Prof. Dr. EBRU ÇAĞLAYAN AKAY

Prof. Dr. Ebru Çağlayan- Akay is a Professor of Econometrics at the Faculty of Economics, Marmara University, Türkiye. She received her B.Sc., M.Sc., and Ph.D. degrees in Econometrics, reflecting an academic career built entirely within the discipline. Over the past 29 years, she has been actively engaged in teaching, research, graduate supervision, and international academic collaboration, contributing to the advancement of econometric methodology and applied empirical research. Her primary research interests are in Applied Microeconometrics, with particular expertise in panel data econometrics, qualitative and limited dependent variable models, nonparametric and semiparametric econometrics, impact evaluation, causal inference, and quantitative policy analysis. In recent years, she has expanded her research to Big Data Econometrics, focusing on the integration of modern machine learning and artificial intelligence techniques with traditional econometric methods to strengthen empirical modelling, prediction, and reproducible research. Her research covers a broad range of application areas, including labour economics, migration, climate change, sustainability, governance, environmental economics, finance, higher education, regional development, and public policy. Across these fields, she is committed to developing empirically grounded, methodologically rigorous, and reproducible analytical frameworks that contribute to evidence-based decision-making.

Prof. Dr. Çağlayan-Akay has published widely in internationally indexed peer-reviewed journals and has participated in numerous national and international research projects. In addition to her journal publications, Prof. Dr. Çağlayan-Akay has authored and co-authored numerous national and international books and book chapters and has served as editor and co-editor of academic books and international handbook projects. She also served as the Translation Editor of the Turkish edition of Jeffrey M. Wooldridge's Introductory Econometrics: A Modern Approach (Nobel Academic Publishing), one of the most widely adopted econometrics textbooks in undergraduate and graduate education.

She has established an active international academic network through research collaborations, visiting appointments, invited lectures, and academic mobility programmes. She has been a Visiting Scholar and Visiting Academic at several internationally recognised institutions, including Boston College (USA), the University of Westminster (United Kingdom), the Budapest University of Technology and Economics (Hungary), Kyrgyzstan-Turkey Manas University (Kyrgyzstan) and the University of Münster (Germany). She has also participated in European research and academic mobility initiatives, including Erasmus+, COST Actions, and Horizon Europe, fostering international collaboration in econometrics, applied economics, and quantitative policy research. Alongside her research activities, Prof. Dr. Çağlayan-Akay teaches undergraduate, master's, and doctoral courses in econometrics. Her teaching portfolio includes econometric theory, applied microeconometrics, panel data econometrics, qualitative dependent variable models, nonparametric econometrics, and Big Data Econometrics. She has delivered invited seminars, workshops, and professional training programmes at national and international institutions on applied econometrics, panel data analysis, impact evaluation, quantitative research methods, and the integration of econometrics with machine learning.

Her current academic work focuses on applied microeconometrics, Big Data Econometrics, empirical modelling, and reproducible research. She is particularly interested in integrating classical econometric approaches with emerging data science techniques to address increasingly complex economic and social problems. Through her research, teaching, editorial activities, and international collaborations, she continues to contribute to the development of applied econometrics and to the promotion of rigorous, transparent, and reproducible empirical research.