Selected crop value chains in Kenya: current conditions and outlook to 2035
What the data show about production, cultivated area, productivity and market demand—and how those conditions inform scenarios to 2035.
This analysis begins with observed conditions: how cultivated area, output, yield and market indicators have changed across the selected crops. The second part sets out the modelling framework, presents the 2025–2035 scenarios, and concludes with a calculator through which users can test alternative assumptions.
The current state of selected crop value chains in Kenya
The data describe markedly different crop economies. Some value chains are expanding through additional cultivated area, others are changing mainly through yield and productivity, and several market-facing crops are shaped as much by imports or exports as by domestic output.
Across the ten crops, three broad patterns stand out. Sunflower and avocado show substantial recent expansion, although sunflower growth has been driven mainly by cultivated area while avocado has combined area growth with higher measured yield. Coffee and canola have changed within comparatively stable land footprints, while tea’s export performance has strengthened despite year-to-year variation in production. Palm oil remains a large import market, and cotton and cashew continue to show pronounced variation in output and productivity.
Where is production concentrated?
Explore reported crop production across all 47 counties of Kenya. Every county boundary and the national outline are shown for every crop; counties without a reported production value remain visible in grey rather than being treated as zero.
Forecasting methodologyRecursive-dynamic partial equilibrium for edible oils Method note
The edible-oils outlook is now specified around the supplied recursive-dynamic partial-equilibrium methodology rather than a single trend or CAGR. The market is treated as import-clearing: domestic supply, trade, stocks, re-exports and distinct food, processing and oleochemical uses are reconciled first, then imports are solved as the residual requirement.
| Module | Method used for edible oils | What the website does now |
|---|---|---|
| 0 · Base-year balance | Reconcile domestic oil output + imports − exports − re-exports ± stocks with food-direct, food-processing, oleochemical and loss uses. Cross-entropy balancing is the specified reconciliation method. | Observed trade/production series are kept separate and data breaks are flagged. The 2025 soybean observation from the supplied 2026 yearbook is shown but is not silently used to re-base the forecast before reconciliation. |
| 1 · Demand | Estimate a censored QUAIDS demand system on KIHBS microdata; use a Gompertz saturation path for long-run food-direct consumption; project processing and oleochemical demand from sector output and technical input coefficients. | The site labels the visible Low/Base/High demand paths as calibrated sensitivity scenarios. It does not claim that QUAIDS/Gompertz coefficients have been re-estimated inside the browser without the required microdata and supply-use inputs. |
| 2 · Domestic supply | Build oil output crop-by-crop and county-by-county from harvested area × yield × (1 − post-harvest loss) × oil content × extraction efficiency × (1 − refining loss). Area follows Nerlovian partial adjustment; yield combines autonomous trend with logistic technology adoption; crush/refining capacity can bind. | The interactive edible-oil calculator now separates physical oil content, extraction efficiency, losses and adoption, and uses a partial-adjustment area path rather than a simple linear area/yield ramp. |
| 3 · Deficit closure | Imports are the residual after domestic utilisation and supply are reconciled. The methodology then inverts substitution targets into area, yield and capacity requirements and can solve a least-cost expansion programme. | For edible-oil calculator runs, a positive demand–domestic-supply gap is labelled as the residual import requirement, not as domestic demand itself. |
| 4 · Prices & policy | World-to-domestic price transmission is estimated with an asymmetric error-correction model; tariff, levy, exchange-rate and world-price scenarios feed both demand and supply incentives. | Existing price/FX scenario controls remain a sensitivity layer. Full ECM estimation requires the monthly price and trade-cost series outside this static file. |
| 5 · Validation & uncertainty | Backcast 2016–2025 and report MAPE/Theil’s U; then run at least 10,000 Monte Carlo draws and report P10/P50/P90 fan charts plus parameter influence. | Low/Base/High lines should be read as deterministic scenario envelopes, not probabilistic confidence intervals, until the external backcast and Monte Carlo workflow is run. |
Crops in the oil complex. Sunflower, soybean, canola/rapeseed, sesame, groundnut, cottonseed and coconut/copra are bulk supply candidates. Avocado and macadamia are retained as minor high-value oils/export chains: they matter for export earnings but should not be treated as major volume substitutes for imported edible oil.
From observed conditions to a 2035 outlook
For edible oils, the forecasting specification now follows the supplied recursive-dynamic partial-equilibrium architecture: reconcile the base-year supply–utilisation account, estimate demand and domestic supply separately, solve prices jointly, and treat imports as the residual requirement. Other value chains retain crop-specific market models where the edible-oil PE framework is not applicable.
The observed evidence and forecast layer remain deliberately separate. The 2026-yearbook soybean observation is displayed as evidence and flagged for reconciliation rather than being allowed to create an automatic structural break in the forecast baseline. Low/Base/High paths are transparent sensitivity scenarios until the full econometric estimation, backcast and stochastic validation described in the methodology are completed. Planning envelopes and analyst-defined scenario parameters are identified as assumptions rather than presented as observed facts.
Summary of the Base scenario
Demand and domestic supply capacity are estimated separately.
Forecast demand
Each crop uses a demand method suited to its market: import substitution, export growth, industrial capacity, or a domestic/export proxy.
Build domestic capacity
Area moves toward scenario targets, new perennial area is lagged to bearing age, and yield moves toward a potential yield.
Convert to the market unit
Seed is converted to oil, FFB to CPO and seed cotton to lint so supply and demand are compared in the same unit.
Compare demand with local supply
Local supply gap = max(demand − domestic supply capacity, 0). Imports are not counted as supply in this comparison.
Historical observations and the 2025–2035 scenario range
The historical series remains visible as a reference. The shaded region begins at the model horizon; the green line shows the verified Base path and the translucent band spans the Low and High scenarios.
View the data behind this chart
Forecast paths and assumptions by crop
The sections below report the Low, Base and High demand paths and the domestic supply-capacity assumptions used to evaluate whether those markets could be served from domestic production.
Test alternative assumptions
The calculator reproduces the structure of the verified model while allowing selected parameters to be changed. The published Base path remains fixed and is shown alongside the user-defined scenario for comparison.
Scenario result
See the calculation logic
How to read these forecasts
- Scenario, not certainty. Low, Base and High are conditional sensitivity paths, not P10/P50/P90 probability bands. The supplied methodology requires backcasting and at least 10,000 Monte Carlo draws before probabilistic fan charts are reported.
- Edible-oil supply now follows the PE physical identity. Area, yield, post-harvest loss, oil content, extraction efficiency and refining loss are separated in the calculator; full county-level Nerlovian estimation and crusher-capacity constraints require the external estimation dataset.
- Demand is crop-specific. Sunflower and canola use direct oil imports as a narrow demand floor; cotton uses spinning capacity; coffee and tea use export-demand growth. Where imports help define the demand market, they are not counted as domestic supply when the local supply gap is calculated.
- Land envelopes differ in evidence quality. Some are official cultivation envelopes; others are analyst or programme planning assumptions and should not be read as national GIS suitability maps.
- Perennial timing matters. New avocado, macadamia, cashew and palm area does not instantly become productive.
Download the forecast data
The web package includes the full 2025–2035 Low/Base/High series and the verified input register used for the charts.