Partial equilibrium analysis of vaccination as an avian influenza control tool in the U.S. poultry sector

The study addresses the economic effectiveness of vaccination in the case of highly pathogenic avian influenza (HPAI) outbreaks. The effectiveness is evaluated in a U.S. case study comparing the outbreak costs under the currently recommended HPAI control practice versus one which also includes vaccination. An integrated economic‐epidemic partial equilibrium model is used to empirically simulate HPAI outbreaks in three different poultry regions within the State of Texas. The simulation results show that the effectiveness of vaccination depends on flock density in the region and risk aversion preferences of the decision maker. In regions with high flock densities, if the decision maker is less risk averse the currently recommended strategy—which includes depopulation, movement restrictions, and flock testing—is more cost‐effective than the same strategy supplemented with vaccination. Addition of vaccination improves cost effectiveness only if the decision maker is highly risk averse or if surveillance, carcass disposal, and cleaning costs are high. In regions with medium and low flock densities, adding vaccination to the currently recommended strategy is not cost‐effective except in the case of high surveillance, carcass disposal, and cleaning costs.     

The importance of seasonal variability and tactical responses to risk on estimating the economic benefits of integrated weed management

Seasonal variability is an important source of risk faced by farmers and, regardless of an individual's attitude to risk, there are options to tactically adjust production strategies as the outcomes of risk become known. The objective of this article is to measure the economic benefits of alternative approaches to managing weeds, one of the most serious production problems in Australian cropping systems. A bioeconomic model that combines weed biology, crop growth and economics is developed to value the effects of seasonal variability and the role of tactical responses and sequential decision making in determining an optimal integrated weed management strategy. This shows that there are substantial differences in the measured long‐term benefits from deterministic and stochastic simulations. It is concluded that, for research evaluation of technologies that involve complex biological and dynamic systems, ignoring the impacts of seasonal variability, responses to risk and sequential decision making can lead to an incorrect estimate of the economic benefits of a technology. In this case study of optimal weed management strategies in Australia, the size of the error is high.     

A stochastic dynamic programming framework for weed control decision making: an application to Avena fatua L.

This paper develops a stochastic multi-period decision model to analyse a continuous wheat cropping system infested by wild oats (Avena fatua L.), in southern Australia. The multi-period solutions is obtained by employing a dynamic programming model in conjunction with a bioeconomic simulation model. An empirically estimated dose response function is used to derive the optimal herbicide rate. Uncertainties due to environmental effects on the performance of herbicide and crop yields are modelled and optimal decision rules derived. The results indicate that substantial economic gains can be realised if herbicide dose decisions are taken by considering future profit effects of current decisions, as opposed to the more common approach of only considering the current-period effect.     

Determinants of the Willingness of Belgian Farmers to Participate in Agri‐environmental Measures

This paper explores the willingness of Belgian farmers to participate in two voluntary agri‐environmental policies. Farmers' contingent behaviour is analysed on the basis of survey data. Derivations based on a conceptual micro‐economic model indicate that decision subject and decision maker characteristics are important for farmers' participation. The model is empirically tested through the specification and estimation of a probit model. Consistency is found between the theoretical framework and the empirical results indicating that both the expected effect on farm production and the farmers' environmental attitude, which is more positive among younger and better educated farmers, are significant determinants of the acceptance rate of agri‐environmental policies. Other variables which influence participation decisions are farm size and previous experience of farmers themselves or of neighbouring farmers with agri‐environmental measures.     

Risk Behaviours and Grazing Land Management: A Framed Field Experiment and Linkages to Range Land Condition

We use a framed field experiment considering hypothetical stocking rate decisions made by grazing enterprise managers and estimate non‐linear multinomial logit models for a range of nested non‐expected utility and expected utility models. The risk and decision‐bias parameters for five models estimated for individual responses are shown to be significantly related to land condition but in ways which suggest behavioural aspects of decision making are critical in understanding land management and stocking rate decisions. Our results show that individual heterogeneity in decision making amongst farming groups is likely to be a significant source of variation in farming intensity and technology adoption decisions. This heterogeneity does not appear to be a reflection of socio‐demographic characteristics. Furthermore, decision functions appear to be biased toward selection of simpler representative functions (e.g. Expected Utility) for sample averages. This suggests that experimental findings that Expected Utility is representative for actual decisions may be due to sample averaging rather than reflect actual behaviour.     

