Gain first-hand knowledge of agribusiness operations using a blend of in-class lectures and site visits.

Topics: Strategic decision-making, valuation methods, long-term sustainability strategies, climate mitigation.

Explore quantitative decision-making models essential for business and resource management decisions.

Topics: Decision, predictive, visual, and prescriptive analytics models.

Explores policy and project evaluation in the global food and agriculture sector using real-world cases.

Topics: Policy Analysis Matrix, Cost-Benefit Analysis, critical evaluation of economic and environmental policies.

Explore futures and options for hedging and speculation through cases in the lumber and foreign exchange markets.

Topics: Real-world cases and and an interactive trading game in options, hedges, opts, calls, and arbitrage.

Explore focus group and survey research design, implementation and data analysis.


Topics: R Studio data analytics, Cluster analysis, Interview techniques, coding of content data.

Learn the critical issues of sustainability, especially in managing “common pool” resources such as capture fishery resources.

Topics: Sustainable economic management models, global capture (wild) fisheries and aquaculture modeling.

Explore the current global landscape of climate emissions regulations and the frameworks.


Topics: Climate change mitigation, methodologies for evaluating the merits and impacts.

Dive into the essential environmental datasets, including weather, ecology, and satellite imagery.


Topics: Practical skills in data extraction, processing, and analysis using R, Python, and JavaScript for Google Earth Engine.

Build expertise in econometric methods such as instrumental variables, panel data, and difference-in-differences.


Topics: Causal relationships such as impact of forest fires on health, income growth on deforestation, national policies on carbon emissions reduction.

Gain hands-on skills in R, SQL, and Python, by applying these tools to real-world finance, climate, and environmental data.


Topics: Big data application in food and environment, areas such as ESG indexing and climate change impact, data wrangling, SQL and machine learning for financial assessments and predictive analytics.

Explore the critical role of Environmental, Social, and Governance (ESG) principles in shaping sustainable business strategies within the global food and resource sectors.


Topics: ESG regulatory landscapes, climate risk management, social responsibility.

Investigate the techniques of time series econometrics models and apply them to policy analysis and forecasting. applications in the business, finance and resource sectors.


Topics: Univariate and multivariate time series models, stationary and non-stationary forecasting models, ARIMA, Vector Auto-regression (VAR), and error correction models.

Explains the role of governments, business, civil society and international institutions in global food and resource policy-making.

Topics: Global food crises, large-scale land acquisitions, WTO agriculture negotiations, alternatives to current global policies and governance arrangements.