Brorsen, B. Wade

May, 2021

By: Mills, Brian E. ; Brorsen, B. Wade ; Arnall, D. Brian
Past research on the profitability of precision phosphorus (P) application has used a small number of fields and a short time frame. Data on grid-sampled fields provided by producers are used to define the distribution of phosphorus within fields. Expected yields and net present value (NPV) are simulated to compare variable and uniform rate P. The highest NPV used a variable rate that changed each year based on yield and predicted carryover. A variable rate using the same rates for 4 years was inferior to simply applying a little extra P at a uniform rate.

January, 2021

By: Cho, Whoi ; Brorsen, B. Wade
This article considers three possible issues about the design of the Rainfall Index Pasture, Rangeland and Forage (RI-PRF) crop insurance program: (i) how well the rainfall index matches actual rainfall, (ii) whether the county base values can be made more accurate using spatial smoothing, and (iii) optimal choices of RI-PRF crop insurance alternatives for producers and reducing the number of choices that producers have to make. Based on the results, we conclude that the RI-PRF crop insurance program needs to reduce the number of choices and provide suggestions for restricting the choices.

September, 2020

By: Park, Eunchun ; Brorsen, B. Wade ; Harri, Ardian
Many crop insurance studies have pointed out that considering spatial yield similarity can help provide more precise premium rating. We use Bayesian Kriging for spatial smoothing to consider such similarities when estimating crop yield densities. This articleÕs innovation is that the spatial smoothing is based on climate space, which is composed of climatological measures. We compare the climate-space smoothing with a general physical space (longitudeÐlatitude space) smoothing. The test results are favorable to the proposed climate-smoothing method. Climate smoothing performs particularly well in states that have many missing counties and varied climate due to varying topography.

September, 2018

By: Kim, Seon-Woong; Lusk, Jayson L.; Brorsen, B. Wade
We investigate whether consumers purchase organic foods to demonstrate social status to others. Subjects were asked to choose among organic and nonorganic milk and apples in a control group and treatments in which: i) an image of another person’s eyes was displayed, ii) responses appeared to not be anonymous, or iii) a vignette placed the choice in the presence of an acquaintance. The vignette treatment increased the willingness-to-pay (WTP) premium for organic by about 90%. The other treatments did not have significant overall effects. When exposed to another person’s eyes, more educated respondents increased their WTP for organic.

May, 2016

By: Thompson, Nathanael M.; DeVuyst, Eric A.; Brorsen, B. Wade; Lusk, Jayson L.
We estimate the value of using genetic information to make fed cattle marketing decisions. Efficiency gains result from sorting cattle into marketing groups, including more accurate optimal days-on-feed and reduced variability of returns to cattle feeding. The value of using genetic information to selectively market cattle ranged from $1–$13/head depending on how a producer currently markets cattle and the grid structure. Although these values of genetic information were generally higher than those reported in previous research, they were still not enough to offset the current cost of genetic testing (about $40/head).

April, 2014

By: Thompson, Nathanael M.; DeVuyst, Eric A.; Brorsen, B. Wade; Lusk, Jayson L.
We estimate the value of using information from genetic marker panels for seven economically relevant feedlot cattle traits. The values of using genetic information to sort cattle by optimal days-on-feed are less than $1/head for each of the traits evaluated. However, the values associated with using genetic information to select cattle for placement are as much as $38/head. The most economically relevant genetic traits are average daily gain and marbling. It would not be profitable at the current testing cost of $38/head to sort cattle by optimal days-on-feed, but it could be profitable to use the genetic tests for breeding cattle selection.

December, 2012

By: Shah, Samarth; Brorsen, B. Wade; Anderson, Kim B.
While considerable research has estimated liquidity costs of futures trading, little comparable research is available about options markets. This study determines effective bid-ask spreads in options and futures markets for Kansas City Board of Trade (KCBT) wheat. Effective bid-ask spreads are estimates of the actual liquidity cost of a round-trip order. Option liquidity costs are estimated using a new measure of effective spreads developed for options markets. Futures effective spreads are estimated using eight different measures developed in previous studies. Estimated effective bid-ask spreads of options contracts are at least double the effective bid-ask spreads of open-outcry futures contracts.

April, 2011

By: Shah, Samarth; Brorsen, B. Wade
This study compares liquidity costs of electronic and open-outcry wheat futures contracts traded side-by-side on the Kansas City Board of Trade. Liquidity costs are considerably lower in the electronic market. Liquidity costs in the electronic market are still considerably lower after eliminating the bias created by splitting orders in the electronic market. Price volatility and transaction size are positively related to liquidity costs, while a negative relation is found between daily volume and liquidity costs. Price clustering at whole cent prices occurs in the open-outcry market which helps explain its higher liquidity costs. Daily volumes were distinctively higher during the Goldman-Sachs roll, but not enough to explain the higher liquidity costs in the open-outcry market. Trade size is larger in the open-outcry market, which suggests large traders prefer open-outcry trading.

April, 2010

By: Hatchett, Robert B.; Brorsen, B. Wade; Anderson, Kim B.
The question addressed in this study is which length of historical moving average provides the best forecast of futures basis. Differences in observed forecast accuracy among the different moving averages are usually less than a cent per bushel, and most are not statistically significant. Further, the search for an optimal length of moving average may be futile since the optimal length depends on how much structural change has occurred. Our recommendation is to use moving averages when there has been no structural change and to use last year’s basis or an alternative approach if the forecaster perceives that a structural change has occurred.