Share Of Jobs Research Articles

The Rise of AI Pricing: Trends, Driving Forces, and Implications for Firm Performance

We document key stylized facts about the time-series trends and cross-sectional distributions of AI pricing and study its implications for firm performance, both on average and conditional on monetary policy shocks. We use the universe of online job posting data from Lightcast to measure the adoption of AI pricing. We infer that a firm is adopting AI pricing if it posts a job opening that requires AI-related skills and contains the keyword “pricing.” At the aggregate level, the share of AI-pricing jobs in all pricing jobs has increased by more than tenfold since 2010. The increase in AI-pricing jobs has been broad-based, spreading to more industries than other types of AI jobs. At the firm level, larger and more productive firms are more likely to adopt AI pricing. Moreover, firms that adopted AI pricing experienced faster growth in sales, employment, assets, and markups, and their stock returns are also more sensitive to high-frequency monetary policy surprises than non-adopters. We show that these empirical observations can be rationalized by a simple model where a monopolist firm with incomplete information about the demand function invests in AI pricing to acquire information.

Place‐based tax incentives and minority employment: Evidence from the New Market Tax Credit Program

AbstractIn this paper, we study the impact of the New Market Tax Credit (NMTC) program in the United States on overall jobs and jobs held by minority and rural populations within the 2010–2019 period using a dynamic event‐study analysis. We also investigate if the jobs that can be attributed to the program stayed in program recipient neighborhoods or whether those jobs were occupied by non‐residents. The results show that there is clear evidence that the program increased overall workplace jobs and workplace jobs held by White and minority populations in the program recipient tracts. We also see that a larger share of workplace jobs due to the program went to minorities compared to the job shares held by various racial and ethnic groups at the beginning of the investment period. The results further show that even though the NMTC program increased the number of jobs available in a program recipient tract, the individuals who live outside that tract are holding many of the jobs created. The results also suggest that the program had a negative impact on jobs held by residents in nonmetropolitan tracts.

From Discrete Skills to Holistic Creative Human Potential: An Emerging Approach in Theory and Practice

The study aims to empirically demonstrate and conceptually interpret the manifestations of an emerging approach to the issues of human capital, its measurement and development on the international academic, expert, and corporate agenda. We document a gradual shift from a focus on individual skills, their measurement and development, to an approach that considers the complexity of human capital and emphasizes holistic individual activity and the proactive role of the individual in his/her human development and in transforming the corporate environment.The authors show that the formation of this novel approach can be associated with new trends in socio-economic development, including the growing share of non-routine jobs, the transformation of work formats and broader processes of de-structuration, which require a proactive role of the individual in the maintenance and development of social structures, including business organizations. The study has shown that the formation of this new approach occurs gradually and simultaneously at the global level on the academic, expert, and corporate agendas, but with varying degrees of intensity and with different focuses. At the same time, it is the corporate agenda that can be regarded as a frontier. This study is based on a content analysis of academic publications, expert reports of international organizations and think tanks, as well as public reports and documents of the world’s leading innovative companies. The research employs the Big Data intelligence system iFORA.

Characterizing collective physical distancing in the U.S. during the first nine months of the COVID-19 pandemic.

The COVID-19 pandemic offers an unprecedented natural experiment providing insights into the emergence of collective behavioral changes of both exogenous (government mandated) and endogenous (spontaneous reaction to infection risks) origin. Here, we characterize collective physical distancing-mobility reductions, minimization of contacts, shortening of contact duration-in response to the COVID-19 pandemic in the pre-vaccine era by analyzing de-identified, privacy-preserving location data for a panel of over 5.5 million anonymized, opted-in U.S. devices. We define five indicators of users' mobility and proximity to investigate how the emerging collective behavior deviates from typical pre-pandemic patterns during the first nine months of the COVID-19 pandemic. We analyze both the dramatic changes due to the government mandated mitigation policies and the more spontaneous societal adaptation into a new (physically distanced) normal in the fall 2020. Using the indicators here defined we show that: a) during the COVID-19 pandemic, collective physical distancing displayed different phases and was heterogeneous across geographies, b) metropolitan areas displayed stronger reductions in mobility and contacts than rural areas; c) stronger reductions in commuting patterns are observed in geographical areas with a higher share of teleworkable jobs; d) commuting volumes during and after the lockdown period negatively correlate with unemployment rates; and e) increases in contact indicators correlate with future values of new deaths at a lag consistent with epidemiological parameters and surveillance reporting delays. In conclusion, this study demonstrates that the framework and indicators here presented can be used to analyze large-scale social distancing phenomena, paving the way for their use in future pandemics to analyze and monitor the effects of pandemic mitigation plans at the national and international levels.

