scholarly journals Implications of Commodity Programs and Crop Insurance Policies for Wheat Producers

2019 ◽  
Vol 51 (02) ◽  
pp. 267-285 ◽  
Author(s):  
Jeff Luckstead ◽  
Stephen Devadoss
Keyword(s):  
Prospect Theory ◽  
Crop Insurance ◽  
Cumulative Prospect Theory ◽  
Certainty Equivalent ◽  
Coverage Level ◽  
Insurance Policies ◽  
Agriculture Risk ◽  
Commodity Programs ◽  
Plc Program ◽  
Risk Coverage

AbstractWe analyze the effects of Price Loss Coverage (PLC), Agriculture Risk Coverage (ARC), individual revenue protection insurance (RP), and Supplemental Coverage Option (SCO) on the RP coverage level, certainty equivalent, and program payments. The model is calibrated to a representative wheat farm in Mitchell County in Kansas to analyze the effects of various policies. The result highlights that when insurance is framed as an investment, cumulative prospect theory predicts farmers’ coverage decisions accurately at 70%. ARC or PLC program increases the RP coverage level to 75%, but PLC and SCO jointly decrease the RP coverage level to 70%.

Certainty Equivalent under Cumulative Prospect Theory

2019 ◽  
Vol 27 (03) ◽  
pp. 415-428 ◽  
Author(s):  
Jacek Chudziak
Keyword(s):  
Utility Function ◽  
Prospect Theory ◽  
Cumulative Prospect Theory ◽  
Certainty Equivalent

We consider the relations between some properties of the certainty equivalent and the form of a utility function under Cumulative Prospect Theory.

scholarly journals IMPLICATIONS AND EVALUATION OF CROP INSURANCE CHOICES FOR COTTON FARMERS UNDER THE 2014 FARM BILL

2018 ◽  
Vol 50 (4) ◽  
pp. 526-543
Author(s):  
KISHOR P. LUITEL ◽  
DARREN HUDSON ◽  
THOMAS KNIGHT
Keyword(s):  
Crop Insurance ◽  
Insurance Premium ◽  
Insurance Policy ◽  
Coverage Level ◽  
Agricultural Risk ◽  
Farm Bill ◽  
Insurance Policies ◽  
Agricultural Risk Management ◽  
Cotton Farmers ◽  
New Crop

AbstractThe Agricultural Act of 2014 introduced new crop insurance policies to manage agricultural risk, especially to cotton farmers. A representative farm panel was used to elicit the yield distribution of the farm, county, and correlation. Results suggest that the optimal underlying insurance policy is Revenue Protection at a 75% coverage level for both high- and low-productivity farms even with a Yield Exclusion provision. The Stacked Income Protection Plan benefit is mostly attributable to a higher insurance premium subsidy. For any crop, efficient agricultural risk management can be achieved through understanding the guaranteed yield and its relation to the farm and county yield.

Research on disruption management of urgent arrival in job shop with deteriorating effect

2021 ◽  
pp. 1-13
Author(s):  
Ning Tao ◽  
Duan Xiaodong ◽  
An Lu ◽  
Gou Tao
Keyword(s):  
Prospect Theory ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Quantum Particle ◽  
Particle Swarm ◽  
Cumulative Prospect Theory ◽  
Disruption Management ◽  
Particle Swarm Algorithm ◽  
Shop Scheduling ◽  
Management Method

A disruption management method based on cumulative prospect theory is proposed for the urgent with deteriorating effect arrival in flexible job shop scheduling problem (FJSP). First, the mathematical model of problem is established with minimizing the completion time of urgent order, minimizing the total process time of the system and minimizing the total cost as the target. Then, the cumulative prospect theory equation of the urgent arrival in job shop scheduling process is induced designed. Based on the selected model, an optimized multi-phase quantum particle swarm algorithm (MQPSO) is proposed for selecting processing route. Finally, using Solomon example simulation and company Z riveting shop example as the study object, the performance of the proposed method is analyzed. It is compared with the current common rescheduling methods, and the results verify that the method proposed in this paper not only meets the goal of the optimized objects, but improves the practical requirements for the stability of production and processing system during urgent arrival. Lastly, the optimized multiphase quantum particle swarm algorithm is used to solve disruption management of urgent arrival problem. Through instance analysis and comparison, the effectiveness and efficiency of urgent arrival disruption management method with deteriorating effect are verified.

Optimal selection of energy storage nodes based on improved cumulative prospect theory in China

2020 ◽  
Vol 12 (6) ◽  
pp. 064101
Author(s):  
Jicheng Liu ◽  
Zhenzhen Wang ◽  
Yu Yin ◽  
Yinghuan Li ◽  
Yunyuan Lu
Keyword(s):  
Energy Storage ◽  
Prospect Theory ◽  
Cumulative Prospect Theory ◽  
Optimal Selection ◽  
Selection Of
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