Global Commodity Data Source Brief

Assessment of source quality for a student project focused on worldwide production and sale/trade data for coffee, tea, cocoa/chocolate, yerba mate, and matcha. Built to help a mixed-interest student team choose a realistic project scope.

Best practical scope: start with coffee + tea + cocoa for a solid cross-country project. Add yerba mate only if a narrower South America angle is acceptable. Treat matcha as a special-case extension because it is often buried inside green-tea categories.

Recommended source stack

Source comparison

FAOSTAT

Primary for production

Best official source for global agricultural production by country and year. Strong for coffee, tea, and cocoa. Useful for consistent historical time series.

Strengths: authoritative, global coverage, long time span, machine-readable.

Weaknesses: not retail sales; processed products may not map cleanly to crop production concepts.

UN Comtrade

Primary for trade

Best for imports/exports using HS codes. Works well for coffee, tea, cocoa beans, cocoa products, yerba mate, and some matcha-related trade categories.

Strengths: global trade coverage, country pairs, product code detail.

Weaknesses: product-code complexity; trade is not the same thing as production or final sales.

ICO / ITC / ICCO

Best commodity-specific support

These bodies are excellent for context, benchmark statistics, and domain-specific reporting for coffee, tea, and cocoa respectively.

Strengths: commodity expertise, curated statistics, useful publications.

Weaknesses: some access may be partial, publication formats may be less tidy than FAOSTAT/Comtrade.

Commercial market reports

Use with caution

Often the only easy source for “market size” or “global sales” estimates for yerba mate and matcha.

Strengths: useful for modern market framing.

Weaknesses: methodology opacity, paywalls, inconsistent definitions, hard to reproduce.

Commodity-by-commodity assessment

Coffee

Strong

Best-supported commodity in the set. Excellent production and trade data. Strong institutional support from ICO.

Tea

Strong

Strong production and trade data. Good industry/statistical support. Global comparisons are feasible.

Cocoa / chocolate

Mixed

Cocoa is strong. Chocolate is harder because it is a processed consumer product and doesn’t map as neatly to agricultural production.

Yerba mate

Usable but narrower

Trade codes exist and market estimates exist, but official global institutional support is weaker. Better for a regional comparison angle.

Matcha

Weak as standalone global category

Best treated as a subcategory of green tea or as a modern specialty-market case study. Hard to compare cleanly against coffee/tea/cocoa at global scale.

Recommended project scopes for a student team

Scope A — safest / strongest

Coffee + tea + cocoa

Best balance of production and trade coverage with credible international sources.

Scope B — beverage crop focus

Coffee + tea + yerba mate

Interesting conceptually, but yerba mate reduces data consistency and global comparability.

Scope C — specialty extension

Coffee + tea + matcha as case study

Good if the team wants a “global commodity + premium niche product” angle, but matcha should not be treated as equally robust in the data model.

Scope D — consumer product angle

Coffee + tea + chocolate

Possible, but be careful: chocolate is not the same data concept as cocoa. This scope needs explicit caveats and a stronger reconciliation layer.

Key methodological warning

Do not casually compare:

The cleanest project will keep production, trade, and market-size questions separated or explicitly reconciled.

Likely next step

Build a reproducible source stack around FAOSTAT + UN Comtrade + commodity-specific organization data, then test whether the chosen project scope has enough overlap in country-year coverage to support the comparison you want.