The impact of artificial intelligence on employment: the role of virtual agglomeration

Sustainable Development Goal 8 proposes the promotion of full and productive employment for all. Intelligent production factors, such as robots, the Internet of Things, and extensive data analysis, are reshaping the dynamics of labour supply and demand. In China, which is a developing country with a large population and labour force, analysing the impact of artificial intelligence technology on the labour market is of particular importance. Based on panel data from 30 provinces in China from 2006 to 2020, a two-way fixed-effect model and the two-stage least squares method are used to analyse the impact of AI on employment and to assess its heterogeneity. The introduction and installation of artificial intelligence technology as represented by industrial robots in Chinese enterprises has increased the number of jobs. The results of some mechanism studies show that the increase of labour productivity, the deepening of capital and the refinement of the division of labour that has been introduced into industrial enterprises through the introduction of robotics have successfully mitigated the damaging impact of the adoption of robot technology on employment. Rather than the traditional perceptions of robotics crowding out labour jobs, the overall impact on the labour market has exerted a promotional effect. The positive effect of artificial intelligence on employment exhibits an inevitable heterogeneity, and it serves to relatively improves the job share of women and workers in labour-intensive industries. Mechanism research has shown that virtual agglomeration, which evolved from traditional industrial agglomeration in the era of the digital economy, is an important channel for increasing employment. The findings of this study contribute to the understanding of the impact of modern digital technologies on the well-being of people in developing countries. To give full play to the positive role of artificial intelligence technology in employment, we should improve the social security system, accelerate the process of developing high-end domestic robots and deepen the reform of the education and training system.

Labor Relations in Reform-Era Cuba

As part of the model-updating reform started in 2011, there has been a significant shift in Cuba's labor relations. Although the share of state jobs in the labor force — in public institutions and enterprises — is the largest, non-state jobs dominate if enterprises alone are considered. In the non-state sector, self- and family employment predominate, but new private enterprises are growing fast while cooperatives and their membership decrease. These changes in the employment structure have greatly impacted Cuban society, with growing inequalities in income, labor conditions, and rights, gender, skin color. The new preponderance of private wage relations has severe implications for Cuban socialism. To be consistent with the agreed-on documents guiding the reform and with the sacrifices made by generations of Cubans to build a post-capitalist society, the Cuban Revolution must build a new socialist hegemony inside workplaces and beyond. The non-state sector cannot be regulated and guided toward satisfying the needs and aspirations of the Cuban people only through norms, incentive policies, and administrative measures. A new hegemony of socialist relations is fundamental to secure a future for the Cuban Revolution.

Migrant penalty in the European labor markets: the interplay between individual characteristics and the regional context.

This study aims to verify if and how migrant penalty in the labor market is associated with sub-national characteristics, exploring the relevance of the regional occupational structure. We expect that a greater relevance of the share of low-status jobs at the regional level reduces the migrant penalty in terms of the probability of being employed, but increases the gap with natives in terms of job quality. We investigate this trade-off by estimating a set of hierarchical models on the EU-LFS data (2009-2015) for 19 countries and 189 regions. Results suggest a pattern consistent with the trade-off hypothesis, nuanced by heterogeneity at the individual level: in regions where the share of low-status jobs is higher, mid-high educated immigrants from less developed countries are less (or not) penalized compared to natives in terms of employment, while they face a stronger penalty in terms of job quality. What is more, the trade-off is not observed when considering low-educated migrants or those from high-income countries.

