Agricultural Decision Analysis: The Causal Challenge

The paper sets out the agenda for reviewing models of decision making in the context of farmers’ use of seasonal climate forecasting. Such forecasts have been framed in terms of shifts in cumulative distribution functions of yields or gross margins. Typically they have been applied to choices about crop variety, crop type, time of planting or level of fertiliser application. Fundamental questions are: how do farmers conceptualise and make use of the information contained in seasonal climate forecasts? Do our models of decision making represent well the way in which these decisions are made?decision making, farmers, seasonal climate forecasts, conceptualisation, review,

Structuring Decisions Under Deep Uncertainty

Innovative research on decision making under ‘deep uncertainty’ is underway in applied fields such as engineering and operational research, largely outside the view of normative theorists grounded in decision theory. Applied methods and tools for decision support under deep uncertainty go beyond standard decision theory in the attention that they give to the structuring of decisions. Decision structuring is an important part of a broader philosophy of managing uncertainty in decision making, and normative decision theorists can both learn from, and contribute to, the growing deep uncertainty decision support literature

Asymmetric Empirical Similarity

The paper offers a formal model of analogical legal reasoning and takes the model to data. Under the model, the outcome of a new case is a weighted average of the outcomes of prior cases. The weights capture precedential influence and depend on fact similarity (distance in fact space) and precedential authority (position in the judicial hierarchy). The empirical analysis suggests that the model is a plausible model for the time series of U.S. maritime salvage cases. Moreover, the results evince that prior cases decided by inferior courts have less influence than prior cases decided by superior courts

Preference for Diversification with Similarity Considerations

The paper studies the connection between the form of the similarity function of a decision-maker and his willingness to diversify. It is shown that preference for diversification obtain for both high and low aspiration levels if the similarity function is convex in the Euclidean distance. However, a decision-maker with a concave similarity function and relatively high aspiration level will fail to choose diversified acts, even if his utility function is concave.

Probability and Uncertainty in Economic Modeling, Second Version

Economic modeling assumes, for the most part, that agents are Bayesian, that is, that they entertain probabilistic beliefs, objective or subjective, regarding any event in question. We argue that the formation of such beliefs calls for a deeper examination and for explicit modeling. Models of belief formation may enhance our understanding of the probabilistic beliefs when these exist, and may also help up characterize situations in which entertaining such beliefs is neither realistic nor necessarily rational.Decision making, Bayesian, Behavioral Economics

Probabilities in Economic Modeling

Economic modeling assumes, for the most part, that agents are Bayesian, that is, that they entertain probabilistic beliefs, objective or subjective, regarding any event in question. We argue that the formation of such beliefs calls for a deeper examination and for explicit modeling. Models of belief formation may enhance our understanding of the probabilistic beliefs when these exist, and may also help up characterize situations in which entertaining such beliefs is neither realistic nor necessarily rational.Decision making, Bayesian, Behavioral Economics