Wage inequality has been the topic of much recent empirical research. Similarly, inequality in the distribution of fringe benefits has also been studied. (1) On the whole, the vast majority of research on inequality has examined wages and fringe benefits separately, even though the cross-sectional relationship between the two has been emphasized and analyzed in terms of the theory of equalizing differences. Rosen (1986) states, "The equalizing difference model is built upon the simple and intuitively compelling idea that it is the combination of wages and job attributes that constitute the relevant 'price' of labor for market analysis of jobs." Thus, inequality analysis based on either wages or fringe benefits alone can overlook the interaction between them and be misleading.
Given equal productivity, workers would trade fringe benefits for higher wages and vice versa. However, across different levels of productivity, skilled workers will demand more fringe benefits simply because the benefits are normal goods. Moreover, fringe benefits, unlike wages, are not taxed, and skilled workers who face higher marginal tax rates are likely to demand more fringe benefits. Overtime, one can expect the discrepancy between wages and compensation to grow, because wages represent a smaller fraction of compensation. (2)
A few studies show potential biases in measured inequality when wages are used instead of compensation. (3) However, the inequality of fringe benefits at the level of the individual workers can be analyzed by focusing on the coverage rate of health insurance and pensions without knowing the monetary value of them due to data availability. (4) Moreover, even though compensation inequality can be analyzed when the monetary values of fringe benefits are available, it can be analyzed only at the level of the industry or job, not at the level of the individual worker.
This research is different in that it uses individual-level data with imputed monetary values for fringe benefits to analyze inequality in the labor market at a point in time and its growth over time. Deeper investigation has been conducted within the distribution to ascertain how each group is affected when fringe benefits are accounted for. Several alternative explanations of the observed discrepancies between wage inequality and compensation inequality are further assessed.
The remainder of this article is organized as follows. Section II describes in detail the data used in this study. Section III supplies the empirical results, possible explanations for which are explored in section IV. Section V provides a conclusion.
The lack of suitable data has precluded analysis of compensation inequality despite widespread interest in the topic. Until now, no data set has contained information on both the demographic characteristics of workers and the monetary value of fringe benefits. However, such a data set has been created by merging individual-level data from the Current Population Survey (CPS) and industry-level data from the Chamber of Commerce's Employee Benefits Survey (BBS).
The March supplement of the CPS for 1988 to 1995 supplies information on age, gender, years of schooling, occupation of employment, industry of employment, wages, weeks worked, health insurance and pension coverage, and imputed monetary value of health insurance for the year preceding the March survey year. This annual survey is the largest source of information on fringe benefits and first included questions on health insurance and pension coverage in 1980. Although the questionnaire items regarding health insurance were changed twice (in survey years 1988 and 1995), I mitigate the problem by restricting the sample to workers ages 25 to 54, the group that the Census Bureau reports is the least likely to be affected (Gruber and Poterba, 1994) and by restricting the survey years to 1988 onward to focus on employer-provided own health insurance coverage, which is also less likely to be affected by the changes in the CPS questionnaire on health insurance coverage. …