Year
1993
The objectives of this study were to: (a) quantify differences in liquidity costs between Kansas City and Chicago wheat futures contracts, and (b) identify the factors which influence liquidity in these two markets. Regression results suggest that there are significant differences in liquidity costs between Chicago and Kansas City which are in part due to the lower trading volume at Kansas City. However, there appears to be a significantly higher cost of doing business at Kansas City which is independent of trading volume. The implications of these findings to traders is that transacting is more expensive in Kansas City than in Chicago.
In the spirit of Leamer’s commitment to sensitivity analysis, we employ Farrell’s nonparametric efficiency methodology and compare our results with those of Sexton, Wilson, and Wann. Testing the implicit assumption of technical efficiency in the methodology employed by Sexton, Wilson, and Wann, we find that the lack of technical efficiency is the cotton gins’ main cause of overall inefficiency. We extend the nonparametric methodology by subjecting the shadow prices of technical efficiency to nonparametric statistical tests to draw stronger conclusions. In addition, the nonparametric methodology permits us to make gin-specific recommendations to improve the performance of the gins.
This article presents a mathematical programming model of wheat cleaning and blending decisions at a country elevator. Simulations are performed to illustrate the sensitivity of cleaning to selected variables, including the value of screenings, transportation costs, and market discounts for excess dockage. In addition, the model is used to assess the impact of including dockage in the grade standards for wheat.
The ultimate loss financial institutions bear for foreclosed loans is determined by their success in liquidating their acquired property portfolios. This study examines the price received for land sold by private individuals and financial institutions from 1977 through 1990. After adjusting for quality differences, financial institutions received on average 9.2% less than private individuals. Further analysis reveals that commercial banks received a discount of 5.8%, the Farm Credit System (FCS) a 9.2% discount, and Farmers Home Administration (FmHA) a 14.7% discount. For this sample of 13,375 Kansas sales, it is estimated that the sum of the transfers from financial institutions to land buyers amounted to $9.2 million.
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The risk premium and the probability premium are used to determine appropriate coefficients of absolute risk aversion under CARA utility. A defensible range of risk aversion coefficients is defined by the coefficients that correspond to risk premiums falling between 1 and 99% of the amount at risk or to probability premiums falling between .005 and .49 for a lottery that pays or loses a given sum. The consequences of ignoring risk premiums when selecting risk-aversion coefficients for representative decision makers are illustrated by calculation of the implied risk premium associated with the levels of absolute risk aversion assumed in six selected studies.
A nonparametric analysis of technical, allocative, scale, and scope efficiency of agricultural production is presented based on a sample of Wisconsin farmers. The results indicate the existence of important economies of scale on very small farms, and of some diseconomies of scale for the larger farms. Also, it is found that most farms exhibit substantial economies of scope, but that such economies tend to decline sharply with the size of the enterprises. Finally, the empirical evidence suggests significant linkages between the financial structure of the farms and their economic efficiency.
Taking the price of futures as a proxy for expected price, this article treats acreage planted to soybean, the price of futures, and other variables as jointly dependent. A futures price equation is embedded in a simultaneous equations model along with the consumption demand and acreage response. The model is estimated using both ordinary and three-stage least squares. Estimated price elasticities for consumption demand, demand for stocks, and acreage response equal, respectively, -.5, -1.8, and +.2 (short run) and +.59 (long run).