FRE 505(1.5): Policy and Project Evaluation Tools - Agricultural and Resource Policy Analysis* 
Provides the analytical tools Policy Analysis Matrix (PAM), Cost Benefit Analysis (CBA) and Domestic Resource Cost (DRC) to evaluate Government policies and projects. Using the analytical framework developed in previous FRE 502.

FRE 515 (3): Agribusiness Management
Brings a grounding experience into “real world” agri-business. Uses the analytic framework developed in FRE 516 and apply concepts of accounting, finance, marketing, operations, human resources, leadership, quality assurance, crisis management, ethics and sustainability, into managerial decision making.

FRE 517 (1.5): Futures Trading of Agricultural Commodities  
This course explores the use of risk management tools in the lumber commodity and foreign exchange markets. In the context of these two markets, students will get a practical understanding of using futures and options to hedge and speculate. The course will begin with knowledge of the lumber cash market and how the various players use futures to hedge their cash positions. We will then follow the life of a futures trade to compare futures and cash prices; this overview will subsequently form the foundation to understand the basis of futures trading. In the next stage, we will incorporate foreign exchange risks in international trade and take a look at other derivative products. As the course progresses, students will integrate and build upon concepts and skills from this and different courses to manage practical problems at hand. Class participation will be encouraged to simulate a trading floor where ideas and information are openly discussed.

FRE 518 (1.5): Survey Design and Data Analysis
Introduce the methods and techniques in applied survey research and data analysis with concentration on the food, agribusiness and resource sector. Content includes the use of focus groups as exploratory research, design of questionnaires, best practices of conducting surveys, sample selection and design, compiling and organizing data, and survey data analysis & presentation.

FRE 520 (2): Professional Masters Seminar
This course provides a forum for students to develop an understanding of real-world applications, trends and practices of applied policy, environment, commodity markets, trade policy and agribusiness economics in the food and resource related sectors.

FRE 521D (1.5): Data Analytics for the Food & Resource sector
The primary objective of business analytics is to find useful patterns in data. This course is designed to help you find these patterns by providing frameworks, models and hands-on experience. The course will begin by providing an overview of field of analytics and then move into specific data analysis techniques and tools. A variety of data manipulation tools will be discussed including R, Tableau, PowerBI and Excel. As well, we’ll examine the role of programming languages and data query languages using both NoSQL (object) and SQL (relational) databases.

FRE 521E (1.5): Supply Chains in Food and Agriculture: Economics Analysis and Technological Transformations
This course uses a set of conceptual economic tools and empirical examples to examine the economics of agri-food supply chains and the significant transformations they have undergone. Transformations reviewed include increasingly dynamic and complex elements in supply chains, contractual relationships, worldwide food retailing, differentiated food products, concentration of supply chains across stages, and strategically important countries (e.g., China, Brazil, Ukraine) becoming major buyers and sellers. Topics include market power; pricing strategies, vertical integration, private labels and standards and technological change in agri-food supply chains.

FRE 521G (1.5): Economic Development in the Food & Resource sector 

The first section of the course examines economic development from the perspective of factor markets including capital investment, labor mobility, and urban versus rural wages. The integrating role of institutions such as mechanisms for risk sharing and incentives for technology adoption is also featured. The second part of the course uses important papers in the field to examine the role of agriculture in economic development, especially how institutions and property rights can explain the economic development of countries, and how these features interact with culture

FRE 523(1.5): Resource Economics - Fisheries
Introduction to Economics of Renewable Resources with focus on marine resource. This analytical framework is then use to assess extraction, depletion, protection and management of marine resources. Emphasis in the efficiencies and failure on economic decision making (management).

FRE 526 (1.5): Environmental Economics and Policy: Theory
In this course, we will build an analytical framework from simple economic principles. We will use it to define society’s optimal pollution and preservation/exploitation of natural resources. We will then ask: can markets function effectively to protect our environment or is government policy necessary? When it comes to the environment, the market often fails. What can we do to improve it? Based on the type of resource, we will study policies to correct market failure. We will understand the realities of government intervention and how governments can do better in steering our environment.

FRE 527 (1.5): Environmental Data Analytics
This course introduces the students to core environmental datasets spanning weather, ecology, and satellite imagery data sources, which are routinely used to support environmental metrics and decision-making in the food and resource sector. It provides hands-on experience with data extraction, processing and analysis techniques, as well as visualization tools, which are particularly adapted to dealing with the complexities of each environmental data type. The programming languages covered are R and Python, as well as some JavaScript for Google Earth Engine.

FRE 529 (1.5): Estimating Econometric Models 
Introduces advance econometric methods extending the analysis from FRE 528. Topics can include instrument variables (IV) estimation, experiments and quasi-experiments (difference-in-difference estimation, ANCOVA, regression discontinuity), and panel data methods (basic models and dynamic panel models). The focus of the course will be on the application of these methods in econometric modeling rather than on theoretical proofs.

FRE 530 (1.5): Applied Econometrics with Time Series Data 

This course will introduce students to the basic techniques of time series econometrics and will investigate both univariate and vector processes in time series models. The goal of this course is to provide students with sufficient understanding and application of time series methods to be comfortable working within food and resource modeling environment that requires time series analysis.  A variety of models and analytical methods will be investigated in this course including stationary and non-stationary forecasting models, asymptotic theory for time series, linear regression with time-series data, and Box-Jenkin’s modeling strategy (ARIMA), Vector Auto-regression (VAR), and error correction models.

FRE 531 (1.5): Global Food and Resource Governance
This course provides an understanding of the role of governments, business, civil society and international institutions in global food and resource policy-making.  The course is organized around the examination of real-world controversies in global food and resource governance – such as, but not limited, to global food crises, large-scale land acquisitions, and the agriculture negotiations at the World Trade Organization. Students taking this course will develop substantive knowledge of global policy-making around food and resources and be able to assess the efficacy, fairness and legitimacy of, and possible alternatives to, current global policies and governance arrangements.

FRE 585 (3): Quantitative Methods for Business and Resource Management

This course will provide the necessary foundation and experience for students to apply a variety of modeling and quantitative techniques to business and resource management problems. This class will concentrate on frequently used quantitative and decision-making models that include decision analysis, resource allocation models, optimization such as linear programming (allocation and scheduling of resources), an introduction to forecasting and predictive analytics, data mining, simulation modeling, operations analysis, and inventory management. Upon completing this course, students will be capable of using a powerful set of functions and tools in Microsoft Excel for solving a broad range of quantitative problems. Student will also be introduced to a Visual Analytics tool called Tableau and will have several assignments that will utilize this tool.