Journal of Agricultural and Resource Economics
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Nitrogen response models are often estimated as plateau type models. Existing plateau models are nonlinear in the parameters. The model introduced here is a multi-degree spline plateau model, which is linear in parameters. The linearity allows using approximation methods so that estimating a spatially varying coefficient model with Bayesian Kriging could be a commercially feasible approach to guide precision nitrogen applications. With proper knot selection, the spline plateau model can fit as well as the linear and quadratic plateau models. The computational efficiency of the spline plateau model was demonstrated using R-INLA and it provided fast and accurate estimation.
This study estimates the impact of joining a cooperative grain alliance on the wheat basis for elevators in Oklahoma. The study uses augmented difference-in-differences regressions to analyze the effects of joining the alliance on an elevator’s grain basis. Entry is not randomly assigned across elevators, and an elevator’s basis is codetermined with its neighboring elevators due to transport costs and other unobserved variables. Instrumental variable regression is used to address these issues. The main takeaway is that joining the alliance did not change the wheat basis.
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.
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.
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 article’s 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 (longitude–latitude 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.
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.
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).
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.
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.
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.
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.
The incentives researchers face depend directly upon what we as a profession value. The impacts of research can be either disciplinary by adding to economic knowledge or real world by being useful to economic agents. Various measures of research impact such as publications, citations, and external funding are discussed, and the strengths and weaknesses of each measure are evaluated. Because of the difficulty of accurately measuring research impact, we must depend on internal incentives to motivate researchers to select topics with the most potential impact.
Little research has been conducted on evaluating out-of sample forecasts of discrete dependent variables. This study describes the large and small sample properties of two forecast evaluation techniques for discrete dependent variables: receiver-operator curves and out-of-sample log-likelihood functions. The methods are shown to provide identical model rankings in large samples and similar rankings in small samples. The likelihood function method is better at detecting forecast accuracy in small samples. By improving forecasts of fed cattle quality grades, the forecast evaluation methods are shown to increase cattle marketing revenues by $2.59/head.
Economists tend to focus on monetary incentives. In the model developed here, both sociological and economic incentives are used to diminish the apparent moral hazard problem existing in commodity grading. Training that promotes graders’ response to sociological incentives is shown to increase expected benefits. The model suggests this training be increased up to the point where the marginal benefit due to training equals its marginal cost. It may be more economical to influence the grader’s behavior by creating cognitive dissonance through training and rules rather than by using economic incentives alone.
A Cox test with parametric bootstrap is developed to select between the linearized version of the First-Difference Almost Ideal Demand System (FDAIDS) and the Rotterdam model. A Cox test with parametric bootstrap has been shown to be more powerful than encompassing tests like those used in past research. The bootstrap approach is used with U.S. meat demand (beef, pork, chicken, fish) and compared to results obtained with an encompassing test. The Cox test with parametric bootstrap consistently indicates the Rotterdam model is preferred to the FDAIDS, while the encompassing test sometimes fails to reject FDAIDS.
Kernel uniformity is an important quality attribute that can now be measured at low cost. This study analyzes the profitability of sorting to increase wheat kernel uniformity. Nonlinear programming is used to sort grain loads to maximize flour yield by increasing uniformity of kernel size and kernel hardness. Results of this analysis suggest increases in flour yield due to higher kernel uniformity are not enough to outweigh the costs of sorting.
A theoretical model is developed to explain the economics of determining price slides for feeder cattle. The contract is viewed as a dynamic game with continuous strategies where the buyer and seller are the players. The model provides a solution for the price slide that guarantees an unbiased estimate of cattle weight. An empirical model using Superior Livestock Auction (SLA) data shows price slides used are smaller than those needed to cause the producer to give unbiased estimates of weight. Consistent with the model’s predictions, producers slightly underestimate cattle weights.
Trends in the accuracy of USDA forecasts of beef and pork production and supply are evaluated for the period 1982-96. Findings of the study show that USDA forecasts underestimated production and supply in the 1980s, but this bias has now disappeared. The variance of forecasts also has declined. Thus the accuracy of the forecasts has improved. The most recent USDA forecasts were found to meet the criteria of optimal forecasts, while those of the 1980s were not optimal.
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