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1 – 10 of over 16000James G. Pritchett, George F. Patrick, Kurt J. Collins and Ana Rios
Returns to a model farm are simulated to assess the impact of marketing and insurance risk management tools as measured by mean net returns and returns at 5% value‐at‐risk (VaR)…
Abstract
Returns to a model farm are simulated to assess the impact of marketing and insurance risk management tools as measured by mean net returns and returns at 5% value‐at‐risk (VaR). Results indicate that revenue insurance strategies and strategies involving a combination of price and yield protection provide substantial downside revenue protection, while mean net returns only modestly differ from the benchmark harvest sale strategy when considering all years between 1986 and 2000.
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Ashok K. Mishra and Barry K. Goodwin
This research examines factors influencing the adoption of crop and revenue insurance. This is accomplished by estimating a multinomial logit model of insurance choices facing…
Abstract
This research examines factors influencing the adoption of crop and revenue insurance. This is accomplished by estimating a multinomial logit model of insurance choices facing U.S. farmers. Results indicate significant differences in the probabilities of adoption of each insurance plan. The levels of selected explanatory variables, such as operator’s education level, debt‐to‐asset ratio, off‐farm income, soil productivity, participation in production and marketing contracts, and type of farm ownership, appear to be the determinants of the probability of having adopted each insurance plan.
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Harun Bulut and Keith J. Collins
The purpose of this paper is to use simulation analysis to assess farmer choice between crop insurance and supplemental revenue options as proposed during development of the…
Abstract
Purpose
The purpose of this paper is to use simulation analysis to assess farmer choice between crop insurance and supplemental revenue options as proposed during development of the Agricultural Act of 2014.
Design/methodology/approach
The certainty equivalent of wealth is used to rank farm choices and assess the effects of supplemental revenue options on the crop insurance plan and coverage level chosen by the producer under a range of farm attributes. The risk-reducing effectiveness of the select programs is also examined through their impact on the farm revenue distribution. The dependence structure of yield and prices is modeled by applying copula techniques on historical data.
Findings
Farm program supplemental revenue programs generally have no effect on crop insurance choices. Crop insurance supplemental revenue programs typically reduce crop insurance coverage at high coverage levels. An individual plan of crop insurance combined with a supplemental revenue insurance plan may substitute for incumbent area crop insurance plans.
Originality/value
The analysis provides insights into farmers’ possible choices by focussing on alternative crops and farm attributes and extensive scenarios, using current data, crop insurance plans and programs contained in the 2014 Farm Bill and related bills. The results should be of value to policy officials and producers in regards to the design and use of risk management tools.
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Gary D. Schnitkey, Bruce J. Sherrick and Scott H. Irwin
This study evaluates the impacts on gross revenue distributions of the use of alternative crop insurance products across different coverage levels and across locations with…
Abstract
This study evaluates the impacts on gross revenue distributions of the use of alternative crop insurance products across different coverage levels and across locations with differing yield risks. Results are presented in terms of net costs, values‐at‐risk, and certainty equivalent returns associated with five types of multi‐peril crop insurance across different coverage levels. Findings show that the group policies often result in average payments exceeding their premium costs. Individual revenue products reduce risk in the tails more than group policies, but result in greater reductions in mean revenues. Rankings based on certainty equivalent returns and low frequency VaRs generally favor revenue products. As expected, crop insurance is associated with greater relative risk reduction in locations with greater underlying yield variability.
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– The purpose of this paper is to determine the sources and factors affecting farm revenue variation on crop and livestock farms in the Northern Great Plains.
Abstract
Purpose
The purpose of this paper is to determine the sources and factors affecting farm revenue variation on crop and livestock farms in the Northern Great Plains.
Design/methodology/approach
A two method approach is used. Variance decomposition analysis is completed on an 18-year balanced panel data set of North Dakota producers to determine the sources of farm revenue variation. The second component of this research uses a random effects estimator to determine the effect of farm characteristics on farm revenue variation measured by coefficient of variation.
Findings
Crop revenue is the largest source of farm revenue variation, with crop insurance being the largest source of revenue variation diversification. Small market crops and corn were found to increase revenue variation compared to those operations that received the largest sum of their revenue from wheat. Government payments and insurance payments were also found to increase farm revenue variation indicating they may provide an incentive to plant more risky crops.
Originality/value
This analysis examined specific enterprises that affect farm revenue variation, which has not been examined in earlier work. This distinction allows for focus on potential policy implications of small market crops and new crops in “transitional planting zones”.
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Aparna Bhatia and Megha Mahendru
The purpose of this article is to evaluate revenue efficiency performance of life insurance companies in India. The study also compares if private or public insurance sector is…
Abstract
Purpose
The purpose of this article is to evaluate revenue efficiency performance of life insurance companies in India. The study also compares if private or public insurance sector is more “revenue efficient”. Furthermore, the study determines the nature of return to scale (RTS) and identifies the leaders and laggards amongst insurance companies operating in India.
Design/methodology/approach
Revenue efficiency is calculated by employing data envelopment analysis – a non-parametric approach, on a data set of 24 insurance companies over the period 2013–2014 to 2017–2018.
Findings
The empirical results suggest that life insurance companies in India could generate only 34.4% of revenue, which is very less than what these are expected to generate from the same inputs. Majority of life insurance companies operating in India are operating at decreasing return to scale (DRS). There is a reduction in leaders and the highest proportion of companies is falling in the category of laggards.
