EcoSta 2024 hybrid conference

The 7th International Conference on Econometrics and Statistics (EcoSta 2024) will be hosted by Beijing Normal University, Beijing, China, 17-19, July 2024. The in-person venue is the School of Statistics (Haidian Campus). A tutorial will be given on Tuesday, the 16th of July, 2024.

The conference will be held in a hybrid form. The keynote talks, the special invited sessions, the hybrid organized sessions, and the virtual sessions will be live-streamed for all the conference participants. Contributed speakers can choose in-person or virtual presentation, while invited speakers should coordinate their presentation mode with the session organizers. All the posters will be posted online, but in-person participants will be able to meet physically during the poster session.

The 6th International Conference on Econometrics and Statistics, EcoSta 2023, has taken place at Waseda University, Japan, and gathered 1180 in-person and virtual participants.

This hybrid conference is co-organized by the Working Group on Computational and Methodological Statistics (CMStatistics), the network of Computational and Financial Econometrics (CFENetwork), and BNU.

The journals Econometrics and Statistics (EcoSta) and Computational Statistics & Data Analysis (CSDA) and their special sections, the Annals of Computational and Financial Econometrics, and Annals of Statistical Data Science are the main sponsors. Selected peer-reviewed papers will be considered for publication in special or regular issues of the journals Econometrics and Statistics, and Computational Statistics & Data Analysis.

The first impact factor of Econometrics and Statistics (EcoSta), released in June 2023, is 1.9. Computational Statistics & Data Analysis (CSDA) keeps its consistently good performance with an impact factor of 1.8.

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Aims and Scope

This conference invites oral and poster presentations containing substantial advances in the broad areas of econometrics and statistics. All topics within the scope of the journal Econometrics and Statistics will be considered. Topics of interest include, but are not limited to:

Part A. Econometrics: estimation of econometric models and associated inference, model selection, panel data, measurement error, time series analyses, filtering, portfolio allocation, option pricing, quantitative risk management, systemic risk and market microstructure, forecasting, volatility and risk, credit risk, pricing models, portfolio management and emerging markets.

Part B. Statistics: high-dimensional problems, functional data analysis, robust statistics, resampling, dependence, extreme value theory, spatial statistics, Bayesian methods, statistical learning, nonparametric statistics, multivariate data analysis, parametric & semiparametric models, numerical methods in statistics, and substantial statistical applications in other areas such as medicine, epidemiology, biology, psychology, climatology and communication. Innovative algorithmic developments are welcome, as are the computer programs and the computational environments that implement them as a complement.