Farmers’ Willingness to Grow Switchgrass as a Cellulosic Bioenergy Crop: A Stated Choice Approach

Farmers’ Willingness to Grow Switchgrass as a Cellulosic Bioenergy Crop: A Stated Choice Approach Agriculture’s role as a source of feedstocks in a potential lignocellulosic-based biofuel industry is a critical economic issue. Several studies have assessed the technical feasibility of producing bioenergy crops on agricultural lands. However, few of these studies have assessed farmers’ willingness to produce or supply bioenergy crops or crop residues. Biomass markets for bioenergy crops do not exist, and developing these markets may take several years. Therefore, an important, yet unaddressed question is under what contractual or pricing arrangements farmers will grow biomass for bioenergy in these nascent markets. The purpose of this paper is to examine farmers’ willingness to produce switchgrass under alternative contractual, pricing, and harvesting arrangements. Contracts are likely to be the preferred method to bring together producers and processors of biomass for bioenergy. Contract design may vary across farmers and crop type, and may include attributes specific to annual crops, contract length, quantity or acreage requirements, quality specifications, payment dates, and other important features. A stated choice survey was administered in three, six-county areas of Kansas by Kansas State University and the USDA, National Agricultural Statistics Service from November 2010 to January 2011 to assess farmers’ willingness to produce cellulosic biomass under different contractual arrangements. This paper focuses on the switchgrass stated choice experiment from the survey. The stated choice experiment asked farmers to rank their preferred contractual arrangement from two contract options and one “do not adopt” option. Contractual attributes included percentage net returns above the next best alternative (e.g. CRP or hay production), contract length, a custom harvest option, insurance availability, and a seed-cost share option. Respondents then ranked their preferred contract option. The survey also collected data on farm characteristics, bioenergy crop preferences, socio-economic demographics, risk preferences, and marketing behavior. The survey used a stratified sample of farmers who farm more than 260 acres and grow corn. A total of 460 surveys were administered with a 65 percent completion rate. The underlying theoretical model uses the random utility model (RUM) approach to assess farmers’ willingness to grow switchgrass for bioenergy and determine the contractual attributes most likely to increase the likelihood of adoption. This framework allows us to define the “price,” or farmers’ mean willingness to accept, for harvested biomass sold to an intermediate processor. The estimated choice models follow the approach of Boxall and Adamowicz (2002) to capture heterogeneity across farmers and geographic regions due to management differences, conservation practices, and risk preferences. Using the percentage net return above CRP or hay production allows prices to float to levels that will entice farmers to adopt switchgrass. This will help determine a market price for bioenergy crops based on current market and production conditions without specifying an exact monetary value for the biomass. In addition, the survey results will facilitate contract designs between biorefineries and farmers while informing policymakers and the biofuel industry about farmers’ willingness to supply biomass for bioenergy production. Reference: Boxall, P.C. and W.L. Adamowicz, “Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach,” Environmental and Resource Economics 23(2002): 421 – 446.Biofuels, Cellulosic, Biomass, Switchgrass, Farmers, Willingness to Pay, Crop Production/Industries, Production Economics, Resource /Energy Economics and Policy,

Cooperative Control and Potential Games

We present a view of cooperative control using the language of learning in games. We review the game-theoretic concepts of potential and weakly acyclic games, and demonstrate how several cooperative control problems, such as consensus and dynamic sensor coverage, can be formulated in these settings. Motivated by this connection, we build upon game-theoretic concepts to better accommodate a broader class of cooperative control problems. In particular, we extend existing learning algorithms to accommodate restricted action sets caused by the limitations of agent capabilities and group based decision making. Furthermore, we also introduce a new class of games called sometimes weakly acyclic games for time-varying objective functions and action sets, and provide distributed algorithms for convergence to an equilibrium

The Origin of Sequential Chromospheric Brightenings

Sequential chromospheric brightenings (SCBs) are often observed in the immediate vicinity of erupting flares and are associated with coronal mass ejections. Since their initial discovery in 2005, there have been several subsequent investigations of SCBs. These studies have used differing detection and analysis techniques, making it difficult to compare results between studies. This work employs the automated detection algorithm of Kirk et al. (Solar Phys. 283, 97, 2013) to extract the physical characteristics of SCBs in 11 flares of varying size and intensity. We demonstrate that the magnetic substructure within the SCB appears to have a significantly smaller area than the corresponding H-alpha emission. We conclude that SCBs originate in the lower corona around 0.1 R_sun above the photosphere, propagate away from the flare center at speeds of 35 - 85 km/s, and have peak photosphere magnetic intensities of 148 +/- 2.9 G. In light of these measurements, we infer SCBs to be distinctive chromospheric signatures of erupting coronal mass ejections.Comment: 25 pages, 9 figures, 5 table

The Effects of Cardiac Specialty Hospitals on the Cost and Quality of Medical Care

The recent rise of specialty hospitals -- typically for-profit firms that are at least partially owned by physicians -- has led to substantial debate about their effects on the cost and quality of care. Advocates of specialty hospitals claim they improve quality and lower cost; critics contend they concentrate on providing profitable procedures and attracting relatively healthy patients, leaving (predominantly nonprofit) general hospitals with a less-remunerative, sicker patient population. We find support for both sides of this debate. Markets experiencing entry by a cardiac specialty hospital have lower spending for cardiac care without significantly worse clinical outcomes. In markets with a specialty hospital, however, specialty hospitals tend to attract healthier patients and provide higher levels of intensive procedures than general hospitals.

Payoff-Based Dynamics for Multiplayer Weakly Acyclic Games

We consider repeated multiplayer games in which players repeatedly and simultaneously choose strategies from a finite set of available strategies according to some strategy adjustment process. We focus on the specific class of weakly acyclic games, which is particularly relevant for multiagent cooperative control problems. A strategy adjustment process determines how players select their strategies at any stage as a function of the information gathered over previous stages. Of particular interest are “payoff-based” processes in which, at any stage, players know only their own actions and (noise corrupted) payoffs from previous stages. In particular, players do not know the actions taken by other players and do not know the structural form of payoff functions. We introduce three different payoff-based processes for increasingly general scenarios and prove that, after a sufficiently large number of stages, player actions constitute a Nash equilibrium at any stage with arbitrarily high probability. We also show how to modify player utility functions through tolls and incentives in so-called congestion games, a special class of weakly acyclic games, to guarantee that a centralized objective can be realized as a Nash equilibrium. We illustrate the methods with a simulation of distributed routing over a network