Industrial organization
ECON 4376
ECON 4376
This course will cover the basic tools and issues in the field of empirical industrial organization. While the standard competitive model covered in Intermediate Micro is an extremely powerful tool, it often fails to characterize much of what is observed in many markets. Each of our topics will cover different cases where one or more of the assumptions of competitive markets fails.
We focus on models where market power of individual firms is created either by the nature of the product, because buyers have limited information about the product, or because firms are able to price discriminate among consumer groups. We close the class by looking at some features of natural monopolies and discuss how public utilities behave on the market, as well as the effects of some regulations on consumer welfare.
This course will emphasize real world case studies, but we will also develop theoretical models that will help us analyze the behavior we see in the case studies. An additional goal of this class is to introduce you to academic research. You will learn how to use library resources and statistical software for data analysis.
FAQ
What are the prerequisites for this class?
You must have taken Intermediate Microeconomics (ECON 3332) and Introduction to Econometrics (ECON 3370). These are strictly enforced.
What is this course about?
This course examines how firms behave in markets that aren’t perfectly competitive. You’ll learn how to model and measure market power, estimate demand, and analyze firm strategies using real-world data.
What types of topics are covered?
We study pricing, product differentiation, advertising, demand estimation, limited information, public utilities, and regulation. The class combines theory and empirical analysis.
What kind of assignments will I do?
You’ll complete 10 homework assignments involving data analysis, reading academic papers, summarizing findings, and hands-on work in STATA.
Will we read academic research papers?
Yes — reading and discussing academic research papers is a major part of the class.
Do I need to use STATA?
Yes. You’ll use STATA for data analysis throughout the course.
Is the course more theoretical or applied?
It’s a combination of both. You’ll first learn simple economic models — like those in Intermediate Micro — and then use real-world data to apply them, much like in an Econometrics class. For example, we might study a model of firm pricing behavior, and then estimate that model using STATA and actual data. If you’ve taken both Intermediate Micro and Econometrics, this course will feel like a natural next step that connects the two.
What kinds of industries do we study?
We use data and case studies from industries like cereals, video-on-demand, personal computers, retail chains, and utilities to explore real pricing and competition issues.
Who is this course good for?
This is a great course for students interested in consulting, industrial organization, applied micro research, antitrust, or regulatory policy. It’s also helpful prep for graduate school.
Do we follow the textbook closely in this course?
Not really. While there are recommended textbooks, most of the course is built around current topics, data analysis, and academic papers. We’ll rely heavily on published research, lecture notes, and handouts for in-class assignments. The textbooks may be helpful occasionally, but it’s not the main source of material.
What kind of data analysis will we do in this course?
We’ll do several in-class data projects, where you’ll bring your laptop and work step-by-step through the analysis together with me. It’s crucial that you follow along during class — no prior coding experience is required beyond what you learned in Intro to Econometrics. For example, we’ll estimate demand for breakfast cereals using real data. Then we’ll get creative: we’ll invent a new cereal (say, adding extra nuts or fruit to a popular brand), and use our model to predict the demand for this brand-new product.
Are there other examples of the in-class data projects?
Yes! One project looks at a real grocery store chain that went out of business — with critics blaming its ineffective pricing strategy. We’ll work with real scanner data on orange juice sales across different neighborhoods. You’ll learn how to analyze price sensitivity by income level and propose a price discrimination strategy: charging different prices for the same product depending on local demand. Then we’ll calculate how much additional profit the store could have earned by adopting your pricing plan. As a bonus, we’ll see that lower-income consumers often benefit under this kind of strategy — because the model may recommend lower prices in more price-sensitive neighborhoods.