Investigating the Impact of Risk of Automation on Health Outcomes of Employees: Evidence from Germany

ended

The proposed research project aims at contributing to the literature on work-related determinants of health, and innovates previous studies by investigating the impact of risk of automation (proxied by a percentage of routine tasks in the occupation) on both subjective and objective measures of health of employees. By merging survey data from the German Socio-Economic Panel (GSOEP) with expert data from BERUFENET and adopting the methodology proposed by Dengler et al. (2014), the project addresses the following research questions: i) to which extend does risk of automation affect health outcomes of German employees; ii) what are possible transmission mechanisms behind the health differences of German employees related to risk of automation; iii) is selection into occupations at a higher risk of automation determined by a health status of individuals. The project will have a meaningful impact on society. To begin with, the scientific community can benefit due to promoting gender specific multidisciplinary research which adopts methodologies from social sciences (e.g. mediation analysis, structural equation modeling) and implements them innovatively in the field of economics. In addition, the project shows how to use different types of data (e.g. surveys, expert databases) to properly address modern challenges and enrich evidence on established topics. Furthermore, the project serves as a “testing ground” for a novel methodology of measuring the risk of automation for a variety of occupations. From the economic and societal perspective, the project estimates the magnitude of the “social costs of digitalization” and provides guidance to policy-makers and companies to decrease negative spill-over effects of technological change on population health. Last but not least, the social impact of the project is related to analysing new trends in the development of society and assessing actual threats for public health due to ongoing digital transformation.