Can expert knowledge compensate for data scarcity in crop insurance pricing?

Zhiwei Shen, Martin Odening and Ostap Okhrin

No 149431, 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. from Agricultural and Applied Economics Association

Abstract: Although there is an increasing interest in index-based insurances in many developing countries, crop data scarcity hinders its implementation by forcing insurers to charge higher premiums. Expert knowledge has been considered a valuable information source to augment limited data in insurance pricing. This article investigates whether the use of expert knowledge can mitigate model risk which arises from insufficient statistical data. We adopt the Bayesian framework that allows for the combination of scarce data and expert knowledge, to estimate the risk parameter and buffer load. In addition, a benchmark for the evaluation of expert information is created by using a richer dataset generated from resampling. We find that expert knowledge reduces the parameter uncertainty and changes the insurance premium in the correct direction, but that the effect of the correction is sensitive to different strike levels of insurance indemnity.

Keywords: Agricultural Finance; Farm Management; Research Methods/ Statistical Methods; Risk and Uncertainty (search for similar items in EconPapers)
Pages: 19
Date: 2013
New Economics Papers: this item is included in nep-agr and nep-ias
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Can expert knowledge compensate for data scarcity in crop insurance pricing? (2016)
Working Paper: Can expert knowledge compensate for data scarcity in crop insurance pricing? (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:aaea13:149431

DOI: 10.22004/ag.econ.149431

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