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Study of unemployment benefit financing in the USA, with particular reference to the allocation of costs among employers through a payroll tax based on experience rating - evaluates this system by examining its success in promoting employment security, its economic implications, management attitude and participation in administrative aspects, solvency of the fund, etc. References and statistical tables.
"This dissertation consists of three essays concerning the way in which the unemployment insurance (UI) system in the United States affects the dynamics of labor markets, through the financing and the provision of unemployment benefits. The first chapter provides background on the financing of the UI system. In the U.S. unemployment benefits are financed with employer payroll taxes using experience rating methods, which consist of assigning a tax rate based on the firm's history of unemployed workers who collected unemployment benefits. This creates a cost to the firm when changing employment downward: the expected UI marginal tax cost (EMTC). However, these methods are imperfect in that not every additional separation increases UI taxes (there are minimum and maximum tax rates). I implement a novel empirical measure of the EMTC assuming firms have rational expectations. I find that, on average, firms expect to pay about 56% of the additional unemployment benefit, with the remaining subsidized. This subsidy has potential implications for the dynamics of labor markets, which I explore in subsequent chapters. The second chapter studies the effect of increasing unemployment benefits on employment under an imperfect experience rating UI system. An endogeneity problem arises because both subsidized and total unemployment benefits respond endogenously to employment shocks. Thus, I construct instruments to overcome endogeneity by interacting systematic differences across states with aggregate shocks. I find that subsidized unemployment benefits reduced employment during the Great Recession. Also, using job flows data, I show that subsidized unemployment benefits have a positive effect on job separations, consistent with the negative effect on employment, while having little effect on job creations. The last chapter studies the effect of unemployment subsidies on the composition of unemployment by UI claims. I show that unemployment subsidies increase the incidence of insured unemployment, but reduce that of uninsured unemployment. While the first result is predicted by the existing theory, the second is not. I rationalize this result by proposing a relabeling hypothesis: firms profitably split the non-negative subsidy with workers by relabeling the job separation as UI eligible. The relabeling hypothesis suggests that if the UI subsidy is high, workers receiving benefits should better resemble the characteristics of workers separating via quits. I in fact see evidence of this hypothesis in terms of the impact of the UI subsidy on unemployment duration, recall rate, and wage growth of separated workers"--Pages vi-vii.
The book collects articles published by Daniel Hamermesh between 1969 and 2013 dealing with the general topic of the demand for labor. The first section presents empirical studies of basic issues in labor demand, including the extent to which different types of labor are substitutes, how firms' and workers' investments affect labor turnover, and how costs of adjusting employment affect the dynamics of employment and patterns of labor turnover. The second section examines the impacts of various labor-market policies, including minimum wages, penalty pay for using overtime hours or hours worked on weekends or nights, severance pay for displaced workers, and payroll taxes to finance unemployment insurance benefits. The final section deals with general questions of discrimination by employers along various dimensions, including looks, gender and ethnicity, in all cases focusing on the process of discrimination and the behavior that results. Throughout the focus is on the development of theoretically-based hypotheses and testing them using the most appropriate data, often data collected uniquely for the particular project.