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

Timing

Annually in the first period

Learning outcomes

After the course, the student should

Know the main properties and limitations of the linear regression model

Be familiar with the basics of asymptotic analysis

Be able to employ the linear regression model and related inferential methods in empirical research

Completion methods

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.

Prerequisites

Basic studies in mathematics and statistics, and familiarity with the linear regression model to the extent covered in a Bachelor-level introductory econometrics course.

Recommended optional studies

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

Contents

This course introduces the basic methods used in the linear regression analysis of economic variables. The classical finite sample theory and asymptotic analysis of the linear regression model as well as the necessary methodological tools required for these topics are covered. Specifically, the topics covered in the course include

Classical finite sample theory in the linear regression model

The basics of asymptotic theory

Asymptotic theory in the linear regression model

Autocorrelation, heteroskedasticity and dynamic regressors

Specification tests

Omitted variables, instrumental variables and the two-stage least squares estimator (2SLS)

Study materials and literature

Lecture slides and other material assigned by the lecturer

Activities and teaching methods in support of learning

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.

Assessment practices and criteria

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.