Parents of preschool fire setters: perceptions of the child-play fire hazard

The present study sought to learn about risk perceptions held by parents of preschool fire-setters. A 41-item survey was distributed to 60 parents whose children, aged 6 years and younger, had previously set fires and who were involved in intervention programmes throughout the US. Most parents did not think their children would play with matches/lighters, or knew how to use these items, although some had witnessed their children playing with matches/lighters previously. Most parents reported having taken precautions to keep matches/lighters out of reach and also educating their children about fire. Regardless, children not only set fires, but in 40% of cases climbed to access the match/lighter. Parents' perceptions of their children's proclivity for fire play were not consistent with their actual fire-play behaviour. Parents underestimated the likelihood that their children would play with matches/lighters. Although most reportedly undertook preventative measures aimed at thwarting fire play, these strategies were ineffective. Traditionally relied upon precautionary techniques, such as storing lighters out of reach and discussing the dangers of fire, were not sufficient to stem interest and resultant fire play.     

The Impact of Spatial Interpolation Techniques on Spatial Basis Risk for Weather Insurance: An Application to Forage Crops

Weather index insurance for crops is at the developmental stage, however, this type of insurance is particularly susceptible to the problem of spatial basis risk. Spatial basis risk occurs when the weather observed at weather stations does not match the weather experienced on the farmer’s property, causing improper indemnities to be paid to the farmer. However, spatial basis risk may be reduced through the use of averaging and spatial interpolation techniques, such as inverse distance weighting and kriging. These techniques make it possible to incorporate multiple weather stations in the estimation process rather than using only the single closest station, potentially resulting in more accurate estimations and thereby reducing spatial basis risk. Therefore, the objective of this study is to examine the extent to which the choice of spatial interpolation techniques can influence the amount of spatial basis risk in a weather-based insurance model. Using forage crops from the province of Ontario, Canada, as an example, a weather insurance index is developed based on cooling degree days. The weather index represents the heat stress that the crops receive over the growing season. This insurance index is used to determine to what extent spatial basis risk can be reduced by the insurer’s choice of spatial interpolation technique. Seven different interpolation methods are applied to temperature data from Ontario, and theoretical indemnities are calculated for forage producers across the province. By analyzing the correlation between the estimated indemnities and reported forage yields, the amount of spatial basis risk in each model is quantified. The results of this study highlight the importance of choosing an appropriate method based on the characteristics of the target region (and data). Operationally this is important because insurers typically apply the same interpolation methods across an entire region. While one finding of this research may suggest that governments and/or insurance companies may wish to invest in additional weather stations to improve the accuracy of the interpolation method and index, this may not be feasible in practice. Given this, future research may consider utilizing satellite-based remote sensing weather estimates to augment the weather station data and reduce basis risk.     

Reducing Risk Through Pooling and Selective Reinsurance Using Simulated Annealing: An Example from Crop Insurance

Agricultural insurance is often faced with the challenge of systemic risk, arising from weather risks that tend to be correlated within a specific region in extreme situations, resulting in large crop losses within the region. However, across many regions, especially if regions are considerable distances apart, weather may be quite different and losses may be much less correlated. The objective of this paper is to improve the diversification of a crop insurance portfolio, through developing a new alternative risk management approach (Model 3) that pools crop risks across all provinces in a country to form a Canada-wide joint insurance pool. This is in contrast to the current approach used in Canada, where crop risks are pooled only within an individual province. Then using a simulated annealing optimization approach, the most suitable combination of the 150 crop types in the portfolio is identified for either retaining in the joint insurance pool or for ceding to reinsurers, such that the variance of the loss coverage ratio of the portfolio is minimized. This model overcomes the problem of insufficient diversification that makes pooling of systemic weather risk challenging. It achieves diversification at a lower cost by using a more efficient combination of pooling and selective reinsurance, resulting in overall higher surplus, higher survival probability, and lower deficit at ruin.