Robert M. Finley

Statistical Analysis of Identities in Random Variables

A random variable of economic interest is sometimes an identity function of two or more separate variables; for example, crop income per acre is the product of price and yield. This article presents a method for partitioning the variance of such a random variable into components that can be associated with the separate random variables in the identity and interactions among them. Under some statistical assumptions on the variables involved, the converse of the partitioning procedure is useful for deriving the variance of a random variable from the moments of the separate variables of the identity.

Gordon, Wendell. Economics from an Institutional Viewpoint. Austin: University Stores, 1973, ix + 389 pp.,

Two errors in manuscript preparation have raised questions about the interpretaton of equations (4) and (8). In equation (4), Xjd(t) is the exponentially lagged value of the rate of change of the output of the jth sector and not the value of the output of the jth sector (pp. 523–24). In equation (8), C(t), I(t), and E(t) are vectors of domestic consumption, capital good demands, and exports, respectively, not the total values defined on p. 524.

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Many studies have concentrated on the optimal location of cattle feeding. Two major limitations of such studies have been (1) reliance on a single demand function for beef and (2) failure to consider existing slaughter capacities. By utilizing separated or split-demand functions for beef and explicitly accounting for present regional slaughter capacity, quite different patterns of beef feeding emerge. In comparison with actual feedlot locations, the models used showed considerable improvement over most previous models. More importantly, results compare favorably with recent trends in the location of cattle feeding.

Effects of Split-Demand and Slaughter-Capacity Assumptionson Optimal Locations of Cattle Feeding

The applied economic literature abounds with reports on the estimation of parameters of consumer demand functions. Early attempts were hindered by an inadequate understanding of the theory and inappropriate statistical methods. In following the developments both from the point of view of the evolution of methods and the applied results the patterns are rather clear. Until rather recently demand parameters were estimated by single equation least squares methods. However, as the theory and econometric methods developed, it became clear that these early results were only under special circumstances correct. That is, it became clear that specific demand equations should be estimated within the complete systems explaining market prices and quantities. This observation spawned a number of empirical studies incorporating simultaneous equations methods in estimating systems of demand functions. Results obtained by this more general approach were again however of rather limited generality. The limitations in this case were due to the ad hockery involved in specifying the systems. More specifically, since demand equations contain all

FURTHER EVIDENCE ON THE STRUCTURE OF CONSUMER DEMAND IN THE U. S.: AN APPLICATION OF THE SEPARABILITY HYPOTHESIS*

Farm record classification criteria vary greatly among states. Taking a given set of records and applying the various typing criteria gave widely divergent groupings. Hence, comparison of results based on varying criteria will likely be misleading. However, dairy farms can be classified consistently with any of the methods considered.

Farm Type Classification Systems: Another Look at an Old Problem

REVIOUS STUDIES pertaining to size of operation have claimed that significant cost savings are associated with size in beef cattle feeding [6, 8, 10, 11, 12, 17]. However, these studies considered only the physical factors associated with the production and marketing of beef, completely ignoring managerial ability and its probable effect on size of operation. Real or imaginary, the internal and external cost-savings factors associated with size have been considered the incentive for the increase in size of feedlots [16]. Other studies have indicated that willingness to assume risk and uncertainty and possession of scientific and economic know-how characterize the managers of large-size feeding operations [4, 5, 13]. These studies suggest that a large-size feedlot is not necessarily only a product of internal and external factors associated with size but that it is also affected by the socioeconomic characteristics of the managerial input. The dilemma faced by economists studying economies of scale may involve violation of the ceteris paribus conditions; the analysis fails to hold everything except for scale constant. If the socioeconomic characteristics of management are related to size of operation, the phenomenon that some studies identified as economies of scale may not be true economies of scale but simply a reflection of the superior managerial capabilities of the large-size operator. However, the extent to which the managers socioeconomic characteristics are related to size -that is, the extent to which ceteris paribus conditions are violated-has not been quantified or empirically tested. In this paper indices are developed to measure the socioeconomic characteristics of feed-