THE SUSTAINABLE GROWTH PARADIGM'S APPLICATION TO U.S. FARM BUSINESSES

The sustainable growth paradigm is used to analyze aggregate output decisions across U.S. agricultural productions regions. Results show that the farm sector has adapted to positive or negative sustainable growth challenges (SGC) and that, from an equilibrium point of view, SGC countercyclical measures indicate a usual tendency towards balanced growth.Production Economics,

FARM FINANCIAL STRUCTURE DECISIONS UNDER DIFFERENT INTERTEMPORAL RISK BEHAVIORAL CONSTRUCTS

An alternative unconstrained expected-utility maximization model of farm debt is developed using the location-scale parameter condition that incorporates the empirically validated hypotheses of decreasing absolute and constant relative risk aversion. Simulation-optimization results based on the old and new model versions provide interesting implications for various levels of risk aversion and initial equity investments.Risk and Uncertainty,

Determinants of the Organic Farmers' Demand for Hired Farm Labor

Labor and Human Capital,

Farmland Control Decisions under Different Intertemporal Risk Behavioral Constructs

Simulation-optimization techniques are employed to analyze changes in farmland control arrangements as a result of using different constructs of intertemporal risk behavior. Risk behavior based on constant absolute risk aversion (CARA) and constant relative risk aversion (CRRA) mean-standard deviation functions are used to achieve this objective. Specfically, a multi-period programming framework for a representative grain farm is developed to explore farmland control decisions under these two behavioral assumptions. Our results suggest that the use of a CRRA behavioral construct in analyzing farmland control decisions produce predictions that are more consistent with observed farm behavior.Farm Management,

FARM-LEVEL EVIDENCE ON THE RISK BALANCING HYPOTHESIS FROM ILLINOIS GRAIN FARMS

This study provides farm-level empirical support to the Risk-Balancing Hypothesis using Illinois grain farm data. The econometric results indicate that risk-balancing farmers comprise more than half of the sample. These farmers tend to be older, have higher leasing ratios, are less financially efficient and manage risk through crop specialization, enterprise diversification, and marketing strategies in addition to risk balancing.Risk and Uncertainty,

Weather Cycles, Production Yields and Georgia's Muscadine

This paper looks at the relationship between weather, crop yield, and market price of muscadines using a dynamic panel data that spans from the 2000 to 2005 and across the state of Georgia. We use a Generalized Methods of Moments technique to estimate the impact of weather on the price of muscadines with the yield per acre as the instrumented variable. The results suggest that there is a relationship between the price and weather for muscadines, which provide important implications for the potential relevance of a weather derivative for muscadine production.muscadines, weather cycles, price, production yields, Georgia, Generalized Method of Moments, Farm Management, Risk and Uncertainty,

von Neumann-Morgenstern and Savage Theorems for Causal Decision Making

Causal thinking and decision making under uncertainty are fundamental aspects of intelligent reasoning. Decision making under uncertainty has been well studied when information is considered at the associative (probabilistic) level. The classical Theorems of von Neumann-Morgenstern and Savage provide a formal criterion for rational choice using purely associative information. Causal inference often yields uncertainty about the exact causal structure, so we consider what kinds of decisions are possible in those conditions. In this work, we consider decision problems in which available actions and consequences are causally connected. After recalling a previous causal decision making result, which relies on a known causal model, we consider the case in which the causal mechanism that controls some environment is unknown to a rational decision maker. In this setting we state and prove a causal version of Savage's Theorem, which we then use to develop a notion of causal games with its respective causal Nash equilibrium. These results highlight the importance of causal models in decision making and the variety of potential applications.Comment: Submitted to Journal of Causal Inferenc