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Explaining Job Polarization: Routine-Biased Technological Change and Offshoring
Abstract
This paper documents the pervasiveness of job polarization in 16 Western European countries over the period 1993–2010. It then develops and estimates a framework to explain job polarization using routine-biased technological change and offshoring. This model can explain much of both total job polarization and the split into within-industry and between-industry components.
... Most works within economic literature have pointed out that employment creation trends in advanced economies from 1980s onwards have followed a polarisation pattern (Autor 2015;Autor and Dorn 2013;Goos et al. 2009Goos et al. , 2014. These works contend that polarisation is a widespread phenomenon characterised by the hollowing out of the centre of the job distribution, i.e. employment growth is higher both at the top and the bottom sides of the wage/skill distribution than in the middle. ...
... Autor et al. 2003Autor et al. , 2006Wright and Dwyer 2003), however an increasing number of works have offered similar evidence in either specific countries like Belgium (Buyst et al. 2018), Germany (Spitz-Oener 2006), Spain (Sebastian 2018), or the UK (Goos and Manning 2007) or on a large sample of European countries (e.g. Acemoglu and Autor 2011;Goos et al. 2014). ...
... To study the evolution of the employment structure of European economies, this paper uses as a unit of analysis the job (not individuals), i.e. specific occupations within specific sectors (Fernandez-Macias 2012, 166). I consider that this approach is preferable to analyse structural transformations of the labour market than using only occupations (Goos et al. 2014; or; Oesch and Piccitto 2019), since it incorporates the abovementioned both horizontal and vertical segmentation of the labour market and because collective bargaining is organised at a sectoral level in most European countries. Thus, there might be a great deal of wage dispersion within the same occupation across sectors. ...
This paper empirically explores occupational change in Europe after the 2008-crisis (the Great Recession). During this period, which has remained relatively unexplored by the literature so far, many European economies have implemented profound institutional changes in their labour markets and transformed their growth models. Using individual-level data of 18 economies, I build three indicators of job quality -the average educational attainment, the median earnings and an index of job instability based on the contractual characteristics of the job- and analyse relative employment growth of jobs. The findings suggest that there is not just one pattern of occupational change in Europe, in opposition to the mainstream view of pervasive polarisation. On the contrary, I detect a variety of occupational change profiles, which even differ within the same country depending on the indicator employed.
... The reason for the emergence of a second approach, the routine-biased technological change (RBTC), is that SBTC cannot explain the recent job polarisation phenomenon (Náplava, 2019). The RBTC (Autor, Levy, and Murnane, 2003;Goos et al., 2014) suggests that the recent technological change leads to the replacement of workers in routine occupations, which is linked mainly to middleskill workers (Nchor and Rozmahel, 2020). Routine occupations can be easily automated and offshored (Autor, Levy, and Murnane, 2003). ...
... For example, according to Nchor and Rozmahel (2020), the results for Central and Eastern European countries are not compelling, and the slight decline in middle-skill workers that appears is the same as the results of Oesch, Rodriguez and Menez (2011). In contrast, Náplava (2019) and Goos et al. (2014) confirm the hypothesis. Further research on the relevance of labour market polarisation to political polarisation should therefore begin with at least a basic determination of whether labour market polarisation is relevant according to the RBTC hypothesis. ...
... However, these measures produced a similar result. The existence of labour market polarisation has already been demonstrated (Náplava, 2019;Goos et al., 2014), but can be partly observed as well as wage polarisation (demonstrated by Wang et al., 2021;Cortes, 2016;Dustmann, Ludsteck and Schönberg, 2009) in the descriptive analysis of this paper. As far as the regression analysis is concerned, the problem may be the insufficient number of variables used to represent the state of the labour market adequately, and the inverse relationship demonstrated is most likely only apparent. ...
The aim of the paper is to prove a hypothesis concerning the dependence of the political polarisation of the European Union on recent developments in labour market structure. The labour market is undergoing changes that stem from technological progress as well as outsourcing of low-skill activities, which are causing an increase in labour market and wage polarisation. The premise is that the depopulation of the middle class is increasing political polarisation. The hypothesis is tested on a sample of 27 European Union countries from 1990 to the present using OLS with fixed effects regression analysis. Political polarization is represented by an own constructed political polarization index based on the ideological division of political parties’ data of the ParlGov project (2022). The index is constructed by combining the election results and four ideological spectrums. In conclusion, the dependence of political polarisation on labour market polarisation and wage polarisation is rejected.
... Economic uncertainty has become more widespread, with individuals often trapped in precarious or low-quality occupations. Low-and medium-educated workers are affected most strongly by the ongoing changes, as routine jobs are being increasingly taken over by robots or moved to low-income countries (Autor et al., 2006;Goos et al., 2014). Whilst emerging new work arrangements (e.g. ...
... Not only do these technologies change the ways in which we work, such as allowing for more flexible working or working from distant locations, but also determine who is in more demand within the labour market. Economic research has demonstrated an increase in the labour demand for cognitive workers, especially those who display strong analytical and social skills, and a decline in the demand for workers who perform routine tasks at work (Acemoglu & Autor, 2011;Autor et al., 2006;Goos et al., 2014;Hardy et al., 2018). In such a context, Adsera and Querin (2023) explore how these changes in the labour demand may affect men and women's earnings. ...
Labour markets in post-industrial countries have been undergoing tremendous transformations in the last two decades, substantially changing the conditions in which young adults take family decisions and raise children. Whilst these changes create new opportunities, they also generate risks which potentially foster uncertain futures and affect individuals’ opportunities to earn income, provide care for family members, and make long-term commitments. This Special Issue aims to stimulate the debate on the effects of rapid labour market transformations and growing uncertainty on families in contemporary wealthiest countries. Its articles suggest that economic uncertainty, the threat of unemployment or precarious employment, and financial difficulties lead to fertility postponement and increase the risk of union disruption. These effects intensify when labour market deregulation goes in tandem with labour market dualization and become more pronounced during periods of economic hardship, such as economic recessions or the COVID-19 pandemic. In addition, the effects of economic activity on family-related behaviours have become less gendered as women increasingly gain economic independence. Finally, it appears that highly educated workers and members of the upper social classes face increasingly better conditions for realising their fertility intentions than their lower-educated counterparts and those of the lower social classes. In this introductory article, we review the theoretical premises and the empirical evidence to provide a comprehensive background on what labour force participation and its conditions imply for family life courses. We then introduce the articles collected in this Special Issue and conclude with a discussion on prospects for future research.
