Improved Program Planning Approaches Generates Large Benefits in High Risk Crop Farming

This paper examines whether there is room for the improvement of farm program decisions through the incorporation of mathematical optimization in the practical planning process. Probing the potential for improvement, we investigate the cases of four German cash crop farms over the last six years. The formal planning approach includes a systematic time series analysis of farmspecific single gross margins and a stochastic optimization model. In order to avoid solutions that simply exceed the farmer's risk tolerance, the apparently accepted variance of the observed program's total gross margin which represents an observable reflection of the individual farmer's risk attitude is used as an upper bound in the optimization. For each of the 24 planning occasions, the formal model is used in a quasi ex-ante approach that provides optimized alternative programs. The total gross margins that could have been realized if the formally optimized programs had been implemented are then ex-post compared to those that were actually realized. We find that the farmers could have increased their total gross margins significantly if - instead of using simple routines and rules of thumb - they had used the more sophisticated formal planning model. However, we also find that the superiority of formalized planning approaches depends on the quality of statistical analysis and the resulting forecasting model. Using our approach for practical decision support implies that farmers first specify their "own" production programs without the formal planning aid. Then, an alternative program can be provided which leads to superior expected total gross margins without exceeding the farmer's accepted total gross margin variance.production program planning, optimization, uncertainty, static distributions, stochastic processes, Crop Production/Industries, C1, C61, M11, Q12,

Understanding and Managing Behavioural Risks -The Case of Food Risks Caused by Malpractice in Poultry Production

The probability that actors in economic relationships break rules increases with the profits they thus expect to earn. It decreases with the probability and level of short- and long-term losses resulting from disclosure. It also decreases with the level of social context factors and intrinsic values which shield actors from yielding to economic temptations. This paper assesses the relative merits of various scientific approaches concerned with risks in economic relationships and outlines their contribution to the study of opportunistic rule-breaking. Since the identification of (misdirected) economic incentives faced by firms and individuals represents the starting point for a systematic analysis of opportunism in any field, we also outline a microeconomic approach that systematically provides this crucial information. The approach is applied to the problem of food quality and safety threatened by opportunistic malpractice of food business operators. Its essentials are illustrated through a study which systematically searches for the temptations to break production-related rules in the poultry industries.asymmetric information, control theories, economic misconduct, game theory, moral hazard, principal-agent model, opportunism, protective factors, relational risks, Food Consumption/Nutrition/Food Safety, A13, K32, K42,

Improved Program Planning Generates Large Benefits in High Risk Crop Farming – A Profitable Application of Time Series Models and Stochastic Optimization

Agricultural production relies to a great extent on biological processes in natural environments. In addition to volatile prices, it is thus heavily exposed to risks caused by the variability of natural conditions such as rainfall, temperature and pests. With a view to the apparently lacking support of risky farm production program decisions through formal planning models, the objective of this paper is to examine whether, and eventually by how much, farmers’ “intuitive” program decisions can be improved through formal statistical analyses and stochastic optimization models. In this performance comparison, we use the results of the formal planning approach that are generated in a quasi ex-ante analysis as a normative benchmark for the empirically observed ones. To avoid benchmark solutions that would possibly exceed the respective farmer’s risk tolerance, we limit the formal search to a subset of solutions that are second-degree stochastically dominant compared to the farmer’s own decision. We furthermore compare the suitability of different statistical (time series) models to forecast the uncertainty of single gross margins.stochastic optimization, program planning, time series analysis, Crop Production/Industries,

Reduction of Behavioural Food Risks: An Analysis of Economic Incentives and Social Context Factors in the German Poultry Chains

This paper describes an interdisciplinary research project carried out on behalf of the Federal Ministry of Consumer Protection, Food and Agriculture. The project combines the knowledge of food experts with decision-orientated approaches from microeconomics and the social sciences. It examines what it is that makes food business operators (from the feed industry to the retail trade) break (or not break) rules. Through the analysis of both economic incentives and social context factors, the project aims at contributing to an adequate design of prevention measures. Four offence-prone regulations identified in the course of the ongoing project are exemplarily examined with regard to the present incentive situation.asymmetric information, moral hazard, opportunistic malpractice, poultry, Agribusiness, Food Consumption/Nutrition/Food Safety,

Sophisticated Program Planning Approaches Generate Large Benefits in High Risk Crop Farming

