师资介绍——ES 官方活动 亚洲计量经济学与统计学暑期学校下周开幕

  • 日期:2022-07-13

世界计量经济学会(Econometric Society)官方网站宣布,世界计量经济学会“亚洲计量经济学与统计学暑期学校”将于2022年7月份在北京举办。主办单位是中国科学院数学与系统科学研究院、中国科学院预测科学研究中心、中国科学院大学经济与管理学院,协办单位有厦门大学邹至庄经济研究院和东北财经大学经济学院。本次暑期学校活动时间为2022年7月18日至2022年7月23日

 

本次暑期学校旨在为海内外经济类、管理类、统计类及相关学科的广大师生介绍计量经济学和统计学领域的若干最新国际前沿发展,积极推动计量经济学教育与研究在亚太地区的发展。

 

 

主办单位将邀请来自莫纳什大学、美利坚大学、剑桥大学、新加坡管理大学、清华大学,以及中国科学院大学等国际知名计量经济学家前来授课,介绍相关领域的国际前沿研究,包括高维面板估计、信息论建模与推断、时变模型、经验模态分解与预测、非参数分析与机器学习,以及分形时间序列等理论方法及其在经济金融的应用。

 

Invited Lecturers:

 

Jiti Gao (Monash University)

 

Topic: Time Varying Models in Econometrics and Statistics

Jiti Gao is Professor and Donald Cochrane Chair of Business Economics and Professor of Econometrics and Business Statistics at Monash University. Prior to joining Monash University in 2011, he was Chair of Economics and Foundation Chair of Econometrics at the University of Adelaide’s School of Economics (2008-2010), and Chair of Statistics and Head of the Statistics Discipline at the University of Western Australia’s School of Mathematics and Statistics (2004-2007). He is a fellow of the Australian Academy of Social Sciences and a fellow of The Journal of Econometrics.

Professor Gao is an expert in time-series analysis, non- and semi-parametric models and methods, spatial and spatial-temporal analysis, stochastic process modeling, and the integration of high-dimensional data. He builds sophisticated statistical models to analyze critical issues in climate change, energy demand, financial markets, and econometrics. His work has been published extensively in academic journals, such as the Journal of Econometrics, the Annals of Statistics and the Journal of American Statistical Association.

 

Amos Golan (American University)

 

Topic: Information-Theoretic Modeling and Inference

Amos Golan is Professor of Economics and directs the Info-Metrics Institute at the American University, an External Professor at the Santa Fe Institute and a Senior Fellow at Rimini Center for Economic Analysis. Professor Golan is also a Senior Research fellow at the NSF/ASA/Census, a Research Fellow at the Max-Planck Institute for Plasma Physics (Munich, Germany) and the Elected Member of International Statistical Institute. His research is primarily in the interdisciplinary field of info-metrics - the science of modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. He has published in economics, econometrics, statistics, mathematics, physics, visualization and philosophy journals. His most recent book is Foundations of Info-Metrics: Modeling, Inference, and Imperfect Information, OUP (2018).

 

Yongmiao Hong (Chinese Academy of Sciences and the University of the Chinese Academy of Sciences)

 

Topic: Nonparametric Analysis and Machine Learning

Professor Yongmiao Hong is currently a Distinguished Research Fellow at the Academy of Mathematics and Systems Science and the Center for Forecasting Science, Chinese Academy of Sciences (CAS), and a special-term Professor at the School of Economics and Management, University of the Chinese Academy of Sciences. He is a Fellow of The World Academy of Sciences (TWAS) for the advancement of science in developing countries, a Fellow of The Econometric Society, a Fellow of International Association of Applied Econometrics (IAAE), and a Senior Fellow of the Rimini Center for Economic Analysis (RCEA). Before he joined CAS and UCAS, Professor Hong was the Ernest S. Liu Professor of Economics and International Studies, a Professor of Statistics, and a field member in the Center of Applied Mathematics at Cornell University

.Professor Hong received his BS in Physics in 1985 and MA in Economics in 1988 from Xiamen University, and his PhD in Economics from the University of California at San Diego in 1993. Upon graduation, he joined, as a faculty member, the Department of Economics and Department of Statistics and Data Science at Cornell University and later became the Ernest S. Liu Professor of Economics and International Studies from 2010 to 2020. He moved from Cornell University to the University of the Chinese Academy of Sciences in December, 2020. He was President of the  Economists’ Society in North America from 2009 to 2010.

Professor Hong's research interests include model specification testing, nonlinear time series analysis, financial econometrics, and empirical studies on the Chinese economy and financial markets. He publishes refereed articles in mainstream economics, financial and statistical journals such as the Annals of Statistics, Biometrika, Econometric Theory, Econometrica, the International Economic Review, the Journal of the American Statistical Association, the Journal of Applied Econometrics, the Journal of Business and Economic Statistics, the Journal of Econometrics, the Journal of Political Economy, the Journal of the Royal Statistical Society (Series B), the Quarterly Journal of Economics, the Review of Economic Studies, the Review of Economics and Statistics, and the Review of Financial Studies.

