Handbook of Labor Economics 

About: Handbook of Labor Economics is an academic journal. The journal publishes majorly in the area(s): Wage & Unemployment. It has an ISSN identifier of 1573-4463. Over the lifetime, 98 publications have been published receiving 36599 citations.

The Economics and Econometrics of Active Labor Market Programs

Abstract: Policy makers view public sector-sponsored employment and training programs and other active labor market policies as tools for integrating the unemployed and economically disadvantaged into the work force. Few public sector programs have received such intensive scrutiny, and been subjected to so many different evaluation strategies. This chapter examines the impacts of active labor market policies, such as job training, job search assistance, and job subsidies, and the methods used to evaluate their effectiveness. Previous evaluations of policies in OECD countries indicate that these programs usually have at best a modest impact on participants’ labor market prospects. But at the same time, they also indicate that there is considerable heterogeneity in the impact of these programs. For some groups, a compelling case can be made that these policies generate high rates of return, while for other groups these policies have had no impact and may have been harmful. Our discussion of the methods used to evaluate these policies has more general interest. We believe that the same issues arise generally in the social sciences and are no easier to address elsewhere. As a result, a major focus of this chapter is on the methodological lessons learned from evaluating these programs. One of the most important of these lessons is that there is no inherent method of choice for conducting program evaluations. The choice between experimental and non-experimental methods or among alternative econometric estimators should be guided by the underlying economic models, the available data, and the questions being addressed. Too much emphasis has been placed on formulating alternative econometric methods for correcting for selection bias and too little given to the quality of the underlying data. Although it is expensive, obtaining better data is the only way to solve the evaluation problem in a convincing way. However, better data are not synonymous with social experiments. © 1999 Elsevier Science B.V. All rights reserved.

The causal effect of education on earnings

Abstract: This paper surveys the recent literature on the causal relationship between education and earnings. I focus on four areas of work: theoretical and econometric advances in modelling the causal effect of education in the presence of heterogeneous returns to schooling; recent studies that use institutional aspects of the education system to form instrumental variables estimates of the return to schooling; recent studies of the earnings and schooling of twins; and recent attempts to explicitly model sources of heterogeneity in the returns to education. Consistent with earlier surveys of the literature, I conclude that the average (or average marginal) return to education is not much below the estimate that emerges from a standard human capital earnings function fit by OLS. Evidence from the latest studies of identical twins suggests a small upward "ability" bias -- on the order of 10%. A consistent finding among studies using instrumental variables based on institutional changes in the education system is that the estimated returns to schooling are 20-40% above the corresponding OLS estimates. Part of the explanation for this finding may be that marginal returns to schooling for certain subgroups -- particularly relatively disadvantaged groups with low education outcomes -- are higher than the average marginal returns to education in the population as a whole.

Changes in the Wage Structure and Earnings Inequality

Abstract: This chapter presents a framework for understanding changes in the wage structure and overall earnings inequality. The framework emphasizes the role of supply and demand factors and the interaction of market forces and labor market institutions. Recent changes in the US wage structure are analyzed in detail to highlight crucial measurement issues that arise in studying wage structure changes and to illustrate the operation of the supply-demand-institution framework. The roles of skill-biased technological change, globalization forces, changes in demographics and relative skill supplies, industry labor rents, unions, and the minimum wage in the evolution of the US wage structure are examined. Recent wage structure changes are placed in a longer-term historical perspective, and differences and similarities in wage structure changes among OECD nations are assessed. © 1999 Elsevier Science B.V. All rights reserved.

Skills, Tasks and Technologies: Implications for Employment and Earnings

Abstract: A central organizing framework of the voluminous recent literature studying changes in the returns to skills and the evolution of earnings inequality is what we refer to as the canonical model, which elegantly and powerfully operationalizes the supply and demand for skills by assuming two distinct skill groups that perform two different and imperfectly substitutable tasks or produce two imperfectly substitutable goods. Technology is assumed to take a factor-augmenting form, which, by complementing either high or low skill workers, can generate skill biased demand shifts. In this paper, we argue that despite its notable successes, the canonical model is largely silent on a number of central empirical developments of the last three decades, including: ( 1 ) significant declines in real wages of low skill workers, particularly low skill males; ( 2 ) non-monotone changes in wages at different parts of the earnings distribution during different decades; ( 3 ) broad-based increases in employment in high skill and low skill occupations relative to middle skilled occupations (i.e., job “polarization’’); ( 4 ) rapid diffusion of new technologies that directly substitute capital for labor in tasks previously performed by moderately skilled workers; and ( 5 ) expanding offshoring in opportunities, enabled by technology, which allow foreign labor to substitute for domestic workers specific tasks. Motivated by these patterns, we argue that it is valuable to consider a richer framework for analyzing how recent changes in the earnings and employment distribution in the United States and other advanced economies are shaped by the interactions among worker skills, job tasks, evolving technologies, and shifting trading opportunities. We propose a tractable task-based model in which the assignment of skills to tasks is endogenous and technical change may involve the substitution of machines for certain tasks previously performed by labor. We further consider how the evolution of technology in this task-based setting may be endogenized. We show how such a framework can be used to interpret several central recent trends, and we also suggest further directions for empirical exploration.

Empirical Strategies in Labor Economics

Abstract: This chapter provides an overview of the methodological and practical issues that arise when estimating causal relationships that are of interest to labor economists. The subject matter includes identification, data collection, and measurement problems. Four identification strategies are discussed, and five empirical examples – the effects of schooling, unions, immigration, military service, and class size – illustrate the methodological points. In discussing each example, we adopt an experimentalist perspective that emphasizes the distinction between variables that have causal effects, control variables, and outcome variables. The chapter also discusses secondary datasets, primary data collection strategies, and administrative data. The section on measurement issues focuses on recent empirical examples, presents a summary of empirical findings on the reliability of key labor market data, and briefly reviews the role of survey sampling weights and the allocation of missing values in empirical research. © 1999 Elsevier Science B.V. All rights reserved.