More reasons why farmers have so little interest in futures markets

The use by farmers of futures contracts and other hedging instruments has been observed to be low in many situations, and this has sometimes seemed to be considered surprising or even mysterious. We propose that it is, in fact, readily understandable and consistent with rational decision making. Standard models of the decision about optimal hedging show that it is negatively related to basis risk, to quantity risk, and to transaction costs. Farmers who have less uncertainty about prices and those with a diversified portfolio of investments have lower optimal levels of hedging. If a farmer has optimistic price expectations relative to the futures market, the incentive to hedge can be greatly reduced. And finally, farmers who have low levels of risk aversion have little to gain from hedging in terms of risk reduction, in that the certainty‐equivalent payoff at their optimal hedge may be little different than the certainty equivalent under zero hedging. These reasons are additional to the argument of Simmons (2002) who showed that, if capital markets are efficient, farmers can manage their risk exposure through adjusting their leverage, obviating the need for hedging instruments.     

Flat Earth Economics: The Far-reaching Consequences of Flat Payoff Functions in Economic Decision Making

Economists tend to emphasize the optimum, but in many cases, even large deviations from optimal decisions make little difference to the payoff. This has far-reaching implications that are under-recognized, including: ( a ) decision makers often have a wide margin for error in their production planning decisions, and flexibility to pursue factors not considered in the calculation of payoffs; ( b ) optimizing techniques are sometimes of limited practical relevance for decision support; ( c ) the value of information used to refine management decisions is often low; and ( d ) the benefits of using "precision farming" technologies to adjust production input levels are often low.     

Faustmann vs. real options theory – An experimental investigation of foresters’ harvesting decisions

Among the most complex decisions in forestry is the decision of when to harvest a stand. Many investment theories have been established and adjusted to maximize profit, yet limited knowledge is available regarding the predictive power of theories. Understanding foresters’ harvesting behavior, however, is important for forest management and policy support. Thus, the question arises as to what extent risky harvesting decisions comply with economic theories. Therefore, we conduct an incentive-based economic experiment with 107 forestry decision makers in order to analyze this research question. This approach is well-established in the field of behavioral economics since it has the advantage of analyzing certain economic parameters isolated from further aspects of the decision situation. We use the Faustmann–Pressler–Ohlin theorem and a real options approach as normative benchmarks. The present study provides evidence that none of the examined theories fully comply with the observed behavior. However, the harvesting behavior coincides significantly more with the real options theory than with the Faustmann–Pressler–Ohlin theorem. It can thus be stated that a higher degree of education leads to decisions that are more in accordance with the real options theory.     

Pests and pesticides,risk and risk aversion

Theoretical and applied literature on risk in decision making for agricultural pest control is reviewed. Risk can affect pesticide decision making either because of risk aversion or because of its influence on expected profit. It is concluded that risk does not necessarily lead to increased pesticide use by individual farmers. Uncertainty about some variables, such as pest density and pest mortality, does lead to higher optimal pesticide use under risk aversion. However, uncertainty about other important variables, such as output price and yield, leads to lower optimal levels of pesticide use. Neglect of these variables in most studies has led to the false assumption that pesticides are always risk-reducing inputs. Furthermore, there is evidence that, in general, the pesticide dosage which maximises expected profit is lower under risk than under certainty. Depending on the balance of forces to increase and decrease pesticide use under risk, in many circumstances the net effect of risk on optimal decision making for pest control may be minimal. The effect on risk of information about pest density and other variables (as in integrated pest management programmes) is discussed. Evidence on this issue is mixed. A range of analytical techniques for analysing risk in pest control is reviewed. Throughout the paper, gaps in the existing literature are identified.     

