Wage rate differentials in the fast food industry: An Atlanta labor market study

The purpose of this study is to explain the pattern of wage rates among Atlanta area fast food restaurants. The theoretical framework utilized to accomplish this looks at supply and demand conditions for each restaurant and distinguishes between compensating and non-compensating wage differentials.; In order to examine these demand and supply conditions data were collected from employees and managers of 103 Atlanta area fast food restaurants. These data are analyzed using the statistical technique of linear regression. The estimated equations represent a reduced form of the demand and supply equations. The reduced form contains variables that measure variance sources of compensating and non-compensating differentials. The dependent variable is the natural logarithm of the mean hourly wage paid by the ith restaurant. The independent variables measure factors related to both characteristics of the individual restaurant and the employees of that restaurant.; The regression results indicate that the variation in restaurant wages is statistically related to several of the independent variables. Specifically, these variables include demand side factors such as the restaurant's average weekly sales and number of fast food competitors within a three-mile radius; supply side factors such as average income of households living within a three-mile radius of the restaurant and whether or not the restaurant is within two blocks of a Marta line; and institutional factors such as the gender of the restaurant's manager and whether or not the restaurant belongs to the Burger King chain.; These results offer evidence that both compensating and non-compensating wage differentials help explain the variation in mean wages across Atlanta area restaurants. The empirical results also show that for the fast food labor market in Atlanta the wage gradient is positively sloped (i.e., wages rise with distance from the central business district). The principal reason for this is that average household income also increases with distance from the city center.