These are the four core courses that students take in their first semester of the program:
This course covers elements of modern microeconomics. It emphasizes the development of skills needed to evaluate the new generation of economic models, tools, and ideas as they apply to recent changes in our economy. Basic tools of game theory, asymmetric information, and modern general equilibrium price formation are introduced and applied to various topics. These topics include consumer and producer choice, decision under uncertainty, and resource allocation under different market structures such as competition, monopoly, and oligopoly. The course also focuses on some newer innovations to the theory, including the role of politics in the determination of economic policy, the impact of spillovers and network externalities in the information economy, and psychological and behavioral factors in individual decision making.
This course develops a coherent framework for analyzing the determination of macroeconomic variables such as national output, unemployment, interest rates, government debt and inflation. The course will also develop the skills needed for interpreting macroeconomic data and macroeconomic policy. One objective of the course is to provide a link between economic theory and current economic policy. Another objective is to provide students with the tools to analyze current macroeconomic policies.
This course is an introduction to Econometrics which is the study of statistical tools used to estimate economic relationships. The course begins with a discussion of the linear regression model. It then proceeds to introduce a number of topics relevant to the analysis of economic data. These include instrumental variables, discrete choice modeling, panel data analysis and program evaluation.
This course is an introduction to the basic concepts and tools of data analysis. Its goal is to enable students to conduct their own empirical research using a standard statistical package. The first part of the course emphasizes practical aspects of implementation using specific statistical software, while the second part emphasizes fundamental ideas such as sampling and nonsampling error, statistical modeling, alternative approaches to estimation, hypothesis testing and model selection, simulation and resampling methods, and issues arising with high-dimensional data. Hands-on exercises and a group research project using actual economic data represent an integral part of the course.