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Abstract:
We investigate factors that drive derivative usage in small and medium-sized enterprises (SMEs). The influence of these factors on hedging behavior cannot a priori be assumed equal for all SMEs. To address this heterogeneity, a generalized mixture regression model is used which classifies firms into segments, so that the hedging response to the determinants of derivative usage is the same within each segment. Using a unique data set of 415 SMEs, containing both accounting and experimental data, we find that factors like risk exposure, risk perception, risk attitude, and the decision-making unit, among others are useful in explaining hedging behavior. However, the effects of these factors are not homogeneous across all managers, and the roots of the heterogeneity can partially be traced to differences in attitudes, perceptions, and to differences in ownership structure.

Derivatives Usage, Hedging Behavior, Unobserved Heterogeneity

Abstract:
Based on recent findings from economics and the neurosciences, we present a conceptual decision-making model that provides insight into human decision-making and illustrates how behavioral outcomes are transformed into phenomena. The model may be viewed as a bridge between the seemingly disparate disciplines of neuroscience and economics that may facilitate more integrative research efforts and provide a framework for developing research agendas for scientists interested in human behavior and economic phenomena.

revealed behavior, economics, neurosciences, synthesis, decision-making model

Abstract:
What drives poverty? We propose a research approach to study poverty by focusing on individual decision-making behavior in which the interaction between individual's innovativeness and time preference rate is crucial to begin understanding poverty. This approach enables policy makers to formulate efficient and effective policy and provides economists with an alternative research tool to study poverty.

Poverty, Decision Making Behavior, Research Approach

Abstract:
The statistical forecasting efficiency of new crop corn and soybean futures is the topic of frequent academic inquiry. However, few studies address the usefulness of these forecasts to economic agents? decision making. Each year Central Illinois producers are faced with the decision to plant either corn or soybeans on marginal acreage. Agronomic concerns aside, these decisions hinge on the expected relative return of corn versus soybeans, which is largely a function of expected new crop prices. Do new crop futures prices reliably guide producers into the correct production decision? The results suggest that over the entire period of the analysis, futures markets provide only marginal decision-making information to the producer; however, more recent signals do appear to be useful. Further analysis explores several possible factors that could explain why the signals have improved so significantly since 1985.

Abstract:
Procedures to measure the producer welfare effects of changes in an output price distribution under uncertainty are reviewed. Theory and numerical integration methods are combined to show how for any form of Marshallian risk-responsive supply, compensating variation of a change in higher moments of an output price distribution can be derived numerically. The numerical procedure enables measurement of producer welfare effects in the many circumstances in which risk and uncertainty are important elements. The practical ease and potential usefulness of the procedure is illustrated by measuring the producer welfare effects of USA rice policy.

Abstract:
Poor convergence performance of CBOT corn, soybean, and wheat futures contracts since late 2005 has been a major source of concern to market participants, regulators, and elected representatives at the state and national levels. After careful review of available evidence, it appears that recent storage rate changes for CBOT corn and soybean contracts were sufficient to address convergence problems is these two markets. The corn and soybean delivery system is functionally sound at the present time because it is located within substantial commercial flows of the commodities. Nonetheless, convergence performance for these two markets should continue to be closely monitored, particularly in light of the downward trend in corn and soybean shipments on the Illinois River. Recent and upcoming storage rate changes for CBOT wheat contracts are also expected to help improve performance of this contract. However, a major change in delivery terms is needed in order to address the underlying structural problems in the CBOT wheat contract. The underlying issue is that historic delivery locations are no longer in the main commercial flow of wheat. Recently approved additions to the delivery locations for wheat are unlikely to address the structural problem because new locations are viewed as “safety-valve” areas that will be used for delivery only when market conditions are unusual.

corn, soybeans, wheat, CBOT, delivery, convergence

Abstract:
Using a flexible method, we develop the term structure of volatility implied by corn futures options with differing maturities, and evaluate its ability to predict subsequent realized price volatility. The implied forward volatilities anticipate realized volatility well. For the nearby interval, the implied forward volatilities provide unbiased forecasts, and are superior to forecasts based on historical volatilities. For more distant intervals, early-year options predict the direction and magnitude of future volatility changes about as well as a three-year moving average and better than a naïve forecast. However, later-year options display less forecast power in part due to reduced trading activity.

