Regression Methods of Estimating Agricultural Income of Counties

Abstract

A WIDESPREAD need exists for personal L7 income data by minor geographic areas, which would provide necessary data for market analysis, administration of local tax burdens, etc. In an attempt to provide data for these requirements, agencies in several states have prepared estimates for counties for various years.' In the South the first comprehensive set of county estimates was published in I952 for seven southeastern states.2 Of all the components of county income developed in these studies, it has generally been considered that farm proprietors' income 3 estimates by county had the least sound basis 4 and therefore probably contained larger errors than any of the other elements in the county totals. The objectives of this study are (i) to determine the factors influencing agricultural income formation for homogeneous groups of states, and (2) to develop a method which will serve as a basis for preparing county estimates of agricultural income with the minimum error. Objective and measurable determinants of agricultural income employed in the analysis are required which are equally available for states and counties. The assumption is that the rate of agricultural income formation from basic factors at the state level for homogeneous groups of states bears either a similar, or some determinable, relation to the rate of income formation from the same factors at the county level. The concept of agricultural income in this study begins with the National Income Division's series of farm proprietors' net farm income. Wages paid hired labor and rents allocated farm landlords are added. Government payments are deducted. The concept for Virginia for I949 is illustrated below: