nep-lma New Economics Papers
on Labor Markets - Supply, Demand, and Wages
Issue of 2022‒07‒11
fourteen papers chosen by
Joseph Marchand
University of Alberta

  1. The Use of Online Job Sites for Measuring Skills and Labour Market Trends: A Review By Oleksii Romanko; Mary O'Mahony
  2. Individual Earnings and Family Income: Dynamics and Distribution By Joseph G. Altonji; Disa M. Hynsjö; Ivan Vidangos
  3. Job Satisfaction, Structure of Working Environment and Firm Size By Aysit Tansel; Saziye Gazioglu
  4. Patterns of Time Use Among Older People By Maddalena Ferranna; JP Sevilla; Leo Zucker; David E. Bloom
  5. Skill Heterogeneity and Aggregate Labor Market Dynamics By John R. Grigsby
  6. The Effects of Advanced Degrees on the Wage Rates, Hours, Earnings and Job Satisfaction of Women and Men By Joseph G. Altonji; John Eric Humphries; Ling Zhong
  7. Workplace Skills as Regional Capabilities: Relatedness, Complexity and Industrial Diversification of Regions By Duygu Buyukyazici; Leonardo Mazzoni; Massimo Riccaboni; Francesco Serti
  8. Grads on the Go: Measuring College-Specific Labor Markets for Graduates By Johnathan G. Conzelmann; Steven W. Hemelt; Brad Hershbein; Shawn M. Martin; Andrew Simon; Kevin M. Stange
  9. A New Approach to Building a Skills Taxonomy By Elizabeth Gallagher; India Kerle; Cath Sleeman; George Richardson
  10. The Labor Market Consequences of Appropriate Technology By de Souza, Gustavo
  11. Down the Rabbit Hole: Habit-formation in Internet Use among Unemployed Workers By Potter, Tristan
  12. Corporate training and skill gaps: Did Covid-19 stem EU convergence in training investments? By Pouliakas, Konstantinos; Wruuck, Patricia
  13. Foreign Ownership and Robot Adoption By Fabrizio Leone
  14. Industrial Robots, and Information and Communication Technology: The Employment Effects in EU Labour Markets By Stefan Jestl

  1. By: Oleksii Romanko; Mary O'Mahony
    Abstract: We explore the use of online job postings as an innovative complementary source of labour demand statistics. The paper concentrates on new developments in the area, including the usage and validation of online data sources, trends, biases and caveats of the data generation and data extraction process. We provide detailed explanations of the data cleansing and data preparation process which proves to be useful for anyone working with raw online data sources. We explore the general data pipeline underpinning continuous data mining and data utilization, that could be beneficial for any organization building its own online data analysis process. We provide detailed discussions of the design of the skills extraction process using word2vec model. We discuss the application of the model and explore some of the skills analysis methods and visualizations, such as job titles, salaries, frequent skills histograms, skills correlation scatterplots, graph analysis of skills co-occurrence, UK regional skills analysis. We applied regression analysis, outlining various effects of person competencies on the salary. We conclude that online job postings provide rich and extensive insights into the labour market and can complement the official statistics.
    Keywords: labour demand, skills analysis, skills demand, skills extraction, web scraping
    JEL: J23 J24 J31
    Date: 2022–05
  2. By: Joseph G. Altonji; Disa M. Hynsjö; Ivan Vidangos
    Abstract: We review research on the dynamics and distribution of individual earnings and family income. We start with univariate earnings models, which dominate the literature and are often used as the exogenous component of family income in structural models of saving. We present a version of the linear model that nests most of the specifications that have been used in the literature, and then discuss recent papers that stress nonnormal shocks, nonlinear and age-dependent processes, and heterogeneous model parameters. The recent work provides a much richer description of the nature of earnings volatility than the basic model. We then turn to models of individual earnings that are based on wages, employment, job mobility, and hours. These multivariate models permit measuring the sources of permanent differences in earnings and distinguishing among shocks that influence earnings through employment, job mobility, general productivity, or hours. Finally, we consider models of lifetime family income that integrate individual earnings, marriage (accounting for marital sorting), and earnings of a spouse (if present). We conclude by discussing directions for future work.
