Search Results (12)

Routine-Biased Technological Change (RBTC) is viewed as reshaping labor markets, yet its implications for gender inequality in developing economies remain underexplored. This study examines these dynamics among formal wage workers in Indonesia from 2001 to 2019. Using stacked first-difference estimations and a dynamic shift-share decomposition, we document three interconnected patterns. First, routine displacement unfolds episodically rather than simultaneously—with relative contraction in routine cognitive jobs (2001–2005), routine manual jobs (2005–2010), and renewed routine cognitive pressures (2015–2019)—a sequence likely shaped by technological change alongside macroeconomic and institutional forces. Second, these adjustments are gender-asymmetric. Women experienced greater exposure to displacement but reallocated substantially toward non-routine interpersonal roles. This occupational upgrading is consistent with both task-based demand shifts associated with technological change and the entry of younger, more educated female cohorts. Third, employment reallocation exerted a narrowing influence on the gender wage gap, particularly in 2005–2010. However, this equalizing channel weakened over time as market valuation (wage exposure) became increasingly unfavorable to female-concentrated occupations, contributing to a renewed widening in 2015–2019. Ultimately, while residual within-task group dynamics dominate the gap’s magnitude, task-based employment and wage channels remain critical in structuring the timing and directional shifts of gender inequality in the formal sector. Full article

Digitalization has reshaped economic systems worldwide, yet its distributional consequences remain uneven and raise new challenges for sustainable development. China, where digital infrastructure has expanded rapidly, provides a critical setting to examine these effects and their implications for sustainable and inclusive growth. Using a balanced panel of 285 prefecture-level cities from 2007 to 2023, this study constructs a text-based index of digital infrastructure from government work reports and applies two-way fixed effects, instrumental variables, nonlinear models, placebo tests, heterogeneity analysis, and spatial Durbin models. The results show that digital infrastructure significantly widens the urban–rural income gap, with the effect becoming increasingly convex as digital development deepens. Two mechanisms drive this pattern: the concentration of innovation resources in urban areas, which crowds out rural R&D, and a modest degree of wage-structure polarization. Spatial spillovers also matter; digital development in neighboring cities partially offsets local inequality by enhancing interregional connectivity and knowledge diffusion. These findings provide city-level causal evidence on the unequal distributional impacts of digitalization in large emerging economies and highlight the need for sustainability-oriented digital governance, inclusive innovation systems, and regionally coordinated strategies to prevent digital infrastructure from reinforcing structural disparities. Strengthening these policies is essential for achieving more sustainable urban–rural integration in the digital era. Full article

In this study, we explore the transformative impact of artificial intelligence (AI) on the job market and argue for the growing importance of critical thinking skills in the face of job automation and changing work dynamics. Advancements in AI have the potential to disrupt various professions, including, for example, programming, legal work, and radiology. However, solely relying on AI systems can lead to errors and misjudgments, emphasizing the need for human oversight. The concept of “job-proof skills” is introduced, highlighting the importance of critical thinking, problem-solving, empathy, ethics, and other human attributes that machines cannot replicate with the same standards and agility. We maintain that critical thinking can be taught and learned through appropriate classroom instruction and transfer-focused approaches. The need for critical thinking skills is further reinforced by the influx of information and the spread of misinformation in the age of social media. Moreover, employers increasingly value critical thinking skills in their workforce, yet there exists a gap between the demand for these skills and the preparedness of college graduates. Critical thinking is not only essential for the future of work, but also for informed citizenship in an increasingly complex world. The potential impact of AI on job disruption, wages, and employment polarization is discussed, highlighting the correlation between jobs requiring critical thinking skills and their resistance to automation. We conclude by discussing collaborative efforts between universities and labor market organizations to adapt curricula and promote the development of critical thinking skills, drawing on examples from European initiatives. The need to prioritize critical thinking skills in education and address the evolving demands of the labor market is emphasized as a crucial step for navigating the future of work and opportunities for workers. Full article

