Introduction
Administrative records report the contract each producer chose; economic analysis of insurance demand requires the set of contracts each producer faced. Without the choice set, revealed preference has no content: a producer’s election identifies preferences only relative to the rejected alternatives. This article documents the fourth stage of the FCIP data system, which reconstructs the feasible menu of Basic FCIP contracts for every transaction’s year and location and evaluates each alternative on the common 500-scenario system of the preceding stage (see Correlated yield–price scenarios under the M-13 framework), so that all alternatives differ by contract terms alone and never by luck. This design underpins the program-combination analysis of Gaku and Tsiboe (2025) and the prospective evaluation of proposed buy-up coverage in Tsiboe and Turner (2025).
The producer’s problem
Let \mathcal{C}_{i} denote the reconstructed choice set of producer (transaction) i, and let c \in \mathcal{C}_{i} index alternatives. Each alternative is characterized by an insurance plan, a coverage level \theta_c, a premium P_{ic}, and a subsidy rate s_c (the legislated share of premium paid by the government). Under scenario d the producer’s net revenue is
\pi^{(d)}_{i}(c) = R^{(d)}_{i} + I^{(d)}_{i}(c) - (1 - s_{c})\, P_{ic},
where R^{(d)}_{i} = y^{(d)}_{i} p^{(d)} is market revenue (yield draw times price draw), I^{(d)}_{i}(c) is the alternative’s indemnity in that scenario, and (1 - s_{c}) P_{ic} is the producer-paid premium. The producer’s election is modeled as
c^{*}_{i} = \arg\max_{c \,\in\, \mathcal{C}_{i}} E\!\left[\, U\!\left(\pi^{(d)}_{i}(c)\right) \right],
for a utility function U(\cdot) left to the analyst; the collection supplies the full distribution \{\pi^{(d)}_{i}(c)\}_{d=1}^{500} for every alternative so that expected-utility, certainty-equivalent, or cumulative-prospect criteria can be applied without re-simulation.
Menu construction
Three blocks compose \mathcal{C}_{i}.
The outside option. No insurance: P = 0, I^{(d)} \equiv 0, so \pi^{(d)} = R^{(d)}. Its inclusion makes participation itself a choice margin, which matters for extensive-margin subsidy analysis (Coble & Barnett, 2013).
Individual plans. YP, RP, RP-HPE, and APH at each legislated coverage level \theta_c \in \{0.50, 0.55, \dots, 0.85\}. The indemnity is the guarantee shortfall, with the guarantee price p^{g}_{c} plan-specific:
I^{(d)}_{i}(c) = \max\!\left(0,\; \theta_{c}\, y^{a}_{i}\, p^{g}_{c} - y^{(d)}_{i}\, p^{v,(d)}_{c}\right), \qquad p^{g}_{c} = \begin{cases} \max\!\left(p^{p}, p^{h,(d)}\right) & \text{RP},\\ p^{p} & \text{RP-HPE, YP, APH}, \end{cases}
where y^{a}_{i} is the approved yield, p^{p} the projected price, p^{h,(d)} the scenario harvest price, and p^{v,(d)}_{c} the plan’s valuation price for production to count (the harvest price for revenue plans, the projected price for yield plans). The harvest-price replacement feature, present under RP and excluded under RP-HPE, is thereby represented exactly, which is essential because that feature is itself a price option with distinct actuarial value. Premiums and subsidies per alternative are computed by the same rating calculators used by the program, evaluated at the transaction’s recovered rating primitives.
Area and margin plans. Area Yield Protection, Area Revenue Protection (with and without harvest-price exclusion), and Margin Protection (with and without harvest-price exclusion). Triggers are driven by the pool-average scenario paths \bar{y}^{(d)}_{j} rather than the farm draw, so the wedge between farm and area outcomes within a scenario, the basis risk that limits area products’ risk-reduction value (Miranda, 1991), is preserved by construction. Area rates are averaged over the pool’s offers, and per-liability premium and subsidy schedules are carried explicitly.
Evaluation on common scenarios
For each alternative and scenario the collection records the guaranteed yield, liability, premium, subsidy, plan-specific harvest liability, production to count, indemnity, and net revenue, then summarizes each alternative’s revenue distribution with moments and downside-risk metrics (variance, skewness, and lower partial moments of the form E\big[\max(0, \tau - \pi)^{n}\big] for target \tau and order n; Fishburn, 1977). Alternatives are ordered within producers as observed election, other insured alternatives, then the outside option, so revealed-preference contrasts read directly from the file.
