Econometrics

ECN402 Econometrics

Autumn 2018

Spring 2019
  • Topics

    The course introduces regression analysis applied to cross-sectional data, panel data and time-series data. Instrumental variables techniques to solve a potential endogeneity problem will also be taught. The course will focus on applications of the econometric techniques and on practical and empirical examples.

    • the simple regression model
    • multiple regression analysis
    • panel data techniques
    • time-series analysis
    • instrumental variable techniques

  • Learning outcome

    After completing this course, students should:

    • be able to interpret the results of empirical analyses and to be able to choose between competing regression models
    • be able to conduct quantitative analysis where several factors can affect an outcome variable simultaneously
    • understand what assumptions econometric models are based on
    • be able to use STATA for doing econometric analysis, produce do-files and log-files, import data from excel, and produce tables and figures.
    • be able to interpret and critically deal with empirical work in applied econometrics
    • know the structure and requirements for a master thesis, and be able to develop a research question
    • be able to choose and apply an appropriate scientific method for analysing the research question
    • understand the ethical issues in collection and interpretation of data
    • have a good background for more advanced econometric courses

  • Teaching

    16 lectures/classes and 5 practical computer sessions where the students learn the use of the econometric software STATA. The first computer session introduces Stata, and in the 4 remaining sessions the students will get help in solving an assignment. Students need to bring their own computer. Two of the four assignments must be submitted in order to get course approval. Assignments may be submitted, in groups of 3-4 students, and some feedback on the assignments will be given. Assignments, must be written in English.

  • Recommended prerequisites

    Basic knowledge about statistics

  • Credit reduction due to overlap

    ECN 402 is a renaming of the previous ECO402, and you will not get credit for both courses. ECN402 can not be combined with BUS444, BUS444E, BAN431, FIE401A/FIE401B or FIE449, due to similarities - and you will not get credit for both courses.

  • Requirements for course approval

    Two of four assignments must be submitted and approved in order to get course approval. Assignments may be submitted, in groups of 3-4 students, and some feedback on the assignments will be given. Assignments must be written in English.

    Students with previous results in ECN402OPPG og ECN402EKS do not need to obtain course approval.

  • Assessment

    One final written school exam of four (4) hours.

  • Grading Scale

    Grading scale A - F.

  • Computer tools

    Econometric software package STATA

  • Literature

    Jeffrey M. Wooldridge (2016): Introductory Econometrics: A Modern Approach, 6th edition. Some additional material will be distributed on Itslearning.

Overview

ECTS Credits
7.5
Teaching language
English
Semester

Autumn and spring.  Offered Autumn 2018

Course responsible

Autumn 2018:  Course responsible professor Øivind A. Nilsen, Department of Economics

Lecturers: Øivind Anti Nilsen and assistant professor Patrick Bennett, Department of Economics