Advanced Industrial Organization: Pricing, Information and Digital Markets

Course content

This course uses theory and empirical methods to delve into a variety of questions related to firm strategic behavior. Why are seemingly identical products often sold for different prices? How does consumer search for product information affect pricing decisions, and when will firms themselves provide this information via advertising? What is the role played by digital platforms and what are the economics of privacy? 

In so doing, the course looks more deeply into how market power affects firm pricing decisions, an issue introduced in the course “Industrial Organization”. We look at, in particular, issues such as price dispersion, advertising, mergers and vertical relationships, and network effects in two-sided platforms, with a particular focus on the role of information asymmetries and how they play out in digital markets, while also briefly touching on ‘behavioral IO’.

The main differences to the course “Industrial Organization” are the focus on topics at the research frontier, and the inclusion of a significant empirical component alongside the theory. Thus, students will be introduced to the most common model of demand used in empirical IO, which also entails working with models numerically (i.e. on a computer) and estimating model parameters with a concrete real-world dataset. 

Education

MSc programme in Economics – elective course

Only students enrolled at the Masters’ level can take the course.

 

The PhD Programme in Economics at the Department of Economics - elective course with resarch module (PhD students must contact the study administration and the lecturer in order to write the research assignment)

The PhD programme in Economics:

  • The course is an elective course with a research module. In order to register for the research module and to be able to write the research assignment, the PhD students must contact the study administration AND the lecturers.

No, the course should not be a requirement for the 5 + 3 phd-study

 

This course explores a number of recent developments in the field of Industrial Organization, with a particular focus on digital markets and on combining both theoretical and empirical methods. As such, it complements the course “Industrial Organization”, which provides an introduction to IO theory.

This course uses game-theoretic methods seen in “Microeconomics III” and econometric methods seen in “Econometrics I”, along with numerical methods seen in “Introduction to Programming and Numerical Analysis”.

 

This course is part of the Microeconomics and Computational Economics course packages.

Learning outcome

After completing the course the student is expected to be able to:

 

Knowledge

  • Summarize key concepts and results related to firm strategic behavior.
  • Understand work-horse models and, where relevant, the data required to estimate model parameters, and point out these models’ main assumptions. 
  • Account for the economic mechanism underlying given results and discuss their interpretation.
  • Describe the core empirical challenges related to demand estimation, such as simultaneity, price endogeneity, etc., and the most common solutions.

Skills

  • Derive formal results in advanced game-theoretic settings, in particular those involving asymmetric information.
  • Carry out analysis using both theoretical and empirical models, and relate these models to one another.
  • Estimate and interpret parameters of an empirical model of demand with a given dataset. 
  • Use an estimated demand function to solve numerically for the price equilibrium and perform a counterfactual analysis (e.g. exogenous entry/exit, merger, taxation). 

Competencies

  • Compare and contrast different theoretical concepts related to firm strategic behavior, and explain key similarities and differences.
  • Answer a research question related to the course topics when applied to a new theoretical or empirical setting.
  • Select the best tool to address a given question and justify why it is appropriate, when faced with a new dataset or empirical market setting. 
  • Assess whether model assumptions (either related to theory or econometrics) are reasonable in specific contexts

The course consists of
1) Lectures: theory and methods are presented
2) Exercises: hands-on experience with problem sets
3) Take-home projects: in-depth projects that students will complete either independently or in groups

The course will draw in large part on recent academic research articles in IO along with handbook chapters. At times we will also use selected chapters from the textbook Belleflamme and Peitz (2015), which can provide a less technically-involved exposition. 

  • Handbook of Industrial Organization (2021), Volume 5, ISSN 1573-448X. 
  • Handbook of the Economics of Marketing (2019), Volume 1, ISSN 2452-2619.
  • Belleflamme, Paul and Martin Peitz (2015), Industrial Organization: Markets and Strategies, 2nd edition, Cambridge University Press.
  • Hortaçsu, Ali and Joo, Joonhwi (2023), Structural Econometric Modeling in Industrial Organization and Quantitative Marketing: Theory and Applications, Princeton University Press

The course will be intensive in terms of game theory, calculus and programming (Python).

It is strongly recommended to have successfully completed the course “Microeconomics III” at the University of Copenhagen, or a similar introduction to game theory.

