Determinants of the Value of Climate Forecasts James W. Mjelde Department of Agricultural Economics Texas A&M University

Current Shortcomings Reinventing the wheel –ignoring previous literature –ignoring physical knowledge Multidisciplinary Studies –Short-run vs. long-run

Research Schematic Conceptual Model Problem Situation Solution Scientific Model Verification Feedback

Multidisciplinary Research Climate Economics Agronomy Decision Sciences

Information Allows decision makers to use inputs more efficiently Is a message which alters probabilistic perceptions of random events

Value of Information Difference between expected value when the information is used optimally and expected value when decisions are made without using the information.

To Have Value Interactions must exist between the decision variables and the stochastic variables Decision maker must have the flexibility to use the information Information must change decisions Different levels of decisions

Determinants of Value Structure of the decision set, x Structure of the decision environment, w(. ) Decision maker’s prior information, p(. ) Characteristics of the information system, p(. | F i )

Structure of the Decision Set Issue -what decisions can be made and at what level What we know

Decision Environment Issue - all aspects of the decision problem given by w(.) Discuss three issues –Constraints on use –Government programs –Risk aversion

Prior Knowledge Issue - individuals may not be accurate in their assessment of probabilities of historical events Most studies assume decision maker knows the historical probabilities

Forecast Characteristics Lead time Predictive accuracy Number of future periods forecasted Specificity Spatial resolution Weather parameters forecasted Time span of the forecast

Accuracy Received the most attention Includes g(.) and f(.) No monotonic relationship between forecast value and accuracy

Lead Time Denotes the time lapse between when the decision maker receives the forecast for a specific period and the occurrence of climate in that period Trade-offs

Specificity Refers to the number of climate conditions forecast for each period Results consistent with general information studies

Number of Future Periods How many future periods are forecasted by the climate system Synergistic effects of knowing climate conditions for adjacent periods

Spatial Resolution For a large geographical region, the forecast is correct, but for any specific area within the region, the forecast maybe incorrect Field-level vs. aggregate-level

Weather Parameters Which parameters are to be forecasted by the system Little economic work since the early 1980’s

Time Span Issue - what time periods for the individual forecasts are relevant to the decision maker – weekly, monthly, growing seasonal etc. No economic studies

Four Emerging Points Winners and Losers Climate variability vs. variability mitigated or caused by the use of climate forecasts Long-run vs. expected present value Communication / use issues

Aggregate Issues Complicates the issue –price effects, adoption rates, aggregation issues Fallacy of composition –whole vs. parts International trade