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THE WAGE RATE AND COMMUTING PATTERNS IN A RURAL MANUFACTURING LABOR FORCE Roger W. White* Among economists, it is virtually a truism that the supply of labor available to a firm depends on the wage rate. Among geographers, the subject has been largely ignored. Yet it is not unreasonable to suppose that the wage rate influences not only the number of people who are willing, ceteris paribus, to take a certain job, but that it also affects the number who are willing to travel the necessary distance to reach the place of employment. This is the geographic component of the labor supply problem. Peterson (1) in a study of an Iowa commuting pattern proposed that indifference curve analysis be borrowed from economic theory to explain the relationship between wage level and commuting distance; unfortunately , he failed to develop the subject in adequate detail. Furthermore , his empirical findings were inconclusive with respect to the link between wages and distance travelled. Lonsdale (2), however, in a study of commuting to two plants in eastern North Carolina, showed that the wage level is important in determining the area of the laborshed of a plant. Furthermore, he demonstrated that a gravity formula can be used with some success to describe the plant's laborshed. The present study is essentially an attempt to generalize Lonsdale's results. It is based on the assumption that the spatial distribution of a factory workforce can be described by a commuting equation of the form (1)c,=k Pi (In1)U(S1)1 where P1=population of township i ITi1=a measure of alternate employment opportunities at i, S1= distance from the plant to i, and C1=number of commuters from township i u,v,k = constants Whereas for a given plant, the parameters u and ? are constants, it is to be expected that they will vary from plant to plant, just as k varies according to the size of the plant. In particular, it is the thesis of the present paper that the exponent, v, on distance is a function of the wage rate. ?Mr. White is instructor of geography at the University of Western Ontario, London. The paper was accepted for publication in March 1972. Vol. XII, No. 1 35 The approach is essentially exploratory. Data were gathered from eleven plants in eastern North Carolina for the purpose of specifying, by means of multiple regression analysis, the values of the parameters in equation (1) appropriate to each of the plants. The resulting eleven estimates of the distance exponents are then compared to the wage rates in the eleven plants, to the accompaniment of speculation concerning the nature of the relationship suggested by the data. The study area, eastern North Carolina, is atypical as a manufacturing region (Figure 1). Both population and industry are largely rural. Manufacturing plants are located either in small towns or, especially in the case of the newer ones, in the open countryside, and the typical employee lives in a rural area and commutes. Industry is largely labor intensive, requiring large numbers of essentially unskilled employees willing to work for moderate wages. Very few plants in the area have specialized labor requirements, so questions as to what constitutes the labor supply are relatively simple: the labor market is not fragmented into a number of separate categories depending on skill level, traditional occupation, or industrial category. As a result, the area is an ideal setting in which to study the effect of the wage rate on commuting behavior without having to deal with a plethora of complicating factors. CONTROL FOR EXTRANEOUS VARIABLES. Clearly, however, there are a certain number of factors other than the wage rate and economic opportunity which may systematically affect commuting behavior as represented by the distance exponent, and these must be taken into account in examining the relationship between the wage rate and the exponent. The most important of these factors are the following: (1)General cultural characteristics: there are a variety of cultural characteristics of the population, such as attitude toward travel, income and educational levels, race, and age structure, which may affect commuting behavior; (2)Density of population: the friction of distance is possibly greater in densely populated areas...

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