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Legislation and regulation have been effective in reducing the gender wage gap in developed countries; however, the gap still exists globally, and progress towards narrowing the gap has been unacceptably slow even in regions where it is improving. This study presents the analysis of gender wage gap in Kenya’s urban labor market by using the World Bank Skills Towards Employability and Productivity Survey (WBSTEPS). This study employed Mincer earnings regressions with Heckman selection correction and the Blinder-Oaxaca and Neumark decomposition procedures to answer the research questions. The results of the wage determination and participation in the labor market show that there is no selectivity-bias problem. Personal characteristics such as education and age, as well as work-related characteristics, are important factors in determining earnings. The magnitude of the gender wage gap varies across the wage distribution, and the results of the wage decomposition reveal that women in urban Kenya earn 84.5-to-86% of men’s earnings. The earnings gap is overwhelmingly due to differences in returns to endowments, which account for between 70% and 94.7% of the total earnings gap. Admittedly, the study found evidence of discrimination against women in the returns to endowments, but also observed pronounced favoritism towards men. However, discrimination against women is more pronounced than favoritism towards men. Addressing the gender wage gap in Kenya requires a multifaceted approach that tackles both systemic biases against women and structural barriers that hinder women from accessing equal opportunities in education, training, and career advancement and government policies that minimize favoritism towards men.

We synthesize two related literatures on firm-level drivers of wage inequality. Studies of rent sharing that use matched worker-firm data find elasticities of wages with respect to value added per worker in the range of 0.05–0.15. Studies of wage determination with worker and firm fixed effects typically find that firm-specific premiums explain 20% of overall wage variation. To interpret these findings, we develop a model of wage setting in which workers have idiosyncratic tastes for different workplaces. Simple versions of this model can rationalize standard fixed effects specifications and also match the typical rent-sharing elasticities in the literature.

We propose leave-out estimators of quadratic forms designed for the study of linear models with unrestricted heteroscedasticity. Applications include analysis of variance and tests of linear restrictions in models with many regressors. An approximation algorithm is provided that enables accurate computation of the estimator in very large data sets. We study the large sample properties of our estimator allowing the number of regressors to grow in proportion to the number of observations. Consistency is established in a variety of settings where plug-in methods and estimators predicated on homoscedasticity exhibit first-order biases. For quadratic forms of increasing rank, the limiting distribution can be represented by a linear combination of normal and non-central χ² random variables, with normality ensuing under strong identification. Standard error estimators are proposed that enable tests of linear restrictions and the construction of uniformly valid confidence intervals for quadratic forms of interest. We find in Italian social security records that leave-out estimates of a variance decomposition in a two-way fixed effects model of wage determination yield substantially different conclusions regarding the relative contribution of workers, firms, and worker-firm sorting to wage inequality than conventional methods. Monte Carlo exercises corroborate the accuracy of our asymptotic approximations, with clear evidence of non-normality emerging when worker mobility between blocks of firms is limited.

When jobs offered by different employers are not perfect substitutes, employers gain wage-setting power; the extent of this power can be captured by the elasticity of labor supply to the firm. The authors collect 1,320 estimates of this parameter from 53 studies. Findings show a prominent discrepancy between estimates of direct elasticity of labor supply to changes in wage (smaller) and the estimates converted from inverse elasticities (larger), suggesting that labor market institutions may rein in a substantial amount of firm wage-setting power. This gap remains after they control for 22 additional variables and use Bayesian Model Averaging and LASSO to address model uncertainty; however, it is less pronounced for studies employing an identification strategy. Furthermore, the authors find strong evidence that implies the literature on direct estimates is prone to selective reporting: Negative estimates of the elasticity of labor supply to the firm tend to be discarded, leading to upward bias in the mean reported estimate. Additionally, they point out several socioeconomic factors that seem to affect the degree of monopsony power.

One explanation advanced for the persistent gender pay differences in labor markets is that women avoid salary negotiations. By using a natural field experiment that randomizes nearly 2,500 job seekers into jobs that vary important details of the labor contract, we are able to observe both the extent of salary negotiations and the nature of sorting. We find that when there is no explicit statement that wages are negotiable, men are more likely to negotiate for a higher wage, whereas women are more likely to signal their willingness to work for a lower wage. However, when we explicitly mention the possibility that wages are negotiable, these differences disappear completely. In terms of sorting, we find that men, in contrast to women, prefer job environments where the “rules of wage determination” are ambiguous. This leads to the gender gap being much more pronounced in jobs that leave negotiation of wage ambiguous. This paper was accepted by Gérard P. Cachon, behavioral economics.

