This dissertation is a study of the changes in the distribution of individual earnings in the United States over a twenty-year period from 1967 to 1986 with a focus upon the relationship between the changing industrial structure and earnings inequality. In the first Chapter, using micro-data from the Current Population Survey (CPS) from 1967 to 1986, I examine the sensitivity of the conclusions regarding time-series changes in inequality among individuals in the United States to (1) the measure of inequality employed; (2) the definition of labor income utilized; and (3) the population group analyzed. I find that conclusions about changes in inequality over time are sensitive to the measure of inequality employed. Despite the heterogeneity among inequality measures, I find a general pattern of stable or decreasing inequality throughout the 1970's followed by a period of increasing inequality beginning in the late 1970's. Based upon a decomposition analysis, I conclude that these changes are not simply the result of the changing employment distribution among groups defined by sex, age or industry. Instead, the trend towards greater inequality results from an increase in inequality within sex, age and industry groups.

In the second Chapter, I explore models of the distribution of earnings when there is heterogenity among individuals and among jobs. Initially, I consider a one-sector model where individuals differ according to their productive ability. This model is expanded to two sectors. In the two sector model, I consider the comparative static effect upon the distribution of earnings of a change in employment from one sector to another. I show that, due to the non-random assignment of workers to jobs, sectoral shifts result in changes in inequality within sectors and in aggregate.

The inter- and intra-industry wage structure is the subject of the third Chapter. Using data from the CPS, I construct a twenty year panel data set for thirty-three goods-producing and series-producing industries. A model explaining average industry wages and industry wage dispersion is estimated using an errors-in-variables estimation procedure. I find significant industry wage differentials and earnings dispersion differentials even after controlling for human capital and demographic variables. The pattern of year fixed effects in the earnings dispersion equation exhibits a U-shaped pattern with inequality increasing in the 1980's.