Oliver Musshoff

Analysis of rainfall derivatives using daily precipitation models: opportunities and pitfalls

This study examines rainfall variability and its implications for wheat production risk in northeast Germany. The hedging effectiveness of rainfall options and the role of geographical basis risk are analyzed using a daily precipitation model. Simpler pricing methods such as the burn analysis and the index value simulation serve as benchmarks for comparison. It is found that the choice of statistical approach may lead to considerable differences in the estimation results. Daily precipitation models should be used with some caution in the context of derivative pricing because they tend to underestimate rainfall variability. This is unexpected, because daily simulation models are usually preferred in the context of temperature‐based weather indexes.

Management of climate risks in agriculture–will weather derivatives permeate?

It is a matter of common knowledge that weather represents the major source of uncertainty in crop production. It is to be expected that weather fluctuations will increase in the future due to climate change. Traditionally, farmers tried to protect themselves against weather-related yield variations by buying insurances. More recently, there has been a discussion regarding the use of weather derivatives to safeguard against volumetric risks. Although weather derivatives display advantages over traditional insurances, there is only a relatively small market for these products in agriculture. This is partly attributed to the fact that it is unclear whether and to what extent weather derivatives are a useful instrument of risk management in agriculture. This study applies real yield and weather data from Northeast Germany in order to quantify the risk-reducing effect that can be achieved in wheat production by using precipitation options. To do so stochastic simulation is used. The hedging effectiveness is controlled by the contract design (index, strike level, tick size). However, the local basis risk and the geographical basis risk remain with the farmer. We separate both causes of basis risk and reveal the extent of each. This enables conclusions regarding the design of weather derivatives; thus the question dealt with here is relevant both for farmers and for potential sellers of weather derivatives.

Measuring the Risk Attitude of Decision‐Makers: Are There Differences between Groups of Methods and Persons?

Many studies quantifying individual risk preferences of test persons show that results of different measuring methods may vary. Additional reservations about the reliability of the results regarding the risk attitude measurement arise from the fact that most studies are based on convenience groups, such as students or businessmen in developing countries. With this in mind, we systematically compare different measuring methods to answer the question how the choice of method affects the results. Moreover, we compare the risk preferences of German farmers with those of students and Kazakhstani farmers to investigate whether farmers’ risk preferences can be approximated through those of convenience groups. The methods applied comprise an incentive-compatible Holt-and-Laury-lottery as well as two psychometric methods. Results show that students respond consistently across all three elicitation methods whereas German and Kazakhstani farmers are more inconsistent. Significant differences exist in the responses of German students and German farmers. The comparison of risk preferences between German and Kazakhstani farmers, however, reveals significant similarities with respect to the psychometric methods.

Land-use choices follow profitability at the expense of ecological functions in Indonesian smallholder landscapes

Smallholder-dominated agricultural mosaic landscapes are highlighted as model production systems that deliver both economic and ecological goods in tropical agricultural landscapes, but trade-offs underlying current land-use dynamics are poorly known. Here, using the most comprehensive quantification of land-use change and associated bundles of ecosystem functions, services and economic benefits to date, we show that Indonesian smallholders predominantly choose farm portfolios with high economic productivity but low ecological value. The more profitable oil palm and rubber monocultures replace forests and agroforests critical for maintaining above- and below-ground ecological functions and the diversity of most taxa. Between the monocultures, the higher economic performance of oil palm over rubber comes with the reliance on fertilizer inputs and with increased nutrient leaching losses. Strategies to achieve an ecological-economic balance and a sustainable management of tropical smallholder landscapes must be prioritized to avoid further environmental degradation.

Weather index‐based insurances for farmers in the North China Plain: An analysis of risk reduction potential and basis risk

Purpose - The purpose of this paper is to analyze the extent to which weather index-based insurances can contribute to reducing shortfall risks of revenues of a representative average farm that produces corn or wheat in the North China Plain (NCP). The geographical basis risk is quantified to analyze the spatial dependency of weather patterns between established weather stations in the area and locations where the local weather patterns are unknown. Design/methodology/approach - Data are based on the Findings - Results suggest significant differences in the potential risk reduction between corn and wheat when using insurance based on a precipitation index. The spatial analysis suggests a potential to expand the insurance around a reference weather station up to community level. Research limitations/implications - Findings are limited by a weak database in China and, in particular, by the unavailability of individual farm data. Moreover, the low density of weather stations currently limits the examination of the approach in a broader context. Practical implications - The risk reduction potential of the proposed insurance is encouraging. From a policy point of view, the approach used here can support the adjustment of insurers towards different crops. Originality/value - This paper is believed to be the first that investigates a weather index-based insurance designed for an average farm in the NCP and the quantification of geographical basis risk.