This paper asks whether pay disclosure in the public sector changes wage setting at the top of the distribution. I examine a 2010 California mandate that required municipal salaries to be posted online. Among top managers, disclosure led to approximately 7 percent average compensation declines, and a 75 percent increase in their quit rate, relative to managers in cities that had already disclosed salaries. The wage cuts were largely nominal. Wage cuts were larger in cities with higher initial compensation, but not in cities where compensation was initially out of line with (measured) fundamentals. The response is more consistent with public aversion to high compensation than the effects of increased accountability.

We show that deterioration in household balance sheets, or the housing net worth channel, played a significant role in the sharp decline in U.S. employment between 2007 and 2009. Counties with a larger decline in housing net worth experience a larger decline in non-tradable employment. This result is not driven by industry-specific supplyside shocks, exposure to the construction sector, policy-induced business uncertainty, or contemporaneous credit supply tightening. We find little evidence of labor market adjustment in response to the housing net worth shock. There is no significant expansion of the tradable sector in counties with the largest decline in housing net worth. Further, there is little evidence of wage adjustment within or emigration out of the hardest hit counties.

This article brings a new perspective to the analysis of the wage effects of the Mariel boatlift crisis, in which an estimated 125,000 Cuban refugees migrated to Florida between April and October, 1980. The author revisits the question of wage impacts from such a supply shock, drawing on the cumulative insights of research on the economic impact of immigration. That literature shows that the wage impact must be measured by carefully matching the skills of the immigrants with those of the incumbent workforce. Given that at least 60% of the Marielitos were high school dropouts, this article specifically examines the wage impact for this low-skill group. This analysis overturns the prior finding that the Mariel boatlift did not affect Miami’s wage structure. The wage of high school dropouts in Miami dropped dramatically, by 10 to 30%, suggesting an elasticity of wages with respect to the number of workers between −0.5 and −1.5.

This study examines the influence of occupational licensing on two significant occupations that provide similar health care services: occupational therapists and physical therapists. Since many of the tasks that these occupations overlap, individuals in both occupations can have legal jurisdiction over these tasks. We examine how these two occupations interact with one another in the labor market on wage determination and employment. Unlike previous analyses of occupational licensing, our study evaluates two professions that are female dominated both within the vocations, and among its leadership. Our results show that the ability of physical therapists to have direct access to patients is associated with a reduction in hourly earnings for occupational therapists, suggesting there is substitution for certain overlapping service tasks across the two occupations. The ability of these two occupations to be mainly substitutes for one another provides new evidence on how the growing numbers of regulated occupations that provide similar tasks influence one another.

Recent technological developments related to the extraction and processing of data have given rise to concerns about a reduction of privacy in the workplace. For many low-income and subordinated racial minority workforces in the United States, however, on-the-job data collection and algorithmic decisionmaking systems are having a more profound yet overlooked impact: These technologies are fundamentally altering the experience of labor and undermining economic stability and job mobility. Drawing on a multi-year, first-of-its-kind ethnographic study of organizing on-demand workers, this Article examines the historical rupture in wage calculation, coordination, and distribution arising from the logic of informational capitalism: the use of granular data to produce unpredictable, variable, and personalized hourly pay. The Article constructs a novel framework rooted in worker on-thejob experiences to understand the ascent of digitalized variable pay practices, or the importation of price discrimination from the consumer context to the labor context—what this Article identifies as algorithmic wage discrimination. Across firms, the opaque practices that constitute algorithmic wage discrimination raise fundamental questions about the changing nature of work and its regulation. What makes payment for labor in platform work fair? How does algorithmic wage discrimination affect the experience of work? And how should the law intervene in this moment of rupture? Algorithmic wage discrimination runs afoul of both longstanding precedent on fairness in wage setting and the spirit of equal pay for equal work laws. For workers, these practices produce unsettling moral expectations about work and remuneration. The Article proposes a nonwaivable restriction on these practices.