HealthDeterminants · Investigating the Impact of Risk of Automation on Health Outcomes of Employees: Evidence from Germany
Horizon Europe — Marie Skłodowska-Curie Actions
- Duration
- 2023-10-01 → 2025-09-30
- EU contribution
- €173,847
- Participants
- 1
- Scheme
- HORIZON-TMA-MSCA-PF-EF
Lines connect the coordinator with its partners.
Results in brief
Investigating the Impact of Risk of Automation on Health Outcomes of Employees: Evidence from Germany
Automation transforms work at a rapid pace, with gradually increasing shares of the workforce at risk of being replaced by machines. However, little is known about how this risk is affecting workers. In line with the original proposal, this project advances the growing body of research on the social outcomes of automation by examining how exposure to high automation risk in the workplace influences various health outcomes among workers in Germany. It leverages a country-specific measure of routine task intensity to capture automation exposure - an approach that has been largely underutilized in previous studies - and exploits the longitudinal design of the German Socio-Economic Panel (GSOEP) to address the following research questions: Q1. To what extent does automation risk affect the health outcomes of German workers? Q2. What are the potential transmission mechanisms (mediating factors) that explain the health disparities among German workers exposed to varying levels of automation risk? Q3. Is selection into occupations with higher automation risk influenced by individuals' pre-existing health conditions, thereby suggesting reverse causality? Q4. Beyond the scope of the original proposal, the project also explores whether exposure to automation risk in the workplace contributes to adverse health behaviors (i.e., drinking patterns), applied to the context of workers in low- and middle-income countries.
Data: CORDIS, © European Union
Project objective
The proposed research project aims at contributing to the literature on work-related determinants of health, and innovates previousstudies by investigating the impact of risk of automation (proxied by a percentage of routine tasks in the occupation) on bothsubjective 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 thefollowing research questions: i) to which extend does risk of automation affect health outcomes of German employees; ii) what arepossible transmission mechanisms behind the health differences of German employees related to risk of automation; iii) is selectioninto 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 specificmultidisciplinary research which adopts methodologies from social sciences (e.g. mediation analysis, structural equationmodeling) and implements them innovatively in the field of economics. In addition, the project shows how to use different types ofdata (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 providesguidance to policy-makers and companies to decrease negative spill-over effects of technological change on population health. Lastbut not least, the social impact of the project is related to analysing new trends in the development of society and assessing actualthreats for public health due to ongoing digital transformation.
Original text from CORDIS.
Participants
- MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV · MUNCHENCoordinatorGermany
Links
- View on CORDIS
- DOI: 10.3030/101103230
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e50a58f607&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e528785b30&appId=PPGMS
Data: CORDIS, © European Union