ECON4137 – Applied Micro Econometrics

Course content

This course covers core micro-econometric methods and the principles of causal inference. The course builds upon and extends the material covered in ECON4150 – Introductory Econometrics. The course will review ordinary least squares and two-stage least squares regressions and specification issues from ECON4150. Building on the potential outcomes framework, we will discuss the interpretation of these estimators in case of heterogeneous treatment effects. We further cover regression discontinuity designs, basic panel data, difference-in-differences, maximum likelihood estimation and binary and multinomial choice models. Both experimental and quasi-experimental approaches to causal inference and program evaluation will be covered.

The emphasis will be on developing a solid understanding of the underlying econometric principles of the methods taught, as well as on their empirical application. Theory, background and examples will be covered in lectures, while the exercises given in seminars will allow students to apply the theory to practical examples using R. Students are expected to prepare for seminars in addition to working on these exercises in the seminars.

Learning outcome

Knowledge

You should know

  • the formal and practical aspects of important microeconometric methods for causal inference.
  • when and how to apply core methods of causal inference and these methods’ limitations.
  • how to evaluate model specification.

Skills

You should be able to

  • apply core methods of causal inference taught in the course on real economic data using R.
  • interpret R output.

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Competence

You should be able to

  • read, understand and evaluate project reports and journal articles that make use of the methods that are introduced in the course.
  • make use of the course content in your own academic work, for example in analyses that are part of the master’s thesis.

Admission to the course

Students admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for in Studentweb.

Students not admitted to the Master’s programme in Economics or the Master’s programme in Economic Theory and Econometrics (Samfunns?konomisk analyse), can apply for admission to one of our study programmes, or apply for guest student status.

Formal prerequisite knowledge

Overlapping courses

Teaching

Lectures and seminars.

At the start of the semester, the course reponsible can update the syllabus list by replacing up to 3 articles, without the scope and thematic content of the syllabus changing significantly.

The syllabus also includes any lecture notes that are made available during the semester.

Examination

A 3-hour written school exam.

Previous exams

Exam papers with comments from examiner

Examination support material

Resources allowed: Open book examination, where all printed and written resources are allowed. There is a digital scientific calculator available in Inspera.

Please note: You are not allowed to bring your own calculator. We strongly advise you to familiarize yourself with the digital calculator here: https://www.desmos.com/scientific

Language of examination

The examination text is given in English, and you submit your response in English.

Grading scale

Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.

Resit an examination

If you are sick or have another valid reason for not attending the regular exam, we offer a postponed exam later in the same semester.

See also our information about resitting an exam.

Students who wish to take the exam again in a later semester are not guaranteed that the course will be given with the same content and syllabus, or that the form of assessment will be the same.

More about examinations at UiO

You will find further guides and resources at the web page on examinations at UiO.

Last updated from FS (Common Student System) Dec. 21, 2024 8:17:51 AM

Facts about this course

Level
Master
Credits
10
Teaching
Spring
Examination
Spring
Teaching language
English