Research background: We are guided by concepts linking political trust with the perceived rank of people in the wealth hierarchy, their confidence in other people, and the means they use to learn about events at home and abroad.Purpose of the article: The aim of the article is to assess and analyse at the micro level the impact of subjective welfare, interpersonal trust and the intensity of usage of ...
We quantify the value of data for the prediction policy problem of reducing antibiotic prescribing to curb antibiotic resistance. Using varying combinations of administrative data, we evaluate machine learning predictions for diagnosing bacterial urinary tract infections and the outcomes of prescription rules based on these predictions. Simple patient demographics improve prediction quality substantially ...
To decarbonize the economy, many governments have set targets for the use of renewable energy sources. These are often formulated as relative shares of electricity demand or supply. Implementing respective constraints in energy models is a surprisingly delicate issue. They may cause a modeling artifact of excessive electricity storage use. We introduce this phenomenon as 'unintended storage cycling', ...
Dieser Artikel befasst sich mit der Vereinbarkeit der Nutzung von Big Data und Künstlicher Intelligenz (KI) durch FinTechs mit den europäischen Datenschutzgrundsätzen. FinTechs ersetzen zunehmend traditionelle Kreditinstitute und gewinnen bei der Bereitstellung von Finanzdienstleistungen an Bedeutung, insbesondere durch die Nutzung von KI und Big Data. Die Fähigkeit, eine große Menge unterschiedlicher ...
Nicht erst seit der Corona Pandemie gibt es weltweit den Trend zum bargeldlosen Zahlungsverkehr. Zudem beflügelt die Vorstellung eines zielgenauen Behavioral (Big Data) Scoring die Fantasien von Investoren in der Datentechnologiebranche. Es scheint ökonomisch verführerisch, beide Trends zusammenführen, wenn man alle Daten aus dem Zahlungsverkehr für ein persönliches Profil auswerten würde. Dieses Geschäftsmodell ...
Nonprobability online panels are commonly used in the social sciences as a fast and inexpensive way of collecting data in contrast to more expensive probability-based panels. Given their ubiquitous use in social science research, a great deal of research is being undertaken to assess the properties of nonprobability panels relative to probability ones. Much of this research focuses on selection bias, ...
Using a new SOEP-IS data module on digitalization including information on the prevalence of AI use in the workplace, this report shows that the term “artificial intelligence” often remains inscrutable in the day-to-day work of many employees. When asked directly about the use of digital systems with the term “artificial intelligence,” around 20 percent of the working respondents in the sample indicate ...
This study provides the first representative analysis of error estimations and willingness to accept errors in a Western country (Germany) with regards to algorithmic decision-making systems (ADM). We examine people’s expectations about the accuracy of algorithms that predict credit default, recidivism of an offender, suitability of a job applicant, and health behavior. Also, we ask whether expectations ...
This paper estimates the effect of home high-speed internet on national test scores of students at age 14. We combine comprehensive information on the telecom network, administrative student records, house prices and local amenities in England in a fuzzy spatial regression discontinuity design across invisible telephone exchange catchment areas. Using this strategy, we find that increasing broadband ...