Originality/value
As per the best knowledge of researchers, no empirical work has been carried out with respect to measuring the revenue efficiency of Indian insurance companies. The current study appropriately fills the gap by not only calculating the revenue efficiency scores of insurance companies in India but also provides insights into the causes of revenue inefficiencies. It also gives implications for efficient and effective management of insurance companies.
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Shyam Adhikari, Eric J. Belasco and Thomas O. Knight
The purpose of this paper is to examine the spatial components of producer heterogeneity in crop insurance product selection among US corn producers and identifies neighborhood…
Abstract
Purpose
The purpose of this paper is to examine the spatial components of producer heterogeneity in crop insurance product selection among US corn producers and identifies neighborhood spillover or agent marketing effects in these decisions.
Design/methodology/approach
County‐level insurance and yield data are used to demonstrate that a gradual shift from yield‐based insurance to revenue‐based insurance has spatial patterns. Conventional risk variables such as yield variability, price variability, prevalence of irrigation, other crops, and yield‐price relationships play an important role in this shift and are consistently estimated only when spatial components are included. A spatial random effects model is used to also identify the impact of spatial lag effects, which include neighborhood spillover and agent marketing effects, on the share of corn acres insured with revenue‐based plans vs yield‐based plans.
Findings
Theoretically consistent variables associated with risk are found to significantly influence the choice between crop revenue and yield insurance. Non‐linear parameters identify the region‐specific effects from changes in irrigation, yield price correlation, and the prevalence of corn production on insurance decisions. In addition, spatial components such as the decisions made by nearby producers and marketing drives are also found to influence decisions. These results may demonstrate the relative influence of trusted sources, such as nearby producers and insurance agents, on insurance decisions.
Originality/value
Traditional risk variables are consistently estimated by controlling for spatial heterogeneity. This study also reveals the propensity of producers to rely on the opinions of other producers or agents that they know.
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Rent seeking is endemic to the process through which any policy or regulatory initiative is developed in the USA. The purpose of this paper is to show how farm and other interest…
Abstract
Purpose
Rent seeking is endemic to the process through which any policy or regulatory initiative is developed in the USA. The purpose of this paper is to show how farm and other interest groups have formed coalitions to benefit themselves at the expense of the federal government by examining the legislative history of the federal crop insurance program.
Design/methodology/approach
The federal crop insurance legislation and the way in which the USDA Risk Management Agency manages federal crop insurance program are replete with complex and subtle policy initiatives. Using a new theoretical framework, the study examines how, since 1980, three major legislative initiatives – the 1980 Federal Crop Insurance Act, the 1994 Crop Insurance Reform Act and the 2000 Agricultural Risk Protection Act – were designed to jointly benefit farm interest groups and the agricultural insurance industry, largely through increases in government subsidies.
Findings
Each of the three legislative initiatives examined here included provisions that, when considered individually, benefitted farmers and adversely affected the insurance industry, and vice versa. However, the joint effects of the multiple adjustments included in each of those legislative initiatives generated net benefits for both sets of interest groups. The evidence, therefore, indicates that coalitions formed between the farm and insurance lobbies to obtain policy changes that, when aggregated, benefited both groups, as well as banks with agricultural lending portfolios. However, those benefits came at an increasingly substantial cost to taxpayers through federal government subsidies.
Originality/value
This is the first analysis of the US federal crop insurance program to examine the issue of coalition formation.
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Due to the low crop insurance participation by grain growers in the Pacific Northwest, the performance of insurance programs and the futures market is assessed in this area…
Abstract
Due to the low crop insurance participation by grain growers in the Pacific Northwest, the performance of insurance programs and the futures market is assessed in this area. Revenue insurance, combined with the futures and government programs, is identified as the optimal risk management portfolio. Although yield risk level, decision maker’s risk preference, and actuarial fairness of premiums can all affect farmers’ choices, the current subsidy policy is most influential. The varying subsidy levels induce farmers’ subsidy‐seeking incentive and suppress the risk‐reducing incentive. There is little diversification effect from growing two crops in the rotation instead of one.
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This paper examines the effect of overconfident yield forecasting (optimism bias) on crop insurance coverage level choices across both yield and revenue insurance.
Abstract
Purpose
This paper examines the effect of overconfident yield forecasting (optimism bias) on crop insurance coverage level choices across both yield and revenue insurance.
Design/methodology/approach
This study simulates a representative producer’s preferred coverage level for both yield and revenue insurance under three potential models of decision-making and four potential manifestations of overconfident yield forecasting. The study then uses this framework to examine how coverage level choices change as overconfidence increases (decreases).
Findings
As overconfidence increases, producers prefer lower levels of crop insurance coverage than they would otherwise prefer, with extreme overconfidence inducing farmers to buy no insurance at all. While overconfidence affects cross-coverage demand for revenue and yield insurance similarly, this effect is more pronounced for yield insurance. Cross-coverage level demand for revenue insurance is relatively stable across changes in the correlation between prices and yields.
Practical implications
This research has important implications for crop insurance subsidy design and crop insurance demand modeling.
Originality/value
There is a growing body of literature suggesting that producers are overconfident with regard to their future yield risk and that this bias reduces their willingness to pay for risk management tools such as crop insurance. This is the first study to look at how such overconfidence affects cross-coverage level demand for crop insurance.
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