Applied Econometrics
Course evaluation
Additional course evaluations for NA0172
Academic year 2024/2025
Applied Econometrics (NA0172-30232)
2025-02-20 - 2025-03-24
Academic year 2023/2024
Applied Econometrics (NA0172-30333)
2024-02-15 - 2024-03-19
Academic year 2022/2023
Applied Econometrics (NA0172-30135)
2023-02-16 - 2023-03-21
Academic year 2021/2022
Applied Econometrics (NA0172-30213)
2022-02-18 - 2022-03-23
Academic year 2020/2021
Applied Econometrics (NA0172-30196)
2021-02-18 - 2021-03-23
Academic year 2019/2020
Applied Econometrics (NA0172-30174)
2020-02-20 - 2020-03-24
Academic year 2018/2019
Applied Econometrics (NA0172-30203)
2019-02-21 - 2019-03-25
Academic year 2017/2018
Applied Econometrics (NA0172-30058)
2018-02-12 - 2018-03-25
Syllabus and other information
Syllabus
NA0172 Applied Econometrics, 7.5 Credits
Applied EconometricsSubjects
Economics EconomicsEducation cycle
Master’s levelModules
Title | Credits | Code |
---|---|---|
Single module | 7.5 | 0201 |
Advanced study in the main field
Second cycle, has only first-cycle course/s as entry requirementsMaster’s level (A1N)
Grading scale
The grade requirements within the course grading system are set out in specific criteria. These criteria must be available by the course start at the latest.
Language
EnglishPrior knowledge
Knowledge equivalent of 180 credits, of which 90 in Economics.Objectives
The 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.
Content
The 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.
Grading form
The grade requirements within the course grading system are set out in specific criteria. These criteria must be available by the course start at the latest.Formats and requirements for examination
Written exam.
If a student has failed an examination, the examiner has the right to issue supplementary assignments. This applies if it is possible and there are grounds to do so.
The examiner can provide an adapted assessment to students entitled to study support for students with disabilities following a decision by the university. Examiners may also issue an adapted examination or provide an alternative way for the students to take the exam.
If this syllabus is withdrawn, SLU may introduce transitional provisions for examining students admitted based on this syllabus and who have not yet passed the course.
For the assessment of an independent project (degree project), the examiner may also allow a student to add supplemental information after the deadline for submission. Read more in the Education Planning and Administration Handbook.
Other information
The right to participate in teaching and/or supervision only applies for the course instance the student was admitted to and registered on.
If there are special reasons, students are entitled to participate in components with compulsory attendance when the course is given again. Read more in the Education Planning and Administration Handbook.
Responsible department
Department of Economics
Further information
Litterature list
- Stock, James H.; Watson, Mark W., Introduction to econometrics, Fourth edition, global edition, Harlow, Pearson, [2020]*
* Compulsory