معرفی
Per Johansson is a Professor in the Department of Statistics at Uppsala University, Sweden, with a distinguished career spanning several decades in causal inference methodology and its applications to labor economics, health economics, and social policy evaluation. His research primarily utilizes Swedish administrative data to examine critical issues in social insurance systems, labor market behavior, and health outcomes.
Professor Johansson's research interests center on causal inference methods broadly defined, with particular focus on applications in labor economics, health economics, and social policy. His work demonstrates methodological rigor while addressing socially relevant questions about sickness absence, disability insurance, retirement decisions, gender differences in labor markets, and the effectiveness of social interventions. He has developed innovative approaches to causal identification in observational settings and has contributed significantly to the methodological literature on experimental design and inference.
His publication record reveals a clear trajectory from foundational methodological work in econometrics and statistics toward increasingly policy-relevant applications. While maintaining strong methodological contributions, particularly in causal inference and experimental design, his recent work shows greater emphasis on healthcare applications, comparative effectiveness research, and interdisciplinary collaborations with medical researchers. This evolution demonstrates his ability to apply sophisticated statistical methods to pressing real-world problems across multiple domains.
- Co-opted member of the Prize Committee for the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel
Professor Johansson has secured numerous research grants supporting his work on causal methods and policy evaluation, with particular emphasis on Swedish social insurance systems. His research has been instrumental in evaluating interventions related to sickness absence, disability insurance, and retirement policies. He has collaborated extensively with researchers across disciplines and institutions, including economists, statisticians, epidemiologists, and medical researchers, reflecting the interdisciplinary nature of his work.
His methodological innovations in causal inference, experimental design, and analysis of administrative data have established him as a leading researcher in applying sophisticated statistical methods to evaluate social policies and healthcare interventions using both experimental and observational data sources.
