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ICEBDA 2026

 

 

 

About ICEBDA 2026

The 2nd International Conference on Econometrics and Big Data Analysis (iCEBDA 2026) is organized by the Centre for Big Data in Economics and Finance (CEBDA) at HSE University. It provides a leading international forum for researchers, practitioners, and policymakers from academia, industry, and government to discuss recent advances and future directions in econometrics, economics, finance, business analytics, big data, and related fields.

This year iCEBDA travels to Xiamen, China, where it will be hosted by the Paula and Gregory Chow Institute for Studies in Economics at Xiamen University. The 2026 edition is especially meaningful, coinciding with the 105th anniversary of Xiamen University and the 10th anniversary of the Paula and Gregory Chow Institute.

 

Important Dates

Submission deadline: 23:59, 15 July 2026 AoE (14:59 Moscow time, 16 July 2026)

Acceptance notification: TBA

Early registration deadline: TBA

Conference dates: 4–7 December 2026

 

Quick Links

Call for Papers (PDF)

Submit your paper

 

Registration Fees

Standard

$300

Student

$180

 

Committees & Organizers

Organizing: Anton Skrobotov, Artem Prokhorov, Dmitry Grigoriev, Madina Karamysheva, Rustam Ibragimov, Violet Chen, Xiaoyi Han, Yongmiao Hong.

Centre for Big Data in Economics and Finance, HSE University
Centre for Big Data in Economics and Finance,

HSE University


Paula and Gregory Chow Institute for Studies in Economics,

Xiamen University

Contacts

Website: bechair.online/iCEBDA-2026
Email: icebda.hse@gmail.com

 

Keynote Speakers

Marc Hallin

Marc Hallin

ECARES, Université Libre de Bruxelles

Internationally recognized statistician and econometrician. Known for foundational work on rank- and sign-based inference, multivariate quantiles via measure transportation, and the General Dynamic Factor Model for high-dimensional time series. Fellow of the IMS and ASA, member of the Royal Academy of Belgium, and recipient of the IMS Pierre-Simon de Laplace Prize (2022).

 

Peter Reinhard Hansen

Peter Reinhard Hansen

Department of Economics, University of North Carolina, Chapel Hill

A leading researcher in forecasting and volatility modelling; his contributions include the Test for Superior Predictive Ability, the Model Confidence Set, the Realized Kernel estimator, and the Realized GARCH framework — for which he received the Richard Stone Prize in Applied Econometrics (2014). Named four times to Thomson Reuters / Clarivate's list of the World's Most Influential Scientific Minds.

 

Yixiao Sun

Yixiao Sun

Department of Economics, University of California, San Diego

Known for foundational work on robust inference under temporal, spatial, and spatio-temporal dependence, with current research on nonparametric and semiparametric inference at the intersection of machine learning and causal inference. Joint Editor-in-Chief of Econometric Theory, Fellow of the Journal of Econometrics, and recipient of the Plura Scripsit (2019) and Multa Scripsit (2007) Awards from Econometric Theory.

More keynote speakers to be announced

 

 

Venue

The conference will be hosted at Siming Campus, Xiamen University, China by the Higher School of Economics together with the Paula and Gregory Chow Institute for Studies in Economics. Founded in 1921, Xiamen University is one of China's oldest and most prestigious universities, and its seaside Siming campus — with palm-lined avenues, a lotus lake, traditional Min-Nan architecture, and a beach within the campus grounds — is widely regarded as one of the most beautiful university campuses in China. The Chow Institute, established in 2016 with the support of Professor Gregory C. Chow of Princeton University and Ms. Paula Chow, brings together the Wang Yanan Institute for Studies in Economics (WISE) and the School of Economics, and is a leading centre for economics and econometrics research in Asia.

Address: Economics Building, No. 422, Siming South Road, Siming District, Xiamen, Fujian 361005, China.

Tel: +86 0592 2188827. Click here for the map.

Xiamen University Campus

 

 

 


 

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