    JEL: D31 J16 J24 J31
    Date: 2022–05
  3. By: Aysit Tansel (Middle East Technical University); Saziye Gazioglu (Department of Economics, Middle East Technical University, Ankara, Turkey)
    Abstract: Employees’ wellbeing is important to the firms. Analysis of job satisfaction may give insight into various aspect of labor market behavior, such as worker productivity, absenteeism and job turn over. Little empirical work has been done on the relationship between structure of working environment and job satisfaction. This paper investigates the relationship between working environment, firm size and worker job satisfaction. We use a unique data of 28,240 British employees, Workplace Employee Relations Survey. In this data set the employee questionnaire is matched with the employer questionnaire. Four measures of job satisfaction considered are satisfaction with influence over job, satisfaction with amount of pay, satisfaction with sense of achievement and satisfaction with respect from supervisors. They are all negatively related to the firm size implying lower levels of job satisfaction in larger firms. The firm size in return is negatively related to the degree of flexibility in the working environment. The small firms have more flexible work environments. We further find that, contrary to the previous results lower levels of job satisfaction in larger firms can not necessarily be attributed to the inflexibility in their structure of working environment.
    Keywords: Job Satisfactions, Firm Size, Working Environment, Linked Employer-Employee data, Britain
    JEL: J21 J28 J29 J81
    Date: 2022–06
  4. By: Maddalena Ferranna; JP Sevilla; Leo Zucker; David E. Bloom
    Abstract: We analyze time use studies to describe how people allocate their time as they age, especially among paid work, unpaid work, leisure, and personal care. We emphasize differences in time allocation between older (i.e., those aged 65+) and younger people; between developed and developing countries; and by other demographic characteristics such as gender, marital status, health status, and educational attainment. We summarize related economic literature and crystallize a framework for thinking about key conceptual issues involving time allocation over the life cycle. We conclude by assessing the adequacy of global data resources in this area and by discussing some promising opportunities to fill salient gaps in the literature.
    JEL: D13 D15 J14 J22
    Date: 2022–05
  5. By: John R. Grigsby
    Abstract: This paper studies aggregate labor market dynamics when workers have heterogeneous skills for tasks which are subject to non-uniform labor demand shocks. When workers have different skills, movements in aggregate wages partly reflect a reallocation of different workers across tasks and into employment. This ensures that there nearly always exists some combination of task-specific demand shocks that induce aggregate employment and wages to negatively comove even in a frictionless economy. Furthermore, such reallocations would be interpreted either as a labor wedge or as a shift in an aggregate labor supply curve in representative agent economies. Developing a method to estimate the multidimensional skill distribution, I show that a frictionless model with realistic heterogeneity can replicate the mean wage increase and employment collapse of the Great Recession. Reduced-form composition-adjustment methods recover positive co-movements between employment and wages in recent periods suggesting an increasing role for composition effects through time, which the model rationalizes through changes in the skill distribution and composition of sectoral shocks.
    JEL: E24 J24
    Date: 2022–05
  6. By: Joseph G. Altonji; John Eric Humphries; Ling Zhong
    Abstract: This paper uses a college-by-graduate degree fixed effects estimator to evaluate the returns to 19 different graduate degrees for men and women. We find substantial variation across degrees, and evidence that OLS overestimates the returns to degrees with high average earnings and underestimates the returns to degrees with low average earnings. Second, we decompose the impacts on earnings into effects on wage rates and effects on hours. For most degrees, the earnings gains come from increased wage rates, though hours play an important role in some degrees, such as medicine, especially for women. Third, we estimate the net present value and internal rate of return for each degree, which account for the time and monetary costs of degrees. We show annual earnings and hours worked while enrolled in graduate school vary a lot by gender and degree. Finally, we provide descriptive evidence that gains in overall job satisfaction and satisfaction with contribution to society vary substantially across degrees.
