This course will provide the fundamentals of applied econometrics. We begin with statistical background useful for regression analysis and forecasting. The second section will include a thorough review of the classical regression model. Instruction will occur in the computer lab, where students will be instructed how to run regressions using actual data.
This class will build on the classical regression model. Heteroskedasticty and endogeneity issues will be further developed. Students will learn cross-sectional and panel techniques. The theory and use of instrumental and dummy variables will be discussed. Problem sets and a practical regression-based project will be required.
This course will emphasize time-series methods. We study serial correlation and univariate and multivariate times-series econometric models. Students will spend time in the computer lab where they will apply the techniques they learn to the study of time series applications including financial econometrics and applied macroeconomics.
The last econometrics class will be practical, where the end goal is the ability to construct models of economic activity. Forecast theory will be studied, including concepts such as structural model specification and forecast errors. The course includes study of modern forecast techniques such as combination and hierarchical forecasting.
This course introduces students to Microeconomics, the study of allocated limited resources. The theories economists use to describe economic behavior will be extensively studied. The class will have two sections: Consumer Theory and Production Theory. Because microeconomics is a math intensive course students will be expected to know Calculus.
The first major goal of the course is to combine consumer and producer theory into a general equilibrium framework. Then, we provide extensive coverage of theories of market power, i.e. monopoly, oligopoly, and various other market structures. Market power gives rise to strategic interactions in the economy, which this class takes seriously, in particular with a intensive study of Game Theory.
This course will establish the core macroeconomic theoretical foundation for the program. It will begin with study of the Historical Keynesian model. The remainder of the course will be spent on the most widely used dynamic modeling technique in macroeconomic research today, the infinite horizon representative agent model. Fiscal policy implications for the models will be a key part of the course.
This class will be policy oriented, with extensive discussion of current topics. We will discuss monetary and fiscal policy and the impacts of each. Additional topics will include incentives and redistribution, moral hazard, and political economy. Students will be expected to participate in class discussions and to complete a project.
As organizations look for ways to leverage data to create value, analytics has become an important source of competitive advantage for businesses. This course provides a hands-on introduction to the collections of predictive modeling techniques used to extract patterns and trends from data, enabling informed business decisions. The topics covered include data preparation, data visualization, predictive analytics, and decision-making under uncertainty.
The course focuses on the application of machine learning methods explored in Analytics I, which use data and statistical techniques to predict outcomes. Students will learn through a hands-on approach to build and tune models using R to predict categorical and continuous outcomes, test those models, interpret and present the results.
Topics and Policy Analysis
Financial theory, the time value of money, portfolio theory, and asset valuation will be presented with emphases on decision making in real-world situations. Problem sets will provide realistic applications of the material.
This applied micro class studies the theory of public bads/externalities, regulation theory, and empirical analysis in the context of environmental problems. We examine when markets maximize net benefits to society. Market failure topics include public goods, externalities, and common pool problems. We will study non-market valuation of environmental goods and econometric tools used to conduct policy analysis. The course includes study of the design of environmental policies to improve the performance of markets.
Mathematics for Economists will cover a variety of mathematical and statistical topics that are used in core MSQE curriculum. These would include: logarithmic/exponential/ polynomial functions, differential calculus, integral calculus, the Taylor approximation, static optimization, the Lagrangian technique, matrix algebra, basic linear algebra and systems of linear equations, probability, probability distributions, the normal distribution, moments, statistical estimation, the Central Limit Theorem, hypothesis testing, simple linear regression, and the matrix form of the multiple linear regression model.