Topics in Microeconometrics

Econ 8833, Ohio State University, Fall 2014
Information | Schedule | Reading List

Course Information


The main goals of this course are to introduce students to current research topics in microeconometrics, primarily in the areas of dynamic structural models of strategic interaction and partial identification, and to familiarize students with a set of tools–both applied and theoretical tools–which they can apply to their own dissertation research. The material will be relevant to students writing dissertations in econometrics and/or applied microeconomics.

The course will begin with a general discussion of identification, in which we attempt to understand what features of econometric models we can even theoretically hope to estimate with the data at hand. Once we know what parameters or functionals are identified, we can discuss estimators, the properties of those estimators, and how to implement them. Before considering more specific models, we will briefly review several useful econometric and computational methods that will be useful in implementing many of the estimators we will see throughout the remainder of the course.

The core part of the course will focus on estimating models of strategic interaction. We will start by discussing identification and estimation of static games–both complete information and incomplete information games. This will include models with multiple equilibria, in which certain model features may be only partially identified, requiring the use of set estimation methods, which we will return to in more detail later. Dynamic single-agent models will be introduced next, leading up to a discussion of identification and estimation of dynamic games. Finally, we will end the course with a broader look at topics in partial identification.


Economics 8732, 8831, and 8832 or equivalent with instructor consent.


This course will primarily consist of discussions of individual research papers. These papers will be challenging, and so students should spend time reading them before class in order to better internalize the material and to facilitate discussion. Participation in class discussion will be a significant factor in determining the final grade.

There will be a small number of applied problem sets which will involve implementing estimators discussed in class. Familiarity with a software package such as Matlab or Gauss will be required to complete these assignments.

Each student will be expected to give a one hour presentation on one of the papers on the reading list at some point during the semester.

Students must also complete a final project, which may be either:

In lieu of a final exam, a write-up of the project must be submitted via email by the exam date (Tuesday, December 16, 2014).


Students will be graded based on the problem sets (40%), final project (30%), and class participation (30%). There will be no in-class exams. Collaboration in small groups of two or three is encouraged, both in discussing the papers and working on the problem sets. However, students must ultimately turn in their own code, write-up, and results.


  1. Identification
  2. Computation and Estimation of Nonlinear Models
  3. Static Games
  4. Single Agent Dynamic Models
  5. Dynamic Games
  6. Partial Identification

Tentative Schedule



Computation and Estimation of Nonlinear Models

Static Games

Single Agent Dynamic Models

Dynamic Games

Partial Identification

Final Project

Reading List

Below are lists of selected papers for each topic we will cover. For each topic, the primary papers which we will cover in class appear first, followed by other related papers in no particular order.


Computation and Estimation of Nonlinear Models

Static Games of Complete Information

Static Games of Incomplete Information

Static Games with Multiple Equilibria

Sequential-Move Static Games

Single-Agent Dynamic Models

Dynamic Games

Partial Identification