Improved index insurance design and yield estimation using a dynamic factor forecasting approach

Li, Hong; Porth, Lysa; Tan, Ken Seng; Zhu, Wenjun

doi:10.1016/j.insmatheco.2020.11.003

Cited by 8 publications

(4 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The R 2 value is as high as 0.9548 and the F-test statistic is high enough to imply that all explanatory variables together significantly explain corn yields. The R 2 values are comparable to those reported in existing studies, such as [43], indicating reasonable goodness of fit. Furthermore, the R 2 values using the individual components are higher than using the original ACI variables.…”

Section: Midwest Analysis With Individual Component Variables Of the ...supporting

confidence: 84%

Assessing the Effectiveness of the Actuaries Climate Index for Estimating the Impact of Extreme Weather on Crop Yield and Insurance Applications

Pan¹,

Porth

2022

Sustainability

Self Cite

View full text Add to dashboard Cite

This paper investigates the effectiveness of the Actuaries Climate Index (ACI), a climate index jointly launched by multiple actuarial societies in North America in 2016, on predicting crop yields and (re)insurance ratemaking. The ACI is created using a variety of climate variables reflecting extreme weather conditions in 12 subregions in the US and Canada. Using data from eight Midwestern states in the US, we find that the ACI has significant predictive power for crop yields. Moreover, allowing the constituting variables of the ACI to have data-driven rather than pre-determined weights could further improve the predictive accuracy. Furthermore, we create the county-level ACI index using high-resolution climate data and investigate its predictive power on county-level corn yields, which are more relevant to insurance practices. We find that although the self-constructed ACI index leads to a slightly worse fit due to noisier county-specific yield data, the predictive results are still reasonable. Our findings suggest that the ACI index is promising for crop yield forecasting and (re)insurance ratemaking, and its effectiveness could be further improved by allowing for the data-driven weights of the constituting variables and could be created at higher resolution levels.

show abstract

Section: Midwest Analysis With Individual Component Variables Of the ...supporting

confidence: 84%

Assessing the Effectiveness of the Actuaries Climate Index for Estimating the Impact of Extreme Weather on Crop Yield and Insurance Applications

Pan¹,

Porth

2022

Sustainability

Self Cite

View full text Add to dashboard Cite

show abstract

“…In Zhu et al (2019), the team proposed new premium principles to help establish actuarial best practices for pricing of agricultural insurance. Advanced weather risk models were used to better understand the dependency of risks, for example in Zhu et al (2018) and Li et al (2021). The research team also expanded their work regarding predictive crop yield models for indexbased insurance applications, including the use of satellite remote sensing for forage insurance, which included important collaborations with government, insurers, reinsurers, and technology providers (Porth et al, 2020).…”

Section: Agricultural Insurancementioning

confidence: 99%

“…His first paper with Adam Kolkiewicz was published in 2003; his latest is Puspita et al (2020). His collaboration with Lysa Porth began in 2011; their most recent joint work is Li et al (2021).…”

Section: Concluding Commentsmentioning

confidence: 99%

Keng Seng Tan 1970–2023 In Memoriam

Hardy

Boyle

2023

Ann. actuar. sci.

View full text Add to dashboard Cite

The editorial is dedicated to the memory of Ken Seng Tan, who passed away on January 1, 2023, at the height of his academic career. He was one of the most influential and prolific actuarial researchers of the last three decades.Ken Seng Tan moved to Canada from Malaysia for his undergraduate studies and remained there until 2019. In 1998, he completed his PhD in Actuarial Science at the University of Waterloo, where his doctoral thesis, Quasi-Monte Carlo Methods: Applications in Finance and Actuarial Science, won a university award for Outstanding Achievement In Graduate Studies.

show abstract

“…2022, 12, 2036 2 of 12 crop yield prediction, several studies have been carried out on the topic using different techniques. Li et al [12] studied a new approach for forecasting crop yield using the dynamic factor technique. The dynamic forecasting technique was developed for wheat yield by Feng et al [13] by successfully using a product simulation method combined with two regression-based models.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Almond Nut Yield and Its Greenhouse Gases Emission Using Different Methodologies

et al. 2022

View full text Add to dashboard Cite

The evaluation of a production system to analyze greenhouse gases is one of the most interesting challenges for researchers. The aim of the present study is to model almond nut production based on inputs by employing artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFIS) procedures. To predict the almond nut yield with respect to the energy inputs, several ANN and ANFIS models were developed, evaluated, and compared. Among the several developed ANNs, a network with an architecture of 8-12-1 and a log-sigmoid, and a linear transfer function in the hidden and output layers, respectively, is found to be the best model. In general, both approaches had a good capability for predicting the nut yield. The comparison results revealed that the ANN procedure could predict the nut yield more precisely than the ANFIS models. Furthermore, greenhouse gas (GHG) emissions in almond orchards are determined where the total GHG emission is estimated to be about 2348.85 kg CO2eq ha−1. Among the inputs, electricity had the largest contribution to GHG emissions, with a share of 72.32%.

show abstract

Improved index insurance design and yield estimation using a dynamic factor forecasting approach

Cited by 8 publications

References 63 publications

Assessing the Effectiveness of the Actuaries Climate Index for Estimating the Impact of Extreme Weather on Crop Yield and Insurance Applications

Assessing the Effectiveness of the Actuaries Climate Index for Estimating the Impact of Extreme Weather on Crop Yield and Insurance Applications

Keng Seng Tan 1970–2023 In Memoriam

Prediction of Almond Nut Yield and Its Greenhouse Gases Emission Using Different Methodologies

Contact Info

Product

Resources

About