Indifference Pricing of Weather Derivatives

Weather derivatives are difficult to price due to the nontradability of weather and the absence of liquid secondary markets for these contracts. We use the concept of indifference pricing to develop a model for calculating the willingness to pay for weather insurance. Compared with other approaches, indifference pricing is less ambitious since it does not attempt to predict a transacted market price. The application of indifference pricing in the case of German crop producers shows that their willingness to pay for weather insurance depends on the production program and varies regionally. This suggests the development of tailored insurance products. Copyright 2008, Oxford University Press.

Portfolio effects and the willingness to pay for weather insurances

Since the mid-1990s, agricultural economists have discussed the relevance of index-based insurances, also called “weather derivatives”, as hedging instruments for volumetric risks in agriculture. Motivated by the question of how weather derivatives should be priced for agricultural firms, this paper describes an extended risk-programming model which can be used to determine farmers’ willingness to pay (demand function) for weather derivative’s farm-specific risk reduction capacity and the individual farmer’s risk acceptance. Applying it to the exemplary case of a Brandenburg farm reveals that even a highly standardized contract which is based on the accumulated rainfall at the capital’s meteorological station in Berlin-Tempelhof generates a relevant willingness to pay. Our findings suggest that a potential underwriter could even add a loading on the actuarially fair price which exceeds the level of traditional insurances. Since translation costs are low compared to insurance contracts, this finding indicates there may be a relevant trading potential.

Meteorological Forecasts and the Pricing of Temperature Futures

Futures contracts on the weather may seemodd, yet weather risk can be a serious matter. Weather is plainly not a storable commodity, so the cost-of-carry pricing model does not apply. Instead, one expects a temperature futures contract to be priced close to the consensus expectation based on current information for the temperature variable at contract maturity. But everyone knows how difficult it is to predict the weather, even though some patterns are well understood (e.g., it is colder in the winter than in the summer, on average). In this article, the authors build and estimate temperature models for three major cities that have traded weather futures contracts. The models include seasonal variation, positive serial correlation over short periods, a possible longterm warming trend, and random fluctuation. To the model based on historically observed temperatures, they add forwardlooking weather forecasts from an online weather service. These forecast-augmented models are more accurate in matching market prices for weather futures, and they are even closer to futures prices than would be “perfect” forecasts constructed from realized temperature data

Investment Planning Under Uncertainty and Flexibility: The Case of a Purchasable Sales Contract

Investment decisions are not only characterised by irreversibility and uncertainty but also by flexibility with regard to the timing of the investment. This paper describes how stochastic simulation can be successfully integrated into a backward recursive programming approach in the context of flexible investment planning. We apply this hybrid approach to a marketing question from primary production which can be viewed as an investment problem: should grain farmers purchase sales contracts which guarantee fixed product prices over the next 10 years? The model results support the conclusion from dynamic investment theory that it is essential to take simultaneously account of uncertainty and flexibility.

Eliciting risk attitudes – how to avoid mean and variance bias in Holt-and-Laury lotteries

This article shows that including inconsistent subjects in a Holt-and-Laury analysis will bias the mean, as well as the variance of the risk attitudes of the subject group of interest to an extent that cannot be determined a priori and that must not be neglected. One might be tempted to simply drop inconsistent subjects from the analysis to avoid such biases in a population-level analysis. Unfortunately, however, this is not a solution: first, the sample size may fall to an unacceptably low level. Second – and even more important – simply dropping inconsistent subjects from the analysis may introduce another unknown bias since systematic differences may exist in the risk preferences of those who answer consistently and those who do not. One must thus conclude that, if the group of interest contains a large proportion of inconsistent subjects, the whole set-up of the Holt-and-Laury lottery (HLL) experiment must be critically reconsidered and the experiment eventually repeated.