4,605 research outputs found

    Do Transaction Costs and Risk Preferences Influence Marketing Arrangements in the Illinois Hog Industry?

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    Risk reduction and transaction costs are often used to explain contracting in the U.S. hog industry with little empirical support. Using a unified conceptual framework that draws from risk behavior and transaction cost theories, in combination with unique survey and accounting data, we demonstrate that risk preferences and asset specificity impact Illinois producers’ use of contracts and spot markets. In particular, producers’ investments in specific hog genetics and human capital are related to selection of long-term marketing contracts over spot markets. Producers who perceive greater levels of price risk and/or are more averse are more (less) likely to use contracts (spot markets).asset specificity, contracts, hogs, risk attitude, risk behavior, risk perception, transaction costs economics, Livestock Production/Industries, Risk and Uncertainty,

    Do Transaction Costs and Risk Preferences Influence Marketing Arrangements in the Illinois Hog Industry?

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    Studies of hog industry structure often invoke risk reduction and transaction costs explanations for empirical observations but fail to directly examine the core concepts of risk behavior and transaction costs theories. Using a more unified conceptual framework and unique survey and accounting data, this study demonstrates that that risk preferences and asset specificity impact Illinois producers’ use of contracts and spot markets as suggested by theory. Factor analytic methods limit measurement error for indirectly observable risk and transaction costs variables employed in logit regressions. In particular, related investments in specific hog genetics and specific human capital regarding the production process increase the probability of selecting long-tem contracts over spot markets. Producers who perceive greater levels of price risk and/or are more averse to it appear more (less) likely to use long-term contracts (spot markets), and hence, to make such investments.risk behavior, transaction costs economics, risk attitude and risk perception, asset specificity, contracts, hogs, Agricultural Finance,

    Risk Attitude & the Structure of Decision Making: Evidence from the Hog Industry

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    We investigate the importance of an appropriate representation of behavior, risk attitude, and related characteristics for owner-managers making marketing decisions. We assess whether managerial/firm characteristics directly affect the decisions or if their influence occurs indirectly through impacts on risk aversion. The findings, which support an indirect effect, indicate that failure to represent the relationship between risk aversion, other characteristics, and behavior appropriately can mask the effect of risk aversion. A more complete understanding of the structure of decision making may assist economists and policymakers in designing and targeting mechanisms to transfer risk.behavior, contract, hogs, marketing, risk attitude, Agribusiness, Institutional and Behavioral Economics, Marketing, Q13,

    Is Storage at a Loss Merely an Illusion of Spatial Aggregation?

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    The storage-at-a-loss paradox—stocks despite inadequate price growth to cover storage costs—is an unresolved issue of long-standing interest to economists. Alternative explanations include risk premiums for futures market speculators, convenience yields from holding stocks, and mismeasurement/aggregation of data. Statistical analyses of regional and elevator corn and soybean price growth in Illinois suggest limited aggregation effects and reveal a pattern of regional- and elevator-level backwardations in the presence of Illinois corn stocks that is inconsistent with aggregation explanations for storage at a loss. Interviews with elevator managers support the existence of convenience yields.aggregation, convenience yield, corn, intertemporal arbitrage, regional and elevator data, soybeans, storage at a loss, Agribusiness, Marketing,

    Is Storage at a Loss Merely an Illusion of Aggregation?

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    The storage at a loss paradox of positive inventories despite inadequate spot-futures price spread coverage of storage costs is an unresolved issue of long-standing interest to economists. Alternative explanations include risk premiums for futures market speculators, convenience yields from having inventories on hand, and the mismeasurement/aggregation of data. T-test analyses of disaggregated data suggest soybean price behavior consistent with intertemporal arbitrage conditions and corn price behavior that may imply convenience yields.Marketing,

    Efficacy of Novel Pyridinium Oximes against Two Organophosphates in Female Sprague Dawley Rats

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    Anticholinesterase organophosphate (OP) compounds were developed as insecticides and are also used as nerve agents in chemical warfare. Treatment against acute OP toxicity includes oximes which reactivate phosphorylated acetylcholinesterase (AChE) restoring enzymatic activity. The oxime currently approved for use in the U.S., pralidoxime (2-PAM), has limited efficacy penetrating the blood-brain barrier. Our laboratory has developed novel substituted phenoxyalkyl pyridinium oximes (US Patent 9,227,937) designed to more effectively penetrate the central nervous system. This research investigated any differences in oxime reactivation among four age/sex groups and also survivability in adult female Sprague Dawley rats challenged with a lethal dose of OP. Initially in in vitro experiments, paraoxon (PXN) and a nerve agent (sarin) surrogate, 4-nitrophenyl isopropyl methylphosphonate (NIMP), were incubated with pooled rat brain homogenate from four sex/age groups: adult male or female, and 12-day old male or female rats. Reactivation was performed utilizing 2-PAM or one of three novel oximes (15, 20, or 55), alone or in combination, and AChE activity was measured in a spectrophotometric assay. Overall, the oximes were more effective reactivating inhibition from PXN than from NIMP. Out of all the oximes tested, 2-PAM showed the greatest reactivation percentages. Of the novel oximes, 15 and 20 displayed the highest reactivation against PXN and NIMP, respectively. No statistical difference was detected in reactivation for any oxime among the age/sex groups. For the in vivo study, female adult Sprague-Dawley rats were treated with LD99 dosages of NIMP or PXN. After development of seizure-like behavior, atropine and one of four oximes, 2-PAM, novel oxime 15, 20, or 55 or Multisol vehicle was administered. Animals were closely monitored for signs of cholinergic toxicity and 24-hour survivability. Against PXN, novel oximes 15 and 55 demonstrated an improved odds ratio of 6.5 and 3.1, respectively, over 2-PAM. The most effective oxime against NIMP was novel oxime 20 demonstrating an odds ratio of 3.2 over treatment with 2-PAM. These data indicate that the novel pyridinium oximes are equally efficacious reactivators in adult and juvenile rats of both sexes and enhance survivability against lethal-level OP toxicity as compared to 2-PAM in adult female rats

    Applications of topological data analysis to natural language processing and computer vision

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    2022 Spring.Includes bibliographical references.Topological Data Analysis (TDA) uses ideas from topology to study the "shape" of data. It provides a set of tools to extract features, such as holes, voids, and connected components, from complex high-dimensional data. This thesis presents an introductory exposition of the mathematics underlying the two main tools of TDA: Persistent Homology and the MAPPER algorithm. Persistent Homology detects topological features that persist over a range of resolutions, capturing both local and global geometric information. The MAPPER algorithm is a visualization tool that provides a type of dimensional reduction that preserves topological properties of the data by projecting them onto lower dimensional simplicial complexes. Furthermore, this thesis explores recent applications of these tools to natural language processing and computer vision. These applications are divided into two main approaches: In the first approach, TDA is used to extract features from data that is then used as input for a variety of machine learning tasks, like image classification or visualizing the semantic structure of text documents. The second approach, applies the tools of TDA to the machine learning algorithms themselves. For example, using MAPPER to study how structure emerges in the weights of a trained neural network. Finally, the results of several experiments are presented. These include using Persistent Homology for image classification, and using MAPPER to visual the global structure of these data sets. Most notably, the MAPPER algorithm is used to visualize vector representations of contextualized word embeddings as they move through the encoding layers of the BERT-base transformer model
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