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Improving weather index-based insurance: better consideration of crop physiology
Based on current research findings, the student will design and compare different weather index insurance schemes with respect to their risk reducing properties. The benefits of considering different phenology models for improving the index design will be evaluated.
Keywords: Improving weather index-based insurance crop physiology design phenology models agricultural production climate related risks crop insurance schemes farmers payout outcomes tranditional insurance schemes asymetric information private market based risk management tools GDD BMT
Context:
Agricultural production is exposed to a variety of climate related risks. In this context, crop insurance schemes are designed to help farmers by providing payout in times of low outcomes. However, traditional insurance schemes come with asymmetric information problems hampering the development of private, unsubsidized insurance markets. With regard to this background, weather index based insurance solutions offer potential benefits for creating private marked based risk management tools. The drawback of these index-based solutions is that if the weather index is not well suited to on farm losses, a discrepancy between insurance payout and on farm damages (Basis Risk) can occur. One reason for such mismatch is the consideration of time windows to measure the index that do not reflect the critical crop growing phases (temporal basis risk). This thesis should contribute to reduce these temporal basis risks by better representation of crop growing phases in these insurance solutions.
Research question:
- Do BMT and Pdays adjusted weather index-based insurances outperform GDD based products in terms of expected utility (EU) maximization.
Methods:
- Flexible Insurance period adjustment using above mentioned approaches (Conradt et al., 2015a)
- Determination of Index parameters focusing on downside risk aversion by using quantile regression (QR) (Conradt et al. 2015b)
- Insurance performance assessment using expected utility and a power utility function (Leblois et al., 2014)
Literature:
Conradt, S.; Finger, R.; Bokusheva, R. (2015b). Tailored to the extremes: Quantile regression for index-based insurance contract design. Agricultural Economics, 1–11.
Conradt, S., Finger, R., Spörri, M. (2015a). Flexible weather index-based insurance design. Climate Risk Management 10, 106-117.
Saiyed, I. M.; Bullock, P. R.; Sapirstein, H. D.; Finlay, G. J.; Jarvis, C. K. (2009). Thermal time models for estimating wheat phenological development and weather-based rela
Context: Agricultural production is exposed to a variety of climate related risks. In this context, crop insurance schemes are designed to help farmers by providing payout in times of low outcomes. However, traditional insurance schemes come with asymmetric information problems hampering the development of private, unsubsidized insurance markets. With regard to this background, weather index based insurance solutions offer potential benefits for creating private marked based risk management tools. The drawback of these index-based solutions is that if the weather index is not well suited to on farm losses, a discrepancy between insurance payout and on farm damages (Basis Risk) can occur. One reason for such mismatch is the consideration of time windows to measure the index that do not reflect the critical crop growing phases (temporal basis risk). This thesis should contribute to reduce these temporal basis risks by better representation of crop growing phases in these insurance solutions.
Research question:
- Do BMT and Pdays adjusted weather index-based insurances outperform GDD based products in terms of expected utility (EU) maximization.
Methods: - Flexible Insurance period adjustment using above mentioned approaches (Conradt et al., 2015a)
- Determination of Index parameters focusing on downside risk aversion by using quantile regression (QR) (Conradt et al. 2015b)
- Insurance performance assessment using expected utility and a power utility function (Leblois et al., 2014)
Literature:
Conradt, S.; Finger, R.; Bokusheva, R. (2015b). Tailored to the extremes: Quantile regression for index-based insurance contract design. Agricultural Economics, 1–11.
Conradt, S., Finger, R., Spörri, M. (2015a). Flexible weather index-based insurance design. Climate Risk Management 10, 106-117.
Saiyed, I. M.; Bullock, P. R.; Sapirstein, H. D.; Finlay, G. J.; Jarvis, C. K. (2009). Thermal time models for estimating wheat phenological development and weather-based rela
The aim of this master thesis is to test approaches to estimate growth stages to be used for weather index-based insurance design. More specifically growing degree days (Conradt et al., 2015), Biometeorological Time (BMT) and physiological days (Pdays), where the latter two are alternatives to the classical GDD based approach (Saiyed et al., 2009).
The aim of this master thesis is to test approaches to estimate growth stages to be used for weather index-based insurance design. More specifically growing degree days (Conradt et al., 2015), Biometeorological Time (BMT) and physiological days (Pdays), where the latter two are alternatives to the classical GDD based approach (Saiyed et al., 2009).