Using data from the New Immigrant Survey 2003, this article shows that skin color and height affect wages among new lawful immigrants to the United States, controlling for education, English language proficiency, occupation in source country, family background, ethnicity, race, and country of birth. Immigrants with the lightest skin color earn on average 17% more than comparable immigrants with the darkest skin color. Taller immigrants have higher wages, but weight does not affect wages. Controls for extensive current labor market characteristics that may be influenced by discrimination do not eliminate the negative effect of darker skin color on wages.

Using a new data set, this paper gives evidence in support of the intuitive notion that overqualified workers are less satisfied with their jobs and are more likely to quit. However, training time is inversely related to overqualification, which suggests why such seeming mismatches occur and may in fact be optimal.

Workplace sexual harassment is illegal, but many workers report that they have been sexually harassed. Exposure to the risk of sexual harassment may decrease productivity, which would reduce wages. Alternatively, workers may receive a compensating differential for exposure to sexual harassment, which would increase wages. Data on claims of sexual harassment filed with the Equal Employment Opportunity Commission are used to calculate the first measures of sexual harassment risks by industry, age group, and sex. Female workers face far higher sexual harassment risks. On balance, workers receive a compensating wage differential for exposure to the risk of sexual harassment.

hourly wage, and employment status using the NSBA and the MCSUI. Lighter skin tone is clearly associated with higher employment rates for women and higher educational attainment for both women and men. The employment rate for women with very dark skin tone in the NSBA is strikingly lower than for women with lighter skin tone. In contrast, evidence that skin tone affects wages is limited. For both sexes, in both datasets, those in the light category have the highest average hourly wage, but this value is significantly different from those with darker skin only for men in the NSBA. Furthermore, the pattern for women based on the MCSUI does not show an increasing wage from darker to lighter skin tone, but instead shows that women in the medium-skin-tone category have the lowest average wage.

Using a large data set, the authors find that smokers select riskier jobs, but receive lower total wage compensation for risk than do nonsmokers. This finding is inconsistent with conventional models of compensating differentials. The authors develop a model in which worker risk preferences and job safety performance lead to smokers facing a flatter market offer curve than nonsmokers. The empirical results support the theoretical model. Smokers are injured more often controlling for their job's objective risk and are paid less for these risks of injury. Smokers and nonsmokers, in effect, are segmented labor market groups with different preferences and different market offer curves.

While the popular press may have declared housework passe with the advent of the two-income household (see Housework is Obsolescent by Barbara Ehrenreich [1993] for one such example), the facts indicate that housework continues to consume a substantial amount of time, particularly for women. While estimates vary widely depending on the sample examined and the methods used to generate the information, representative values of housework time range around 6-14 hours per week for men and 20-30 hours for women. Since wages are likely to be influenced both directly and indirectly by the time and effort devoted to other activities, and since gender differences in household responsibilities are significant and often assumed to be a driving force behind gender earnings differentials, decisions regarding the overall amount of time spent on housework and the division of that time within the household are important ones. The goal of this paper is to shed some light on these allocation decisions. We begin by discussing the various methods by which time and effort spent on housework may affect wages and summarize the available empirical evidence. Overall, the empirical evidence indicates that time spent on housework has a negative effect on wages, an effect which is most pronounced for women. We next examine the amount of time spent on housework and the division of that time between working spouses. To do so, we draw upon the human-capital literature and the bargaining literature to construct simple regression equations for time spent on housework by each spouse as well as the share of housework time contributed by the husband. The results indicate that husbands do less housework than their wives as their relative earnings and hours spent in the labor market increase.