Kaisa_2012_3_photo by Veikko Somerpuro

Enrol

Timetable

Here is the course’s teaching schedule. Check the description for possible other schedules.

DateTimeLocation
Tue 10.3.2020
14:15 - 15:45
Thu 12.3.2020
14:15 - 15:45
Tue 17.3.2020
14:15 - 15:45
Thu 19.3.2020
10:15 - 11:45
Thu 19.3.2020
14:15 - 15:45
Tue 24.3.2020
14:15 - 15:45
Thu 26.3.2020
14:15 - 15:45
Tue 31.3.2020
14:15 - 15:45
Thu 2.4.2020
10:15 - 11:45
Thu 2.4.2020
14:15 - 15:45
Tue 7.4.2020
14:15 - 15:45
Thu 16.4.2020
10:15 - 11:45
Thu 16.4.2020
14:15 - 15:45
Tue 21.4.2020
14:15 - 15:45
Thu 23.4.2020
10:15 - 11:45
Thu 23.4.2020
14:15 - 15:45
Fri 8.5.2020
10:00 - 12:00
Fri 29.5.2020
10:00 - 12:00

Description

Master’s Programme in Economics (Research track). Open also to doctoral students in economics.

Advanced Econometrics 1 and 2

Knowledge of R (or some other matrix programming language) is useful.

After the course, the student should know the basic properties and limitations of the microeconometric models discussed, and be able to implement them in empirical research. The course also works as a foundation for more advanced methodological and applied courses in microeconometrics.

Annually in the fourth period

This course covers a number of central models and methods employed in modern microeconometric research. The emphasis is on different types of dependent variables and data structures (cross section and panel data). In addition, the basic ideas of causal inference are briefly discussed. Specifically, the topics covered in the course include binary and discrete dependent variable models, limited dependent variable models, panel data models, duration models, and causal inference.

Lecture slides and other material assigned by the lecturer

All material related to the course is delivered through the Moodle area of the course, which also contains a discussion forum where students can discuss issues related to the course with each other and the teacher.

The grade on a scale from 0 (fail) to 5 is based on the points earned in the final exam. At least 40% of the homework assignments must be completed to take the exam.

Please note! Registration only through Aalto Universitys' Weboodi. Read more and apply for the study right at Aalto via this link.

The course consists of lectures (24 hours) and exercise sessions (8 hours), where solutions to the homework assignments are discussed. The lectures and exercise sessions are not mandatory. The course is completed by (i) a written final exam and (ii) homework assignments. The homework assignments consist of both analytical and empirical exercises.