Agricultural production relies to a great extent on biological processes in natural environments. In addition to volatile prices, it is thus heavily exposed to risks caused by the variability of natural conditions such as rainfall, temperature and pests. With a view to the apparently lacking support of risky farm production program decisions through formal planning models, the objective of this paper is to examine whether, and eventually by how much, farmers’ “intuitive” program decisions can be improved through formal statistical analyses and stochastic optimization models. In this performance comparison, we use the results of the formal planning approach that are generated in a quasi ex-ante analysis as a normative benchmark for the empirically observed ones. To avoid benchmark solutions that would possibly exceed the respective farmer’s risk tolerance, we limit the formal search to a subset of solutions that are second- degree stochastically dominant compared to the farmer’s own decision. We furthermore compare the suitability of different statistical (time series) models to forecast the uncertainty of single gross margins.stochastic optimization, stochastic processes, production risk, program planning, time series analysis, C1, C61, M11, Q12,

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.dynamic programming, flexibility, investment, sales contract, stochastic simulation, uncertainty, Agricultural Finance, Risk and Uncertainty,

An Interdisciplinary Approach to White-collar Crime in the Food Sector

The probability that buyers are deceived with regard to the quality or safety of purchased products (moral hazard) increases with the profits which suppliers can earn through opportunistic behaviour. It decreases with the probability and level of losses that result from disclosure of malpractice. It also decreases with protective factors rooted in the suppliers' social contexts - such as values, emotional bonds etc. - that shield them from yielding to economic temptations. This paper describes how a systematic analysis of economic incentives and social context factors can be provided through an interdisciplinary approach which combines the analytical powers of microeconomics (game theory) and criminology (control theories). The approach is discussed with regard to food quality and safety threatened by moral hazard. Its essentials are illustrated through a case study of grain farmers who might be tempted to infringe upon production-related regulations.asymmetric information, behavioural food risks, control theories, game theory, moral hazard, opportunistic malpractice, Agribusiness, Institutional and Behavioral Economics, A13, K32, K42,

Die Berücksichtigung von Unsicherheit und Flexibilität in der Investitionsplanung – dargestellt am Beispiel einer Vertragsinvestition für Roggen

Investment decisions are, as a rule, characterized by uncertainty, irreversibility and flexibility. Simple net present value calculations will not account for these features. In many situations even flexible investment planning with decision trees, which represents the most advanced method of traditional investment appraisal, does not have the capacity to solve practical decision problems adequately. One handicap is a realistic and manageable representation of stochastic variables. It has long been known that stochastic simulation procedures offer a nearly unlimited capacity to represent distributions and stochastic processes. However, a standard simulation will not allow for the consideration of flexibility. The problem is that with a simple forward moving simulation of stochastic paths it is not clear at potential investment dates whether waiting or investing represents the optimal strategy. In this paper we show how stochastic simulation procedures can be integrated successfully into a backward recursive programming approach. The resulting modus operandi can be called “Bounded Recursive Stochastic Simulation†(BRSS). We use this efficient combination of simulation and dynamic programming to answer the question whether farmers should buy sales contracts which guarantee fixed prices for rye in the future. The results of the model affirm the importance of uncertainty and flexibility for investment decisions. They also show that the actual conditions offered by the wholesale buyer are not economically attractive for farmers, unless they are extremely risk averse. Thus, model results coincide with the empirical evidence that farmers do not enter these contracts.investment, uncertainty, flexibility, stochastic simulation, dynamic programming, sales contracts with fixed prices, Farm Management, Research Methods/ Statistical Methods, Risk and Uncertainty,

Hedging von Mengenrisiken in der Landwirtschaft – Wie teuer dürfen „ineffektive“ Wetterderivate sein?

Since the mid-nineties, agricultural economists discuss the suitability of “weather derivatives†as hedging instruments for volumetric risks in agriculture. Contrary to traditional insurance contracts, the payoffs of such derivatives are linked to weather indices (e.g. accumulated rainfall or temperature over a certain period) that are measured objectively at a defined meteorological station. While weather derivatives thus circumvent the problem of moral hazard and adverse selection, weather derivative markets for the agricultural sector are still in their infancy all-over the world. Some economists attribute this to theoretical valuation problems and the lack of a pricing method which is accepted by all market participants. Others think that the low hedging effectiveness of (standardized and noncustomized) weather contracts cripple the market. Motivated by the question of how weather derivatives should be priced to agricultural firms, this paper describes a risk programming model which can be used to determine farmers’ willingness-to-pay (demand function) for weather derivatives. The model considers both the derivative’s farmspecific 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. We find that a potential underwriter could even add a loading on the actuarially fair price that exceeds the loading level of traditional insurances. Since transaction costs are low compared to insurance contracts, this indicates that there may be a significant trading potential.weather derivatives, rainfall risk, willingness-to-pay, portfolio optimization, hedging of volumetric risk, Farm Management, Financial Economics, Risk and Uncertainty,