling
3 Hour(s)
Student's own work with learning resources
42 Hour(s)
Examination
20 Hour(s)
Sum workload: 
80

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 3 ECTS credit corresponds to a workload of at least 80 hours.