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Topics are divided between forecasting techniques and econometric time-series modeling. Discovering the data generating process of a random variable. Univariate approaches for dealing with a time series: exponential smoothing methods and ARIMA models. Tests for stationarity. Unit roots. Dickey-Fuller tests. Augmented Dickey-Fuller models. Multivariate approaches for modeling. Spurious relationships. Cointegration. Vector autoregression. Error correction models.

This course will introduce you to the building blocks of microeconomic theory. We cover consumer theory, producer theory, partial equilibrium, and public goods and externalities. This will provide you with the tools necessary to both understand and conduct research in economics.

This course introduces advanced econometric theory and tools for estimating and testing models, evaluating policy changes quantitatively, and more generally studying the relation between economic variables. The goal is to learn enough theory and get enough practice to be able to conduct sensible economic analysis. The course covers most contemporary methods on nonlinear estimation, including the Maximum Likelihood Estimator, Nonlinear Least Squares, and General Method of Moments.

This course will focus on probability theory and statistical inference, the foundations of econometric analysis. Probability theory is the building block that will allow you to understand estimation and statistical inference. The first part focuses on univariate distributions and multivariate distributions, with care taken to differentiate discrete and continuous random variables. The second part covers estimation and inference.

Market structure models with application to various industries. Firm behavioral strategies under different market structures. The role of product differentiation, advertising, market power, mergers, barriers to entry, price and non-price rivalry. Market performance including prices, costs, profits, labor issues, and progressiveness. BS-ResEc majors can satisfy their Integrative Experience requirement by taking this course plus Res-Econ 394LI and 453.

Introduction to contemporary quantitative methods as applied to production, marketing and resource management problems in both private and public settings. Topics include: linear programming and decision making under uncertainty.

The purpose of this course is to present intermediate level microeconomic theory. Primarily we will focus on consumer demand theory and economics of production. Both geometric and mathematical approaches will be presented. This course provides the background necessary for more advanced courses in the department.

Economic analysis of natural resource use and conservation. Includes analyses of the use of fuel, forest, marine and biodiversity resources. Focuses on evaluating natural resource use in terms of efficiency and sustainability, and designing regulations for correcting inefficient and unsustainable resource markets. (Gen.Ed. SB)

Designed for students in the social science and business related fields of study. Introduction to basic statistical methods used to collect, summarize, and analyze numerical data. Emphasis on application to decision making; examples from the social sciences and business. Topics include: common statistical notation, elementary probability theory, sampling, descriptive statistics, statistical estimation and hypothesis testing. Basic algebra and familiarity with computer and internet necessary. (Gen.Ed. R2)