Graduate Courses

The first part of the course utilizes the tools of microeconomic theory to analyze and understand essential topics related to optimal business decisions. Topics include the characteristics of costs and demand and profit maximization pricing.  Market structures are studied with a focus on differences and the concomitant consequences for business decisions. Students will understand the various market structures in the context of the global trade environment. Regression analysis is used to rigorously estimate costs and demand. The class utilizes many examples from the Silicon Valley to help integrate market theory and practice and provides a powerful analytical basis for the further study of business topics.

Demand, cost, production, and pricing at the level of the individual firm or industry. Market structure and the regulatory environment. Emphasis on applications as well as theory.

This course analyzes the economic behavior of individuals and firms and explores how their interactions in markets affect managerial decisions. Basic concepts include supply and demand, price elasticity, and optimal decision making by consumers and firms. These analytical tools will be applied to understand how key managerial decisions are made in different industrial structures (such as competition vs. monopoly) and the implications of government policies for market outcomes. Students will also apply relevant data analysis techniques.

Studies theoretical concepts and tools for analyzing issues in the business environment such as conflict, bargaining, pretending and shirking in organizations and markets, agenda construction, and strategic commitment. Teaches game theoretical topics such as Nash-equilibrium, Sub game perfection, Bayesian Nash-equilibrium, Harsanyi transformation, commitment, and Perfect Bayesian Equilibrium.

This course focuses on economic forecasting. Many decisions made in business, economics, finance, and government depend on the forecasts that are constantly generated in these and other disciplines. This course will introduce the students to econometric time series models and methods that can be used to generate forecasts. A wide range of topics will be covered, including basic concepts of time-series forecasting, trends and seasonality, ARIMA processes, and evaluation of forecasts. Illustrative examples applying these techniques to actual data will be presented in class, and students will perform a variety of data analyses on the computer. Upon completion of this course, students will have mastered basic properties of time-series forecasting models, and be able to skillfully select appropriate forecasting models to fit real world data sets and generate their own forecasts.