    JEL: I21 I24 I26 J16 J24 J28
    Date: 2022–06
  7. By: Duygu Buyukyazici; Leonardo Mazzoni; Massimo Riccaboni; Francesco Serti
    Abstract: The literature reaches a unanimous agreement that industrial diversification is path-dependent because new industries build on preexisting capabilities of regions that are partly embodied and reflected in the skills of regions’ workforce. This paper explicitly accounts for regional capabilities as workforce skills to build skill relatedness and complexity measures, skill-spaces, for 107 Italian regions for the period 2013-2019. Data-driven techniques we use reveal that skill-spaces form two highly polarised clusters into social-cognitive and technical-physical skills. We show that industries have a higher (lower) probability of developing comparative advantage if their required skill set is (not) similar to those available in the region regardless of the skill type. We find evidence that similarity to technical-physical skills and higher complexity in social cognitive skills yields the highest probabilities of regional competitive advantage.
    Keywords: Skill relatedness; Economic complexity; Industrial specialisation; Regional capabilities; Regional diversification.
    JEL: J24 O18 R10 R23
    Date: 2022–06
  8. By: Johnathan G. Conzelmann; Steven W. Hemelt; Brad Hershbein; Shawn M. Martin; Andrew Simon; Kevin M. Stange
    Abstract: This paper introduces a new measure of the labor markets served by colleges and universities across the United States. About 50 percent of recent college graduates are living and working in the metro area nearest the institution they attended, with this figure climbing to 67 percent in-state. The geographic dispersion of alumni is more than twice as great for highly selective 4-year institutions as for 2-year institutions. However, more than one-quarter of 2-year institutions disperse alumni more diversely than the average public 4-year institution. In one application of these data, we find that the average strength of the labor market to which a college sends its graduates predicts college-specific intergenerational economic mobility. In a second application, we quantify the extent of “brain drain” across areas and illustrate the importance of considering migration patterns of college graduates when estimating the social return on public investment in higher education.
    JEL: H41 I23 J24 J61
    Date: 2022–05
  9. By: Elizabeth Gallagher; India Kerle; Cath Sleeman; George Richardson
    Abstract: This paper presents a new data-driven approach to building a UK skills taxonomy, improving upon the original approach developed in Djumalieva and Sleeman (2018). The new method improves on the original method as it does not rely on a predetermined list of skills, and can instead automatically detect previously unseen skills. This 'minimal judgement' approach is made possible by a classifier that automatically detects sentences within job adverts that are likely to contain skills. These 'skill sentences' are then grouped to define distinct skills, and a hierarchy is formed. The resulting taxonomy contains three levels and 6,685 separate skills. The taxonomy could be used as a base for developing the first UK-specific skills taxonomy, which domain experts would then refine and extend. It could also be used to spot regional skill clusters, and for rapid assessments of skill changes following shocks such as the COVID-19 pandemic.
    Keywords: big data, cluster analysis, job market, labour demand, machine learning, nlp, online job adverts, sentence embeddings, skills, skills taxonomy
    JEL: C18 C38 J23 J24
    Date: 2022–05
  10. By: de Souza, Gustavo
    Abstract: Developing countries rely on technology created by developed countries. This paper demonstrates that such reliance increases wage inequality but leads to greater production in developing countries. I study a Brazilian innovation program that taxed the leasing of international technology to subsidize national innovation. By exploiting heterogeneous exposure, I show that the program led firms to replace technology licensed from developed countries with in-house innovations, which led to a decline in both employment and the share of high-skilled workers. I explain these findings using a model of directed technological change and cross-country technology transactions. Firms in a developing country can either innovate or lease technology from a developed country, and these two technologies differ endogenously regarding productivity and skill bias due to factor supply disparities in the two countries. I show that the difference in skill bias and productivity can be identified using closed-form solutions by the effect of the innovation program on firms’ expenditure share with lowskilled workers and employ- ment. By calibrating the model to reproduce these effects, I find that increasing the share of firms that patent in Brazil by 1 p.p. decreases the skilled wage premium by 0.02% and production by 0.2%.
