DRE 7051 Topics in Empirical Microeconomics II
This course deals with state-of-the-art empirical approaches used in several fields of applied microeconomics such as public economics, labor economics, health economics, urban economics, and political economics. Particular attention will be given to various experimental research designs as well as econometric methods for analyzing spatial and high-dimensional data. The course will also address good research practices and raise students’ awareness of the promise and pitfalls of certain types of empirical tools and data.
After having completed this course, students should have a strong and critical understanding of several state of the art methods employed in modern empirical microeconomics (e.g., randomized control trials, difference-in-differences, regression discontinuity designs, instrumental variable methods, event studies, bunching, text analysis, spatial econometric techniques). In addition, students will gain insight into good (and less good) research practices, into the evaluation of empirical research designs, and into ways to buttress the quality and reliability of their own empirical work.
After having completed this course, students should have developed skills on how to critically assess, defend and communicate their methodological choices in light of the data at hand. They should be able to use these skills to develop reliable and credible research designs for (field) experiments, to exploit natural experiments, and to deal with spatial and/or high-dimensional data structures.
Students are trained to pay particular attention to the benefits as well as downsides of state of the art empirical approaches in applied microeconomics.They also gain insight into the real-world application of these methods, as well as into when and how these methods can allow researchers to draw trustworthy (causal) inferences during their implementation.
- What makes a research design credible (or not)?
- Field experiments
- Natural experiments
- High-dimensional data
- Spatial econometrics
Lectures and in-class applications. Students are expected to participate actively in class.
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 confirmation letters will not be issued for sitting in on courses.
|Exam category||Weight||Invigilation||Duration||Grouping||Comment exam|
Form of assessment:
Examination when next scheduled course
|Form of assessment:||Written submission|
|Exam code:||DRE 70511|
|Resit:||Examination when next scheduled course|
Feedback activities and counselling
Student's own work with learning resources
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.