Applied Quantitative Methods for Management Research - 2017

Course syllabus
Applied Quantitative Methods for Management Research

Workload: 5 ECTS

Kaleb Girma Abreha
John Thøgersen
Michael S. Dahl

Course coordinator
Michael S. Dahl (

Time and place
5 September, 7 September, 12 September, 14 September, 21 September, 26 September, 28 September, 5 October, 12 October & 25 October 2017; Aarhus BSS, Aarhus University; Fuglesangs Allé 4, DK-8210 Aarhus V. Room: 2636-U111 / 2636-U332 / 2610-S530.

What does it mean when seminar participants or journal referees claim that your pape
has an endogeneity problem or no identification strategy? How can you deal with these
challenges? With a point of departure in the ideal randomised experiments, this PhD
course at the Department of Management introduces a tool-box with various techniques
to deal with these questions in quantitative analysis of non-experimental data.
This course will introduce participants to state-of-the-art quantitative empirical methods in
management with a focus on application and understanding the underlying intuition. This
will include topics ranging from regression models to quasi-experimental designs and
structural equation models. We will address the discussion of identification, correlation
and causality with a point of departure in recent empirical studies from the broad field of
management and marketing. This course will introduce two software packages, Stata and
AMOS, which are frequently used among empirical scholars.
The goal is to provide participants with a foundation for collecting and analysing datasets
in management research with a focus on establishing causality. Even for students, who are
not themselves working with quantitative empirics, we aim at building an understanding
of the central topics, enabling them to read, understand, review and comment on
quantitative empirical contributions for their thesis, at conferences and as reviewers for
international journals. The ultimate goal is to spark an interest for quantitative analysis and
de-mystify the concepts and skills involved.

Identification, Causality, Types of research questions, Quality of data, Matching, Differences-in-differences, Instrumental variable regression, Regression discontinuity design, Structural equation modelling, stata, AMOS.

Main literature, you need to buy these:
- Joshua D. Angrist and Jörn-Steffen Pischke (2014), Mastering ‘Metrics. Princeton
University Press. (MGMT PhD students should contact Michael before ordering this book)
- Niels Blunch (2013), Introduction to Structural Equation Modeling using IBM SPSS
Statistics and Amos, Sage Publishing.
See Lecture Plan below for additional readings for each session.

The techniques introduced in the first part of this course will be demonstrated using Stata.
All participants are expected to obtain and install the Stata system before the beginning
of the course and are familiar with the basic operations. Aarhus BSS students should
contact the IT department to obtain a Stata license (IC-version is sufficient for this course).
A 1-year subscription is a good option, if you do not plan to use it after the course.
Structural equation modelling is demonstrated with the IBS SPSS AMOS software
package, which can be obtained in the Aarhus BSS webshop. A free trial is also available
from the IBM SPSS AMOS website.

A basic understanding of probability and statistics is required. Most master-level programs in management (including cand.merc.) have courses providing the prerequisite for participating in this course. Revisiting the text books and material from these basic classes would be recommended. Several universities are providing excellent and easy accessible online courses (so-called MOOCs, massive open online courses) in basic statistics and regression analysis, which also provide an opportunity to revisit these topics, also if you have a different background. While this course focuses on intuition and application rather than proof and formal equations, some technical content should be expected.

Exam form
Full and active participation is expected during lectures. Each participant will submit a written assignment. The assignments will be evaluated in terms of pass or fail. Deadline for submission is November 15. Assignments will be distributed after the final lecture, but introduced during the second lecture.

Lecture plan

Day 1: September 5, 9.00 - 12.30 (room 2636-U111)
Introduction to Stata
- Cameron and Trivedi (2010), “Microeconometrics using Stata”, Chapter 1
and 2

Day 2: September 7, 9.15 - 15.00 (room 2636-U332)
What is identification and why do we care in management research?
- Mastering ‘Metrics, Chapter 1, 46 p.
- Bertrand & Mullainathan (2004) “Are Emily and Greg More Employable
Than Lakisha and Jamal?”,

Day 3: September 12, 9.00 - 12.30 (room 2636-U111)
Linear regression basics
- Cameron and Trivedi (2010), “Microeconometrics using Stata”, Chapter 3,
pp. 73-111

Day 4: September 14, 10.00 - 15.00 (room 2636-U332)
Regression and matching
- Mastering ‘Metrics, Chapter 2 (not Appendix), 32 p.
- Krueger (1993) “How Computers Have Changed the Wage Structure:
Evidence from Microdata 1984-1993”

Day 5: September 21, 9.15 - 15.00 (2636-U332)
Instrumental variable regression
- Mastering ‘Metrics, Chapter 3 (not Appendix), 44 p.
- Acemoglu, Johnson & Robinson (2001) “The Colonial Origins of
Comparative Development: An Empirical Investigation”

Day 6: September 26, 9.00 - 12.30 (room 2636-U111)
Survey data analysis
- Cameron and Trivedi (2010), “Microeconometrics using Stata”, Chapter 3
(pp. 111-115) and Chapter 5 (pp. 169-175)
- Stata Survey Data Reference Manual

Day 7: September 28, 9.15 - 15.00 (room 2636-U332)
Regression discontinuity design
- Mastering ‘Metrics, Chapter 4

Day 8: October 5, 9.15 - 15.00 (room 2636-U332)
Differences in differences
- Mastering ‘Metrics, Chapter 5 (not Appendix)
- Card & Krueger, (1994) “Minimum Wages and Employment: A Case
Study of the Fast Food Industry in New Jersey and Pennsylvania,”

Day 9: October 12, 9.15 - 15.00 (room 2610-S530)
Structural equation modeling
- Introduction to Structural Equation Modeling

Day 10: October 25, 9.15 - 15.00 (room 2610-S530)
Structural equation modeling
- Introduction to Structural Equation Modeling

MSD: Michael S. Dahl, KGA: Kaleb Girma Abreha, JT: John Thøgersen 

Deadline: 10 August 2017 to: Lisbeth Widahl, Aarhus BSS, Aarhus University, Department of Management (preferably by email: The application form can be downloaded from the website (Application Form). Please note that your application is binding.

The total number of participants is limited to 20 students. Applicants from the Department of Management (MGMT), Aarhus University will be given priority over applicants from other departments and universities. Only PhD students will be accepted.

Participants from other universities will be charged a fee that covers meals during the course (for more information, please contact Lisbeth Widahl).

Participants are required to find their own accommodation.

Further information
Michael S. Dahl or Lisbeth Widahl