DRE 7006 Panel Data/ Microeconometrics
This is an advanced econometric course on specification, estimation, and inference based on microeconometric data. The course covers regression analysis with panel data and other techniques useful for making causal inference with non-experimental data.
After having completed this course, students should be able to critically discuss different estimation strategies in the context of models that include unobserved individual (firm, person, etc.) effects.They should be familiar with the potensial outcome framework and microeconomics methods useful for policy analysis using non-experimental data. Students should be able to implement these methods using statistical software (STATA).
1. Ordinary least squares (OLS) estimation (W 4)
2. Basic Panel data models (W 10)
a. Pooled OLS/ Random effects
b. Fixed effects/ First-differencing
3. Difference in differences estimator (W 6.5 )
4. Dynamic panel data models (W 11.6)
5.Treatment effects estimation (W 21)
a. Selection on observables
b. Instrumental variable methods
c. Regression discontinuity designs
Enrollment in 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 enrollment in a PhD programme when signing up for a course. Other candidates may be allowed to sit in on courses by approval of the course leader. Sitting in on a course does not permit registration for the course, 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:
Internal and external examiner
Examination when next scheduled course
|Form of assessment:||Written submission|
|Resit:||Examination when next scheduled course|
|Workload activity||Duration||Type of duration||Comment student effort|
|Group work / Assignments||75||Hour(s)||Specified learning activities (including reading).|
|Self study||75||Hour(s)||Autonomous student learning (including exam preparation)|
|Workload activity:||Group work / Assignments|
|Comment:||Specified learning activities (including reading).|
|Workload activity:||Self study|
|Comment:||Autonomous student learning (including exam preparation)|
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.