Data Science and Machine Learning for Economic Research

Check also:

Mini Track Chair:

Adriana DAVIDESCU, The Bucharest University of Economic Studies, Romania
Rim Jallouli, Higher School of Digital Economy (ESEN), University of Manouba, Tunisia
Mohamed Anis Bach Tobji, Higher School of Digital Economy (ESEN), University of Manouba, Tunisia

This mini track examines the application of advanced data science and machine learning models in solving modern economic problems. It highlights the ways that these models can help in the analysis of the economic phenomena, decision making and building of forecasts over economic processes. Topics include issues in macroeconomics, finance, labor economics, and policy analysis demonstrating the application of new techniques and cross disciplinary methods enhancing the quality of the research done. This mini-track is supported by the project 101182756 — INSEAI 2023 –Marie Sklodowska-Curie Actions & Support to Experts A.3 MSCA Staff Exchanges International Network for Knowledge and Comparative Socioeconomic Analysis of Informality and the Policies to be Implemented for their Formalization in the European Unión and Latin America.

We welcome theoretical, empirical, and applied research papers addressing, but not limited to, the following topics:

Predictive Modeling in Economics
Natural Language Processing (NLP) in Economic Analysis
Causal Inference and Econometrics.
Behavioral Economics and Data Science.
Time Series Analysis.
Social Network Analysis in Economics.
Sustainability and Green Economics.
Policy Evaluation and Impact Assessment.
Explainable AI in Economics:
Data Visualization for Economic Insights.
Integration of Traditional Econometrics and Machine Learning.
Data Science for Sustainable Development
Integrating ESG Metrics in Digital Systems
Data-Driven Public Policies
Economic Impacts of Digital Transformation
Challenges in Data Integration and Ethics
Assessing the Impact of Artificial Intelligence Strategies on Company Performance
AI Knowledge and Innovation Networks
Analyzing Causality vs. Correlation for Sustainable Development.
Machine Learning Techniques for Causal Inference in Digital Economies
The Role of Digital Innovation in Achieving Sustainable Development Goals in Developing Countries
Strategies to Integrate the Shadow Economy into the Formal Sector in Achieving Sustainable Development Goals in Developing Countries
Analyzing the Interaction between Digitalisation and the Shadow Economy in Sustainable Development Efforts.
Bridging the Gap: Leveraging Digital Tools to Integrate Informal Sectors into Sustainable Economic Frameworks.
Assessing the Social Implications of the Shadow Economy in the Digital Transformation of Developing Economies
Machine learning in the shadow economy analysis
AI to detect informality patterns
Youth in Informal work
ML methods used in the estimation of the shadow economy
The Role of AI in Regional and Global Economic Inequality Analysis
AI in Forecasting and Analyzing Global Supply Chain Disruptions
Applications of Explainable AI in Economic Research
Machine Learning for Evaluating Climate and Economic Risk Interaction
AI and Blockchain Integration for Economic Data Integrity and Transparency
Data Science in Regional and Global Policy Coordination
AI and Data Science for Labor Market Analysis
Time Series Forecasting for Economic Processes
Social Network Analysis in Macroeconomic and Financial Context
Behavioral Economics Supported by Data Science Approaches

Adriana AnaMaria Davidescu
is a Full Professor at the Department of Statistics and Econometrics, Bucharest University of Economic Studies, Romania. She is the Head of the Data Science Research Lab, specialising in applications for business and economics, and a senior researcher at the Department of Labour Market Policies of the National Scientific Research Institute for Labour and Social Protection. With over 17 years of experience in socio-economic research, she has been deeply involved in various analytical pursuits.For over 17 years, she has delved into informality issues at both national and international levels. She has led various national research projects and served as a senior expert for the European Commission, specifically for the European Platform that addresses Undeclared Work. Prof. Davidescu possesses extensive expertise in the evaluation of public projects and programs. Her prowess in project team management is evident, having coordinated more than 14 national projects and played a pivotal role as a senior expert in over 50 national and international endeavours. She has showcased her expertise in counterfactual methods during the assessment process, especially in empirically testing causal chains in interventions related to the Operational Program Competitiveness 2014-2020 Evaluation Plan, the Human Capital Operational Program 2014-2020 Evaluation, and the Partnership Agreement Evaluation Plan. She held the esteemed position of a modelling key expert. She served as the team leader for the Operational Program Competitiveness 2014-2020 Evaluation Plan, focusing on evaluating POC interventions in research, development, and innovation. Additionally, she was a senior modelling expert, instrumental in assessing the impact of interventions for both the Human Capital Operational Program 2014-2020 Evaluation Plan and the Partnership Agreement Evaluation Plan, with an emphasis on economic, social, and territorial cohesion.

Rim Jallouli is a Professor of Marketing and Innovation Management at the Higher School of Digital Economy (ESEN), University of Manouba, Tunisia. She supervises several PhD projects and research initiatives in the field of text mining applied to advanced marketing research methods. Prof. Jallouli has edited several books and special issues in prestigious journals. She is also the founder of the International Conference on Digital Economy (ICDEc), promoting scientific collaboration across Europe, Africa, and the MENA region. Her research interests include AI-driven marketing strategies, opinion leader detection, and digital transformation in organizations. Rim Jallouli is also a senior expert with leading international organisations where she has contributed to strategic missions on cultural policy and capacity-building in the era of emerging technologies, digital transformation, and marketing analytics.

Mohamed Anis Bach Tobji obtained his PhD in Business Computing in 2012 and his University Habilitation in 2018. He is an Associate Professor at ESEN (University of Manouba), which he joined in 2009, and where he has held a number of positions, including Director for the 2020–2024 term, Director of Studies and Internships (2015–2020), Head of ESEN’s Information Systems Technologies Department (2011–2014), and elected member of the Scientific Advisory Board since 2011 (for five successive terms). He is currently the coordinator of the Web Intelligence research master’s programme. He conducts his scientific research within the LARODEC laboratory (ISG Tunis – University of Tunis), focusing mainly on data science, artificial intelligence, imperfect databases, preference queries, Dempster–Shafer theory, social network analysis, and other related fields.

He is also a member of the STARTUP ACT College (2022–2025) and of the Scientific College of the Tunisian Agency for Evaluation and Accreditation (2024–2027). He is the co-founder of the ICDEc International Conference (founded in 2016), co-editor of several special issues in indexed journals, and member of the programme committees of several international conferences.