... The growing interest in task content as an explanation for the heterogeneity in the costs of job loss is linked to the research showing that technological change affects the task structures of the economy (e.g., Acemoglu and Autor 2011;Goos et al. 2014;Atalay et al. 2018). There is less demand for routine tasks (see, e.g., Cortes et al. 2017;Atalay et al. 2020), and the occupational wage premia for routine occupations has decreased (Cortes 2016). 2 The demand for social tasks has, in turn, increased, and their labor market return has risen during the past decades (Deming 2017). ...
... As shown in Table 1, occupations differ in both the level and the combination of the various tasks used. The ranking of occupations in terms of routine intensity is similar to that of Goos et al. (2014) and Autor and Dorn (2013). For example, managers and professionals are both occupations that have fewer routine tasks than average across all occupations, whereas plant and machine operators have more routine tasks. ...
Do different tasks shield differently from the scarring effects of job loss? This study examines how the effects of job loss depend on task usage. We use Finnish linked employer–employee data from 2001 to 2016, representative survey data on task usage, and plant closures to identify individuals who involuntarily lose their jobs. We find that heterogeneity in the cost of job loss is linked to task usage. Workers in more social task-intensive origin jobs have smaller employment and earnings losses, whereas workers in routine jobs face larger wage losses. The probability of being employed is 8.3 pp higher (3.9 pp lower) per one standard deviation higher than mean social (routine) task usage 1 year after the job loss event. We also find that workers with longer tenure face larger losses and that task usage contributes more to their losses. The results show that the costs of job loss depend on task usage in the origin job. Public policy measures should be targeted at employees in routine-intensive jobs, since they face the largest losses.
... To explain recent changes, such as increasing job polarization and wage inequality, some researchers have studied skill-biased technological change (SBTC) and routine-biased technological change (RBTC) [39][40][41][42][43][44][45][46]. SBTC refers to the adoption of new technologies that augment the productivity of skilled workers more than unskilled workers. ...
... Nevertheless, the investigation of Goos et al. [44] critiques the SBTC theory because it cannot fully explain why some jobs are disappearing and others are growing in advanced countries. SBTC explains why more educated workers are in demand, but it does not explain job polarization, where both high-skilled and low-skilled jobs increase while middle-skilled jobs decrease. ...
The objective of this work is to predict the impact of technology on employment demand by profession in Spain between 2023 and 2035. The evaluation of this effect involved the comparison of two scenarios: a trend scenario obtained by predicting the evolution of occupations in demand and a technological scenario anticipated in the case of technological progress. To accomplish this goal, a new approach was developed in the present study based on previous research. Thus, we estimated the proportion of jobs likely to be automated using a task-based approach. Each occupation was examined based on its components to determine the degree to which these tasks could be automated. The results suggest that technology may influence job demand but with low percentages (between 3% and 5% for both low- and high-qualified workers) in the long term. However, job losses are greater in absolute difference in low-skilled professions, where a great share of the labor force is engaged.
... Several studies argue that formal and informal institutions play an important role in generating inequality in the labor market (Weeden, 2002;Charles and Grusky, 2004;Bol and Weeden, 2015), but a dominant explanation is to be found in the skills used at work. In particular, recent economic research has argued that the key to understanding inequality across occupations lies in the nature of the tasks performed at work (Autor et al., 2003;Acemoglu and Autor, 2010;Goos et al., 2014;Deming, 2017): workers earn different wages because they are not equally capable of performing the tasks required in occupations. And with technological change, wage premiums go to those who have the skills to meet the growing need for analytical, complex and non-routine tasks (e.g., Autor and Handel, 2013;Haslberger, 2021). ...
... All of this suggests that workers in the same occu-pation possess a distinctive set of skills that is relevant for explaining their labor market outcomes, such as the wage they receive or their ability to change jobs. Previous research has thus tended to conceptually conflate the effects of skills and occupations and to use occupations as an empirical proxy for skills (e.g., Liu and Grusky, 2013;Goos et al., 2014;Fernández-Macías and Hurley, 2016;Mouw et al., 2024). ...
Occupations are a central unit for understanding inequality in the labor market, yet we know little about why occupations matter. The existing literature often assumes that occupations are distinct bundles of skills, so skills are rarely conceptualized and measured independently of occupations. How does this limit our understanding of wage inequality? In this article, we use a unique dataset of millions of online job postings in the United Kingdom to capture the skill content of work at the job level and analyze its relationship to existing occupational classifications. While previous literature has often defined different skills as uni-dimensional and independent from each other, we propose a skill profile approach to capture the combination of skills that workers need on the job. Using topic modeling on highly detailed job skill requirements, we identify the skill profiles of job postings and analyze the extent to which they affect wages within or across occupational categories. Our results reveal substantial heterogeneity in skill content within occupations, and show that both job-level skills and occupations are key to explaining wage differentials across jobs. These findings challenge the often assumed role of occupations as bundles of skills, and offer new perspectives for analyzing labor market stratification.
... Firstly, I can see that there is a substantial variation in the change in exposure across cities. The largest 3 Their mapping of occupations into four different groups (routine-manual, routine-analytic, non-routine routine, and non-routine analytic) is based on Autor et al. (2003) and Goos et al. (2014). 4 The 18 IFR industries are the following. ...
... The increase in robot exposure is negatively associated with the job vacancy growth in routine jobs (Panel A of Fig. 6). Since routine tasks are easily automated by industrial robots, it is natural that the declines in labor demand resulting from robot adoption are pronounced for routine jobs (Autor et al. 2003;Goos et al. 2014). The point estimate for routine jobs is − 0.023 (p value = 0.020), similar to that for the manufacturing sector. 9 One can see there is no evidence that an increase in robot exposure affects the job vacancy growth for non-routine jobs (Panel B of Fig. 6). ...
The debate about the impact of robots on employment has been lively. In this paper, I examine the effect of robots on local labor demand in South Korea, one of the most technologically advanced countries in terms of robotics. Using the regional variation in robot exposure constructed from national industry-level robot adoption data and the initial distribution of industrial employment in cities, I find that robots did not reduce local labor demand. However, I estimate declines in labor demand in the manufacturing sector and routine jobs. An increase in one robot per 1000 workers in terms of exposure to robots is correlated with a decline in the job vacancy growth rate of 2.6%p in the manufacturing sector and of 2.5%p in routine jobs. No significant relationship is found between robot exposure and labor demand in the service sector or non-routine jobs.
... 20 Susskind (2022, 644) refers to Autor (2019) for evidence on declining wages of non-college workers. 21 See Goos, Manning and Salomons (2014). 22 The SA model is not mentioned much in the literature on AI and work. ...
