Courses

Course descriptions, instructors, and syllabi for the most recent academic year are listed below:

Summer Semester (July – August, 6 weeks)

Fall Semester (August – December)

  • ECO 394K Microeconomics
    Short description:  Rigorous introduction to the methods of microeconomic theory, including consumer and producer theory, decision under uncertainty, markets and competition, and general equilibrium.
    Sample textbook:  Advanced Microeconomic Theory by Jehle and Reny
    Sample syllabus: Fall 2024
  • ECO 394L Macroeconomics
    Short description:  Dynamic optimization concepts and methods used in modern macroeconomics. General equilibrium applications in the areas of economic growth, business cycles, and the role of monetary and fiscal policy.
    Sample textbook: Advanced Macroeconomics by Romer
    Sample syllabus: Fall 2024
  • ECO 394M Econometrics
    Short description:  Identification and estimation of linear and nonlinear regression models. Inference and hypothesis testing.
    Sample textbooks:  Introductory Econometrics: A Modern Approach by Wooldridge, Econometric Analysis of Cross Section and Panel Data by Wooldridge
    Sample syllabus:  Fall 2024
  • ECO 394M: Data Mining/Statistical Learning (elective)
    Short description: A machine learning course taught in R, focusing on practical applications rather than theory. Topics include data wrangling, linear regression, classification, resampling methods, regularization, feature selection, nonlinear models, trees and ensembles, latent feature models, principal component analysis, and clustering.
    Sample textbook: Introduction to Statistical Learning by James, Witten, Hastie, and Tibshirani
    Sample syllabus: Fall 2024
  • ECO 395K Economics of Auctions (elective)
    Short description: A myriad of market mechanisms, that can be classified as auctions, allocate resources. Students will learn how these various market mechanisms work.
    Sample textbooks:  Auctions  by Hubbard and Paarsch
    Sample syllabus: Fall 2024
  • ECO 395K Markets for Electricity (elective)
    Short description:  This class explores the design and performance of electricity markets and the challenges of confronting these markets.
    Sample textbooks:  The Economics of Electricity Markets by Biggar, Hesamzaden, and Wiley, IEEE Press, 2014.
    Sample syllabus: Fall 2024
  • ECO 395L International Macroeconomics (elective)
    Short description:  This course develops models for analyzing the determinants of international capital flows, trade imbalances, and exchange rates. We will explore key topics in international macroeconomics, including the implications of fixed and flexible exchange rates in models with nominal rigidities, the interactions between monetary and fiscal policy, and the dynamics of balance of payments crises.
    Sample textbooks: International Macroeconomics: A Modern Approach by Schmitt-Grohe, Uribe, and Woodford (Princeton University Press).
    Sample syllabus: Fall 2024
  • ECO 395M Introduction to Python, Databases, and Big Data (elective)
    Short description: This course teaches the fundamental programming and data skills for working with data using a standard, modern tech stack. It is a foundational course that emphasizes practical applications over theoretical explorations and introduces students to Python, SQL, GitHub and other tools of data management and analysis.
    Sample textbooks: Think Python: How to Think Like a Computer Scientist by Allen B. Downey, Pandas 1. x Cookbook : Practical Recipes for Scientific Computing, Time Series Analysis, and Exploratory Data Analysis Using Python by Harrison and Petrou, and Practical SQL: A Beginner’s Guide to Storytelling with Data by Anthony DeBarros.
    Sample Syllabus: Fall 2024
  • ECO 395M Data Science Practicum (elective)
    Short description: The Data Science Practicum offers a practical immersion into the realm of data science through engagement in real-world projects provided by industry partners. Collaborating in teams, you will undertake substantial data-driven initiatives with established organizations, enriching your understanding of techniques such as data analysis, predictive modeling, machine learning, and data-driven decision-making.
    Looking to partner with our students? See here: https://ma.eco.utexas.edu/data-science-practicum/

Spring Semester (January – May)

While students take their core courses in the fall semester, the spring semester provides ample opportunity to explore various fields of economics through elective coursework. In addition to traditional economics subfields, we offer three methods courses that aim to develop students’ skills in data science and econometric analysis.

  • ECO 395K Game Theory (elective)
    Short description: Introduction to game theoretic concepts and analyses and their application to study strategic interactions between individuals, firms, and other economic agents.
    Sample textbook: A Course in Game Theory by Martin J. Osborne and Ariel Rubinstein
    Sample syllabus: Spring 2024
  • ECO 394K Industrial Organization (elective)
    Short description: Covers the way markets are configured, how many firms exist, how they relate to each other, and how this interaction affects production, pricing, investment, advertising, and other managerial decisions. This is an advanced course which teaches underlying theory but also introduces students to practical methods commonly used in consulting and antitrust enforcement.
    Sample textbook: The Theory of Industrial Organization, by Jean Tirole and The Antitrust Revolution, by J. Kwoka and L. White
    Sample Syllabus: Spring 2024
  • ECO 394K Labor Economics (elective)
    Short description: Presents major theoretical models for understanding behavior and outcomes in the labor market. Topics include labor supply of individuals; labor demand by firms; wage determination in competitive labor markets and the wage structure; nonwage job attributes and compensating wage differentials; investment in human capital and wage differentials related to education and experience; and labor market discrimination and wage differentials by race and gender.
    Sample textbook: Labor Economics, by George Borjas
    Sample syllabus: Spring 2024
  • ECO 394M: Causal Inference (elective)
    Short description: An advanced course in econometrics covering topics related to causal inference and empirical research in economics. The goal is to introduce students to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques (regression discontinuity design, instrumental variables, differences-in-differences) and coding instructions.
    Sample textbook: Causal Inference: The Mixtape by Scott Cunningham
    Sample syllabus: Spring 2024
  • ECO 394M: Time Series Econometrics (elective)
    Short description: An advanced course in econometrics covering current techniques used in time series models with applications in macroeconomics and finance. Topics include distributed lag models, ARMA models, ARCH and GARCH models of volatility, unit roots; forecasting; impulse response functions, local projections, VARs; state-space models, recursive estimation and Kalman filtering. S pecial applications on monetary policy shocks and fiscal shocks.
    Sample textbook: A Guide to Modern Econometrics by M. Verbeek; Elements of Forecasting by F. Diebold, and other textbooks and journal articles
    Sample syllabus: Spring 2024

Internship Course Credit

  • ECO 380D and ECO 180D are available in Summer, Fall, and Spring semesters. See the Internship page for details.