It is also strongly recommended to have successfully completed the course “Introduction to Programming and Numerical Analysis” (if you have not taken the last course then please at least go through the first 3 lectures, available via numeconcopenhagen.netlify.app).

Note that the course “Advanced Industrial Organization” is self-contained and introduces all material and concepts above and beyond those in the above-mentioned strongly recommended courses.

Nonetheless, it is also recommended, but is not a strict requirement, to have followed or to follow concurrently the courses “Industrial Organizational” and “Advanced Microeconometrics” at the University of Copenhagen, or similar.

Schedule:
Schedule:
· Lectures: 3 hours in a row per week,
· Exercises: 2 hours per week.
from week 36 to 50 (except week 42).

Schema:
The overall schema for the Master can be seen at KUnet:
MSc in Economics => "Courses and teaching" => "Planning and overview" => "Your timetable"
KA i Økonomi => "Kurser og undervisning" => "Planlægning og overblik" => "Dit skema"

Timetable and venue:
To see the time and location of lectures and exercise classes please press the link/links under "Se skema" (See schedule) at the right side of this page. E means Autumn. The lectures is shown in each link.

You can find the similar information partly in English at
https:/​/​skema.ku.dk/​ku2425/​uk/​module.htm
-Select Department: “2200-Økonomisk Institut” (and wait for respond)
-Select Module:: “2200-E24; [Name of course]””
-Select Report Type: “List – Weekdays”
-Select Period: “Efterår/Autumn – Weeks 31-5”
Press: “ View Timetable”

Oral
Collective
Peer feedback (Students give each other feedback)
ECTS
7,5 ECTS
Type of assessment
Portfolio, 48 hours under invigilation
Type of assessment details
The portfolio exam consists of two parts, each of which has equal weight in the overall assessment.
· Part I: one take-home project from the semester is selected at random to be resubmitted as a part of the exam.
· Part II: a new assignment.

Be aware that
· The exam may be completed in groups of at most three. The submitted exam manuscript must specify which student in the group has written which part.
· No communication across groups is allowed during the 48 hours of the exam
Exam registration requirements

To qualify for the exam, the student must:

·  Hand in at least one take-home project by the assigned deadline.

·  Give peer feedback to another student on at least one take-home project by the assigned deadline.

Aid
Without aids
Marking scale
7-point grading scale
Censorship form
No external censorship
for the written exam. The exam may be chosen for external censorship by random check.
____
Exam period

Exam information:

The exact time and room will be available in the Digital Exam from the middle of the semester.

 

In special cases, the exam date can be changed to another day and time within the exam period.

 

For enrolled students more information about examination, rules etc. is available at the intranet for Master students (UK) and Master students (DK).

____

Re-exam

The reexam is a 30 minute oral exam with 30 minutes preparation time.

All written aids are allowed during the preparation time. Notes made during the preparation are allowed at the examination

Reexam information:

Information about the reexam will be available in the Digital Exam early February.

 

More information is available at Master(UK) and Master(DK).

 

Criteria for exam assessment

Students are assessed on the extent to which they master the learning outcome for the course.

 

To receive the top grade, the student must with no or only a few minor weaknesses be able to demonstrate an excellent performance displaying a high level of command of all aspects of the relevant material and can make use of the knowledge, skills and competencies listed in the learning outcomes.

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 42
  • Preparation
  • 162
  • Exam
  • 2
  • English
  • 206

Kursusinformation

Language
English
Course number
AØKA08082U
ECTS
7,5 ECTS
Programme level
Full Degree Master
Ph.D.
Duration

1 semester

Placement
Autumn
Price

Information about admission and tuition fee:  Master and Exchange Programme, credit students and guest students (Open University)

Schedulegroup
and venue:
Go to "Remarks".

Exam and re-sits: Go to "Exam".
Studyboard
Department of Economics, Study Council
Contracting department
  • Department of Economics
Contracting faculty
  • Faculty of Social Sciences
Course Coordinators
  • Nick Vikander   (13-7b7670783b8376786e7b71727f4d72707c7b3b78823b7178)
  • Anders Munk-Nielsen   (3-6470714368667271316e7831676e)
There will be regular office hours, where students can ask questions about the course
material etc.
Teacher

see 'Course Coordinators'

Saved on the 27-05-2024

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Courseinformation of students