The thesis of a capitalist road to communism (van der Veen and Van Parijs, 1986) asserts that Marx realm of freedom can be reached from within welfare capitalism, skipping socialism, by using a tax-financed unconditional basic income until it is close to disposable income per head, so that the very distinction between paid work and free time is cancelled as a result. We revisit and update this thesis for two reasons: the recent prospect of a post-labor society following the automation revolution in technology, and that welfare capitalism has become more inegalitarian and less hospitable to basic income. We use a simple economic model which incorporates an upward adjustment of basic income to labor-saving technical change and distinguishes between capital that complements labor and capital that is fully substitutable with labor. A baseline simulation of the model shows the economic feasibility of a capitalist transition to communism. Two versions of a scenario incorporating interplay between technical change and market socialist institutional reforms are set out which make the transition politically viable to some extent, depending on the social distribution of power over technology. The most promising version is one in which the productivity of labor and automation capital grow at similar rates. We show in which respects it approximates the ideal of communism. One finding is that communism does not require reaching the final stage of a post-labor society. We conclude with a reflection on the relevance of our present update for the more immediate future of unconditional basic income.
... And for good empirical reasons it seems, as studies have repeatedly highlighted such a correlation between automation and job polarisation (e.g. Jaimovich 2022; Jerbashian 2019;Goos, Manning, and Salomons 2014). ...
Over the last decade, rapid advancements in artificial intelligence and other automation technologies have sparked extensive and sometimes heated debates over the wider societal impacts of ongoing technological shifts. Even if there is wide agreement that policymaking will play a crucial role for how the future of automation will unfold, these debates tend to emphasise the technical and economic aspects of labour automation while largely overlooking its inherently political dimensions. In recent years, critical scholars within the social sciences have sought to challenge this narrow focus by bringing attention to the various biased effects that automation processes give rise to in terms of justice and power, but automation of labour as a political issue in and of itself remains underexplored. Given the broad acknowledgement of the importance of policymaking, what is especially needed is an increased understanding of how policymakers themselves interpret this issue, as well as their own roles in relation to it. This thesis aims to narrow this knowledge gap by examining the manifest and latent political ideas that underpin the ways in which Swedish policymakers interpret and negotiate the issue of automation, to thereby gain a fuller understanding of what key values that are at stake in the Swedish automation debate. To do so, an ideational analysis has been conducted using parliamentary documents, media and party texts, as well as semi-structured interviews with policymakers as data.
The analysis shows that while Swedish policymakers generally perceive automation of labour as a non-contentious issue in Swedish politics, their ideas on the matter are informed by underlying normative and empirical assumptions that lead to conflicting conclusions regarding both the desirability of increased automation and the roles of policymaking for governing the technologies in question. The analysis also finds that actors’ views on automation are tightly connected to their views on a range of related, more fundamental, political issues – such as the character and values of human labour, and the role of the state in relation to the market. Since these related issues are indeed quite ideologically polarising in the Swedish context, the findings indicate that also automation is a more polarising issue than many policymakers perceive it to be. In other words, while the issue has yet to cause any explicit political conflicts in the Swedish debate, the identified disparities and ideational tensions clearly suggest that automation is not merely a technological inevitability but a complex, politically charged arena where different, if often latent, visions of the future contend.
Thus, the portrayal of automation as a politically neutral phenomenon risks obscuring its inherently contestable character and preventing the critical ideological debates that therefore ought to surround it. By bringing our attention to the different and sometimes conflicting political ideas that automation is subject to, the thesis aims to contribute to a more politicised automation debate in which said ideas are not shied away from but openly contested and deliberated over. Such a debate would not only be more democratic, but also more likely to realise some of the unprecedented opportunities that automation technologies grant us.
... Some of the economic causes can be globalization and technological advances. see Guriev and Papaioannou (2022) and Rodrik (2021) because, despite being in times of the greatest economic prosperity in human history, globalization creates losers and winners, implying labor polarization in advanced economies, see Autor and Dorn (2013) and Goos, Manning, and Salomons (2014). Another important factor that has encouraged the rise of populism is people's distrust of traditional parties, leading them to vote for "antiestablishment" parties , see Algan et al. (2017), Gidron and Hall (2017), and Colantone and Stanig (2018). ...
This study examines the effects of political instability on macroeconomic and human capital variables using two distinctive measures. I use a database covering over 180 countries from 1960-2022 to do so. The estimates are based on panel data regressions and local projections. The findings show that political instability significantly negatively affects economic growth and foreign direct investment and increases government spending, inflation rate, unemployment rate, total factor productivity, and trade openness. Additionally, it negatively affects inequality, migration, poverty, vulnerability , and migration. It also finds that free countries or full democracies are more resilient to political instability. These findings suggest that strengthening political and economic institutions is crucial to mitigate the negative effects of political instability on economic and social well-being.
... More recently, Michaels et al. (2014) and Epifani and Gancia (2008) find results suggesting polarizing and skillbiased effects of international trade, respectively. Goos et al. (2014) also find evidence to suggest that offshoring can lead to job polarization. ...
In this paper, we study the asymmetric effects of different types of capital-embodied technological change, as proxied by tangible and intangible assets, on relative wages (high- to medium-skilled, high- to low-skilled and medium- to low-skilled workers), relying upon the technology-skill complementarity and polarization of the labor force frameworks. We also consider two additional major channels that contribute to shaping wage differentials: globalization (in terms of trade openness and global value chains participation) and labor market institutions. The empirical analysis is carried out using a panel dataset comprising 17 mostly advanced European economies and 5 industries, with annual observations spanning the period 2008–2017. Our findings suggest that software and databases—as a proxy for intangible technologies—exert downward pressure on low-skilled wages, while robotics is associated with a polarization of the wage distribution at the expense of middle-skilled labor. Additionally, less-skilled workers’ relative wages are negatively affected by trade openness and global value chain participation, but positively influenced by sector-specific labor market regulations.
... Computer applications have led to a polarization phenomenon in the US labor market [36]. Subsequently, scholars used the ALM model and data from various countries such as the United States, the United Kingdom, Japan, and Europe to verify the polarized impact of information and communication technology on employment [37,38]. ...
One of the key driving factors for achieving the goal of sustainable economic development is to ensure decent employment opportunities. This article explores the relationship between industrial intelligence and sustainable development in China from the perspective of employment. Based on interprovincial panel data from 2006 to 2019, using the fixed-effect regression model and mediating-effect regression model, this study empirically tests the impact of industrial intelligence on sustainable employment in China. The following conclusions are drawn: (1) Industrial intelligence has a significant positive impact on the overall scale of employment. Industrial intelligence has promoted the optimization and upgrading of employment skill structure and industrial structure. Industrial intelligence will reduce the employment proportion of low-skilled labor and increase the employment proportion of medium-skilled labor and high-skilled labor. Industrial intelligence significantly reduces the employment share of the manufacturing sector and increases the employment share of the service sector. (2) Industrial intelligence reduces employment levels through capital deepening effects. Industrial intelligence has significantly improved regional labor productivity and significantly improved employment levels through productivity effects. (3) The results of regional heterogeneity show that industrial intelligence has promoted the improvement of employment level and the upgrading of employment structure in the eastern region but has not had a significant positive impact on other regions.
