Relaxing Heteroscedasticity Assumptions in Area‐Yield Crop Insurance Rating

Harri, Ardian; Coble, Keith H.; Ker, Alan P.; Goodwin, Barry K.

doi:10.1093/ajae/aar009

Cited by 64 publications

(69 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In light with previous studies, the trend estimation approach adopted in this research is similar to one used in Harri et al (2011) where they examined the effect of different heteroskedasticity assumptions on crop insurance rating. The main exception is that they considered both one knot and two knot spline specifications.…”

Section: Mean and Trend Estimationmentioning

confidence: 99%

“…Following Deng et al (2008) and Harri et al (2011), the rating of GRP insurance contract is formally presented as follows. In particular, both the indemnity and premium rates calculations are discussed.…”

Section: Valuation Of Grp Insurance Contractmentioning

confidence: 99%

“…In general, the U.S. crop insurance programs have been characterized by low participation and weak actuarial performance (Ker and Coble 2003), resulting in some General Accounting Office (GAO) investigations. According to Harri et al (2011), the GRP had an insurance liability of $2.5 million in its first year. Together with its revenue insurance counterpart, GRIP, they covered a liability of about $8.5 billion on over 34 million acres insured by the year 2008.…”

mentioning

confidence: 99%

“…On the contrary, the tendency for a farm to produce below a county-yield level guarantee and yet receive no indemnity and vice versa has been cited to affect the risk reduction of the area-yield insurance GRP (Miranda 1991;Barnett 2005;Harri et al 2011). This problem is caused by what insurance experts refer to as 'basis risk' which can be thought of as the lack of perfect correlation between county and farm-yields.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Spatial Pattern of Yield Distributions: Implications for Crop Insurance

Annan

Tack

Harri

et al. 2013

American J Agri Economics

Self Cite

View full text Add to dashboard Cite

Despite the potential benefits of larger datasets for crop insurance ratings, pooling yields with similar distributions is not a common practice. The current USDA-RMA county insurance ratings do not consider information across state lines, a politically driven assumption that ignores a wealth of climate and agronomic evidence suggesting that growing regions are not constrained by state boundaries. We test the appropriateness of this assumption, and provide empirical grounds for benefits of pooling datasets.We find evidence in favor of pooling across state lines, with poolable counties sometimes being as far as 2,500 miles apart. An out-of-sample performance exercise suggests our proposed pooling framework out-performs a no-pooling alternative, and supports the hypothesis that economic losses should be expected as a result of not adopting our pooling framework. Our findings have strong empirical and policy implications for accurate modeling of yield distributions and vis-à-vis the rating of crop insurance products.

show abstract

Section: Mean and Trend Estimationmentioning

confidence: 99%

Section: Valuation Of Grp Insurance Contractmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Spatial Pattern of Yield Distributions: Implications for Crop Insurance

Annan

Tack

Harri

et al. 2013

American J Agri Economics

Self Cite

View full text Add to dashboard Cite

show abstract

“…In addition, Deng et al (2008) and Vedenov and Barnett (2004) applied log-linear model. While Harri et al (2011) and Adhikari et al (2012) applied bilinear spline and knot methods. On the other hand, Ker (1996), Goodwin and Ker (1998), and Ker and Goodwin (2000) used stochastic model such as autoregressive integrative moving average (ARIMA) for the yield prediction.…”

Section: Yield Estimation Approachesmentioning

confidence: 99%

Designing a whole-farm revenue insurance for agricultural crops in Zanjan province of Iran

Ghahremanzadeh

Mohammadrezaei

Dashti

et al. 2018

EARN

View full text Add to dashboard Cite

ABSTRACT:The purpose of this article is to design and empirically evaluate the Whole Farm Insurance (WFI) over the conventional insurance programs in Zanjan province of Iran. Historical farm-level and county-level data were used to estimate yield and price density functions. Both parametric and nonparametric methods were applied for predicting the future values and the PQH simulation method was utilized to calculate premium rates. Results revealed that loss ratios of the WFI are lower for farmers who insured more than one crop. Additionally, utilizing WFI reduces premiums. Moreover, premiums obtained from nonparametric method are relatively lower compared to the parametric approach.KEYWORDS: Indemnity, Iran, price risk, whole-farm insurance, yield risk, Zanjan.Diseño de un seguro de ingresos de toda la granja para cultivos agrícolas en la provincia de Zanjan de Irán RESUMEN: El propósito de este artículo es diseñar y evaluar empíricamente el Seguro Agrario Integral (SAI) con respecto a los programas de seguros convencionales en la provincia de Zanjan de Irán. Se usaron datos históricos a nivel de explotación y de comarca para estimar las funciones de rendimiento y de densidad de precios. Se aplicaron métodos paramétricos y no paramétricos para predecir los valores futuros y se utilizó el método de simulación SAI para calcular las tasas de primas. Los resultados revelaron que los índices de pérdida del SAI son más bajos para los agricultores que aseguraron más de un cultivo. Además, la utilización del SAI reduce las primas. Las primas obtenidas del método no paramétrico son relativamente más bajas en comparación con el enfoque paramétrico.PALABRAS CLAVE: Indemnización, Irán, riesgo de precio, seguro de granja completa, riesgo de rendimiento, Zanjan.JEL classification/Clasificación JEL: G22, C15, C53, C63.

show abstract

Actuarial implications of prevented planting coverage

Turner,

Tsiboe,

Biram

et al. 2024

Applied Eco Perspectives Pol

View full text Add to dashboard Cite

Within the Federal Crop Insurance Program (FCIP), prevented planting (PP) coverage provides payments for pre‐planting costs associated with crops that ultimately cannot be planted due to adverse weather. PP indemnities, which are not considered production losses within the FCIP rating methodology, influence premium rates differently than typical losses. This study utilizes a panel data set consisting of approximately 77,697 county level observations from RMA's summary of business to identify the relationship between the prevalence of prevent plant use and a number of actuarial related outcomes. Overall, we find that increases in the share of total indemnities attributable to PP claims over the preceding 10 years produce generally negligible changes to loss ratios, but can significantly increase loss ratios among subsets of the FCIP that heavily utilize PP coverage (greater than 20% of total indemnities). This suggests that, despite loss ratios being robust to typical rates of PP claims, actuarial performance can degrade when PP payments are high relative to indemnities from all other perils. Additionally, a simulation is conducted in which prevent plant indemnities are counterfactually treated as production losses when pricing FCIP contracts as opposed to current practice of recovering prevent plant costs via a fixed rate load. Doing so suggests significant improvements in loss ratios for crops that have historically had high shares of prevent plant indemnities, however, these improvements come at the expense of higher premiums and reduced demand for crop insurance.

show abstract

Relaxing Heteroscedasticity Assumptions in Area‐Yield Crop Insurance Rating

Cited by 64 publications

References 20 publications

Spatial Pattern of Yield Distributions: Implications for Crop Insurance

Spatial Pattern of Yield Distributions: Implications for Crop Insurance

Designing a whole-farm revenue insurance for agricultural crops in Zanjan province of Iran

Actuarial implications of prevented planting coverage

Contact Info

Product

Resources

About