Tracking Potential Renewable Energy Jobs in ASEAN

Job creation in renewable is among the most significant social impacts of higher renewable penetration to the energy mix, but it also poses a challenge for countries to adapt to the changing work landscape amidst the energy transition. Hence mapping the distribution and projecting renewable employment in the coming years in ASEAN will be crucial as it would support the policy ramifications, job market, and economy. This research adopted data and scenarios trajectory from the 7th ASEAN Energy Outlook (AEO7) from 2020 up to 2050 with four technologies: Solar PV Utility-Scale, Onshore Wind, Hydropower Dam, and Geothermal. It is limited to three job types: manufacturing, construction, installation, and operation and maintenance. The data was processed using Low Emissions Analysis Platform (LEAP) software. The findings indicate that ASEAN’s renewable energy (RE) jobs will reach between 3.9 – 5.5 million, with Vietnam and Indonesia dominating the share. Meanwhile, job share growth based on the technology is most robust in hydropower and solar. As new plants are established during the early years, job creation will be relatively higher, especially in manufacturing and construction. Further refinement of methodologies and continuous data improvement is vital to allow the better projection of the region’s workforce on energy transition and provide opportunities for better coordination, planning, and investment to improve employment outcomes.

529 Job Sharing: An Innovative Approach to Increasing Research Resources and Improving Staff Satisfaction

Abstract Introduction Pre-pandemic job openings for clinical research staff increased by nearly 10% a month nationwide yet was outpaced by an increase of greater than 12% in clinical trial activity. With the onset of the pandemic, the gulf between supply and demand widened in research. Simultaneously hospitals were stretched to capacity, staff suffered extreme burn-out and there was a dire need for additional bedside nurses. The pandemic shown a bright light on an age-old problem in nursing, whereas for a nurse to grow professionally, it often required leaving the bedside and giving up vital clinical skills, skills that were suddenly in great demand. The purpose of this project was to create a novel new job role, utilizing existing burn nursing staff to job share a research position, while maintaining their clinical expertise. Methods Nurse leaders from both areas worked in concert with the burn center’s director of research, senior hospital administration, human resources and existing staff to develop a new job role. The job description incorporated the scope and standards for nursing practice in both areas into one document. Additionally, a second-level position was created which allowed bedside nurses to trial the new role without a formal commitment to the permanent position. Staff were scheduled to rotate every 2 weeks between the two areas. Two months following implementation, core research staff and job-sharing staff were polled for feedback on benefits and challenges. Results Staff members (n=4) provided feedback independently from each other. A total of 41 comments were received, 27 benefit responses vs 14 challenges responses. Responses were grouped into themes and both benefits and challenges had 6 themes each. Benefit themes included: increased interdepartmental collaboration / trust (26%), professional growth (26%), supported learning (22%), enhanced screening for research patients (11%), unit-based resources (7%) and prevention of burnout (7%). Challenge themes included: scheduling (29%), variability in training opportunities (21%), role transitioning (21%), communication (14%), success personnel driven (7%), compensation (7%). Anecdotally, study investigators have expressed great satisfaction with the new position and there has been an increased interest expressed by other bedside staff in research involvement. Conclusions The response to the new position has been overwhelmingly positive. Staff entered the trial period realizing that it may be “messy” at first but quickly adapted and have worked through many of the challenges. Based on this early success, we are exploring the viability of cross training additional staff. Applicability of Research to Practice Cross training has been demonstrated to increase efficiencies, improve collaboration, trust and job satisfaction.

The role of political economy in the strategic choice for automation: a case study in a German logistics firm

The current automation debate neglects the social conditions underpinning technological change. Following recent labour process analysis (LPA) concepts and the Regulation School theory of the firm, I apply a firm-level strategic choice approach to trace the political-economic and organisational conditions associated with automation in logistics. To this end, I reconstruct the strategic choice of industrial automation in a German parcel logistics firm. Moreover, I compare two types of distribution centres on the level of task automation in the company and discuss the failed implementation of the automation project. I employ qualitative data about the company and four of its facilities to trace the process. The case selection fits the current debate as logistics has a high share of routine jobs, and therefore – according to labour economists – the industry faces a high risk of automation-induced job displacement. The analysis yields that actors drew on six essential conditions for the automation project at the firm and the political-economic level. The case study demonstrates the working of an ambivalent causal mechanism and stresses the relevance of organisational affordances and material-technical requirements for successful automation projects. The results synthesise the political-economic and organisational conditions that need to be considered in technological change in logistics. Thereby the article adds to a political economy of automation. Ultimately, the findings also emphasise the need for labour strategies centring on technological change in logistics.