... Scholars have referred to this phenomenon as 'Skilled-Biased Technological Changes' (SBTC). The analysis of the empirical data of the manufacturing industries in European and American countries confirmed that AI has the strongest substitution effect on the medium-skilled labor force while positively affecting the high-and low-skilled labor forces [12,13]. Lv and Zhang conducted an in-depth analysis of China's manufacturing industry and showed similar results, with an increased employment structure for high-and low-skilled workforce, an increased proportion of high-and low-technology industries, and a decreased proportion of employment in the technology industry [14]. ...
As the wave of industrial intelligence (AI) swept, the demographic dividend era in the Chinese labor market continued to decrease. This study aimed to explore how AI reshaped the labor employment structure of the floating population. Additionally, it clarified the internal mechanism of AI on the employment structure of the floating population based on the existing AI model and the theoretical model of AI technology. At the same time, the workforce was divided into high-, medium-, and low-skilled groups according to education level. Empirical analysis was conducted using relevant data from 31 Chinese provinces spanning from 2012 to 2018. The aim was to test the impact of AI technology on the employment of different types of floating populations. The results indicated that: (1) industrial robots impacted heterogeneous skilled floating population labor by bipolar promotion and central substitution. (2) The application of industrial robots had a promotion effect on unfinished school and primary school groups, a substitution effect on middle school, high school/technical secondary school, and college specialties, and a promotion effect on college undergraduate and graduate students. (3) Distinguish employment status, industrial robot application had a significant negative impact on low-skilled employees and significant positive effects on high-skilled employers. Hence, it was recommended to put forward corresponding policy suggestions to address this issue.
... Moreover, technological change represents a well-known driver of income disparities, especially because of the positive impact it may exert on wage inequality in advanced countries (Autor et al., 1999;Card and DiNardo, 2002;Acemoglu and Autor, 2011). Controlling for the technological progress of economies is especially important in our analysis in order to disentangle the specific impact of countries' involvement in GVCs from the effects that technology may have on wage income polarization (Goos et al., 2014). In fact, phenomena of skill-and routine-biased technological change can resemble the distributional effects predicted by the literature on production offshoring, therefore representing a confounding factor in our empirical estimates (Acemoglu and Autor, 2011;Jaumotte et al., 2013;Reijnders and de Vries, 2018). ...
This work addresses the nexus between Global Value Chains (GVCs) and within-country inequality by distinguishing two key dimensions: the “product-level positioning” of economies, i.e. their involvement in more upstream or downstream industries, and their “functional positioning”, defined by the value-adding activities performed along GVCs. Using trade and FDI data on 101 countries in 2003-2015, we show that a more upstream product-level positioning is associated with higher inequality in low- and middle-income countries. This is consistent with these countries’ greater involvement in industries supplying raw materials and energy inputs, characterised by a remarkable income polarisation. Conversely, a more downstream product-level positioning goes together with greater inequality in high-income countries, reflecting downward pressures on labour income due to massive outsourcing of inputs to foreign suppliers. As for functional positioning, we find that a greater involvement of economies in pre- and post-production stages is associated with lower income disparities, while a larger engagement in production operations goes together with higher inequality. This result is driven by low- and middle-income countries, suggesting that a greater involvement in knowledge-intensive GVC activities fosters technological upgrading in these economies, with beneficial effects also on the lower segments of the labour force.
... I therefore rely on similarity of the content of occupations between the two countries. Other researchers have applied the O*NET data to the European context (e.g., Goos et al., 2014;Hardy, Keister, and Lewandowski, 2018;Lewandowski, 2020), including the UK (Jolivet & Postel-Vinay, 2020). Applying the O*NET data to the UK is appropriate for several reasons: firstly, the UK and the US are at similar stages of economic development, with similar levels of education 7 and access to technology. ...
I investigate heterogeneity across occupational characteristics in the effect of retirement eligibility on mental health in the United Kingdom. I use K‐means clustering to define three occupational clusters, differing across multiple dimensions. I estimate the effect of retirement eligibility using a Regression Discontinuity Design, allowing the effect to differ by cluster. The effects of retirement eligibility are beneficial, and greater in two clusters: one comprised of white‐collar jobs in an office setting and another of blue‐collar jobs with high physical demands and hazards. The cluster with smaller benefits mixes blue‐ and white‐collar uncompetitive jobs with high levels of customer interaction. The results have implications for the distributional effect of raising the retirement age.
... One important driver of lack of job opportunities and wage growth for less educated workers has been the adoption of new technologies. Automation and other forms of technology have replace the routine tasks previously done by low-and medium-skilled workers, putting pressure on job opportunities and wages at the bottom (see, e.g., Acemoglu and Autor, 2011;Autor et al., 2003;Goos et al., 2014;Michaels et al., 2014). ...
Several decades ago, Sig Prais concluded that the root cause of the UK’s poor industrial performance was the poor quality of education and training. In this lecture, I will make a related argument, focussing on the lack of opportunity in the United Kingdom for workers who have not succeeded in the formal education system and the long-lasting impacts this has on their economic, health and social wellbeing. I will highlight the importance of providing opportunities for continued training over a worker’s lifetime for appropriate skills that are valued in the workplace in order to achieve inclusive growth.
... -збільшилася кількість високооплачуваних професій, особливо у сфері фізики, математики та інженерії, у всіх досліджуваних країнах, зокрема в Люксембурзі, Фінляндії, Ірландії та Іспанії [42]. ...
Як зазначає Б. Рідінгс, ми спостерігаємо, як значно збільшуються показники міжнародної міграції. Головними причинами міграційних процесів стають економічні чинники. На вимогу глобального ринку, міжнародні об’єднання документально фіксують необхідність міжнародної і міждисциплінарної гнучкості (мобільності) як окремих індивідів, так і суб’єктів господарювання. Сутність сучасної влади є такою, що концепція «розподілу культурного капіталу залежно від близькості до культурного центру» стає неактуальною. «Центр вже не є реальним місцем… у центрі більше нікого немає». Унаслідок занепаду інституту національної держави, що раніше «втілювала капітал і виражала його у формі культури, яка проникала по всьому полю культури», сьогодні «капітал не розтікається з центру, скоріше він циркулює по колу, за спинами тих, хто не відводить очей з центра.
... However, the next thing is overcapacity, and the problem of ecological environment has become more prominent, which has followed the old path of "development first and governance later", making the contradiction between ecological environment, governance and protection, the contradiction between unreasonable industrial structure and excess capacity, the contradiction between the domestic market and the international market (Goos et al, 2014). ...
