Volume 40, Issue 2, May 2015

By: Liaukonyte, Jura; Streletskaya, Nadia A.; Kaiser, Harry M.
Consumer preferences for labeled products are often assumed to be exogenous to the presence of labels. However, the label itself (and not the information on the label) can be interpreted as a noisy warning signal. We measure the impact of “contains” labels and additional information about the labeled ingredients, treating preferences for labeled characteristics as endogenous. We find that for organic-food shoppers, the “contains” label absent additional information serves as a noisy warning signal leading them to overestimate the riskiness of consuming the product. Providing additional information mitigates the large negative signaling effect of the label.
By: Çakır, Metin; Nolan, James
We explore how market power in a complementary input sector compares to that in a downstream sector for producer and consumer welfare. We develop a model of a homogeneous product market encompassing bilateral and complementary relationships. Our main finding is that market power exercised by the supplier of a complementary input generates greater negative welfare effects than the same level of market power exercised by downstream firms. We provide a discussion of the implications of the results for policy in the context of current problems in the Canadian grain-handling and transportation system.
By: Schulz, Lee L.; Dhuyvetter, Kevin C.; Doran, Beth E.
Feeder-calf prices are determined by the interaction of many factors. This study uses transaction data from Iowa preconditioned and regular feeder-calf auction sales to quantify the impact of a wide variety of factors, several of which have not been used in previous studies on feeder-calf prices. Notably, market premiums for preconditioned sales versus regular sales, feedlot capacity utilization, and seller reputation are found to be significant factors affecting feeder-calf prices. Estimated coefficients are then used to predict prices to demonstrate how this information can be used in making management and marketing decisions.
By: Kim, Jong-Jin; Zheng, Xiaoyong
We propose a model that elucidates the two channels through which alternative marketing arrangements affect spot price in livestock markets. The direct effect works through their effect on demand and supply. The indirect effect works through spot price volatility, which has been ignored in the literature. We then estimate a dynamic model with data from the U.S. hog market to test our model implications and quantify the two effects. We find increases in the use of AMAs increase spot price volatility and decrease spot price level. The short-run effects are small but the long-run effects are nontrivial.
By: Park, Timothy A.
This paper examines the impact of participation in direct marketing on the entire distribution of farm sales using the unconditional quantile regression (UQR) estimator. Our analysis yields unbiased estimates of the unconditional impact of direct marketing on farm sales and reveals the heterogeneous effects that occur across the distribution of farm sales. The impacts of direct marketing efforts are uniformly negative across the UQR results, but declines in sales tend to grow smaller as sales increase. Producers planning to sell more in local outlets should expect sales to decline. Marketing experts and extension professionals can use this information to guide farmers who are considering initiating or expanding direct marketing activities.
By: Belasco, Eric J.; Cheng, Yuanshan; Schroeder, Ted C.
While large feedlots commonly hedge corn and fed cattle prices, weather remains the largest uncontrollable component of production risk. This research examines the economic losses to cattle feeding associated with extreme weather. Profit losses are assessed using nonlinear regressions that relate weather outcomes, based on the Comprehensive Climate Index ( Mader, Johnson, and Gaughan , 2010 ), and their impact on production variables. Actuarially fair insurance premium rates are derived for an insurance product designed to mitigate the potential cost of extreme weather. Finally, we discuss additional issues associated with using weather-index insurance products and insuring feedlot cattle against adverse weather.
By: Rejesus, Roderick M.; Coble, Keith H.; Miller, Mary France; Boyles, Ryan; Goodwin, Barry K; Knight, Thomas O.
This article develops a procedure for weighting historical loss cost experience based on longer time-series weather information. Using a fractional logit model and out-of-sample competitions, weather variables are selected to construct an index that allows proper assessment of the relative probability of weather events that drive production losses and to construct proper “weather weights” that are used in averaging historical loss cost data. A variable-width binning approach with equal probabilities is determined as the best approach for classifying each year in the shorter historical loss cost data used for rating. When the weather-weighting approach described above is applied, we find that the weather-weighted average loss costs at the national level are different from the average loss costs without weather weighting for all crops examined.
By: Lambert, Dayton M.; Paudel, Krishna P.; Larson, James A.
This research analyzes the adoption patterns among cotton farmers for remote sensing, yield monitors, soil testing, soil electrical conductivity, and other precision agriculture technologies using a Multiple Indicator Multiple Causation regression model. Adoption patterns are analyzed using principle component analysis to determine natural technology groupings. Identified bundles are regressed on farm structure and operator characteristics. The propensity to adopt technology bundles was greater for producers managing relatively larger operations who used a variety of information sources to learn about precision farming, irrigated cotton, practiced crop rotation, and participated in working land conservation programs.