Information from the course leader
Welcome to the course Applied Econometrics, 7.5 hp!
This course is a collaboration with Uppsala University. All education and examination will be held at Uppsala University.
You will find more updated information about the course if you click on the link below.
Registration at SLU:
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Register for the course at SLU in Ladok Student. If there is a problem contact the administration at SLU firstname.lastname@example.org. Registration at SLU is open 2021-12-27 – 2022-01-09. After registration closes, we send a registration list to Uppsala University so they can register you manually. Please remember to register as soon as possible.
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Additional course evaluations for NA0172
Academic year 2020/2021Applied Econometrics (NA0172-30196) 2021-02-18 - 2021-03-23
Academic year 2019/2020Applied Econometrics (NA0172-30174) 2020-02-20 - 2020-03-24
Academic year 2018/2019Applied Econometrics (NA0172-30203) 2019-02-21 - 2019-03-25
Academic year 2017/2018Applied Econometrics (NA0172-30058) 2018-02-15 - 2018-03-20
NA0172 Applied Econometrics, 7.5 CreditsApplied Econometrics
Education cycleMaster’s level
Advanced study in the main fieldSecond cycle, only first-cycle courses as entry requirements(A1N)
Prior knowledgeKnowledge equivalent of 180 credits, of which 90 in Economics.
ObjectivesThe aim of this course is to give students advanced practice of how to conduct empirical economic research. After having taken the course, students should have an advanced understanding of causal inference, and be able to compare, implement and interpret different methods used to estimate causal effects.
ContentThe course will cover multivariate regression, nonlinear regression, panel data, instrumental variables, regression discontinuity designs, and differences between experimental and quasi-experimental methods. The course will also cover ways to deal with econometric problems which often arise in applied work, such as missing values, multiple outcomes, non-random samples and outliers. The course will also discuss different philosophies and approaches to causal inference, including the potential outcomes framework, reduced form estimation and structural estimation. The course will cover basic to advanced statistical programming.
Formats and requirements for examinationWritten exam.
- If the student fails a test, the examiner may give the student a supplementary assignment, provided this is possible and there is reason to do so.
- If the student has been granted special educational support because of a disability, the examiner has the right to offer the student an adapted test, or provide an alternative assessment.
- If changes are made to this course syllabus, or if the course is closed, SLU shall decide on transitional rules for examination of students admitted under this syllabus but who have not yet passed the course.
- For the examination of a degree project (independent project), the examiner may also allow the student to add supplemental information after the deadline. For more information on this, please refer to the regulations for education at Bachelor's and Master's level.
- The right to take part in teaching and/or supervision only applies to the course date to which the student has been admitted and registered on.
- If there are special reasons, the student may take part in course components that require compulsory attendance at a later date. For more information on this, please refer to the regulations for education at Bachelor's and Master's level.