As a core part of the national economy, manufacturing is the key to achieving sustainable economic development. However, the development of China's manufacturing industry faces many problems, such as poor industrial structure, lack of key core technologies, and serious overcapacity, which seriously affect the quality of China's manufacturing industry. The Yangtze River Economic Belt not only has great strategic significance for coordinating the development of the east, middle and west China, but also a demonstration belt for the sustainable development of manufacturing industries. Amid the Chinese government's "double carbon" implementation in 2020, how to transform and upgrade these export manufacturing enterprises and find a path to sustainable development is a major challenge they will have to face. Therefore, on the basis of combing domestic and foreign literature, taking "quality-sustainable development-sustainable development of manufacturing industry" as the logic line, and combine the theory of sustainable development, environmental Kuznets curve theory, equatorial principle theory, and corporate governance theory. Second, it measures and evaluates the sustainable development of manufacturing industry in the Yangtze River Economic Belt from 2007 to 2019 through quantitative research. Conclusions: When assessing the status, the quality level of sustainable development of manufacturing industry in the Yangtze River Economic Belt has been steadily improving, more than 80% of the provinces and cities in the Yangtze River Economic Belt have high and medium quality. Finally, targeted countermeasures and proposals are put forward.
... On the other hand, the routine-based technological change (RBTC) hypothesis states that new technologies tend to replace job functions that follow predictable and repetitive patterns (routine tasks), while more complex and non-routine tasks may require human intervention, which may lead to a displacement of unskilled workers (Goos et al., 2014;Jaimovich and Siu, 2020). This hypothesis could also be applied to eco-innovation by considering how technologies affect routine tasks in the context of sustainable practices. ...
Purpose
This paper aims to clarify the relationship between digital transformation and labor structure from the perspectives of microenterprise business strategies and factor allocation efficiency. It attempts to address the gap in existing research by explaining the impact of digital transformation on multidimensional workforce structures and the positive effects of this structural adjustment on labor allocation efficiency. In addition, the study further explores the economic ramifications of digital transformation, clarifying the correlation between changes in labor force structure and enterprise human resource allocation, thus enhancing the employment mobility effects of digital innovation at the enterprise level.
Design/methodology/approach
In contrast to prior research, our approach uses text analytics to assess the internal labor structure, incorporating labor skill, position and age into the analytical framework. This approach yields a more comprehensive data set, shedding light on variations in multidimensional employment structures.
Findings
The paper asserts that digital transformation significantly influences labor structure changes, evidenced by increased proportions of high-skilled, non-routine and younger laborers, as well as decreased shares of low-skilled, routine and older-age workers. Furthermore, it captures internal labor structure impacts, influenced by enterprise size, ownership, industry density and regional digitization levels. Mechanism analysis indicates moderation of digital transformation effects on labor structure by innovative tasks, labor productivity and management shareholding.
Social implications
The paper reveals the specific impact of corporate digital transformation on workforce structure, enriching the employment mobility effects of digital innovation at the enterprise level and providing theoretical support for the formulation and implementation of relevant policies.
Originality/value
First, this paper delves into the impact of digital transformation on the internal labor structure from a microlevel perspective, elucidating its mechanisms. Second, in contrast to prior research, it uses text analytics to assess the internal labor structure, incorporating labor skill, position and age into the analytical framework. This approach yields a more comprehensive data set, shedding light on variations in multidimensional employment structures. Lastly, the study investigates the economic ramifications of shifts in employment structures. The findings of this study furnish novel empirical evidence for the debate regarding whether digital transformation can indeed enhance labor allocation efficiency.
Résumé
Les auteurs font appel à l'apprentissage profond et au traitement du langage naturel pour construire des indicateurs de compétences et de distance professionnelle comparables entre pays, qu'ils utilisent pour produire des faits descriptifs sur les transitions professionnelles et la distribution des salaires au Brésil. À partir de données sur l'ensemble des contrats de travail formels conclus entre 2003 et 2018, ils constatent que les travailleurs mobilisant surtout des compétences cognitives non routinières sont mieux lotis en termes d'emploi, de salaire et de transition professionnelle. Ils observent des signes de progrès technologique biaisé et de polarisation de l'emploi après la crise économique brésilienne de 2014.
Resumen
En este artículo se presentan dos métodos para obtener medidas de calificación profesional y distancias ocupacionales de comparabilidad internacional, basados en técnicas de aprendizaje automático y de procesamiento del lenguaje natural. Con estas medidas se generan hechos descriptivos sobre las transiciones laborales y la distribución salarial en el Brasil, tras analizar todos los contratos de trabajo formales registrados en el periodo 2003‐2018. Los trabajadores que utilizan intensivamente competencias cognitivas no rutinarias obtienen mejores resultados en cuanto al empleo, los salarios y el cambio de ocupación. Tras la crisis económica brasileña de 2014, se observan indicios de cambio tecnológico con sesgo de rutina y de polarización del empleo.
This is the introductory chapter for the book entitled Scrutinizing Polarization: Patterns and consequences of occupational transformations in the Swedish labour market (Routledge). The starting point of the book is the changing employment and job structure in Western economies, and the Swedish economy in particular, and the question of whether these economies are moving towards polarisation. A lot of the previous research has regarded digital technological advancements as the main driver of occupational change. However, in this book we argue that the perspective must be widened, both when it comes to indicators measuring change, and regarding causes of occupational transformation. Concerning the latter, and particularly in the Swedish or Nordic context, changes in the large public sector, mainly caused by political priorities rather than technological change, need to be considered. This introductory chapter also scrutinises what the concept of polarisation means and refers to. Distinctions among value polarisation, bi-polarisation and social polarisation are discussed and put in motion in the analyses in this book. The chapter ends with a brief overview of the themes and analysis of the different chapters.
In this article, we study the role of automation risks in the school-to-work transition (STWT) of secondary vocational education (VET) graduates in the Netherlands. We use a combination of administrative and survey data, enriched with estimates of automation risks. Using sequence analysis, we find four ideal-type school-to-work trajectories representing the first 10 years in the labor market: employment, further education, further VET, and NEET. Multinomial regressions show that automation risk is not consistently associated with the type of school-to-work trajectory. We also investigate the relation between automation risk and starting wages and wage growth. We find that automation risk is negatively associated with starting wages, but not with wage growth.
