Course Descriptions

Foundation Courses to be taken in senior year: 

Econ 526 (3 hours), Quantitative Methods I: Assuming that students are familiar with differential calculus and integration of a single variable, this course, as a first sequence of quantitative methods, covers matrix algebra, functions of several variables, unconstrained and constrained optimization of multiple variables, and economic dynamics in discrete and/or continuous time – first-order difference and/or differential equations. This course aims to help students build solid quantitative foundations for upper-level applied courses in the master's program. During each class, theoretical concepts and methods are presented, accompanied by examples in economics. Prerequisite(s): Permission of the Director of Masters Programs.

Econ 725 (3 hours), Computer Programming & Data Management in Economics: This course equips students with essential programming and computational data science skills tailored for economic analysis. Students will learn to use tools like Python, Git, Docker, and Cloud Computing to create reproducible workflows, analyze data, and present results through dashboards and visualizations. The course also covers machine learning techniques and practical methods for deploying models in real-world scenarios. Additionally, students will develop proficiency in SQL and Tableau for data manipulation and visualization. A key component of the course is its hands-on practice with data analysis challenges, where students apply the tools and techniques learned to manipulate and analyze datasets effectively. Prerequisite: Permission of the Director of Masters Programs.

Econ 520 (3 hours), Data Sciences for Economics: The first part of the course focuses on the necessary background material such as statistics, probability, linear algebra and some calculus to understand econometrics at a more advanced level. The second part of the course emphasizes the construction and application of econometric models such as linear regression models, difference-in-difference models, instrumental variables, as well as randomized control trials. The goal of the course is to prepare students with a fundamental understanding of how causal inference can be established, which students can then utilize to develop more complex models in later courses. Research papers directly relevant to the theory will be discussed weekly, and students will complete a research project using real-world data at the end of the semester. Prerequisite(s): Econ 526 and Econ 725 or permission of the Director of Masters Programs.       

Core courses to be taken in the +1 year:      

Econ 521 (4 hours), Econometrics of Policy-Analysis & Causal-Inference: This is an applied microeconometrics course with a central focus on causal inference and the empirical evaluation of policies and programs.  As part of this course, the students will learn and employ econometric methods to questions of causal inference, and analyze research questions relevant to contemporary microeconomic policies. The content of the course is split into two general areas: 1) establishing and understanding the theoretical foundations for asking and answering questions of causal inference, and 2) learning and applying a set of the most common empirical methods for program evaluation and causal inference. Students will replicate the results of existing studies as well as undertake a final project answering a novel research question. The course seeks to build the background and technical capacity to apply methods of causal inference using real-world data, and explain research results in written and presentation-based formats. Pre-requisite(s): Econ 520, 526, and 725 or permission of the Director of Masters Programs.  

Econ 522 (4 hours), Forecasting and Macroeconomic Analytics:  The course is intended to fulfill two needs: (1) introduce students to the tools to analyze time series data in an univariate and multivariate framework (2) to provide students with applied interests with the most sophisticated and up to date techniques used in empirical time series analysis and forecasting. The empirical relevance of every model will be emphasized while also maintaining a theoretical rigor. Computer exercises will help in keeping the class relevant. The importance of forecasting in macroeconomics research conducted at private and public sectors will be discussed with leaders in the field that will come as guests during the semester. Pre-requisite(s): Econ 520, 526, and 725 or permission of the Director of Masters Programs.  

Econ 524 (4 hours), Big Data Econometrics: This course provides an introduction to machine learning and its applications to causal inference with big data in economics.  It covers both linear machine learning methods, such as LASSO, logistic regression and support vector classifier, and nonlinear machine learning methods, such as decisions trees, random forests, boosted trees, neural networks (deep learning) and support vector machines. These methods serve as building blocks for the introduction of debiased machine learning, which is crucial for delivering reliable statistical results when conducting causal inference with big data. Computation and empirical applications are important components of this course. In the Lab sessions, students learn implementations of the algorithms introduced in class using Python. Pre-requisite(s): Econ 520, 526, and 725 or permission of the Director of Masters Programs.   

Econ 540 (3 hours), Empirical Writing and Communication: This course aims to provide opportunities to develop professional writing and communication skills through the experiences of doing actual real-world economic/management consulting. Students will practice how to properly report data analysis outcomes and effectively communicate the information with "clients." Economic/management consulting requires abilities to: 1) clearly define the right questions to solve the problem; 2) find relevant data and properly extract information; 3) clearly communicate and present the information and findings in non-technical language 4) provide a clear solution to the problem in a timely manner and in an implementable format. By the end of this course, students will be able to produce graphs and tables that summarize and interpret raw/complex quantitative and qualitative data; effectively communicate data, technical, professional information to audiences with diverse backgrounds and varying levels of expertise; produce written reports that interpret, analyze, and evaluate data and professional documents; understand, conduct, and execute research and projects that require effective writing and communication skills. Pre-requisite(s): Permission of the Director of Masters Programs.

Elective courses to be taken in the +1 year:  

Econ 541 (3 hours), Pricing and Revenue Management: This course covers many pricing tools as well as techniques for selling goods and services under capacity constraints with advance booking, refunds, and overbooking. Applications will be drawn from a variety of industries, including soft drink manufacturing, grocery stores, Internet content providers, cable TV operators, airlines, hotels, phone operators, concert halls, movie theaters, and electricity and gas companies. A part of the assessment will be based on case study analyses. The main objective of the course is to equip students with the knowledge in pricing and revenue management strategy necessary for working as a business or academic economist, operations researcher, marketing scientist, pricing manager, or an economic consultant. Pre-requisite(s): Econ 521, 522, and 724 or permission of the Director of Masters Programs.     

Econ 542 (3 hours), Transfer Pricing: This course will introduce students to the economics of transfer pricing.  Transfer pricing involves finding reliable intercompany pricing in situations where free markets do not exist and accounts for over half of all international trade.  Given the extent of globalization in the current business environment, multinational enterprises must address transfer pricing issues on a day-to-day basis.  Taxing authorities throughout the world have instituted transfer pricing legislation to claim their “fair share” of profits from the multinational enterprises’ global income. As a result, this field has attracted significant attention from policy makers and businesses. Pre-requisite(s): Econ 521, 522, and 724 or permission of the Director of Masters Programs.  

Econ 543 (3 hours), Cost-Benefit Analysis: The objective of this course is to introduce students to how the combination of economic theory and data can be used to make cost-benefit analysis for business planning by firms, for decision making by consumers, for regulatory practices by agencies, and for policy formulation by the legislature. Such analyses are a foundational tool for selecting policies that maximize economic efficiency or for assessing economic efficiency when it is one of the goals relevant to policy choice. The richness of the methodology for both public and private sector decision making is demonstrated with many examples and case studies, emphasizing practical applications and correct use of analytical tools. Pre-requisite(s): Econ 521, 522, and 724 or permission of the Director of Masters Programs.  

Econ 544 (3 hours), Internet Economics: There is no doubt that the Internet will play an increasingly bigger role in society and the economy. This course introduces various fundamental ideas and theories in economics that can help us understand online businesses better and more deeply. We will mainly cover several foundational theories, including search, two-sided markets, matching, and auctions. We will also discuss some contemporaneous topics, such as recommendation and ratings systems, net neutrality, and cryptocurrencies.  Pre-requisite(s): Econ 521, 522, and 724 or permission of the  Director of Masters Programs.

Econ 599, Research and writing for the Master of Science thesis: Students conduct a research project aimed at examining an important economic question using the empirical methods learned in this curriculum.  The research will be conducted under the guidance of a faculty member.