The DOI matches its Crossref record.
Designing and Rating an Area Yield Crop Insurance Contract
Abstract
This article documents the design and rate‐making procedures used in the development of the Group Risk Plan (GRP)—the new federal crop insurance product that insures based on area yield. The authors of this article worked closely with personnel in the Federal Crop Insurance Corporation and others in developing methodological and practical constraints needed in implementing a workable area yield contract. GRP indemnity payments are made based on percentage shortfalls in actual county yields relative to a forecasted yield. Historical county yield data are used to develop forecasted yields and premium rates.
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Citations
Cited by
Glauber, J. W. (2004) · American Journal of Agricultural Economics · doi:10.1111/j.0002-9092.2004.00663.x · Cited by 293
Probabilistic assessment of extreme heat stress on Indian wheat yields under climate change
Zachariah, M., Mondal, A., & AghaKouchak, A. (2021) · Geophysical Research Letters · doi:10.1029/2021gl094702 · Cited by 23
Metadata
- Authors
- Skees, J. R., Black, J. R., & Barnett, B. J.
- Venue
- American Journal of Agricultural Economics
- Publisher
- Wiley
- Published
- 1997-05
- Volume
- 79
- Issue
- 2
- Pages
- 430-438
- ISSN
- 0002-9092 (ISSN-L)
- 1467-8276
- OpenAlex
- W1971123613
- Cited by
- 263
- References
- 0
- FWCI
- 25.08
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Designing and Rating an Area Yield Crop Insurance Contract. https://app.cochat.ai/papers/10.2307/1244141
- The paper
- Skees, J. R., Black, J. R., & Barnett, B. J. (1997). Designing and Rating an Area Yield Crop Insurance Contract. American Journal of Agricultural Economics. https://doi.org/10.2307/1244141
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.