A decision support system for strategic planning on pig farms

This paper reported on a decision support system (DSS) for strategic planning on pig farms. The DSS was based on a stochastic simulation model of investment decisions (ISM). ISM described a farm with one loan and one building using 23 variables. The simulation model calculated the results of a strategic plan for an individual pig farm over a time horizon of a maximum of 20 years for a given scenario. For six distinct replacement strategies, regression metamodels were specified to describe the outcome of the response variable as a function of the farm variables. The regression results indicated that a linear function with only nine or ten farm variables gave a reasonable estimate of the results of the simulation model. Turnover ratio, feed conversion ratio, percentage of meat, farm size, family expenses, and experience were the main parameters determining future relative farm position. For farms with high levels of family expenditures and/or financial leverage an economic replacement strategy was optimal. Risk attitudes played a minor role in the choice of the optimal strategy, because one strategy was preferred to another regardless of risk preference. To analyze the attractiveness of a chosen strategic plan for different ‘what-if’ scenarios, the visual method using graphical representations offered sufficient information. The number of years ahead for which the decision maker evaluated the consequences of simulated strategic plans influenced which strategy was preferred.     

THE USE OF A DECISION MAKER'S UTILITY FUNCTION IN A LINEAR PROGRAMMING ANALYSIS OF AGRICULTURAL POLICY*

A decision theoretic approach to agricultural policy decision making is examined to discover whether a utility function of an Australian Wool Corporation decision maker can be established and, if so, whether this can be used to improve the policy analysing performance of an agricultural sector linear programming model. After discussing the theoretical requirements of the utility function elicitation and the elicitation procedures, the characteristics of the resulting functions are examined. A means for its inclusion in a linear programming framework is described and some analysis of policy is carried out. The general conclusions are that the relevance of the agricultural sector analysis is enhanced by the use of such a utility function.     

RESPONSES TO RISK IN WEED CONTROL DECISIONS UNDER EXPECTED PROFIT MAXIMISATION: COMMENT

Pannell's finding that risk reduces the optimal rate of herbicide use and raises the economic threshold for weed control is found to depend upon the form of the yield function. Pannell's results apply only to convex yield functions. For sigmoidal functions, such as the logistic, risk has the opposite effect over the concave portion of the function's range.     

Classical decision rules and adaptation to climate change*

One approach to rationalising policies for addressing potentially catastrophic climate change when such policies may prove unnecessary is to suppose the policies provide a form of social insurance even in the presence of pure uncertainty. Then, provided the policies are effective, such insurance can be justified as a precautionary or minimax response. Even if the policies are potentially ineffective however, intervention can be justified as an attempt to minimise the regret experienced by future generations. This reasoning extends to justify ‘all weather’ policies provided such policies always reduce policy costs. If, however, policy decisions provide ‘all weather’ benefits in only certain states of the world, this rationale breaks down. Minimising regret can establish a case for ‘mixed’ policy responses provided adopting a policy mix precludes the chance that intervention will fail altogether. Precautionary policies and policies which minimise regret are computed for a simple, dynamic, adaptive climate change planning problem and sufficient conditions for policy maker pessimism provided.     

Savings and technology choice for risk averse farmers

Farmers in developing countries have limited opportunities for borrowing to even out variability associated with risky farm income, but they can save. A dynamic programming model of savings is presented in the current paper which examines optimal savings strategies for farmers, using a case study of integrated rice–shrimp farms in Vietnam. It is shown that when savings are accounted for, the expected utility ranking of different risky farm choices may not differ that much between farmers with different levels of risk aversion.     

Effect of yield and price risk on conversion from conventional to organic farming*

Although the benefits of organic farming are already well known, the conversion to organic farming does not proceed as the Dutch government expected. In order to investigate the conversion decisions of Dutch arable farms, a discrete stochastic dynamic utility‐efficient programming (DUEP) model is developed with special attention for yield and price risk of conventional, conversion and organic crops. The model maximizes the expected utility of the farmer depending on the farmer’s risk attitude. The DUEP model is an extension of a dynamic linear programming model that maximized the labour income of conversion from conventional to organic farming over a 10 year planning horizon. The DUEP model was used to model a typical farm for the central clay region in the Netherlands. The results show that for a risk‐neutral farmer it is optimal to convert to organic farming. However, for a more risk‐averse farmer it is only optimal to fully convert if policy incentives are applied such as taxes on pesticides or subsidies on conversion, or if the market for the organic products becomes more stable.     