A Middle Model of Economic Development? Revisiting the Economic Geography of Middle-Wage Occupations in the United States

High-wage regions have frequently been models for economic development policy. However, these places have also been more likely to experience a “hollowing out” of the middle of the labor market, whereby college-educated residents experience high-wage growth, while residents without a college degree do not. This paper studies regions where—in contrast to hollowing out—the share of middle-wage jobs has grown since 1980. Its aim is to understand how—if at all—the characteristics of these regions could suggest a model of economic development that prioritizes opportunities for noncollege graduates. The authors find that regions with a growing share of middle-wage jobs have been associated with higher levels of upward mobility and wage growth for workers without a college degree. These places, such as Wausau, Wisconsin, and Manhattan, Kansas, are associated with higher local school performance and have experienced comparatively high growth in production jobs.

Understanding Divergence in the Performance of Central Business District Economies Among U.S. Metropolitan Regions, 1995–2019

Although references to an urban resurgence are pervasive, on average, the share of regional jobs found in central business district (CBD) areas has fallen since the 1990s. Yet, this fact masks great variation in the performance of CBD economies. In several metropolitan regions, the share of jobs found in CBD areas increased over this period. This paper seeks to understand the factors that explain such variation. Relying on a panel of metropolitan regions for the period 1995 to 2019, the paper finds that, as a regional economy increasingly comprises tasks that are more cognitive in nature, the share of its jobs found in CBD areas increases. Although the “great divergence” has been linked to an increasing dispersion of incomes, health care outcomes, and cultural identities among regions, the paper's findings suggest it may also be associated with divergent economic performance among CBD areas.

The STEM Wage Premium Across the OECD

Using data from the Program for the International Assessment of Adult Competencies, this paper compares the earnings premium and employment share of jobs in Science, Technology, Engineering and Mathematics (STEM) across 11 member countries of the Organisation for Economic Co-operation and Development. The results reveal that the STEM wage premium is higher in the United States than in any of the other comparison countries, despite the fact that the U.S. has a larger share of workers in STEM jobs. We also find evidence that the premium varies significantly across STEM sub-fields and education levels, and that the premium tends to be higher in countries with lower unionization rates, less employment protection, or a larger share of employment in the public sector.

Failing Young and Temporary Workers? The Impact of a Disruptive Crisis on a Dual Labour Market

Abstract We study the impact of the pandemic crisis using monthly data covering the universe of individuals registered as unemployed in mainland Portuguese municipalities, complemented with electronic payments, linked employer–employee data, and furlough records. Event study designs identify a sharp increase in unemployment, driven mostly by termination of temporary contracts, and a decrease in new job placements. With triple difference-in-differences, we show that the effects are stronger in more dual municipal labour markets, i.e. with a higher share of temporary jobs, concentrated in young workers and middle educated individuals. The asymmetries are exacerbated by the duality of the municipal labour market.

Non-College Occupations, Workplace Routinization, and the Gender Gap in College Enrollment

Women used to lag behind men in college enrollment but now exceed them. We argue that changes in non-college job prospects contributed to these trends. We first document that routine-biased technical change disproportionately displaced non-college occupations held by women. We next employ a shift-share instrument for the impact of routinization to show that declining non-college job prospects for women increased female enrollment. Results show that a one percentage point decline in the share of routine task intensive jobs leads to a 0.6 percentage point rise in female college enrollment, while the effect for male enrollment is directionally smaller and insignificant. We next embed this instrumental variation into a dynamic model that links education and occupation choices. The model finds that routinization decreased returns to non-college occupations for women, leading them to shift to cognitive work and increasing their college premium. In contrast, non-college occupations for men were less susceptible to routinization. Altogether, our model estimates that workplace routinization accounted for 63% of the growth in female enrollment and 23% of the change in male enrollment between 1980 to 2000.