Abstract:
We investigate factors that drive derivative usage in small and medium-sized enterprises (SMEs). The influence of these factors on hedging behavior cannot a priori be assumed equal for all SMEs. To address this heterogeneity, a generalized mixture regression model is used which classifies firms into segments, so that the hedging response to the determinants of derivative usage is the same within each segment. Using a unique data set of 415 SMEs, containing both accounting and experimental data, we find that factors like risk exposure, risk perception, risk attitude, and the decision-making unit, among others are useful in explaining hedging behavior. However, the effects of these factors are not homogeneous across all managers, and the roots of the heterogeneity can partially be traced to differences in attitudes, perceptions, and to differences in ownership structure.

Derivatives Usage, Hedging Behavior, Unobserved Heterogeneity

Abstract:
The informational value of USDA corn and soybean production forecasts is investigated for the period 1971-1992. Three tests of informational content are considered: i) a relative forecast accuracy test, ii) a price reaction test, and iii) a willingness-to-pay test. Overall, the results suggest USDA corn and soybean forecasts provide valuable information to commodity markets. This value, however, does appear to have declined, especially since the mid-1980s. This is consistent with large declines in the cost of information due to technological improvements in computers, communications equipment, remote-sensing satellites, etc.

Abstract:
Using settlement prices and 9 years of daily commitments for large reporting traders in the frozen pork bellies futures market, we find that these traders generate significant profits and the distribution of trader returns over time is not random. Further analysis finds that a subset of large elite traders possesses significant forecasting ability, indicating that they not only are able to consistently anticipate the direction of price changes but are also on the right side of the market when large price changes occur. Hence, certain futures market traders accumulate trading experience and knowledge, permitting them to accrue considerable wealth.

Abstract:
This paper focuses on the HFCS-55 industry and pricing practices, and the principal factors causing the demise of the HFCS-55 futures contract, which traded on the Minneapolis Grain Exchange between April 1987 and December 1988. Consideration is given to factors that promote and inhibit the success of a futures contract. Results from a survey of producers and commercial users of HFCS-55 are presented, and cash and futures market data are analyzed. Results suggest that if a contract is not well designed, or if there is little commercial demand for it, these failings will be quickly revealed in the futures market.

Abstract:
The study investigates price relationships and linkages among different markets using daily futures prices of corn, live hogs, crude oil, Treasury bills, and deutsche marks with two alternative time series techniques. Results suggest that price linkages consistent over time are extremely limited.

Abstract:
Basis behavior can have a direct affect on hedging and pricing decisions. Here, ex ante basis risk for selected live hog cash markets is analyzed from 1985 through 1994. One and five month ahead econometric, time series, and naive forecasts are used to construct measures of basis risk based on mean squared forecast errors and market timing ability. The findings suggest that basis risk has not increased nor has basis predictability declined relative to historical levels. The recent decline in demand for futures contracts is likely attributable to other structural changes in the industry.

Abstract:
This paper is concerned with estimation of optimal hedge ratios. Many researchers have demonstrated the inadequancies of the ordinary least squares (OLS) method that gives constant hedge ratio and suggested the use of bivariate autoregressive conditional heteroskedastic (BGARCH) model. We introduce the use of a random coefficient autoregressive (RCAR) model to estimate time varying hedge ratios. Using daily data of spot and future prices of corn and soybeans we find substantial presence of both ARCH and random coefficient effects. Hedging performance in terms of variance reduction of returns from alternative models have also been conducted.

Abstract:
This paper deals with the estimation of optimal hedge ratios. A number of recent papers have demonstrated that ordinary least squares (OLS) method which gives constant hedge ratio is inappropriate and recommended the use of bivariate autoregressive conditional heteroskedastic (BGARCH) model. In this paper we introduce the use of a random coefficient autoregressive (RCAR) model to estimate time varying hedge ratios. Using daily data of spot and futures prices of corn and soybeans we find substantial presence of conditional heteroskedasticity, and also of random coefficients in the regression of return from the spot market on the return from the futures markets. Hedging performance in terms of variance reduction of returns from alternative models are also conducted. For our data set diagonal vech presentation of BGARCH model provides the largest reduction in the variance of the return portfolio.