No abstract

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.

I N THE analysis of farm financial data it is a common practice to evaluate the level of management on the individual farmas a residual earning expressed as management earnings, operator's labor earnings, tate earned on the investment, etc. These factors ate in a sense measures of management; but they ate not entirely satisfactory for this purpose for perhaps three main reasons: (1) they axe "after the faet" measures: they can be used only after the activity has been completed, and hence they have no prior predictire value; (~ 91 they ate not reliable as measures of management beeause they also refleet windfall profits and losses entirely apart from management. Likewise, they ate not corrected, in the usual methods of calculation for eaxnings which result from varying degrees of exploitation of both human and physical resources; (3) and, finally, they measure a residual output rather than management as an input factor. It is quite conceivable that varying proportions of land, labor and capital associated with the same level of management will yield varying residual returns as measured by the factors mentioned.So we ate interested in finding a measure for the management factor per se, and such a measure as will admit, ir possible, of predicting the leve] of management prior to the completion of the activity in question. Our problem then is a special segment of the more general problem of predicting human behavior.Prediction research in human behavior coneerns itself with two general problems: (1) finding a suitable criterion of measure of success in the activity, and (~ 91 ~inding those situational and personal factors which ate related to success, of ate indices of factors which ate related to suceess in the aetivity. Given the criterion and the predictive factors, appropriate statistical techniques can be applied to measure the degree of relationship and provide a quantitative basis for making predictions.Predictions ate usually based upon the degree of relationship between the criterion and one of more of three main types of predictire factors: (1) previous performance, (~) proficiency tests, and (3) personal eharacteristics. The first one requires that the individual be engaged in of have had previous experience in the activity.

No abstract

No abstract