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Designed for students majoring in the Isenberg School of Management, Resource Economics, Economics, and other social science majors, and for students who haven't declared a major. Introduction to basic statistical methods used to collect, summarize, and analyze numerical data. Emphasis on application to decision making; examples from the social sciences. Topics include: common statistical notation, elementary probability theory, sampling, descriptive statistics, statistical estimation and hypothesis testing. Basic algebra required. (Gen.Ed. R1, R2)

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.

Basic theory of monopoly and competitive markets; market equilibria; comparative statics; and adjustment process. Analysis of optimizing decisions for firms and consumers; production, cost, and utility functions; comparative static analysis; the derivation of supply and demand curves; risk and uncertainty.

Methodologies for dealing with collinearity, autocorrelation, heteroscedasticity, and endogenous right-hand-side variables. Stochastic restrictions and evaluating restrictions via alternative norms. Generalized least squares procedures. Zellner estimation. Pooling data. Simultaneous systems of equations. Fixed-effects and random-effects models.

Market structure models with application to the food system and to natural resource industries. Firm behavioral strategies under various market structures. The role of product differentiation, advertising, market power, mergers, barriers to entry, pricing and non-price rivalry. Market performance including prices, costs, profits, labor issues, and progressiveness. Prerequisite: RES-ECON 305 or ECON 203.
BS-ResEc majors can satisfy their Integrative Experience requirement by taking this course plus Res-Econ 394 and 453.

Introduction to contemporary quantitative methods as applied to production, marketing and resource management problems in both a private and public setting. Linear programming and decision making under uncertainty. Prerequisite: RES-ECON 211 or equivalent.

Intermediate level microeconomic theory. Consumer demand theory and economics of production. Geometric and mathematical approaches. Models of market behavior, related to examples. Applications to business and government decision making emphasized. Required course for more advanced departmental offerings. Prerequisite: RES-ECON 102 or ECON 103 and MATH 127 or 131.

Economic analysis of natural resource use and conservation, including minerals, forests, fisheries, wildlife, land, and outdoor recreation economics. Focuses on resource use patterns that are socially efficient and sustainable, and institutional arrangements for bringing these about. (Gen.Ed. SB)

Designed for students majoring in the Isenberg School of Management, Resource Economics, Economics, and other social science majors, and for students who haven't declared a major. Introduction to basic statistical methods used to collect, summarize, and analyze numerical data. Emphasis on application to decision making; examples from the social sciences. Topics include: common statistical notation, elementary probability theory, sampling, descriptive statistics, statistical estimation and hypothesis testing. Basic algebra required. (Gen.Ed. R1, R2)