(1) Background: Wage polarization and skill polarization are frequently mentioned in the literature, but relatively few empirical studies have focused on the relationship between skill polarization and wage polarization. (2) Methods: Using occupation–skill data from the O*NET database in the United States from 2009 to 2021, this study constructs the occupational socio-cognitive skill scores and the number of perceived physical skills effectively used by an occupation as proxies for measuring skill polarization and matches the Occupational Employment and Wage Statistics data from the corresponding years to explore the relationship between skill polarization and wage polarization by using 2SLS. (3) Results: Increases in both the occupational socio-cognitive skills scores and the number of sensory–physical skills effectively used by an occupation lead to higher wages, but the magnitude of the positive effects of these two indicators are different. We also find that these control variables can reduce occupational wages with a lagged effect. (4) Conclusion: Our findings confirm that skills polarization has a positive effect on wage polarization, providing new insights into understanding employment inequality in the labor market. Authorities should focus more attention on increasing the earnings of the low- and middle-skilled workers, especially through vocational skills training to increase the number of sensory–physical skills that can ultimately mitigate wage polarization. Full article

Robotics and computerization have drastically changed the agricultural production sector and thus moved it into a new automation era. Robots have historically been used for carrying out routine tasks that require physical strength, accuracy, and repeatability, whereas humans are used to engage with more value-added tasks that need reasoning and decision-making skills. On the other hand, robots are also increasingly exploited in several non-routine tasks that require cognitive skills. This technological evolution will create a fundamental and an unavoidable transformation of the agricultural occupations landscape with a high social and economic impact in terms of jobs creation and jobs destruction. To that effect, the aim of the present work is two-fold: (a) to map agricultural occupations in terms of their cognitive/manual and routine/non-routine characteristics and (b) to assess the susceptibility of each agricultural occupation to robotization. Seventeen (17) agricultural occupations were reviewed in relation to the characteristics of each individual task they entail and mapped onto a two-dimensional space representing the manual versus cognitive nature and the routine versus non-routine nature of an occupation. Subsequently, the potential for robotization was investigated, again concerning each task individually, and resulted in a weighted average potential adoption rate for each one of the agricultural occupations. It can be concluded that most of the occupations entail manual tasks that need to be performed in a standardised manner. Considering also that almost 81% of the agricultural work force is involved with these activities, it turns out that there is strong evidence for possible robotization of 70% of the agricultural domain, which, in turn, could affect 56% of the total annual budget dedicated to agricultural occupations. The presented work silhouettes the expected transformation of occupational landscape in agricultural production as an effort for a subsequent identification of social threats in terms of unemployment and job and wages polarization, among others, but also of opportunities in terms of emerged skills and training requirements for a social sustainable development of agricultural domain. Full article

The sustained growth of non-farm wages has led to large-scale migration of rural population to cities in China, especially in mountainous areas. It is of great significance to study the spatial and temporal pattern of population migration mentioned above for guiding population spatial optimization and the effective supply of public services in the mountainous areas. Here, we determined the spatiotemporal evolution of population in the Chongqing municipality of China from 2000–2018 by employing multi-period spatial distribution data, including nighttime light (NTL) data from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) and the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). There was a power function relationship between the two datasets at the pixel scale, with a mean relative error of NTL integration of 8.19%, 4.78% less than achieved by a previous study at the provincial scale. The spatial simulations of population distribution achieved a mean relative error of 26.98%, improved the simulation accuracy for mountainous population by nearly 20% and confirmed the feasibility of this method in Chongqing. During the study period, the spatial distribution of Chongqing’s population has increased in the west and decreased in the east, while also increased in low-altitude areas and decreased in medium-high altitude areas. Population agglomeration was common in all of districts and counties and the population density of central urban areas and its surrounding areas significantly increased, while that of non-urban areas such as northeast Chongqing significantly decreased. Full article

Since workplace skills present diverse dimensions of a worker’s ability, it has recently received renewed interest by researchers examining the growth of cities. The purpose of the paper explores the advantage of regional concentrations of workers specialized in different types of skills. Specifically, the analysis estimates the agglomeration effects of skill-based labor pooling on wage levels and wage growth in South Korea. To this end, it constructs skill-based labor pool indices for cognitive, social, technical, and physical skills at a provincial level. The indices show an uneven geographical distribution in varying degrees across four types of skills. The regression results indicate that the urban wage premium of skill-based local labor pooling varies according to types of skills. The greatest magnitude of benefit is incurred by workers in cognitive-skill-oriented occupations and moderate benefits are found in technical- and physical-skill-oriented occupations. An urban wage premium is non-existent in social-skill-oriented occupations. In addition, the wage growth model with job mobility shows that the urban wage premium immediately affects workers who change jobs and relocate to denser areas. As high-wage occupations earn higher wage premiums when workers in these occupations are concentrated, it supports patterns of the polarization of both skills and their effects. Full article

