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Value of perfect ENSO phase predictions for agriculture: evaluating the impact of land tenure and decision objectives
Authors:David Letson  Carlos E Laciana  Federico E Bert  Elke U Weber  Richard W Katz  Xavier I Gonzalez  Guillermo P Podestá
Institution:1. Rosenstiel School of Marine and Atmospheric Science, University of Miami, 4600 Rickenbacker CSWY, Miami, FL, 33149-1098, USA
2. Departamento de Hidráulica, Facultad de Ingeniería, Universidad de Buenos Aires, Buenos Aires, Argentina
3. Cátedra de Cerealicultura, Facultad de Agronomía, Universidad de Buenos Aires, Buenos Aires, Argentina
4. Department of Psychology and Graduate School of Business, Center for Research on Environmental Decisions, Columbia University, New York, NY, USA
5. Institute for Study of Society and Environment, National Center for Atmospheric Research, Boulder, CO, USA
Abstract:In many places, predictions of regional climate variability associated with the El Niño–Southern Oscillation phenomenon offer the potential to improve farmers’ decision outcomes, by mitigating the negative impacts of adverse conditions or by taking advantage of favorable conditions. While the notion that climate forecasts are potentially valuable has been established, questions of when they may be more or less valuable have proven harder to resolve. Using simulations, we estimate the expected value of seasonal climate information under alternative assumptions about (a) land tenure (ownership vs. short-term leases) and (b) the decision maker’s objective function (expected utility vs. prospect theory value function maximization), employing a full range of plausible parameter values for each objective function. This allows us to show the extent to which the value of information depends on risk preferences, loss aversion, wealth levels and expectations, as well as situational constraints. Our results demonstrate in a non-laboratory decision context that, in some cases, psychologically plausible deviations from expected utility maximization can lead to substantial differences in estimates of the expected value of climate forecasts. Efforts to foster effective use of climate information and forecasts in agriculture must be grounded in a firm understanding of the goals, objectives and constraints of decision makers.
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