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Input Demand under Yield and Revenue Insurance
Open accessAbstract
Previous studies disagree on the effects of insurance on fertilizer application rates. The effect of increased fertilizer on the probability of low yields primarily determines whether fertilizer and insurance are substitutes or complements. We estimate conditional distributions of corn yields to determine if the technical relationship between yields and fertilizer supports the hypothesis that insurance increases optimal application rates. Our results indicate no support for this hypothesis. At all nitrogen fertilizer rates and reasonable levels of risk aversion, nitrogen fertilizer and insurance are substitutes, suggesting that those who purchase insurance are likely to decrease nitrogen fertilizer applications.
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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
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Lee, C.-C., Zeng, M., & Luo, K. (2024) · Environmental Impact Assessment Review · doi:10.1016/j.eiar.2023.107324 · Cited by 269
Aubert, C., Raineau, Y., & Raynal, M. (2026) · European Review of Agricultural Economics · doi:10.1093/erae/jbaf065
Metadata
- Authors
- Babcock, B. A., & Hennessy, D. A.
- Venue
- American Journal of Agricultural Economics
- Publisher
- Wiley
- Published
- 1996-05
- Volume
- 78
- Issue
- 2
- Pages
- 416-427
- ISSN
- 0002-9092 (ISSN-L)
- 1467-8276
- OpenAlex
- W1989679018
- Cited by
- 339
- References
- 0
- FWCI
- 14.64
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Input Demand under Yield and Revenue Insurance. https://app.cochat.ai/papers/10.2307/1243713
- The paper
- Babcock, B. A., & Hennessy, D. A. (1996). Input Demand under Yield and Revenue Insurance. American Journal of Agricultural Economics. https://doi.org/10.2307/1243713
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.