Recent robotics and artificial intelligence advancements have exacerbated fears of technology-driven unemployment and inequality. However, the relationship between automation risks and regulatory policy support remains inconclusive. Moreover, the role of institutional safety net in shaping this connection, and factors influencing preference shifts regarding automation, remain understudied. This study conducts an online survey experiment in the UK and Sweden to address these gaps. First, we find subjective concern, and occupational risks combined with perceived weaker labor market safeguards, lead to calls for automation restriction and job loss compensation. These trends are particularly pronounced in the UK, where institutional protection for workers is less robust. Second, people support accelerating technology-driven change when they see its benefits shared widely, but this shift is mainly observed among individuals relatively safer from automation risks. Our findings suggest strengthening the institutional safety net and envisioning equitable benefit-sharing are crucial for moderating public anxiety toward technology-driven economic change.
We examine the rise of “Guard Labor”—defined as occupations devoted to labor extraction—at the commuting zone level in the United States. Between 1950 and 2017 the share of the labor force employed in guard labor increased from 19.5 percent to 29.4 percent. We explore the local labor market correlates of guard labor and validate several predictions of the labor discipline model, while extending the model to the context of contemporary racial capitalism. The share of the labor force employed in guard labor is positively correlated with the household income Gini coefficient, negatively correlated with the fraction of the labor force in a union, and positively correlated with contemporary measures of local racial animosity. Consistent with the labor discipline model, an increase in the share of the labor force employed in supervisory occupations has a significant negative effect on nonsupervisory wages.
JEL Classification: O17, P16, Z13, B51, B52
This chapter focuses on the impact of digitalisation on employees, labour markets and the distribution of incomes. It distinguishes between occupations and tasks and shows that digitalisation may cause displacement effects, but can hold the potential for employment growth. It also treats qualitative aspects and how digital technology effects the structure of employment. It discusses changes in working conditions and employment relationships and discusses the extent to which the opportunities offered by digitalisation are leading to concentration trends. Accordingly, it draws some conclusions about the corresponding implications for policy.
This article introduces two methods to derive internationally comparable skill and occupational distance measures based on machine learning and natural language processing techniques. We apply these measures to produce descriptive facts about employment transitions and workers’ wage distribution in Brazil using all formal labour contracts registered in the period 2003‐18. Our findings indicate that workers who use non‐routine cognitive skills intensively are better off in terms of employment, wages and switching occupation. Overall, we observe signs of routine‐biased technological change and employment polarization following the Brazilian economic crisis of 2014.
Using an occupational probability of computerization, we measure a firm’s ability to replace labor with automated capital. Our evidence suggests that the potential to automate a workforce enhances operating flexibility, allowing firms to hold less precautionary cash. To provide evidence for this mechanism, we exploit the 2011–2012 Thailand hard drive crisis as an exogenous shock to the cost of automation. In addition, the negative relation between prospective automation and cash holdings is greater for firms with a lower expected cost of worker displacement and greater labor-induced operating leverage.
This paper was accepted by Lukas Schmid, finance.
Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.03902 .
Lifelong education has proven to be a significant challenge in the policy arena. The combination of formal education and labor-centered institutions has pressed the development of different mechanisms to understand the role of human capital accumulation in socioeconomic mobility and organizational performance. While the narratives of lifelong education have primed labor and educational studies across developed economies, in the case of developing economies, those logics appear contested by development economics conditions. In this paper, I use the context of the expansion of the graduate educational market and its policy reforms to analyze how a developing economy copes with a change in the availability of a highly educated workforce. Using panel and pseudo-panel data, I examine the evolution of educational returns for the graduate workforce in Chile between 1990 and 2018, considering the differences between industries and public and private sectors. The results point out that there are no public-private differences and high heterogeneity across economic sectors. The policy- and individual-level consequences are discussed.
How should the government respond to automation? We study this question in a heterogeneous agent model that takes worker displacement seriously. We recognize that displaced workers face two frictions in practice: reallocation is slow and borrowing is limited. We analyze a second best problem where the government can tax automation but lacks redistributive tools to fully alleviate borrowing frictions. The equilibrium is (constrained) inefficient and automation is excessive. Firms do not internalize that automation depresses the income of automated workers early on during the transition, precisely when they become borrowing constrained. The government finds it optimal to slow down automation on efficiency grounds, even when it does not value equity. Quantitatively, the optimal speed of automation is considerably lower than at the laissez-faire. The optimal policy improves efficiency and delivers meaningful welfare gains.
Para entender as mudanças sociais ocorridas nos últimos anos, o Instituto de Pesquisa Econômica Aplicada (Ipea) criou o projeto Dinâmica Econômica, Mudanças Sociais e Novas Pautas de Políticas Públicas. O objetivo deste projeto é propor tipologias de estruturas de classe no Brasil que possam ser úteis para a elaboração de políticas públicas, em um contexto de mudança da estrutura produtiva da economia brasileira e da estrutura ocupacional, marcada pela redução relativa da ocupação industrial e do crescimento dos serviços. A hipótese que dirige a proposta de pesquisa é que essa nova reconfiguração produtiva tem implicações para a estratificação social brasileira, com o surgimento de novas demandas de políticas sociais, em razão do surgimento de novos grupos ocupacionais ou da ampliação/redução de grupos sociais que já existem. Ou seja, a dinâmica econômica do início do século XXI está reconfigurando a estrutura social brasileira. Nesse sentido, a aplicação da metodologia do mapeamento da estrutura de classes permite identificar essa reconfiguração da estrutura social brasileira, detectar o surgimento de demandas de políticas públicas ou possibilitar a adaptação de outras.
This paper demonstrates that the decline in routine occupations and concurrent rise in abstract occupations are largely due to workers changing jobs. The reduction in routine manual tasks is further explained by workers transitioning to unemployment or retirement. In contrast, the increase in non‐routine manual occupations is primarily driven by the entry of young or unemployed individuals into the workforce. Plant closure information is used to identify involuntary job separations. These findings indicate that routine cognitive workers can adjust to smaller employment disruptions compared to routine manual workers among women. However, a contrasting pattern is observed for men.
Is labor-saving technological change efficient when labor market frictions arise? Does it exacerbate them? This paper presents a growth model with R&D and two types of technological change: labor-saving technological change, which reduces the labor share (the output elasticity of labor), and labor-complementary, which increases it. The paper presents two kinds of friction in the labor market: unemployment and dual labor markets. When there are dual labor markets, the marginal product of labor and the wages are higher in the “good-jobs sector” than in the “bad-jobs sector,” involving an inefficiently low amount of labor allocated to the good-jobs sector. Labor-saving technological change exacerbates the source of inefficiency in the labor market. It raises unemployment and destroys jobs in the good-jobs sector, generating negative external effects in the labor market. Consequently, investment in labor-saving technological change is inefficiently large and should be taxed. The results regarding labor-complementary technological change are the opposite.
JEL: D60, E24, J31, J50, J60, H21, H23, O30, O41.
Purpose
This study developed new measures of the routine and non-routine task contents of managerial, professional, technical, and clerical occupations from a workload perspective. Here, we present a comparative analysis of the workload structures of state and industrial sector employees.
