This is part 2 in my 3-part series on valuing farm data in the event that data were lost. Part 1 provided the background information on the farm scenario.
Estimating Consequential Damages
To conduct the forensic economics for the consequential damages, I estimated the value of discounted stream of income that would have been realized if the data had not been destroyed (i.e. net present value or NPV). Two scenarios were evaluated. The first scenario evaluated the revenue stream if the data were available. The second scenario evaluated the revenue stream for when farm data were unavailable to the decision making process. The difference in revenue streams between these two scenarios is the forgone revenue.
To set the precedent of historical use of data in farm management decision making, the value of completed on-farm experiments from the last several years were estimated. A series of NPV analyses were conducted on several recent experiments to demonstrate a history of utilizing yield monitor data from on-farm experiments to make farm management decisions. This indicated that the farmer had a history of using yield monitor data for farm management purposes; and that the data had a substantial value to the farmer’s overall net farm income. For the on farm experiments that yield data were not available, the cost of conducting the research were calculated then a reasonable expected yearly revenue stream were estimated for the net present value analysis. These can be thought of as the cost of making the wrong decision.
One of the first decisions to be made is how many years that the results will be usable for the farm. Discussions with the farmer revealed how many years the results from the on-farm experiment typically were used. As a guideline, corn hybrid results are usable for only 1 or maybe 2 years given the relatively short market life of corn genetics. Other input products such as herbicides, fungicides, and insecticides have a longer market life than corn hybrids. Results may be usable for 1 to potentially 10 or more years. For fertilizer rates, the results may be useful for several additional years since the products typically do not have a defined market life. In any case, on-farm research results have a finite lifespan and the value of that data diminishes over time. The results from on-farm research may also be limited in time due to results becoming common knowledge to farmers once public research results are released and/or neighboring farmers providing anecdotal insights. Therefore, the revenue stream may be reduced to fewer years than even the market life of the product.
A key component of the benefit-cost analysis for the expert witness is to compare the ‘best’ decision from an on-farm experiment relative to the status quo practice, not the worst case practice scenario. As an extreme example, a corn hybrid that had an expected yield of 175 bushels per acre (bu per ac) should be compared against the most likely hybrid choice (say 170 bu per ac) and not the option of no seeds (i.e. 0 bu per acre). So the net benefit for a given year would be the price of corn times yield difference (175 bu minus 170 bu = 5 bu) minus difference in seed costs. A more relevant example may be testing two fungicides against no fungicide at all, i.e. the untreated control treatment, where Fungicide A resulted in 15 bu per acre more than the control of no fungicide and Fungicide B resulted in 12 bu per acre more than the control. The expert witness would not use a difference of 15 bu per ac but rather a difference of 3 bu per ac (15 bu – 12 bu = 3 bu per ac). Economists refer to these calculations as partial budget analysis.
One of the leading debates in forensic economics literature is the choice of discount rate used in the net present value analysis. Given that the pertinent farm data examples are shorter time periods relative to the class human lifespan examples, the chosen discount rate has relatively less importance to the outcome of the analyses. That being said, some farm data plaintiffs may prefer higher discount rates and others prefer smaller discount rates depending upon the length of the discounted revenues and relative size of annual returns.
Although there is substantial variability in commodity crop prices over time, a constant price were used for all years of the analysis. A long-run planning price for each crop was chosen for all analyses. An alternative was to assign two or three planning prices (low, expected, high) and perform the analysis at three different levels of commodity crop prices. This provides the decision maker with a set of analysis to choose from and is common practice in benefit-cost analyses. Consequential damages were estimated using the process described in this article. In the final blog of this series, speculative damages are described with respect to this scenario.