Overview

This conference convenes econometricians, statisticians, researchers, and practitioners to explore advances in econometric theory, methodology, and applications. The program covers classical and generalized linear models, time series, panel data, limited dependent variable models, causal inference, Bayesian econometrics, machine learning, and recent developments addressing real-world economic phenomena.

Structure and Sessions (Who Does What)

• Opening & Keynotes: Leading experts deliver visionary talks on current trends and challenges in econometrics.
• Technical Sessions: Peer-reviewed presentations across topics such as regression models, time series and panel analysis, simultaneous equation models, causal inference, and machine learning applications.
• Workshops & Tutorials: Interactive sessions on model diagnostics, forecasting, experimental methods, Bayesian approaches, and econometric software tools.
• Panel Discussions: Multi-disciplinary panels addressing methodological debates, data challenges, and practical implementation issues.
• Poster Sessions: Early-career researchers present empirical studies and novel methodological contributions.
• Awards & Closing: Recognizing outstanding papers and contributions, with closing remarks.

Participate and Contribute (Who Benefits)

• Academics & Researchers: Present novel econometric methods, receive feedback, and foster collaboration.
• Policy Analysts & Practitioners: Learn advanced analytical techniques for evidence-based policy and business decision-making.
• Students & Early-Career Professionals: Develop skills, showcase research, and build professional networks.
• Data Scientists & Econometric Software Developers: Share innovations and learn about emerging econometric applications.

Benefits for Attendees

• Certificate of participation awarded based on engagement and feedback.
• Digital memento recognizing attendance.
• Opportunities to publish abstracts and full papers in indexed journals (Scopus, CrossRef, Web of Science, Elsevier, SCI).
• Awards for best research paper, poster, and active participation.
• Access to all recorded sessions and supplementary materials.
• Structured networking and mentoring sessions.

Abstract Topics / CFP Tracks – Registration

• Classical and generalized linear regression models.
• Time series analysis, stationarity, cointegration, VAR models.
• Panel data and cross-sectional econometrics.
• Simultaneous equation and instrumental variable models.
• Limited dependent variable and qualitative response models (Logit, Probit).
• Forecasting methods and model diagnostics.
• Heteroskedasticity, autocorrelation, and specification testing.
• Structural equation modeling and causal inference.
• Experimental, quasi-experimental and treatment effect methods.
• Bayesian econometrics and machine learning applications.

Submissions undergo peer review; accepted abstracts/papers require registration for presentation and publication.

Detailed Program Grid (2 Days) — Online Conference (with Breaks)

Conclusion:

The International Virtual Conference on Econometrics and Advanced Statistical Methods 2026 provides an exceptional platform for advancing econometric theory, methodology, and practical applications across diverse fields. By bringing together leading academics, practitioners, and emerging researchers, the conference fosters rigorous scholarly exchange, skill development, and interdisciplinary collaboration. With a rich program featuring cutting-edge sessions, interactive workshops, and engaging panel discussions, attendees gain valuable insights into both foundational and innovative econometric techniques. The conference’s inclusive design further supports professional growth through mentoring, networking, and opportunities for publication and recognition. Overall, this event promises to strengthen the global econometrics community and contribute to the robust use of quantitative methods in addressing complex economic and policy challenges.