Design/methodology/approach
Our method involves detailed descriptions of work processes and an element-wise time study. We collected and analysed data to obtain a workload structure that falls within three conceptual task categories: (i) non-routine analytic tasks, (ii) non-routine interactive tasks and (iii) routine cognitive tasks. A total of 2,312 state and industrial sector employees in Kazakhstan participated in the study. The data were collected using a proprietary web application that resembles a timesheet.
Findings
The study results are consistent with the general trend reported by previous studies: the higher the job level, the lower the occupation’s routine task content. In addition, the routine cognitive task contents of managerial, professional, technical, and clerical occupations in the industrial sector are higher than those in local governments. The work of women is also more routinary than that of men. Finally, vthe routine cognitive task contents of occupations in administrative units are higher than those of occupations in substantive units.
Originality/value
Our study sought to address the challenges of using the task-based approach associated with measuring tasks by introducing a new measurement framework. The main advantage of our task measures is a direct approach to assessing workloads consisting of routine tasks, which allows for an accurate estimation of potential staff reductions due to the automation of work processes.
This paper analyzes a marked change in the evolution of the U.S. wage structure over the past fifteen years: divergent trends in upper-tail (90/50) and lower-tail (50/10) wage inequality. We document that wage inequality in the top half of distribution has displayed an unchecked and rather smooth secular rise for the last 25 years (since 1980). Wage inequality in the bottom half of the distribution also grew rapidly from 1979 to 1987, but it has ceased growing (and for some measures actually narrowed) since the late 1980s. Furthermore we find that occupational employment growth shifted from monotonically increasing in wages (education) in the 1980s to a pattern of more rapid growth in jobs at the top and bottom relative to the middles of the wage (education) distribution in the 1990s. We characterize these patterns as the %u201Cpolarization%u201D of the U.S. labor market, with employment polarizing into high-wage and low-wage jobs at the expense of middle-wage work. We show how a model of computerization in which computers most strongly complement the non-routine (abstract) cognitive tasks of high-wage jobs, directly substitute for the routine tasks found in many traditional middle-wage jobs, and may have little direct impact on non-routine manual tasks in relatively low-wage jobs can help explain the observed polarization of the U.S. labor market.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.
We estimate how offshoring and exporting affect wages by skill type. Our data match the population of Danish workers to the universe of private-sector Danish firms, whose trade flows are broken down by product and origin and destination countries. Our data reveal new stylized facts about offshoring activities at the firm level, and allow us to both condition our identification on within-job-spell changes and construct instruments for offshoring and exporting that are time varying and uncorrelated with the wage setting of the firm. We find that within job spells, (1) offshoring tends to increase the high-skilled wage and decrease the low-skilled wage; (2) exporting tends to increase the wages of all skill types; (3) the net wage effect of trade varies substantially across workers of the same skill type; and (4) conditional on skill, the wage effect of offshoring exhibits additional variation depending on task characteristics. We then track the outcomes for workers after a job spell and find that those displaced from offshoring firms suffer greater earnings losses than other displaced workers, and that low-skilled workers suffer greater and more persistent earnings losses than high-skilled workers.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.
Using the 2003 National Survey of College Graduates, I examine how immigrants perform relative to natives in activities likely to increase U.S. productivity, according to the type of visa on which they first entered the United States. Immigrants who first entered on a student/trainee visa or a temporary work visa have a large advantage over natives in wages, patenting, commercializing or licensing patents, and publishing. In general, this advantage is explained by immigrants' higher education and field of study, but this is not the case for publishing, and immigrants are more likely to start companies than natives with similar education. Immigrants without U.S. education and who arrived at older ages suffer a wage handicap, which offsets savings to the United States from their having completed more education abroad. Immigrants who entered with legal permanent residence do not outperform natives for any of the outcomes considered.
OECD labor markets have become more “polarized” with employment in the middle of the skill distribution falling relative to the top and (in recent years) also the bottom of the skill distribution. We test the hypothesis of Autor, Levy, and Murnane (2003) that this is partly due to information and communication technologies (ICT) complementing the analytical tasks primarily performed by highly educated workers and substituting for routine tasks generally performed by middle educated workers (with little effect on low educated workers performing manual non-routine tasks). Using industry level data on the US, Japan, and nine European countries 1980-2004 we find evidence consistent with ICT-based polarization. Industries with faster growth of ICT had greater increases in relative demand for high educated workers and bigger falls in relative demand for middle educated workers. Trade openness is also associated with polarization, but this is not robust to controls for technology (like R&D). Technologies can account for up to a quarter of the growth in demand for the college educated in the quarter century since 1980.
Empirical work has been limited in its ability to directly study whether skill requirements in the workplace have been rising and whether these changes have been related to technological change. This article answers these questions using a unique data set from West Germany that enabled me to look at how skill requirements have changed within occupations. I show that occupations require more complex skills today than in 1979 and that the changes in skill requirements have been most pronounced in rapidly computerizing occupations. Changes in occupational content account for about 36% of the recent educational upgrading in employment.
A recent "revisionist" literature characterizes the pronounced rise in U.S. wage inequality since 1980 as an "episodic" event of the first half of the 1980s driven by nonmarket factors (particularly a falling real minimum wage) and concludes that continued increases in wage inequality since the late 1980s substantially reflect the mechanical confounding effects of changes in labor force composition. Analyzing data from the Current Population Survey for 1963 to 2005, we find limited support for these claims. The slowing of the growth of overall wage inequality in the 1990s hides a divergence in the paths of upper-tail (90/50) inequality-which has increased steadily since 1980, even adjusting for changes in labor force composition-and lower-tail (50/10) inequality, which rose sharply in the first half of the 1980s and plateaued or contracted thereafter. Fluctuations in the real minimum wage are not a plausible explanation for these trends since the bulk of inequality growth occurs above the median of the wage distribution. Models emphasizing rapid secular growth in the relative demand for skills-attributable to skill-biased technical change-and a sharp deceleration in the relative supply of college workers in the 1980s do an excellent job of capturing the evolution of the college/high school wage premium over four decades. But these models also imply a puzzling deceleration in relative demand growth for college workers in the early 1990s, also visible in a recent "polarization" of skill demands in which employment has expanded in high-wage and low-wage work at the expense of middle-wage jobs. These patterns are potentially reconciled by a modified version of the skill-biased technical change hypothesis that emphasizes the role of information technology in complementing abstract (high-education) tasks and substituting for routine (middle-education) tasks. Copyright by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.
This paper develops tools and techniques to study the impact of exogenous changes in factor supply and factor demand on factor allocation and factor prices in economies with a large number of goods and factors. The main results of our paper characterize sufficient conditions for robust monotone comparative statics predictions in a Roy-like assignment model. These general results are then used to generate new insights about the consequences of globalization.
