Gergo Toth (p), Zoltan Elekes, Petrus Garafelt, Rikard Eriksson

Johan Klaesson

Labour mobility has become a central focus of economics in recent times. This is partly due to the recognition that labour mobility is no longer seen as merely a random feature of social stratification but increasingly as a complex system. Essentially, labour mobility is a transition matrix illustrating how workers move between different occupations. Labour mobility has also given rise to the concept of skill-relatedness providing a good approximation of the distribution and relation of skills and capabilities found in countries and regions. Yet little is known about the formation and evolution of these networks and the economic, social, and geographical phenomena driving the development of different capability structures. In our paper two main research questions are tackled: first, identifying the factors driving labour mobility, and second, assessing how much skill-relatedness explains occupational changes. Preliminary results, combining JobTech data with an administrative database, highlight the significance of skill similarity in understanding labour mobility. Using a machine learning technique, we discovered that skill overlap outweighs other known factors. A classification model, incorporating both skill similarity and social factors, improves predictive accuracy to nearly 85%. Despite skill similarity's dominance, a 15% residual "noise" remains, showcasing the intricate nature of labour market movements.

Johan Lundberg (p)

Gergo Toth

After decades of disinvestment and population decline, several areas of northern Sweden are now attracting largescale industrial investments, such as wind farms, battery factories, and underground mines. The Norrbotten and Västerbotten Chambers of Commerce have estimated that the area will receive close to SEK 1000 billion in new investments over the next two decades. If realized, the region will need an estimated 100,000 additional inhabitants in the next ten years to meet the anticipated increased demand for labor, a population growth of about 20%. A large share of these jobs will be created in the manufacturing industry (low-skilled). Such large investment relative to the regional economy is expected to have a long-term positive effect on regional employment, but large investment could also crowd out incumbent activities. However, there is scant knowledge of the effects of a relatively large industrial investment on employment, especially on the employment in the local public sector.

In this paper, we address this issue. We derive a theoretical model which consists of three parts; labor supply, production and the housing market. Our theoretical model differs from the typical setting where a positive local productivity shock is assumed to occur among high-skilled workers. We consider three periods with different time spans. To set the stage, consider a large industrial investment in one region. The productivity shock appears among low-skilled workers in the first period. The investment has a positive effect on the productivity of relatively low-educated workers which translates to higher wages among this group of workers. Higher wages within manufacturing attract both low- and highly-educated workers in the public sector. It could for instance be a nurse dissatisfied with his work hours or other issues related to the work environment or benefits within the public sector. If not compensated for this, through higher wages, workers will move from the public to the private sector independently of her qualifications (e.g. both high- and low-skilled in the public sector). With no migration across regions housing prices are unaffected.

In the second period, the semi-long period, the restricted labor mobility is relaxed. Now low-skilled (and perhaps also high-skilled in the public sector) in other areas will be attracted by higher wages. This will cause housing prices to increase and benefit landowners. In the long-run, wages and housing prices will stabilize across regions.

When confronted with register data, the main predictions from the theoretical model is confirmed.

Johan Klaesson (p), Lina Bjerke (p), Peter Njekwa Ryberg

Johan Lundberg

The purpose of the current paper is to augment the literature by investigating the timing and triggers of effects from the introduction of new automation technology. We do this by looking at individuals employed in manufacturing firms. These firms may or may not invest in automation technologies in a certain period. We then observe the outcomes for individual workers after an external shock. The external shock we will exploit is the great recession of 2007-2010. More succinctly put, we will examine the probability of job loss for workers in automating compared to non-automating manufacturing firms in the wake of the crisis in 2007. The hypothesis we aim to test is that the effects on employees of different skill levels from investing in automation technology may not be evident until there occurs a sizable pressure on the firm financially or otherwise. One important benefit following this design is that the economic shock comes much faster and is external to both firms and workers. This is in contradiction to investment programs of firms that may unfold in a much more gradual and piecemeal fashion. Thus, effects are more readily identified to a shorter time window.