nep-hrm New Economics Papers
on Human Capital and Human Resource Management
Issue of 2018‒01‒15
four papers chosen by
Patrick Kampkötter
Eberhard Karls Universität Tübingen

  1. Productivity and Pay: Is the link broken? By Anna M. Stansbury; Lawrence H. Summers
  2. Parenthood, Family Friendly Firms, and the Gender Gaps in Early Work Careers By V. Joseph Hotz; Per Johansson; Arizo Karimi
  3. Human Capital, Signaling, and Employer Learning. What Ingsights Do We Gain from Regression Discontinuity Designs By Georg Graetz
  4. Real Wages and Hours in the Great Recession: Evidence from Firms and their Entry-Level Jobs By Daniel Schaefer; Carl Singleton

  1. By: Anna M. Stansbury; Lawrence H. Summers
    Abstract: Since 1973 median compensation has diverged starkly from average labor productivity. Since 2000, average compensation has also begun to diverge from labor productivity. These divergences lead to the question: to what extent does productivity growth translate into compensation growth for typical American workers? We investigate this, regressing median, average and production/nonsupervisory compensation growth on productivity growth in various specifications. We find substantial evidence of linkage between productivity and compensation: over 1973-2016, one percentage point higher productivity growth has been associated with 0.7 to 1 percentage points higher median and average compensation growth and with 0.4 to 0.7 percentage points higher production/nonsupervisory compensation growth. These results suggest that other factors orthogonal to productivity have been acting to suppress typical compensation even as productivity growth has been acting to raise it. Several theories of the cause of the productivity-compensation divergence focus on technological progress. These theories have a testable implication: periods of higher productivity growth should be associated with periods of faster productivity-pay divergence. We do not find substantial evidence of co-movement between productivity growth and the labor share or mean/median compensation ratio. This tends not to provide strong support for pure technology-based theories of the productivity-compensation divergence.
    JEL: E24 J24 J3
    Date: 2017–12
  2. By: V. Joseph Hotz; Per Johansson; Arizo Karimi
    Abstract: We consider the role that firm attributes play in accounting for the divergence in the careers of women and men, with the onset of parenthood. We exploit a matched employer-employee data set from Sweden that provides a rich set of firm and worker attributes. We index firms by their “family friendliness” and analyze the effect of firm family friendliness on the career gap between mothers and fathers. We find that women disproportionately sort into family friendly firms after first birth and that the wage penalty to motherhood is diminished by being assigned to a more family friendly firm or job. We also find that working in a more family friendly firm or job diminishes the parenthood penalty to labor earnings and makes it easier for mothers to work more hours. At the same time, the smaller wage and income penalties to parents from working in family friendly firms and jobs come at the expense of their occupational progression, especially among mothers, impeding their ability to climb career ladders. Finally, we find that family friendly jobs are more easily substitutable for one another. This latter finding suggests that family friendly firms are able to accommodate the family responsibilities of their workers while still managing to keep their costs low. Our findings also suggest that paid parental leave with job protection – which are features of the Swedish context – may not be sufficient to achieve the balancing of career and family responsibilities, but that the way firms and jobs are structured can play a crucial role in facilitating this balance.
    JEL: J13 J16 J24 J31 J62
    Date: 2017–12
  3. By: Georg Graetz
    Abstract: Several recent papers employ the regression discontinuity design (RDD) to estimate the causal effect of a diploma (or similar credentials) on wages. Using a simple model of asymmetric information, I show that RDD estimates the information value of a diploma. A positive information value arises if employers, unable to observe the test score that determines diploma receipt, infer that workers with a diploma have higher average productivity than those without. Crucially, a diploma can have information value regardless of whether workers’ productivity is solely determined by acquisition of knowledge and skills through studying (the pure human capital model) or whether studying has no effect on productivity (the pure signaling model). Thus, while RDD estimates of diploma effects are evidence for information frictions and statistical discrimination, they do not help to distinguish between human capital and signaling. However, with longitudinal data, RDD can be used to estimate the speed of employer learning, since RDD coefficients are direct estimates of (differences in) expectation errors.
    Keywords: human capital, signaling, employer learning, statistical discrimination, regression discontinuity design
    JEL: C20 D80 J20
    Date: 2017
  4. By: Daniel Schaefer; Carl Singleton
    Abstract: Using employer-employee panel data, we provide novel facts on how real wages and working hours within jobs responded to the UK’s Great Recession. In contrast to previous studies, our data enables us to address the cyclical composition of jobs. We show that firms were able to respond to the Great Recession with substantial real wage cuts and by recruiting more part-time workers. A one percentage point increase in the unemployment rate led to an average decline in real hourly wages of 2.8 per cent for new hires and 2.6 per cent for job stayers. Hours of new hires in entry-level jobs were also substantially procyclical, while job-stayer hours were nearly constant. Our findings suggest that models assuming rigid labour costs of new hires are not helpful for understanding the behaviour of unemployment over the business cycle.
    Keywords: wage rigidity, Great Recession, hours worked, job-level analysis
    JEL: E24 E32 J31
    Date: 2017

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