Census data show that since 1980 low-skill workers in the United States have been increasingly employed in the provision of non-tradeable time-intensive services - such as food preparation and cleaning - that can be broadly thought as substitutes of home production activities. Meanwhile the wage gap between this sector and the rest of the economy has shrunk. If skilled workers, with their high opportunity cost of time, demand more of these time-intensive services, then wage gains at the top of the wage distribution (such as those observed in the last three decades) are expected to raise the consumption of these services, consistent with these stylized facts. Using both consumption expenditure data and city-level data on employment and wages of workers of different skills, we provide several pieces of evidence in favor of these demand shifts, and we argue that they provide a viable explanation for the growth in wages at the bottom quantiles observed in the last fifteen years.
We apply an understanding of what computers do to study how computerization alters job skill demands. We argue that computer capital (1) substitutes for workers in performing cognitive and manual tasks that can be accomplished by following explicit rules; and (2) complements workers in performing nonroutine problem-solving and complex communications tasks. Provided these tasks are imperfect substitutes, our model implies measurable changes in the composition of job tasks, which we explore using representative data on task input for 1960 to 1998. We find that within industries, occupations and education groups, computerization is associated with reduced labor input of routine manual and routine cognitive tasks and increased labor input of nonroutine cognitive tasks. Translating task shifts into education demand, the model can explain sixty percent of the estimated relative demand shift favoring college labor during 1970 to 1998. Task changes within nominally identical occupations account for almost half of this impact.
I apply Ricardo’s principle of comparative advantage to a theory of factor substitutability in a model with a continuum of worker and job types. Highly skilled workers have a comparative advantage in complex jobs. The model satisfies the distance‐dependent elasticity of substitution (DIDES) characteristic: substitutability between types declines with their skill distance. I analyze changes in relative wages due to human capital accumulation. The concept of a complexity dispersion parameter or compression elasticity is introduced. Empirical studies suggest its value to be equal to two: a 1 percent increase in the stock of human capital reduces the Mincerian return by 2 percent.
This paper reports on a household survey specially designed to measure what we call the “offshorability” of jobs, defined as the ability to perform the work duties from abroad. We develop multiple measures of offshorability, using both self-reporting and professional coders. All the measures find that roughly 25% of U.S. jobs are offshorable. Our three preferred measures agree between 70% and 80% of the time. Furthermore, professional coders appear to provide the most accurate assessments, which is good news because the Census Bureau could collect data on offshorability without adding a single question to the CPS. Empirically, more educated workers appear to hold somewhat more offshorable jobs, and offshorability does not have systematic effects on either wages or the probability of layoff. Perhaps most surprisingly, routine work is no more offshorable than other work.
There is little doubt that technology has had the most profound effect on altering the tasks that we humans do in our jobs. Economists have long speculated on how technical change affects both the absolute demand for labour as a whole and the relative demands for different types of labour. In recent years, the idea of skill-biased technical change has become the consensus view about the current impact of technology on labour demand, namely that technical change leads to an increase in the demand for skilled relative to unskilled labour painting a bleak future for the employment prospects of less-skilled workers. But, drawing on a recent paper by Autor, Levy and Murnane (2003) about the impact of technology on the demand for different types of skills, this paper argues that the demand in the least-skilled jobs may be growing. But, it is argued that employment of the less-skilled is increasingly dependent on physical proximity to the more-skilled and may also be vulnerable in the long-run to further technological developments.
This paper shows the employment structure of 16 European countries has been polarizing in recent years with the employment shares of managers, professionals and low-paid personal services workers increasing at the expense of the employment shares of middling manufacturing and routine office workers. To explain this job polarization, the paper develops and estimates a simple model to capture the effects of technology, globalization, institutions and product demand effects on the demand for different occupations. The results suggest that the routinization hypothesis of Autor, Levy and Murnane (2003) is the single most important factor behind the observed shifts in employment structure. We find some evidence for offshoring to explain job polarization although its impact is much smaller. We also find that shifts in product demand are acting to attenuate the polarizing impact of routinization and that differences or changes in wage-setting institutions play little role in explaining job polarization in Europe.
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.
This paper shows that wage inequality in West Germany has increased over the past three decades, contrary to common perceptions.
During the 1980s, the increase was concentrated at the top of the distribution; in the 1990s, it occurred at the bottom end
as well. Our findings are consistent with the view that both in Germany and in the United States, technological change is
responsible for the widening of the wage distribution at the top. At the bottom of the wage distribution, the increase in
inequality is better explained by episodic events, such as supply shocks and changes in labor market institutions. These events
happened a decade later in Germany than in the United States.
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 opportunities, enabled by technology, which allow foreign labor to substitute for domestic workers in 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 th
This paper discusses a general equilibrium model of the assignment of heterogeneous workers to heterogeneous jobs. Both jobs and workers are measured along a continuous one-dimensional scale. The composition of labor supply is represented by a distribution function. Highly skilled workers have an absolute advantage in all jobs and a comparative advantage in complex jobs. Equilibrium is characterized by a mapping of skills on complexities. The model is able simultaneously to explain the remuneration of skill, the allocation of skills to jobs, and variations in labor demand per job type. Estimation results for the Netherlands offer support for its relevance. Copyright 1995 by University of Chicago Press.
This paper shows that the United Kingdom since 1975 has exhibited a pattern of job polarization with rises in employment shares in the highest- and lowest-wage occupations. This is not entirely consistent with the idea of skill-biased technical change as a hypothesis about the impact of technology on the labor market. We argue that the "routinization" hypothesis recently proposed by Autor, Levy, and Murnane (2003) is a better explanation of job polarization, though other factors may also be important. We show that job polarization can explain one-third of the rise in the log(50/10) wage differential and one-half of the rise in the log(90/50). Copyright by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.
A simple supply and demand framework is used to analyze changes in the U. S. wage structure from 1963 to 1987. Rapid secular
growth in the demand for more-educated workers, “more-skilled” workers, and females appears to be the driving force behind
observed changes in the wage structure. Measured changes in the allocation of labor between industries and occupations strongly
favored college graduates and females throughout the period. Movements in the college wage premium over this period appear
to be strongly related to fluctuations in the rate of growth of the supply of college graduates.
We propose a theory of the global production process that focuses on tradeable tasks, and use it to study how falling costs of offshoring affect factor prices in the source country. We identify a productivity effect of task trade that benefits the factor whose tasks are more easily moved offshore. In the light of this effect, reductions in the cost of trading tasks can generate shared gains for all domestic factors, in contrast to the distributional conflict that typically results from reductions in the cost of trading goods. (JEL F11, F16)