Hedging weather risk on aggregated and individual farm‐level

Abstract

Purpose -Since the 1990s, there has been a discussion about the use of weather index-based insurance, also called weather derivatives, as a new instrument to hedge against volumetric risks in agriculture. It particularly differs from other insurance schemes by pay-offs being related to objectively measurable weather variables. Due to the absence of individual farm yield time series, the hedging effectiveness of weather index-based insurance is often estimated on the basis of aggregated farm data. The authors expect that there are differences in the hedging effectiveness of insurance on the aggregated level and on the individual farm-level. The purpose of this paper is to estimate the magnitude of bias which occurs if the hedging effectiveness of weather index-based insurance is estimated on aggregated yield data. Design/methodology/approach -The study is based on yield time series from individual farms in central Germany and weather data provided by the German Meteorological Service. Insurance is structured as put-option on a cumulated precipitation index. The analysis includes the estimation of the hedging effectiveness of insurance on aggregated level and on individual farm-level. The hedging effectiveness is measured non-parametrically regarding the relative reduction of the standard deviation and the value at risk of wheat revenues. Findings -Findings indicate that the hedging effectiveness of a weather index-based insurance estimated on aggregated level is considerably higher than the realizable hedging effectiveness on the individual farm-level. This refers to: hedging effectiveness estimated on the aggregated level is higher than the mean of realized hedging effectiveness on the individual farm-level and almost every evaluated individual farm in the analysis realizes a lower hedging effectiveness than estimated on the aggregated level of the study area. Nevertheless, weather index-based insurance designed on the aggregated level can lead to a notable risk reduction for individual farms. Originality/value -To the authors' knowledge, this paper is the first that analyzes the influence of crop yield aggregation with regard to the hedging effectiveness of weather index-based insurance.

Do high-resolution satellite indices at field level reduce basis risk of satellite-based weather index insurance?

“…As a result, the basis risk of satellite-based weather index insurance contracts AFR 82,4 decreases with the increasing aggregation of winter wheat yield data and satellite data. Heimfarth et al (2012) reveal the same results in their study on the impact of data aggregation for index insurance purposes at individual farm level and at aggregated level. Yield outliers can become less significant by aggregating the yield data, as the yield fluctuations of the individual farms can compensate each other to a certain extent.…”

“…most the average farm yields as the lowest aggregation level of yield data (Finger, 2012;Heimfarth et al, 2012;Woodard and Garcia, 2008b). The results of the studies indicate that as the level of aggregation of data increases, the hedging effectiveness of weather index insurance contracts also increases.…”

“…In the past, due to the coarser spatial resolution of satellite data, only satellite-based weather index insurance contracts could be analyzed based on satellite index calculations at farm level compared to county level (Bokusheva et al , 2016; Möllmann et al , 2019). Also within the framework of traditional station-based weather index insurance, previous studies examining the data aggregation effect of weather index insurance used at most the average farm yields as the lowest aggregation level of yield data (Finger, 2012; Heimfarth et al , 2012; Woodard and Garcia, 2008b). The results of the studies indicate that as the level of aggregation of data increases, the hedging effectiveness of weather index insurance contracts also increases.…”

Phenology Information Contributes to Reduce Temporal Basis Risk in Agricultural Weather Index Insurance

“…They conclude from Heimfarth et al . 58 that considering more robust regression approaches 59 did not lead to differences in the results.

Figure 3 Location of Immediate Reporters.

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Satellitenbasierte Indexversicherungen zur Absicherung des witterungsbedingten Produktionsrisikos in der Land- und Forstwirtschaft

“…Für drei landwirtschaftliche Betriebe in Nordostdeutschland, das aufgrund sandiger Böden und geringer Niederschläge einem hohen Wetterrisiko ausgesetzt ist, untersucht der zweite Beitrag, ob eine zunehmende räumliche Auflösung der Satellitenindizes das Basisrisiko der räumlichen Auflösung von satellitenbasierten Wetterindexversicherungen reduziert. Weiterhin wird untersucht, ob es einen Aggregationseffekt zwischen dem Design der satellitenbasierten Indexversicherungen auf Schlag-und Betriebsebene gibt, der in früheren Studien zu wetterstationsbasierten Wetterindexversicherungskontrakten beobachtet wurde(Finger, 2012;Heimfarth et al, 2012; Woodard und Garcia, 2008). Als Grundlage für die hypothetisch gestalteten Wetterindexversicherungskontrakte wurde der NDVI als Index verwendet.…”