This ICEAQM features a diverse range of session tracks designed to cover key research areas, emerging trends, and interdisciplinary innovations within the field of Economics.
Each track offers researchers, academicians, industry professionals, and practitioners a platform to present their work, exchange ideas, and explore the advancements shaping the future of the domain.
This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals, fostering knowledge exchange, innovation, and collaborative engagement.
Browse every track scheduled for this conference.
This track focuses on the latest developments in econometric methodologies and their applications in economic research. Researchers are encouraged to present innovative approaches to estimation and hypothesis testing.
This session will explore cutting-edge techniques in time series analysis, emphasizing their relevance in economic forecasting. Contributions that demonstrate practical applications and theoretical advancements are particularly welcome.
This track will delve into the complexities of panel data analysis, highlighting both methodological advancements and empirical applications. Papers that address issues of unobserved heterogeneity and dynamic modeling are encouraged.
This session aims to bridge the gap between machine learning and traditional econometric methods. Researchers are invited to showcase how machine learning techniques can enhance economic modeling and data analysis.
This track will examine the role of causal inference in econometrics, focusing on structural models and their implications for economic theory. Contributions that provide empirical evidence or methodological insights are highly encouraged.
This session will investigate the intersection of risk analysis and economic policy, emphasizing quantitative methods for evaluating policy impacts. Papers that utilize econometric techniques to assess risk and policy effectiveness are welcome.
This track focuses on the application of predictive analytics in economic research, exploring both theoretical frameworks and empirical studies. Contributions that demonstrate the utility of predictive models in economic decision-making are encouraged.
This session will highlight various estimation techniques used in applied econometrics, discussing their advantages and limitations. Researchers are invited to present case studies that illustrate the practical application of these methods.
This track will explore the role of statistical analysis in the development and validation of economic models. Papers that integrate statistical rigor with economic theory are particularly encouraged.
This session will focus on innovative approaches to economic data analysis, emphasizing the importance of data quality and methodology. Contributions that address challenges in data handling and interpretation are welcome.
This track will examine emerging trends and future directions in quantitative economics, including the integration of new technologies and methodologies. Researchers are encouraged to discuss the implications of these trends for economic research and policy.