Arbeitspapier
Can expert knowledge compensate for data scarcity in crop insurance pricing?
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.
- Sprache
-
Englisch
- Erschienen in
-
Series: SFB 649 Discussion Paper ; No. 2013-030
- Klassifikation
-
Wirtschaft
Semiparametric and Nonparametric Methods: General
Agriculture: Other
- Thema
-
expert knowledge
data scarcity
crop insurance pricing
Bayesian estimation
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Shen, Zhiwei
Odening, Martin
Okhrin, Ostap
- Ereignis
-
Veröffentlichung
- (wer)
-
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
- (wo)
-
Berlin
- (wann)
-
2013
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Shen, Zhiwei
- Odening, Martin
- Okhrin, Ostap
- Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
Entstanden
- 2013
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