Farm economics · policy timing · trade and welfare
What does an FMD disruption cost?
Who gains, who pays, and when?
Explore three complementary economic models adapted from Syntera farm-management, dynamic-programming and market-welfare models. Compare a published market baseline, an FMD economic disruption, and disruption with economic mitigation.
LP / DP / PEResearch edition · 24 September 2026
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Farm resource optimisation
Two livestock enterprises, six feeds and twelve months. Optimise herd size and feeding subject to energy, protein, intake, labour and forage constraints.
Repeated policy decisions and farm responses
A finite-horizon government DP chooses among four programmes. Farm types respond to private costs and anticipated benefits. Seasonal exposure and protection change across quarters.
Who bears the market impact?
Clear sheepmeat, beef and pigmeat markets with domestic supply and demand, imports and exports. Show consumer welfare, producer welfare and government spending separately.
Methods, provenance and interpretation
Model map
| Module | Repository lineage | What is solved |
|---|---|---|
| Farm LP | legacy_pages/506_Syntera_Farm_LP_TAD.py: lpMatrix/solve_lp adaptation | Monthly sheep/cattle enterprise and feed allocation under energy, protein, intake, labour and forage constraints. |
| Policy DP | State/action/Bellman structure from page 521 and the Syntera BTV laboratory; FMD economic state labels and costs are new. | Finite-horizon choice among four preparedness/recovery programmes with farm response and a quarterly public budget. |
| Market PE | Market-clearing structure adapted from Syntera PE lineage and model/uk_fmd_pe_engine.py. | Domestic supply/demand, imports and exports; price, quantities, consumer surplus, producer surplus, government account and total domestic welfare. |
Scenario boundary
The published FMD market results of Feng, Patton and Davis (2017) provide context and strategy labels. The laboratory does not reproduce EXODIS or generate premises, spatial spread, infections or outbreak duration. Editable affected shares, export-demand shocks and mitigation effects are economic scenario assumptions. They are not estimates inferred from a current event.
The LP, DP and PE address different decision scales. Their monetary results must not be added.
LP equations
Maximise farm contribution: gross enterprise output minus non-feed variable costs, monthly feed costs, fixed intervention cost and uncompensated disruption losses. Decision variables are sheep head, cattle head and feed dry matter by species, feed source and month. Constraints cover head bounds, monthly labour, feed intake, metabolisable energy, crude protein, forage availability, silage stocks, bought hay and concentrates.
The simplex solver reports status, iterations, constraint slack and maximum residual. Defaults are inherited repository planning assumptions, not representative UK farm accounts.
DP equations
The Bellman recursion is V_t(s)=min_a{C(s,a)+beta E[V_{t+1}(s')]}. The aggregate economic state contains disruption pressure, preparedness coverage and recovered market capacity. Policies affect public resource cost, farm response, disruption and future states. The DP is a conditional economic decision model, not an epidemiological simulator. Transition coefficients remain research assumptions until calibrated against matched aggregate scenario outputs.
PE equations
For each market, domestic supply, demand, imports and exports respond to price through constant elasticities. Market price solves Q_unaffected(p)+Q_exposed(p)+M(p)-D(p)-X(p)=0. Consumer and producer surplus changes are integrated from those curves. Subsidies and compensation appear in producer and government accounts and cancel from domestic welfare except for administration and real resource costs.
The 2025 reference quantities and prices are editable. The central export-demand shock is deliberately severe and conditional; it is not a forecast. Northern Ireland and product-level eligibility require a more granular trade dataset.
Sources and defaults
- Feng, Patton & Davis (2017), Market Impact of Foot-and-Mouth Disease Control Strategies: A UK Case Study, Frontiers in Veterinary Science 4:129.
- Defra, Agriculture in the United Kingdom 2025, livestock chapter: production, market and trade anchors.
- Syntera repository:
legacy_pages/506_Syntera_Farm_LP_TAD.py,app/fmd_uk_economic_twin.py,model/uk_fmd_pe_engine.py,config/uk_fmd_params.json. - Barnes et al. (2023), bTB consequential-cost survey: costing taxonomy only; no bTB unit cost is transferred to FMD.
dp_bridge is not a Bellman solver; this laboratory uses the audited Syntera DP architecture with new FMD economic assumptions. Pig and dairy enterprises are not present in the source monthly farm LP. They are included in DP/PE only and are clearly separated from LP results.