MSE Courses


Students must complete a minimum of 27 graded semester credits. Of these, a maximum of 6 graded credits can be at the 400-level (equivalent to two 3-credit courses), and all other graded credits must be at the 500-level.

Fall semester, 1st year

  • Required courses:
    • EconS 526 (Mathematical Economics with Applications), 3 cr.
    • EconS 527 (Masters Microeconomic Analysis), 3 cr.
    • EconS 528 (Masters Macroeconomics), 3 cr.
    • EconS 700 (Masters research, thesis), 1 cr.
  • The above three courses are relatively demanding, so we generally don’t recommend students taking any elective courses in the Fall semester.


Spring semester, 1st year

  • Required course:
    • EconS 525 (Masters Econometrics), 3 cr.
    • EconS 700 (Masters research, thesis), 1 cr.
  • Elective courses  (choose at least two, but not limited to the following):
    • Stat 437 High Dimensional Data Learning and Visualization, 3 cr.
    • EconS 522 Financial and Commodity Derivatives, 3 cr.
    • EconS 533 International Trade and Policy, 3 cr.
    • AgEc 535 Applied Industrial Organization, 3 cr.
    • EconS 536 (Applied Statistics and Econometrics for Economics and Finance), 3 cr.
    • EconS 573 – Economics of Development and Health, 3 cr.

2nd year courses, all are electives

  • EconS 424 (Strategy and Game Theory), 3 cr. (Typically offered in the Spring semester).
  • EconS 425 (Industrial Organization), 3 cr. (Typically offered in the Spring semester).
  • Stat 435 (Statistical Modeling for Data Analytics), 3 cr. (Typically offered in the Fall semester).
  • EconS 524 (new course) Applied Machine Learning for Economics and Business, 3 cr.
  • EconS 529 (revised course) Writing and Presentation Skills for Economists (research methods), 3 cr. (Typically offered in the Fall semester).

EconS 700

Students must complete 6 semester credits of EconS 700 to graduate (1 credit project proposal in the first semester, followed by the remaining credits in subsequent semesters). In this course, students first choose their Thesis advisors, starting to narrow the topic they would like to study (often by the end of the first semester in the program), and then work on completing and improving their research, with the goal to present it before a Thesis Committee of SES faculty (one of the members can be from another WSU department or institution). Thesis are generally around 20-30 pages long, and once the student’s advisor agrees, the student provides the thesis to all Thesis Committee members at least 3 weeks before the day of his defense.

Courses in other disciplines

Students can enroll in elective courses in other disciplines, such as Statistics, Environmental Science, Management, or related fields, as long as they are at the 500 level.
This degree program classifies as STEM (CIP Code 45.0603: Econometrics and Quantitative Economics). A student enrolled in full-time study can finish the program in 3-4 semesters, including the summer semesters prior to the Fall semester.

More information about course content:

  • Stat 435 Statistical Modeling for Data Analytics, 3 cr. Multiple linear regression with model selection, dealing with multicollinearity, assessing model assumptions, the LASSO, ridge regression, elastic nets, Loess smoothing, logistic regression, Poisson regression, and the application of the bootstrap to regression modeling.
  • Stat 437 High Dimensional Data Learning and Visualization, 3 cr. Course Prerequisite: STAT 435. Data visualization, metric-based clustering, probabilistic and metric-based classification, algebraic and probabilistic dimension reduction, scalable inferential methods, and analysis of non-Euclidean data. Typically offered in Spring.
  • EconS 522 Financial and Commodity Derivatives, 3 cr. Design, trading, structure, and pricing of derivatives; working knowledge of how derivative securities work, how they are used, and how they are priced..
  • EconS 523 (new course) Big Data for Economics and Business, 3 cr. Introduction to data and programming. Students will work with data in spreadsheet format, explore what it means to have a ‘tidy’ dataset and its benefits, gain experience programming in R and version control with Git, and engage in data exploration and the benefits of exploratory analysis and data visualization as a subspace of data exploration.
  • EconS 524 (new course) Applied Machine Learning for Economics and Business, 3 cr. This course introduces machine learning algorithms and concepts. Broadly, the course will cover supervised and unsupervised learning methods, providing foundational theory and application to data in order to build theoretical understanding. The statistical and computational methods associated with each learning problem will also be explored.
  • EconS 525 Master’s Econometrics, 3 cr. Theory and practice of multiple regression methods; applications to the study of economic and other phenomena; use of computer regression programs. Required preparation must include an introductory statistics course. Cooperative: Open to UI degree-seeking students.
  • EconS 527 Microeconomic Analysis, 3 cr. Consumer and producer behavior; partial and general equilibrium; game theory; imperfectly competitive markets; and market failures. Required preparation must include intermediate microeconomics and calculus coursework. Cooperative: Open to UI degree-seeking students.
  • EconS 528 Master’s Macroeconomics Analysis, 3 cr. Master’s-level course to develop a coherent theoretical framework to interpret macro data and to analyze macro policy. Cooperative: Open to UI degree-seeking students.
  • EconS 529 (revised) Research Methods/Writing and Presentation Skills for Economists, 3 cr. Designed to develop communication and presentation skills essential for success in any aspect of business. Practice in writing economics documents for a variety of professional audiences. Writing is taught as a process—brainstorming, collaborating, continually revising, and challenging ideas. Presentation skills to focus on presenting information clearly and organizing ideas, with emphasis on the role of the audience when presenting, because the audience determines diction, style, tone, organization, research, and ideas. Grammar is incorporated as needed, especially in regard to writing.
  • EconS 533 International Trade and Policy, 3 cr. International trade theories, policies, and research issues related to world trade with emphasis on agricultural commodity markets. Cooperative: Open to UI degree-seeking students.
  • 536 Applied Statistics and Econometrics for Economics and Finance, 3 cr. Data and problem-driven approach to formulating, estimating, and interpreting models that address problems in the area of finance and financial economics; review relevant basic statistics and probability concepts, and apply these to linear regression, regression diagnostics, and time series econometrics.
  • EconS 573 – Economics of Development and Health, 3 cr. This course will introduce students to selected methodological and topical issues related to the study of development and health economics, within the context of low- and middle-income countries (LMICs). In addressing important issues surrounding methodology and current topics, development, and health are conceptualized as an integrated whole in this course. The course is divided in two. The first 6-weeks introduce the domains of development and health economics as they relate to low-middle-income countries and then focus on common methodological approaches. The following topics are included in this section of the course: a case study of the integration of health and development in improvements in maternal health, and causal identification in study design with examples from random control trials and behavioral experimental designs. The second part of the course focuses on selected topics. These include poverty, education and health, nutrition, and economics of epidemiology, among others. Applications will tend to focus on human health.
  • EconS 701 (new course) Economics Capstone, 3 cr. Course Prerequisite: Admitted to the Master of Applied Economics program. Capstone for professional master’s degree under the Graduate School. Integration of coursework in a project; assessment. The course will be graded and include a balloted evaluation of the student’s completion of the capstone project by the program’s graduate faculty.