Managing basis risk with multiscale index insurance

Elabed, Ghada; Bellemare, Marc F.; Carter, Michael R.; Guirkinger, Catherine

doi:10.1111/agec.12025

Cited by 123 publications

(131 citation statements)

References 16 publications

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“…Of particular concern in this paper, most index insurance policy holders face some remaining basis risk. This has two potential sources: design risk due to differences between the index and the actual covariate risk it is meant to mimic, and idiosyncratic risk resulting from heterogeneity among individuals' losses within the same index region (Elabed et al 2013).…”

Section: Basis Riskmentioning

confidence: 99%

“…Other papers have used simulations, aggregate-level data, and/or experiments to examine basis risk (e.g., Breustedt, Bokusheva & Heidelback 2008;Dercon et al 2014;Elabed et al 2013;Leblois, Quirion & Sultan 2014;Norton, Turvey & Osgood 2012). Again, basis risk is consistently identified as a key factor in product quality and uptake, but little or nothing can be said about the relative magnitude or distribution of basis risk among households.…”

Section: Introductionmentioning

confidence: 99%

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Basis Risk and the Welfare Gains from Index Insurance: Evidence from Northern Kenya

Jensen

2014

SSRN Journal

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Index insurance products circumvent many of the transaction costs and asymmetric information problems that obstruct provision of low value conventional insurance policies in developing countries. Recent years have seen tremendous growth in index insurance pilots in developing countries, but there has been little progress in our understanding of the quality of those products. Basis risk, or remaining uninsured risk, is a widely recognized, but rarely measured drawback of index insurance that carries significant implications for the quality of any such product. This research uses a rich longitudinal household dataset to examine basis risk associated with an index based livestock insurance (IBLI) product available to pastoralists in northern Kenya since 2010. We find that IBLI coverage reduces downside risk for most households when purchased at actuarially fair premium rates and has net utility benefits for most even at commercial rates. Examining the components of basis risk, we find that IBLI reduces exposure to covariate risk due to high loss events by an average of 62.8%. The benefits of reduced covariate risk exposure are relatively small, however, due to high exposure to seemingly mostly random idiosyncratic risk, even in this population often thought to suffer largely from covariate shocks. Depending on covariate region, IBLI policy holders are left with an average of between 62.3% and 76.7% of their original risk due to high loss events. This research underscores the need for caution when promoting index insurance as a tool for reducing exposure to risk and the importance of ex post product evaluation.

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Section: Basis Riskmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Basis Risk and the Welfare Gains from Index Insurance: Evidence from Northern Kenya

Jensen

2014

SSRN Journal

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“…Norton et al (2012) quantified and developed concepts on how to price spatial basis risk for WII. Elabed et al (2013) analyzed a multi-scale index insurance contract to reduce basis risk. Other studies concentrated on the role of government and suggested that the government should not only establish an appropriate legal and regulatory framework (Barnett and Mahul 2007) but also provide more subsidies to crop insurance (Clarke et al 2012;Skees 2011).…”

Section: Discussionmentioning

confidence: 99%

“…Finding practical and reasonable indices that can capture weather fluctuations and be strongly correlated with crop yield losses is necessary and critically important for improving crop insurance operation (Stoppa and Hess 2003;Barnett and Mahul 2007;Elabed et al 2013). Therefore, the present study focused on the following objectives: (1) to determine which temperature-based index could potentially be used at the county scale; (2) to characterize the spatial pattern of insurable counties and spatial relationship between different groups of insurable counties; and (3) to analyze correlation coefficients of insurable counties at different spatial scales.…”

Section: Introductionmentioning

confidence: 99%

Performance of Temperature-Related Weather Index for Agricultural Insurance of Three Main Crops in China

Zhang

Tao

2017

Int J Disaster Risk Sci

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In this study, two categories of weather indexabsolute index and relative index-for chilling injury and heat damage of three main crops in China were assessed to identify insurable counties. First, correlations between selected weather indices and yield losses were examined for each county. If a correlation was significant, the county was categorized as ''insurable'' for the corresponding hazard or index. Second, the spatial distribution of insurable counties was characterized and finally, their correlation coefficients were analyzed at various spatial scales. The results show that the spatial patterns of insurable areas varied by categories of weather indices, crops, and hazards. Moreover, the weather indices based on relative threshold of temperature were more suitable for chilling injury in most regions, whereas the indices based on absolute threshold were more suitable for heat damage. The findings could help the Chinese government and insurance companies to design effective insurance products.

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“…The color represents frequency at which rainfall intensity and frequency fall into a given range, based on 80 years of historical data at Belleville, KS. Designing the strike level and payoff function following the RIF-driven yield contour (red line) will eliminate the unnecessary tradeoff between basis risk and strike frequency captured in Figure 4b. among farmers, the first challenge lies in reducing BR (Carter et al, 2014;Elabed et al, 2013;Elabed & Carter, 2015;Jensen & Barrett, 2016;Miranda & Farrin, 2012). The low correspondence between weather indexes and crop damages has prompted the use of alternative indexes such as ET, normalized difference vegetation index (NDVI), and soil moisture.…”

Section: Discussionmentioning

confidence: 99%

Rainfall Intensity and Frequency Explain Production Basis Risk in Cumulative Rain Index Insurance

Muneepeerakul

Huffaker

2017

Earth's Future

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With minimal moral hazard and adverse selection, weather index insurance promises financial resilience to farmers struck by harsh weather conditions through swift compensation at affordable premium. Despite these advantages, the very nature of indexing gives rise to production basis risk as the selected weather indexes do not sufficiently correspond to actual damages. To address this problem, we develop a stochastic yield model, built upon a stochastic soil moisture model driven by marked Poisson rainfall. Our analysis shows that even under similar temperature and rainfall amount yields can differ significantly; this was empirically supported by a 2‐year field experiment in which rain‐fed maize was grown under very similar total rainfall. Here, the year with more intense, less‐frequent rainfall produces a better yield—a rare counter evidence to most climate change projections. Through a stochastic yield model, we demonstrate the crucial roles of rainfall intensity and frequency in determining the yield. Importantly, the model allows us to compute rainfall pattern‐related basis risk inherent in cumulative rain index insurance. The model results and a case study herein clearly show that total rainfall is a poor indicator of yield, imposing unnecessary production basis risk on farmers and false‐positive payouts on insurers. Incorporating rainfall intensity and frequency in the design of rain index insurance can offer farmers better protection, while maintaining the attractive features of the weather index insurance and thus fulfilling its promise of financial resilience.

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Managing basis risk with multiscale index insurance

Cited by 123 publications

References 16 publications

Basis Risk and the Welfare Gains from Index Insurance: Evidence from Northern Kenya

Basis Risk and the Welfare Gains from Index Insurance: Evidence from Northern Kenya

Performance of Temperature-Related Weather Index for Agricultural Insurance of Three Main Crops in China

Rainfall Intensity and Frequency Explain Production Basis Risk in Cumulative Rain Index Insurance

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