Microeconomic Theory: A Mathematical Approach

Description of Course Goals and Curriculum

A Mathematical Approach to Microeconomics: you go over individuals and their preference, firms and their choices as well as game theory and uncertainty / lottery situations. A good foundation of economics (solid understanding of ECO 100 material) is very helpful, but he does review material in lecture as a quick refresher. A lot of emphasis is placed on understanding models and how they work, notably the first few weeks are quite intimidating as you go through all the assumptions behind models. The second half of the course is spent providing a foundation for principal-agent problems (incentives with wages in a work environment for example) and game theory (which is interesting due to real-world applications) The course is sort of unique since there is no textbook, Professor Urgun has quite clearly shaped the course around what he is interested in, so the curriculum appears more game theory and “matching” – heavy than most microeconomics classes. It is the mathematical version, so a lot of formulas are derived and proven on the board in lectures, which is very nice if you think that way and it helps you understand the material. The large majority of math required is a constrained optimization problem (Lagrangian and multipliers) and other straightforward derivatives. On both exams you get an extensive formula sheet, so the emphasis really is on using the math to help your understanding rather than memorization. Proof-type questions are quite rare, and you do always have the choice to use words in your explanations rather than formal notations.

Learning From Classroom Instruction

Lectures are quite long, and they are truly your main source of information. Professor Urgun really tries to make them engaging and funny, but at the end of the day it is 80min of talking and clicking through slides. Many people managed without attending lectures and going through lecture slides alone. I would recommend attending class: there is not much outside weekly work for the course, and he does emphasize some slides more than others (and explains notation that otherwise can be quite confusing). He also goes through example problems and hearing him talk through the procedure helps quite a bit. The notes posted online are very thorough, so in don’t bother copying down information from the slides: focus on explaining things to your future self, such as notation (which might not be outlined on the slide) or the correlation between the model and real people. When in lecture, try to remember about the big picture: a lot of the slides are overly detailed and quite mathematical with confusing proofs: try to remember why the formulas matter, what they say about the individuals and their preferences. For example there is some complicated explanation of concavity and concave preferences: at the end of the day, you need to understand it means that balance is good and mixtures are preferred (not all the averaging and tangency math).   Precepts are your chance to put the theories into action and try practice problems. They are very helpful in preparation for tests, so keep the exams in mind when in precept: try creating a procedure or a method to solve various types of problems: a lot of the problems have some sort of recipe. Combine a framework for solving a given problem type with a conceptual understanding of the basics and you are good to go!

Learning For and From Assignments

The 6 problem sets are definitely manageable, and 2 of them are dropped at the end. The bulk of the work and grade in this course comes from exams (25% midterm and 50% final). You don’t really have much of a chance to learn from feedback, given that there are only 2 assignments, but the professor gives you everything you need to succeed on them. This is one of those classes where you can quite easily predict 80-90% of the exam just by looking through the problem sets and example questions: there will be one constrained optimization problem, one Edgeworth box problem… (this is just an example). Go to office hours if you need help with problem sets, but also the biggest thing is to make sure that you understand concepts as the semester goes on. Topics don’t necessarily build on each other, but because there aren’t really large projects or tests to keep you on track, it is up to you to make sure you are keeping up with the material (and this makes for a much less stressful midterms/finals week).

DO THE PRACTICE EXERCISES! They are the best resource to prepare for the exams. Do a few to start out, then identify the topics you need further practice for, and go back to them as a final check to test your skills. There are many of them, but they are essentially like doing past exams for a math class: the question types are very similar just with different numbers. If you complete the packet and ask preceptors to clarify problems, nothing on the exam should be a massive surprise. Also note that Professor Urgun likes to make stories during his exams (in contrast to practice problems which are normally quite straightforward). It doesn’t necessarily affect your study strategies, since it doesn’t relate to the material being tested, but in terms of test-taking strategy, be prepared to read paragraph-long questions and parse through for the relevant information (which does relate to time management skills in a test-taking environment). Lastly, don’t panic. The exams are curved quite heavily, so getting part marks on some problems is key: even if you don’t know how to solve it or do the math, you get generous part marks for writing out the first step (example: setting up the Lagrangian). (also a good trick if you find yourself running low on time during an exam; the midterm is in class so only about 75 minutes, whereas the final is 3 hours).

External Resources

This course is quite particular in terms of structure since there is no textbook. Professor Urgun does post extensive lecture slides and shortened notes Office hours with preceptors are very helpful (they were also very kind about staying a few minutes after precept to answer individual questions). Piazza is a great resource for pset-panic (chances are if you have a query someone has already posted it on there), and the average response time was under an hour the entire semester.

What Students Should Know About This Course For Purposes Of Course Selection

This course is mostly taken as a core class for economics and a straightforward yet interesting / applicable departmental for ORFE majors. The lectures are quite long (2x1.5 hours each week, as well as a precept) but the concepts are not particularly challenging, and the math required isn’t too intensive (almost exclusively optimization problems, notably constrained optimization with Lagrangians). The weekly workload is definitely manageable, and grade – wise attending lectures throughout the semester really does relieve the pressure because it is an exam-heavy class (midterm and final make up 75% of your grade).