    Keywords: labor market, technology, wages
    Date: 2022–06
  11. By: Potter, Tristan (Drexel University)
    Abstract: This paper tests for habit-formation in leisure-related internet use (LIU) using time-diary data from a panel of unemployed workers. Drawing on insights from the consumption-habit literature, I use a model of intertemporal time allocation to derive a test for habit-formation in leisure activities. The data reveal strong evidence of habit-formation in LIU among the Generation-X age cohort. With the exception of reading, I find no evidence of habit-formation in offline leisure.
    Keywords: Habit-formation; leisure; internet use
    JEL: D91 J22
    Date: 2022–03–15
  12. By: Pouliakas, Konstantinos; Wruuck, Patricia
    Abstract: European firms have increasingly invested in training of employees but differences across countries and types of firms remain - and the COVID-19 shock may have exacerbated them. This report analyses European firms' investment in training over the last six years examining trends, factors supporting training investment as well as the impact of the COVID-19 shock. We base the empirical analysis on a unique dataset, the European Investment Bank's Investment Survey (EIBIS), which allows tracking corporate training investment on a yearly basis. To understand dynamics underpinning firms' decision to invest in their workforce, we examine transition patterns and employ dynamic panel data estimation. Finally, we analyze the impact of the COVID-19 pandemic on firms' investment in workforce training and transitions in and out of training. We find that despite a slow upward trend in training investment observed in recent years, supported by labour market recovery, differences across firms and countries have persisted. The pandemic risks aggravating these, through its asymmetric impact on labour markets and differences in corporate innovation, firm structure and resilience. While firm training can be an important element for firms and their workforce to adjust to the post-pandemic environment, asymmetries in training investment could make it harder for those already lagging. The paper concludes with a discussion of policy implications.
    Date: 2022
  13. By: Fabrizio Leone
    Abstract: This paper shows that multinational enterprises (MNEs) spur the adoption of industrial robots. First, I document a positive and robust correlation between multinational production and robot adoption using a new cross-country industry-level panel. Second, using detailed data about Spanish manufacturing, I combine a difference-in-differences approach with a propensity score reweighing estimator and provide evidence that firms switching from domestic to foreign ownership become about 10% more likely to employ robots. In terms of mechanism, increased foreign market access via the parental network generates incentives to scale-up production, and robot adoption is one way to achieve this goal. An empirical model of rm investment reveals that multinational-induced robot adoption raises productivity but decreases the labor share at the industry level. Theseresults provide new evidence about the efficiency versus equity trade-off that policymakers face when attracting MNEs.
    Keywords: Foreign Ownership, Industrial Robots, Total Factor Productivity, Factor-Biased Productivity, Labor Share
    Date: 2022–05
  14. By: Stefan Jestl (The Vienna Institute for International Economic Studies, wiiw)
    Abstract: This paper explores the effects of industrial robots and information and communication technology (ICT) on regional employment in EU countries. The empirical analysis relies on a harmonised comprehensive regional dataset, which combines business statistics and national and regional accounts data. This rich dataset enables us to provide detailed insights into the employment effects of automation and computerisation in EU regions for the period 2001-2016. The results suggest relatively weak effects on regional total employment dynamics. However, employment effects differ between manufacturing and non-manufacturing industries. Industrial robots show negative employment effects in local manufacturing industries, but positive employment effects in local non-manufacturing industries. While the negative effect is concentrated in particular local manufacturing industries, the positive effect operates in local service industries. IT investments show positive employment effects only in local manufacturing industries, while CT investments are shown to be irrelevant for employment dynamics. In contrast, software and database investments have had a predominantly negative impact on local employment in both local manufacturing and non-manufacturing industries.
    Keywords: Industrial robots, ICT, EU labour markets, employment effects
    JEL: J23 L60 O33 R11
    Date: 2022–06

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