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This is the study programme for 2019/2020. It is subject to change.


The purpose of this course is to provide students with an introduction to econometrics and basic competence in applying statistical methods as a scientific tool in the analysis of practical economic problems. The course will begin with a brief review of basic statistics and data analysis before moving into the core material, which is the linear regression model. Students will learn to specify and estimate econometric models, interpret results, and uncover and correct for common statistical problems. The lectures will balance theory and mathematical derivations on the one hand and applications to real-world data sets on the other. The training received in this course can shape attractive job candidates, and the computer work will provide skills that can be taken directly into the workplace. All of the course materials, including lectures, assignments, and exams, are in English.

Learning outcome

Knowledge:
Upon completion of the course, students will:
  • Have a good knowledge of basic econometrics and statistical methods as a scientific tool in the analysis of practical economic problems
  • Be familiar with the basic methods of regression analysis

Skills:
At the end of the course, students should be able to:
  • Specify and estimate appropriate econometric models to test their research questions
  • Interpret and understand the estimation results
  • Uncover and correct common statistical problems in economic data and models
  • Balance theory and mathematical derivatives on the one hand and applications to real-world data sets on the other

General competence:
  • At the end of the course, students are expected to have a comprehensive understanding of basic regression methods and analysis

Contents

The main themes include (but are not limited to):
  • Simple and multiple regression models
  • Hypothesis testing
  • Model specification issues
  • Models with qualitative information
  • Heteroscedastic models
  • Instrumental variables estimation
  • Simultaneous equation models
  • An introduction to time series and panel data

Required prerequisite knowledge

Undergraduate Statistics and basic mathematics

Recommended previous knowledge

Undergraduate Microeconomics

Exam

Take-home assignment and In-class written exam
Weight Duration Marks Aid
Take-home assignment3/1030 hoursA - F
In-class written exam7/105 hoursA - FOpen book exam
Valid calculator.
Take-home exam (30%)
Individual exam based on Stata data analysis and interpretation of results. Scheduled at 8th week after lecture starts. Duration: 30 hours (one day)

In-class written exam (70%)
Individual exam. Duration: 5 hours. This is an open book exam. Students are allowed to bring only the reference book, in addition to calculator. Follow the university exam schedule.

Course teacher(s)

Casual teacher
Maximiliaan Willem Thijssen
Course teacher
Niaz Bashiri Behmiri , Andreea-Laura Cojocaru
Course coordinator
Yuko Onozaka

Method of work

The course will consist of weekly lectures and computer lab sessions. Students are expected to attend lectures and lab sessions. It is, therefore, students' responsibility to catch up with the materials they miss due to the absence. In addition to attendance at these sessions, students are expected to prepare and review the lecture materials (including the corresponding chapters in the textbook) on their own. Regular assignments (bi-weekly) typically include both conceptual and computer exercises using the econometric software Stata. The assignments are not for handing in, and detailed answer keys will be provided one week after the assignments are made available.
The expected workloads for this course are:
  • Lectures: 48 hours
  • Computer lab sessions: 24 hours
  • Assignments: 90 hours
  • Preparation and reviews of materials: 88 hours

TOTAL: 250 hours

Overlapping courses

Course Reduction (SP)
Methodology in Economic Analysis (MØA105_1) 5

Open to

Business Administration - Master of Science, Private

Also open to bachelor students who are considering applying for master/doctoral programs in economics in foreign institutions (e.g., USA, UK) upon approval from the instructor.  

Course assessment

Student evaluation will be carried out in accordance with the UiS Business School's evaluation system.

Literature

Introduction to Econometrics, Europe, Middle East & Africa Edition by Jeffrey M. Wooldridge


This is the study programme for 2019/2020. It is subject to change.

Sist oppdatert: 21.08.2019