Applications
Reconstructed choice sets evaluated on common scenarios have supported three strands of policy analysis. Gaku and Tsiboe (2025) rank combinations of Title I commodity programs (PLC, ARC-CO, ARC-IC) with crop insurance for 28,615 observations across 2,486 Kansas farms over 2014–2022, finding that combinations with high profit-enhancement potential also carry low profit risk for dryland wheat and sorghum, while no such alignment exists for corn and soybeans: low-cost strategies that enhance corn and soybean profits do not necessarily reduce their risk. Tsiboe and Turner (2025) use the same apparatus prospectively, pricing a proposed buy-up Price Loss Coverage option under crop insurance principles and finding a 23 percent reduction in revenue variability when combined with existing farm-based policies, at higher expected government cost per unit of variability removed. Tsiboe, Biram, and Hagerman (2026) extend the evaluation to supplemental area-based policies that cover part of the deductible (motivated by the fact that the most-participated policies leave producers exposed to the first 15 percent or more of losses) and find that low participation leaves meaningful downside-risk reduction and income transfer untapped, with benefit-per-premium calculations favoring broader use.
Limitations
Menus are limited to Basic coverage: endorsements (SCO, ECO, hurricane protection) and whole-farm products are outside the current scope, so the choice set understates the full policy space in recent years (see Tsiboe, Biram, & Hagerman, 2026, for the supplemental extension). Area triggers use pool-average paths rather than the official area-yield series, which preserves within-pool correlation but abstracts from idiosyncratic index noise. Eligibility reflects published offerings; administrative restrictions not visible in the actuarial records (e.g., written agreements) are not modeled.
Data availability
Two collections, one file per crop year: the enumerated menus
(menu_option_<year>.rds) and the scenario-evaluated
menus (calibrated_menu_<year>.rds). Both are hosted
on a private repository; an access token is available on request from
the author (ftsiboe@hotmail.com). With the token in hand:
# One-time setup: store the token provided on request
Sys.setenv(GITHUB_PAT = "<token provided on request>")
piggyback::pb_download(
file = "calibrated_menu_2022.rds", dest = tempdir(),
repo = "ftsiboe/rfcipCalibrate", tag = "calibrated_menu")Recommended citation
Tsiboe, F. (2026). Reconstructing FCIP choice sets. In FCIP calibrated and synthetic data catalogue. https://ftsiboe.github.io/rfcipCalibrate/articles/insurance-menus.html
Data users should additionally cite Tsiboe, Turner, and Yu (2025).
Disclaimer
This product uses data provided by USDA/RMA but is neither endorsed by nor affiliated with USDA or the U.S. Government.
References
Coble, K. H., & Barnett, B. J. (2013). Why do we subsidize crop insurance? American Journal of Agricultural Economics, 95(2), 498–504. https://doi.org/10.1093/ajae/aas093
Fishburn, P. C. (1977). Mean-risk analysis with risk associated with below-target returns. American Economic Review, 67(2), 116–126.
Gaku, S., & Tsiboe, F. (2025). Evaluation of alternative farm safety net program combination strategies. Agricultural Finance Review, 85(2), 254–273. https://doi.org/10.1108/AFR-11-2023-0150
Just, R. E., Calvin, L., & Quiggin, J. (1999). Adverse selection in crop insurance: Actuarial and asymmetric information incentives. American Journal of Agricultural Economics, 81(4), 834–849. https://doi.org/10.2307/1244328
Miranda, M. J. (1991). Area-yield crop insurance reconsidered. American Journal of Agricultural Economics, 73(2), 233–242. https://doi.org/10.2307/1242708
Tsiboe, F., & Turner, D. (2025). Incorporating buy-up price loss coverage into the United States farm safety net. Applied Economic Perspectives and Policy, 47. https://doi.org/10.1002/aepp.13536
Tsiboe, F., Biram, H., & Hagerman, A. (2026). Low participation and untapped benefits of supplemental crop insurance in the United States (working paper). Agricultural Risk Policy Center, North Dakota State University.