Servicification of Firms and Trade Policy Implications
Lodefalk, M. (2017). Servicification of Firms and Trade Policy Implications. World Trade Review, 16(1), 59-83. DOI: 10.1017/S147474561600029X
Lodefalk, M. (2017). Servicification of Firms and Trade Policy Implications. World Trade Review, 16(1), 59-83. DOI: 10.1017/S147474561600029X
In the OECD countries, the decline of manufacturing and the employment implications have long been matters of concern. Recently, policymakers in several countries have set out to try and achieve reindustrialization. The servicification of firms is related to these concerns and aspirations. However, servicification, and particularly its role in trade policy, has received limited attention. I review micro-level evidence and discuss its implications. I find that imported, domestic and exported services are all important to contemporary firm competitiveness and participation in international value chains. Therefore, historic policymaking divisions between trade in manufactures and trade in services services, between export and import interests, and among modes of supply are becoming less relevant. I conclude by suggesting potential steps forward.
2024
Ratio.
Andra upplagan av boken finns tillgänglig i bokhandeln, exempelvis här.
Artificiell intelligens (AI) väcker oro och nyfikenhet. Kommer AI att ta våra jobb? I denna tankeväckande bok tar sig forskaren Magnus Lodefalk an denna fråga – och de många delfrågor som frågan egentligen består utav.
Med hjälp av historiska exempel och dagsaktuell forskning diskuterar Lodefalk vilka jobb som kan försvinna med AI:s intåg, men också vilka typer av jobb som kan uppstå. Vad som skiljer AI från andra teknikers intåg är att den kan användas för att utföra kognitiva arbetsuppgifter. I boken diskuteras därför hur AI generellt sett kan förmodas påverka nästan alla jobb i termer av löneutveckling, produktivitet, kompetenskrav och innehåll.
Det görs genom att dissekera vad AI, och vad jobb, faktiskt är. Redan här kan konstateras att AI kan användas för att ersätta mänskliga förmågor eller för att förstärka desamma – det beror på hur man väljer att utveckla och använda tekniken. Och det, skriver Lodefalk, är i sin tur upp till oss.
I denna bok görs en pedagogisk översyn av forskningsläget gällande AI och arbetsmarknaden. Dessutom innehåller boken konkreta verktyg till dig som vill ha svar på hur AI-exponerat ditt yrke egentligen är.
2023
Ratio Working Paper Series.
This paper documents novel facts on within-occupation task and skill changes over the past two decades in Germany. In a second step, it reveals a distinct relationship between occupational work content and exposure to artificial intelligence (AI) and automation (robots). Workers in occupations with high AI exposure perform different activities and face different skill requirements compared to workers in occupations exposed to robots. In a third step, the study uses individual labour market biographies to investigate the impact on wages between 2010 and 2017. Results indicate a wage growth premium in occupations more exposed to AI, contrasting with a wage growth discount in occupations exposed to robots. Finally, the study further explores the dynamic influence of AI exposure on individual wages over time, uncovering positive associations with wages, with nuanced variations across occupational groups.
2023
Ratio Working Paper Series.
We unbox developments in artificial intelligence (AI) to estimate how exposure to these developments affect firm-level labour demand, using detailed register data from Denmark, Portugal, and Sweden over two decades. Based on data on AI capabilities and occupational work content, we develop and validate a time-variant measure for occupational exposure to AI across subdomains of AI, including language modelling. According to our model, white collar occupations are most exposed to AI, and especially white collar work that entails relatively little social interaction. We illustrate its usefulness by applying it to near-universal data on firms and individuals from Sweden, Denmark, and Portugal, and estimating firm labour demand regressions. We find a positive (negative) association between AI exposure and labour demand for high-skilled white (blue) collar work. Overall, there is an up-skilling effect, with the share of white-collar to blue collar workers increasing with AI exposure. Exposure to AI within the subdomains of image and language are positively (negatively) linked to demand for high-skilled white collar (blue collar) work, whereas other AI-areas are heterogeneously linked to groups of workers.