 

 Oliver Linton (University of Cambridge)

 

Topic: Some Nonparametric Methods for High Frequency Empirical Finance

Oliver Linton is a Professor of Political Economy and Econometrics at Cambridge University and a Fellow of Trinity College and is author of The Models and Methods of Financial Econometrics. He is a Fellow of the British Academy, a Fellow of the Econometric Society, and a Fellow of the Institute of Mathematical Statistics. His research interests are nonparametric and semiparametric methods, particularly as applied to bandwidth choice and to efficiency comparisons between first order equivalent procedures, leading to examination of practical problems such as how to choose bandwidth, the curse of dimensionality, and how to obtain good approximations to the actual sampling variability of the estimators. He is also interested in financial econometrics.

Professor Linton is a member of the Government Office for Science Foresight Lead Expert Group on The Future of Computer Trading in Financial Markets. He has also acted in a consulting or advisory capacity for (amongst others) Rio Tinto, the Financial Services Authority (FSA), Royal and Sun Alliance and Concordia.

 

Liangjun Su (Tsinghua University)

 

Topic: Regularized Estimation of High Dimensional Panels: Unobserved Heterogeneity, Cross Section Dependence, and Endogeneity

Professor Liangjun Su is C.V. Starr Chair Professor of Economics at the School of Economics and Management, Tsinghua University. His main research interests include econometric theory, nonparametric econometrics, panel data models, factor models, big data analysis, and machine learning. He has published more than 70 papers in top international economics, statistics and informatics journals such as Econometrica, Econometric Theory, IEEE Transactions on Information Theory, the Journal of Machine Learning Research, the Journal of Applied Econometrics, the Journal of Econometrics, the Journal of the American Statistical Association, the Journal of Businessand Economic Statistics, and Quantitative Economics. His works have been cited in various textbooks including Li and Racine (2006, Nonparametric Econometrics, Princeton University Press), Hsiao (2014, Analysis of Panel Data, Cambridge University Press), Pesaran (2015, Time Series and Panel Data Econometrics, Oxford University Press), Henderson and Parmeter (2015, Applied Nonparametric Econometrics, Cambridge University Press) and Racine (2019, An Introduction to the Advanced Theory and Practice of Nonparametric Econometrics). He won the Multa Scripsit award from Econometric Theory and was elected as a fellow of Journal of Econometrics in 2014. He is a Senior Fellow at the Rimini Centre for Economic Analysis (RCEA).

Currently, Professor Su is a Co-Editor for Econometric Theory and an Associate Editor for the Journal of Econometrics, the Journal of Business and Economic Statistics and Econometric Reviews. He also serves on the editorial board of the Journal of Systems Science and Complexity.

 

Shouyang Wang (Chinese Academy of Sciences and University of Chinese Academy of Sciences)

 

Topic: Data Decomposition Methods and Their Applications

Professor Shouyang Wang is on the editorial boards of more than ten journals, including Energy Economics, Information and Management, the Journal of Management Systems, Information Technology and Decision Making, the Journal of Systems Science and Complexity, the Journal of Management Science, and the Journal of Systems Science and Mathematical Sciences. He has alkso also served as the Guest Editor of an issue/volume of several journals including Annals of Operations Research, and the European Journal of Operational Research.

Professor Shouyang Wang is the Chairman of the Decision Sciences Society of China, Vice Chairman of the Operations Research Society of China, Secretary-General of the Systems Engineering Society of China, and serves, as an expert, on the Disciplinary Consultative Group of the Academic Degrees Committee of the State Council. His is also a member of the National Postdoctoral Management Committee of the Ministry of Human Resources and Social Security, and a member of the Advisory Committee of Management Sciences of the National Natural Science Foundation of China. IN addition, he is an Honorary Professor or part-time Professor at over twenty prestigious universities at home and abroad.

 

Jun Yu (Singapore Management University)

 

Topic: Estimation, Inference, Prediction, Identification of Fractional Time Series

Professor Jun Yu is the Lee Kong Chian Professor of Economics and Finance at the School of Economics and Lee Kong Chian School of Business, Singapore Management University. Professor Yu also serves as the Associate Editor of the Journal of Econometrics, Econometric Theory and the Journal of Financial Econometrics. Currently, Prof. Jun Yu is a council member of the Society for Financial Econometrics. He is the first Asian economist to be invited to serve as

the council member of the society. His research interests include financial econometrics, econometric theory, empirical asset pricing, real estate economics and finance and empirical macroeconomics.

Professor Yu Jun's research has won several awards and national research funding, including the University of Auckland Outstanding Research Award in 2002, the Singapore Management University Outstanding Research Award in 2005, the Singapore Management University Outstanding Research Award in 2010, and the Marsden Research Award of the Royal New Zealand Academy of Sciences in 2000. He has secured funding from the AcRF Fund in Singapore in 2006 and 2012. From 2014 to 2020, he began to Chair the Singapore National Key Project (Tier-3 AcRF Project) - Economic Challenges of Population Ageing, as a Lead Principal Investigator.

 

For more information, please visit

 

We look forward to seeing you in Beijing in July!