BUS444E Econometrics for Business Research

• Topics

  Modern companies produce large amounts of data. These data can be valuable both as inputs to internal management and for analysts outside the company. The objective of this course is to give students an introduction to econometric methods useful for analyzing data, and particularly to estimate causal effects. Students will learn basic tools for quantifying and interpreting economic relationships.

  The course mixes practical work with data in the software package R and a theoretical treatment of econometrics. Throughout, the emphasis is on the skills needed to do high-quality data analysis in practice, and to competently interpret other people's data analysis. Practical experience in uploading data, creating tables and running regressions is a crucial part of this, and therefore covered in the course. But the most difficult part of econometrics is to know how to interpret regression results. This requires a thorough conceptual understanding. Although we use formal and rigorous reasoning, the mathematics involved is quite basic. 

• Learning outcome

  After completing the course, students will be familiar with the Ordinary Least Squares (OLS) estimator and some related methods. Students will be able to interpret and explain results from econometric studies, and be able to conduct econometric studies of their own.

  After completing the course, students can:

  Knowledge

  • Explain the assumptions underlying causal inference and regression analysis.
  • Describe the role of causal diagrams and identification strategies in empirical research.
  • Distinguish between prediction and estimation of causal effects.

  Skills

  • Formulate empirical research questions and design feasible strategies to answer them.
  • Draw causal diagrams for empirical studies and use them to evaluate research design.
  • Apply core econometric methods (e.g., OLS and common quasi-experimental designs) to estimate causal effects.
  • Collect, organize, and analyze cross-sectional and panel data.
  • Present empirical findings clearly to both technical and non-technical audiences.

  General Competence

  • Assess whether regression results support a causal interpretation.
  • Critically evaluate the strengths and weaknesses of empirical research designs, including through the use of causal diagrams.
  • Communicate evidence-based recommendations in academic and applied contexts.
  • Structure and carry out an independent empirical project, such as a master’s thesis 

• Teaching

  The teaching consists of lectures and student activities (problem sets, data exercises, discussion).

• Recommended prerequisites

  Basic knowledge of mathematics, probability and statistics, as acquired in a Business or Economics undergraduate degree. 

  Knowledge of R is not required.

• Credit reduction due to overlap

  The course cannot be combined with ECN402, BAN431, BUS444, BUS444N, or FIE401(A/B)

• Compulsory Activity

  Compulsory assignments:

  Two individual problem sets / data exercises (graded approved/not approved).

  Compulsory activities from previous years are still valid.

• Assessment

  A 3-hour written digital school exam (answered in English).

• Grading Scale

  A-F

• Computer tools

  R, RStudio

• Literature

  The main reading is a set of lecture notes that will be provided on Canvas at the start of the semester. 

  It is not necessary to buy a textbook, but you may find it useful to get an alternative exposition of the material, additional problems, etc.

  Textbook:

  Nick Huntington-Klein, The Effect: An Introduction to Research Design and Causality, Chapman & Hall/CRC, 1st ed. 2021; 2nd ed. 2025.

  Freely available as an HTML textbook here: https://theeffectbook.nethttps://theeffectbook.net

   

  Alternative textbook:

  Wooldridge, J.: Introductory Econometrics, 7th edition (slightly more technical than Stock and Watson but overall similar)

   

  If time: one or two academic articles on business topics.

• Permitted Support Material

  Calculator

  One bilingual dictionary (Category I)

  All in accordance with Supplementary provisions to the Regulations for Full-time Study Programmes at the Norwegian School of Economics Ch.4 Permitted support materialhttps://www.nhh.no/en/for-students/regulations/https://www.nhh.no/en/for-students/regulations/and https://www.nhh.no/en/for-students/examinations/examination-support-materials/https://www.nhh.no/en/for-students/examinations/examination-support-materials/