Applied Quantitative Methods for Management Research - 2020

Course coordinator: Tünde Cserpes

Office hours: on Fridays between 10:00-12:00 (during the duration of the course)

Lecturers: Tünde Cserpes, Carsten Bergenholtz and John Thøgersen

Administrative assistance: Lisbeth Widahl

Work load: 5 ECTS

Time: 8 Tuesdays between 9:00-15:00
Week 41: 6 October 2020
Week 43: 20 October 2020
Week 44: 27 October 2020
Week 45: 3 November 2020
Week 46: 10 November 2020
Week 47: 17 November 2020
Week 48: 24 November 2020
Week 49: 1 December 2020

Place: Aarhus BSS, Aarhus University; Fuglesangs Allé 4, DK-8210 Aarhus V. Room: 2636-U112 (week 41, 44, 45, 46, 47 and 49) and 2636-U115 (week 43 and 48).

Important! We are closely monitoring the COVID-19 situation and will modify course policy according to the guidelines set out by the Danish authorities and university officials.

Course description and objectives

What does it mean when seminar participants or journal referees claim that your paper has an endogeneity problem or no identification strategy? How can you deal with these challenges? With a point of departure in the ideal randomized experiments, this PhD course at the Department of Management introduces a toolbox with various techniques to deal with these questions in quantitative analysis of non-experimental data. We do this from two different perspectives, i.e., structural equation modeling and quasi-experimental design.

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. We explore topics ranging from regression models to quasi-experimental designs and structural equation models. We address 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.

Course outcomes

The goal is to provide participants with a foundation for collecting and analyzing datasets in management research and create causal research designs. For students who are not themselves working with quantitative empirics, this course enables 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 in quantitative analysis and de-mystify the concepts and skills involved.

Topics

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

Prerequisites

Ideally, you have already acquired a basic understanding of probability theory and statistics. Most master level programs in management (including cand.merc.) give you the foundations to participate in this course. We recommend revisiting the textbooks and material from these classes. Moreover, several universities provide online courses in inferential statistics and regression analysis, which also offer an opportunity to revisit these topics.

Course Requirements

There are four main requirements to this course:

1) Pre-course survey

2) Reading, note-taking, and review questions

3) Attendance and active participation

4) Final exam

1) Pre-course survey

While our curriculum focuses on intuition and application rather than proof and formal equations, some technical content is necessary. For this reason, we ask course participants to fill out a short quantitative survey before the first class to assess the level of familiarity with statistical concepts.

2) Reading, note-taking and review questions

Reading is the foundation of this course. This course requires you to read both methods books that explain the tenets of econometrics and applied papers, which will sometimes seem abstract and difficult. Your reading assignments will be in the ballpark of 100 pages for each class requiring you to spend about 3-4 hours reading and taking notes at home. During the course, we will work towards making this task gradually easier.

BOOKS (you need to buy them!)

We ask you to buy these books. Both of these are worth adding to your personal library as they are an accessible guide to the essential tools of econometric research.

Joshua D. Angrist and Jörn-Steffen Pischke (2014), Mastering ‘Metrics. Princeton University Press.

Niels Blunch (2013), Introduction to Structural Equation Modeling using IBM SPSS Statistics and Amos, Sage Publishing.

The detailed lecture plan will include additional readings (mostly journal articles) for each session. These materials will be posted on Blackboard. 

3) Attendance and active participation

Full and active participation is expected during lectures. We will alternate between lectures and small-group exercises.

4) Final exam

Each participant submits a written assignment. The assignments will be evaluated in terms of pass or fail. Deadline for submission is 15 December 2020. We will post assignments to Blackboard in Week 47.

Application / intent to register

Send your application and intent to register no later than 15 September 2020 to Lisbeth Widahl, Aarhus BSS, Aarhus University, Department of Management (by email). The application form can be downloaded from the website: Application Form. Please note that your registration is binding.

Fee

Participants from other universities than Aarhus University are asked to bear the cost of meals (lunch and refreshments on each day of the course). If corona-related regulations prevent us from providing meals, we will adjust our policy and communicate it to participants. For more information regarding dietary plans and fee structure, please contact Lisbeth Widahl.

Participants who might be commuting from other places need to arrange accommodation on their own.

Software

During the first six lectures, we will use Stata 16. All participants need to purchase and install Stata before the first class. The second part of the course demonstrates structural equation modelling using SPSS 26 and SPSS AMOS. Please buy these packages by November 24.

Aarhus BSS PhD students can buy a copy of Stata 16 IC, SPSS 26, and SPSS AMOS from the BSS IT department using the following link:  https://medarbejdere.au.dk/en/administration/it/buy-it-equipment-and-software/aarhus-bss-it-webshop/bss-it-webshop-20/. Please contact BSS IT with further software-related questions: bss.it@au.dk.

Important! Aarhus BSS PhD students should delay purchasing these software packages until after September 1, 2020 to enjoy a full one-year subscription.

Availability to course participants

If you have any questions, worries, or constructive feedback, please feel free to contact Tünde Cserpes. She will be available for meetings during office hours or by appointment if those times conflict with your schedule.

A detailed lecture plan will be posted once the enrollment period is over.