Identification of emerging digital automation technologies is critical to understanding the changing patterns of work, firm and industry organisation, and labor demand, and thus formulating policies to mitigate the associated risks while harnessing their potential benefits. In this paper, we analyse a large corpus comprising millions of patents and scientific publications from Derwent, PATSTAT, and OpenAlex databases related to automation technologies across a wide range of domains, including but not limited to industrial robots and artificial intelligence.
This paper investigates the impact of job training on workers’ susceptibility to automation. Using rich individual-level data from the Programme for the International Assessment of Adult Competencies (PIAAC) across 37 industrialized countries, we construct a unique individual-level measure of automation risk based on the tasks performed at work. We uncover substantial variation in automation risk within detailed occupations,which would have been overlooked by previous occupation-level automation measures.
This report aims to study the speed and direction of change that occupations undergo regarding skills composition for different European regions. One peculiar aspect of this research is the application of AI methods, such as word embeddings and machine learning to conduct economic analysis. We measure changes in the occupation skill sets based on the words used to advertise job vacancies in online job ads (OJAs) to measure changes between and within European countries, considering occupations’ specificity.
Which occupations will grow in the future and where? What skills will be demanded the most in the next years? How technology and digitalisation will affect existing and well-consolidated occupations? Those are the questions at the forefront of the policy debate among economists and policymakers. To address these questions, data-driven and real-time analysis of the labour market is needed to catch novelties - in terms of skills and new emerging jobs - as soon as they emerge from the labour market demand.
CESifo Working Paper No. 10288
We develop novel measures of early-career skills that are more detailed, comprehensive, and labor-market-relevant than existing skill proxies. We exploit that skill requirements of apprenticeships in Germany are codified in state-approved, nationally standardized apprenticeship plans. These plans provide more than 13,000 different skills and the exact duration of learning each skill. Following workers over their careers in administrative data, we find that cognitive, social, and digital skills acquired during apprenticeship are highly – yet differently – rewarded.
CESifo Working Paper No. 10281
We study how technology adoption and changes in global value chain (GVC) integration jointly affect labor shares and business function specialization in a sample of 14 manufacturing industries in 14 European countries in 1999–2011. Our main contribution is to highlight the indirect effect of robotization on relative demand for labor via GVC integration. To do this, we develop a methodology to separately account for robots in the total capital stock.
CESifo Working Paper No. 10237
This paper examines the labor market adjustments to four automation technologies (i.e. robots, communication technology, information technology, and software/database) in 227 regions across 22 European countries from 1995 to 2017. By constructing a measure of technology penetration, we estimate changes in regional employment and wages affected by automation technologies along with the reallocation of workers between sectors.
Papers in Evolutionary Economic Geography (PEEG) 23-02, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography
In this report we evaluate the opportunities for regional diversification in Europe over the last decade. We use microdata from the European Labour Force Survey to empirically test the entry and exit of occupational specializations at the regional level. Our results show that NUTS 2 regions are more likely to diversify into new occupations that are related to their existing local labour markets. So, the new opportunities for diversification are path-dependent, that is, they depend on the previous (occupational) production structure of the regions.
The paper examines the long-run versus short-run implications for labour markets of exposure to four automation technologies—robots, communication, information and software and databases. By applying a multiple break-point algorithm we identify investment cycles for each technology as affecting employment, wages, and wage shares for 163 NUTS-2 regions in 12 European countries over 1995-2017. In the long run, we find that robots have increased employment but reduced wages and the wage share in the region.
In recent decades, major secular trends in the labor market have significantly changed occupations and the skills demanded in occupations. In particular, advances in technologies and international outsourcing have decreased demand for certain types of tasks. Routine occupations are particularly vulnerable to automation risks, i.e., the risk that their tasks will be replaced by robots and automation technologies. Further, workers in occupations performing tasks that can be outsourced abroad face similar changes in skill demand due to lower trade barriers and technological advances.
There is a aggregate decline of manual-routine occupations due to substitution by automation capital, as these occupations perform tasks that can be easily replaced by machines. Similarly, technological progress and reduced trade barriers put occupations at an increased risk of offshoring, as their tasks can be performed abroad.
This report addresses is taking stock of the extant literature on the potential effects of technological change on labour outcomes. The paper focusses on the link between technological change, jobs and tasks. The paper makes a crucial contribution to existing reviews of the technology-employment nexus, by focusing on the technical and engineering literature, that describes the design of new technologies and how these execute tasks and jobs across industries.
Labor market developments such as globalization, structural transformation, and accelerating technological change can lead to mismatches between firms’ skill demand and employees’ skill supply. While skill mismatch is heavily discussed in research and policy, empirical evidence on the existence and determinants of skill mismatch in Europe is very scarce. In this paper, we develop novel measures of skill mismatch in Europe to address various questions of high relevance for labor market policies in the European Union: (1) How prevalent is skill mismatch in Europe?
CESifo Working Paper No. 10026
Immigration is one of the most divisive political issues in many countries today. Competing narratives, circulated via the media, are crucial in shaping how immigrants’ role in society is perceived. We propose a new method combining advanced natural language processing tools with dictionaries to identify sentences containing one or more of seven immigrant narrative themes and assign a sentiment to each of these. Our narrative dataset covers 107,428 newspaper articles from 70 German newspapers over the 2000 to 2019 period.
EconPol Forum 23 (5), 43-47
In B. Wawrzyniak & M. Herter (ed.), Neue Dimensionen in Data Science (Chapter 20, p. 227-242). Wichmann Fachmedien Berlin - Offenbach.
We analyze the prevalence of working from home (WfH) in Germany using more than 35 million online job advertisements from 2014 to 2021. While the option to work from home was rare in job advertisements before the coronavirus crisis, the shock of the pandemic led to a boom. At the same time, regional, occupational, and sectoral inequalities in access to WfH have decreased during the pandemic.
Regional Studies, Forthcoming special issue: The dark side of innovation and its geography.
As regions evolve, their economies become more complex, and they tend to diversify into related activities. Although there is a bright side to this diversification process in terms of economic development, there may also be a dark side to it, as it possibly contributes to regional inequalities. The paper uses data on industries and patents to analyse the diversification patterns of 283 regions in 32 European countries over the past 15 years. We find that only the most economically advanced regions have the opportunity to diversify into highly complex activities.
Papers in Evolutionary Economic Geography (PEEG) 22-16, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography
The literature has shown that related diversification in more complex industries enhances economic growth in regions but also inter-regional inequality. However, it has drawn little attention to the relationship between industrial dynamics (i.e. the rise and fall of industries) and intra-regional wage inequality.
We study the effects of technological change on immigration flows as well as the labor market outcomes of migrants versus natives. We analyse and compare the effects of two different automation technologies: Industrial robots and artificial intelligence. We exploit data provided by the Industrial Federation of Robotics as well as online job vacancy data on Germany, a highly automated economy and the main destination for migrants in Europe.
CESifo Working Paper No.9758
In this paper, we present theory and global evidence on how mobile internet access affects desire and plans to emigrate. Our theory predicts that mobile internet access increases desire and plans to emigrate. Our empirical analysis combines survey data on 617,402 individuals from 2,120 subnational districts in 112 countries with data on worldwide 3G mobile internet rollout from 2008 to 2018. We show that an increase in mobile internet access increases the desire and plans to emigrate. Instrumenting 3G rollout with pre-existing 2G infrastructure suggests that the effects are causal.