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1. Introduction. 1.1. Formulating the risk problem. 1.2. Decision criteria. 1.3. Decision making under risk : fact and fiction -- 2. Probability theory - a mathematical basis for making decisions under risk and uncertainty. 2.1. Set theory and probability. 2.2. Random variables. 2.3. Conditional probability and independence. 2.4. Some useful distribution functions. 2.5. Expected value, moments, and the moment generating function. 2.6. Estimating probability functions. 2.7. Martingales and random walks. 2.8. Summary -- 3. Expected utility - the economic basis of decision making under risk. 3.1. Consumption and utility. 3.2. Expected utility. 3.3. Expected value - variance and expected utility models. 3.4. Problems with expected utility. 3.5. Summary -- 4. Risk aversion in the large and small. 4.1. Arrow-Pratt risk aversion coefficient. 4.2. Eliciting risk aversion coefficients. 4.3 Summary -- 5. Portfolio theory and decision making under risk. 5.1. The expected value - variance frontier. 5.2. A simple portfolio. 5.3. A graphical depiction of the expected value-variance frontier. 5.4. Mean-variance versus direct utility maximization. 5.5. Derivation of the expected value-variance frontier. 5.6. Summary -- 6. Whole farm-planning models. 6.1. Farm portfolio models. 6.2. Minimize total absolute deviation. 6.3. Focus-loss. 6.4. Target MOTAD. 6.5. Direct utility maximization. 6.6. Discrete sequential stochastic programming. 6.7. Chance-constrained programming. 6.8. Interpreting shadow values from risk programming models. 6.9. Summary -- 7. Risk efficiency approaches - stochastic dominance. 7.1. Stochastic dominance. 7.2. Applications of stochastic dominance. 7.3. Summary -- 8. Dynamic decision rules and the value of information. 8.1. Decision making and Bayesian probabilities. 8.2. Concepts of information. 8.3. A model of information. 8.4. Summary -- 9. Market models of decision making under risk. 9.1. Risk equilibrium from the consumer's point of view. 9.2. The role of the riskless asset. 9.3. Risk equilibrium from the firm's perspective. 9.4. Arbitrage pricing theorem. 9.5. Empirical applications of capital market models. 9.6. Summary -- 10. Option pricing approaches to risk. 10.1. Introductions to options and futures. 10.2. Real option valuation. 10.3. Crop insurance. 10.4. Summary -- 11. State contingent production model : the stochastic production set. 11.1. Depicting risk and input decisions in the production function. 11.2. State Production set and input requirement set. 11.3. Distance functions and risk aversion. 11.4. Summary -- 12. Risk, uncertainty, and the agricultural firm - a summary and outlook
This text is the first major survey of risk analysis from the perspective of the agricultural firms since Agricultural Decision Analysis by Anderson, Dillon, and Hardaker published in 1977. In addition to updating the traditional material from that text, this book includes the statistical foundations of decision making under risk and uncertainty. Adding to the material covered in Anderson, Dillon, and Hardaker, the text includes material on dynamic decision rules, the arbitrage pricing model, real options theory, and state-contingent production relationships. Risk, Uncertainty, and the Agricultural Firm provides a unique discussion of each application ? developing the theoretical basis for each model and presenting an empirical roadmap (or the ?nuts and bolts?) of each model to facilitate the empirical application of each technique.
A timeless classic of economic theory that remains fascinating and pertinent today, this is Frank Knight's famous explanation of why perfect competition cannot eliminate profits, the important differences between "risk" and "uncertainty," and the vital role of the entrepreneur in profitmaking. Based on Knight's PhD dissertation, this 1921 work, balancing theory with fact to come to stunning insights, is a distinct pleasure to read. FRANK H. KNIGHT (1885-1972) is considered by some the greatest American scholar of economics of the 20th century. An economics professor at the University of Chicago from 1927 until 1955, he was one of the founders of the Chicago school of economics, which influenced Milton Friedman and George Stigler.