A macro analysis of gender segregation and job quality in Latin America

Latin America has seen vast improvements in gender educational and health equality. Favorable supply-side conditions, however, have not translated into greater gender economic equality, a process that also depends on structural economic change and global macroeconomic conditions. In this paper, we assess the role of a variety of macro-level policies and structures in influencing trends in women’s access to high-quality jobs for a sample of 15 countries in Latin America over the period 1990–2018. Using micro-level data, we first evaluate women’s relative share of good jobs, defined in terms of women’s weekly earnings in an industry or occupation relative to the national median wage. Further, we econometrically estimate the association between a variety of macro-level variables and the relative quality of women’s jobs. Results indicate that the most significant and robust positive correlate of women’s relative access to good jobs is public social spending as a share of GDP. Other important macro-covariates include measures of labor market regulation, monetary and fiscal policy, and macroeconomic structure and global orientation, including financial openness. The results suggest that macro-level structures and policies related to globalization that hamper the achievement of greater gender equality can be offset by appropriately targeted government policies.

Jobs not Threatened by Automation in the Future in the Slovak Republic

Industry 4.0 brings with it an increase in new forms and methods of work based on automation and digitization, which gradually threaten jobs in individual countries. Most studies published on this topic describe the expected proportion of jobs that are threatened with extinction. The aim of the presented study is to investigate the opportunities that the introduction of Industry 4.0 brings with it.
 The presented study calculates the share of jobs with a low risk of being threatened by automation in the Slovak Republic. This is a unique approach to researching the impact of innovation trends on the labor market, which identifies jobs that are difficult to replace by machines. The calculation of the share of jobs with a low risk of being threatened by automation is based on the connection of two data sources – National system of occupations (a description of the skills required for every job in the Slovak Republic) and Information system on the price of work (modern and effective national labour cost statistical survey focus on wage earnings, including the calculation of the number of employees in individual job positions). 
 Of the total number of 2 million working people in the Slovak Republic, 24% will not be threatened by automation. These are jobs that require at least one of the following skills for their performance: creativity, organizing and planning work, the ability to make decisions and take responsibility, leadership skills, critical thinking and talent. Several authors investigating the issue of innovations and their effects on jobs define the above-mentioned skills as difficult to be replaced by machines.
 The findings presented in the paper create space for further discussion at the national level about which skills and competences will need to be supported in lifelong learning among employees in order to prevent the high rate of replacement of jobs by automation, which the OECD predicts for the Slovak Republic.

A Tale of a Few CBDs: The Uneven Resurgence of Central Business District Economies across U.S. Cities, 1994–2019

In many central business districts (CBDs), job growth has occurred since the 1990s, but at a far slower rate than in non-CBD areas. Over this time, there has been a great divergence in economic performance among CBD areas, with a handful of CBD economies far outperforming the rest. Overall, CBD economies have become home to higher paying economic activities, compared with non-CBD areas, because industries comprising higher levels of “cognitive” tasks locate a higher share of jobs in CBD areas. As such, CBD performance seems to be tied to the mix of industries present in a given region’s economy.

Influenza and labour investment efficiency

ABSTRACTThis study investigates the relationship between the spread of influenza and labour investment efficiency using a sample of United States (US) firms from 2004–2019. The spread of influenza is found to be positively associated with an inefficient investment in labour. Further analyses show that the impact of the spread of influenza on labour investment inefficiency is less pronounced for firms in states mandating paid sick leave, for firms operating in the industries where a higher share of jobs can be done at home, and for firms in the industries where there is a lower level of interpersonal contact. Given the raising awareness of public health and firm outcomes, our findings should be of great interest to investors, directors, managers, and public policymakers.

Engineering Intangibles: Technical Employment in the US Service Economy

Engineering occupations coevolved with industries producing material outputs: mining, construction, manufacturing. Yet wealthy economies have long been moving toward intangible services, the products of industries including finance, wholesale and retail trade, entertainment, travel and transportation, health care, and the public sector (including, e.g. much of education). For the United States the shift is evident in statistical data going back well over a century and services now account for nearly 90 percent of all employment. The job share is lower for engineers, but even so the majority work for service-producing entities. Entanglement and interdependence of services and goods hinders understanding of the dynamics, as does rapid growth in jobs classed in official employment statistics as computer-related even though much of the work resembles engineering. Because of this, field studies that explore actual job content will be needed to develop clearer pictures of the everyday tasks employers assign technical workers in postindustrial economies.