Differential uncertainties and risk attitudes between conventional and organic producers: the case of Spanish arable crop farmers

The growing importance of economic factors in farmers' decisions to go organic has raised interest in characterizing the economic behavior of organic versus conventional farms. In general, published analyses so far have not considered differential uncertainties, abilities to control production risk, and farmers' risk preferences between conventional and organic practices when comparing these techniques. Our article attempts to assess this issue. We use a model of farmer decision under risk to analyze the differential values between organic and conventional Spanish arable crop farms and to assess the incentives for adoption of organic practices. Results show that organic and conventional farms do have different production risks as well as different aversions to risk. Organic price premiums and subsidies are found to be powerful instruments to motivate adoption of organic techniques.     

Economic contribution of French serradella (Ornithopus sativus Brot.) pasture to integrated weed management in Western Australian mixed‐farming systems: an application of compressed annealing*

Sowing phases of French serradella (Ornithopus sativus Brot.) pasture between extended cropping sequences in the Western Australian wheatbelt can sustain grain production through restoring soil fertility and reducing selective herbicide use. The objective of this article is to investigate the profitability of rotations involving this pasture under a variety of weed management scenarios to obtain greater insight into its value for mixed farming systems in this region. A stochastic search procedure, compressed annealing, is used to identify profitable sets of weed management strategies in a simulation model representing a large number of potential combinations of chemical and non‐chemical forms of weed control. In contrast to a continuous‐cropping sequence, the inclusion of a serradella phase in a rotation is profitable at high weed densities and with increasing levels of herbicide resistance. A single year of pasture in the rotation is optimal if resistance to Group A selective herbicides is present at the beginning of the planning horizon, but a three‐year phase is required if resistance to multiple herbicide groups is observed. Sowing a serradella pasture twice over a two‐year phase is also shown to be economically attractive given benefits of successive high weed kills.     

THE ECONOMIC OPTIMISATION OF SOW REPLACEMENT DECISIONS BY STOCHASTIC DYNAMIC PROGRAMMING

A stochastic dynamic programming model is designed to determine the economic optimal replacement policy in swine breeding herds. This optimal policy maximises the present value of net revenues from sows present in the herd and from subsequent replacement gilts over a given planning horizon. The model also calculates the total extra profit to be expected from trying to retain an individual sow until her optimal lifespan and not replacing her immediately. This total extra profit is an economic index which makes it possible to rank sows within the herd on future profitability and, therefore, can be used as a management guide in culling decisions. For typical Dutch values the optimal replacement decisions result in an average herd life of 3.43 parities. The maximum economic life of sows of average productivity turns out to be 10 parities. All data can easily be adjusted to represent a specific herd or a different region of the world.     

Optimal pest control in greenhouse production of ornamental crops

In this study, we develop a conceptual bioeconomic model of floriculture production with aesthetic benefits, wherein optimal decision rules depend on an intertemporal economic objective to maximize profits subject to economic and biological processes. Necessary conditions of the model identify optimal trajectories (e.g., simultaneous, single, or cycling controls) that define decision rules and economic thresholds for profit maximizing growers producing crops with aesthetic attributes. The necessary conditions also highlight intertemporal trade‐offs between aesthetic benefits and expected future net benefits of arthropod stocks, which have important policy implications. The model is applied to the greenhouse production system of ivy geranium.     

Incentive Perception in Livestock Disease Control

The economic incentives facing people making decisions about infectious disease control have been given due theoretical consideration in the literature, based on principles of economic rationality. Such deductive models provide important tools for generating hypotheses. However, the application of such models in a predictive capacity has been criticised. Simultaneously, empirical studies aimed at quantitative exploration of farmer behaviour have relied heavily on social cognitive models, such as the theory of planned behaviour, without exploration of the epidemiological consequences of variability in behaviour within populations. Advances in other social sciences have revealed systematic biases in human reasoning which cast doubt on the validity of the rational economic model as a generalisation of human decision making. We review the characteristics of infectious disease and disease‐control interventions and the potential for bias in implementation decision making at primary producer level. Specific focus is given to the generation of externalities, both positive and negative; the perception of risk, relating to disease incidence, technology adoption and time preference; and finally uncertainty, and its potential to be moderated by trust in information sources. This information is then used to summarise supplemental psychological constructs which taken holistically may strengthen our ability to quantitatively explore human behaviour in this complex decision‐making environment.