This paper draws upon influence function regression methods to determine where foreign workers stand in the distribution of private sector wages in Luxembourg, and assess whether and how much their wages contribute to wage inequality. This is quantified by measuring the effect that a marginal increase in the proportion of foreign workers—foreign residents or cross-border workers—would have on selected quantiles and measures of inequality. Analysis of the 2006 Structure of Earnings Survey reveals that foreign workers have generally lower wages than natives and therefore tend to haul the overall wage distribution downwards. Yet, their influence on wage inequality reveals small and negative. All impacts are further muted when accounting for human capital and, especially, job characteristics. Not observing any large positive inequality contribution on the Luxembourg labour market is a striking result given the sheer size of the foreign workforce and its polarization at both ends of the skill distribution. Full article

This paper provides a detailed exposition of an extension of the Oaxaca-Blinder decomposition method that can be applied to various distributional measures. The two-stage procedure first divides distributional changes into a wage structure effect and a composition effect using a reweighting method. Second, the two components are further divided into the contribution of each explanatory variable using recentered influence function (RIF) regressions. We illustrate the practical aspects of the procedure by analyzing how the polarization of U.S. male wages between the late 1980s and the mid 2010s was affected by factors such as de-unionization, education, occupations, and industry changes. Full article

The unprecedented growth in foreign direct investment in the last few decades has caused drastic changes in the labor markets of the host countries. The major part of FDI takes place in low-tech industries, where the wages and skills are low, or in high-tech, where they offer a wage premium for the highly skilled workers. This mechanism may increase the polarization of employment into high-wage and low-wage jobs, at the expense of middle-skill jobs. This paper looks at the effects of two types of FDI inflows, namely foreign investment in high-skill and low-skill activities, on job polarization. We match data on greenfield FDI aggregated by country and sector with data on employment by occupational skill to investigate the extent to which different types of greenfield FDI are responsible for skill polarization. Our results show that low-skill foreign investment shifts employment from high- to medium- and low-skill jobs, while skill-intensive FDI generally leads to skill upgrading. Only FDI in information and communication technology (ICT) is associated with job polarization, but only when accounting for the plurality of job polarization patterns across European sectors. Full article

Since the late 1970s, wage inequality has increased strongly both in the U.S. and Germany but the trends have been different. Wage inequality increased along the entire wage distribution during the 1980s in the U.S. and since the mid 1990s in Germany. There is evidence for wage polarization in the U.S. in the 1990s, and the increase in wage inequality in Germany was restricted to the top of the distribution before the 1990s. Using an approach developed by MaCurdy and Mroz (1995) to separate age, time, and cohort effects, we find a large role played by cohort effects in Germany, while we find only small cohort effects in the U.S. Employment trends in both countries are consistent with polarization since the 1990s. The evidence is consistent with a technology-driven polarization of the labor market, but this cannot explain the country specific differences. Full article

Building on studies on the impact of the Great Recession on the occupational and skill structure of employment, this article investigates developments over the last business cycle (2002–2007 and 2007–2011) in 36 manufacturing and service industries of five major European countries (Germany, France, Spain, Italy and United Kingdom). We analyse how technology, education and wages have shaped the evolution of four professional groups—Managers, Clerks, Craft and Manual workers—defined on the basis of ISCO classes. During the upswing in manufacturing industries all professional groups except managers have experienced job losses, while new jobs in services have followed a pattern of growing occupational polarization. Demand growth has a general positive effect across all occupations; new products lead to job creation in the group of managers only; wage increases slow down job creation except in the lowest occupational group. During the downswing, large job losses are concentrated in the lowest occupations and most relationships—including the role of demand and wages—break down; product innovation loses its positive impact on jobs while new processes drive restructuring and job destruction across all professional groups. Full article