After all the research on agricultural risk to date, the treatment of risk in agricultural research is far from harmonious. Many competing risk models have been proposed. Some new methodologies are largely untested. Some of the leading empirical methodologies in agricultural economic research are poorly suited for problems with aggregate data where risk averse behavior is less likely to be important. This book is intended to (i) define the current state of the literature on agricultural risk research, (ii) provide a critical evaluation of economic risk research on agriculture to date and (iii) set a research agenda that will meet future needs and prospects. This type of research promises to become of increasing importance because agricultural policy in the United States and elsewhere has decidedly shifted from explicit income support objectives to risk-related motivations of helping farmers deal with risk. Beginning with the 1996 Farm Bill, the primary set of policy instruments from U.S. agriculture has shifted from target prices and set aside acreage to agricultural crop insurance. Because this book is intended to have specific implications for U.S. agricultural policy, it has a decidedly domestic scope, but clearly many of the issues have application abroad. For each of the papers and topics included in this volume, individuals have been selected to give the strongest and broadest possible treatment of each facet of the problem. The result is this comprehensive reference book on the economics of agricultural risk.
Annotation This book contains a collection of papers that address various aspects of risk, including riskmanagement and how it is applied to decisionmaking and the impact of risk on markets
Risk and uncertainty are inescapable factors in agriculture which require careful management. Farmers face production risks from the weather, crop and livestock performance, and pests and diseases, as well as institutional, personal and business risks. This revised third edition of the popular textbook includes updated chapters on theory and methods and contains a new chapter discussing the state-contingent approach to the analysis of production and the use of copulas to better model stochastic dependency. Aiming to introduce agricultural decision making, probability and risk preference, this book is an indispensable guide for students and researchers of agriculture and agribusiness management.
This guide is intended to help extension workers better understand the concept of risk, the situation where risk occurs and management strategies that can be used to reduce, or at least soften, its effect. It is hoped that the guide will be useful in assisting extension workers to provide farmers with advice on the kind of risk management strategies that they can employ to deal with risk in their day-to-day operations. In this way extension workers can help farmers recognize and understand the risks that they are likely to face and assist them in making better farm management decisions that reduce the negative effect of the risks encountered in farming.
Ulrich Koester researches and teaches at the Institute for Agricultural Economics at the Christian-Albrechts-University of Kiel, Germany. He has been a member of the Scientific Advisory Board of the Ministry of Food, Agriculture and Forestry for over 20 years. Moreover, he gained experience working with the International Food Policy Research Institute in Washington D.C. and with numerous international organizations, including the World Bank, FAO, the European Commission, the European Parliament and the European Court of Auditors. His teaching experience is based on courses taught at more than ten universities in general economics and agricultural economics. Part I of the book lays the theoretical foundations for understanding price formation in product and factor markets. In addition to neoclassical theory, institutional economics is of particular importance. Part II presents and evaluates agricultural policy with special reference to the EU, whereby the evaluation framework goes beyond the usual welfare theory analysis. The book is also a valuable aid for students of economic policy, especially because of its detailed evaluation of individual agricultural market policy instruments. The book is aimed at students at universities, technical colleges as well as politicians interested in rational agricultural policy making.
The objective of Risk Analysis in Theory and Practice is to present this analytical framework and to illustrate how it can be used in the investigation of economic decisions under risk. In a sense, the economics of risk is a difficult subject: it involves understanding human decisions in the absence of perfect information. How do we make decisions when we do not know some of events affecting us? The complexities of our uncertain world and of how humans obtain and process information make this difficult. In spite of these difficulties, much progress has been made. First, probability theory is the corner stone of risk assessment. This allows us to measure risk in a fashion that can be communicated among decision makers or researchers. Second, risk preferences are now better understood. This provides useful insights into the economic rationality of decision making under uncertainty. Third, over the last decades, good insights have been developed about the value of information. This helps better understand the role of information in human decision making and this book provides a systematic treatment of these issues in the context of both private and public decisions under uncertainty. - Balanced treatment of conceptual models and applied analysis - Considers both private and public decisions under uncertainty - Website presents application exercises in Excel