2023年11月17日，第31届澳大利亚新西兰计量经济学研究组年会（31st Annual Meeting of Australia New Zealand Econometric Study Group）在澳大利亚阿德莱德大学公布了澳大利亚新西兰计量经济学研究组（以下简称“ANZESG”）青年计量经济学家奖项的获奖者，厦门大学邹至庄经济研究院2020级数量经济学专业博士生叶仕奇以题为“Multi-Matrix Autoregressive Models with an Application to Multi-Modal Network”的论文报告获得该年会的最佳论文报告奖（Best Presentation Award），是本次年会唯一来自中国高校的获奖人员。据悉，本次年会由于收到高质量投稿众多，故组委会将入选论文择优推荐为主会场论文报告，其余则以海报形式展示。最佳论文报告奖从主会场论文报告人员中评选获得。
ANZESG年会的前身是著名计量经济学家、美国耶鲁大学斯特林经济学教授兼统计学教授彼得·菲利普斯（Peter C.B. Phillips）教授于1997年创办的新西兰计量经济学研究组（New Zealand Econometric Study Group，简称NZESG）会议。近年来，随着NZESG的影响力增加，逐步成为澳大利亚、新西兰乃至中国、美国、加拿大、欧洲、新加坡等地的计量经济学者相互交流前沿学术进展的活跃平台，该会议逐步扩展成为ANZESG年会。年会为表现优秀的在读博士生或博士毕业两年内的青年研究者专设青年计量经济学家奖项（Young Econometrician ANZESG Awards），旨在支持并鼓励青年计量经济学研究者的发展。
【获奖人介绍】
叶仕奇，厦门大学邹至庄经济研究院2020级博士研究生，目前作为交换博士生在中国科学院数学与系统科学研究院进行交流，研究领域为时间序列计量经济学、应用宏观计量经济学以及金融计量经济学等。论文已被《经济研究》、Journal of Economic Dynamics and Control、Energy Economics、Journal of Management Science and Engineering、International Conference on Data Science and Advanced Analytics等期刊接收或发表，合作（第一作者）著作《高级计量经济学——学习辅导和习题解答》。
【获奖论文介绍】
题目：“Multi-Matrix Autoregressive Models with an Application to Multi-Modal Network”
合作者：厦门大学经济学科郑挺国教授、美国罗格斯大学统计系萧寒教授
论文摘要：Matrix time series data have become increasingly prevalent across diverse fields, including economics, finance, computer science, engineering, and signal processing. This study introduces a novel multi-matrix autoregressive (MMAR) model designed to jointly model matrix time series with varying structures. Notably, the well-known matrix-valued autoregressive model and three-order tensor autoregressive model are special cases of the proposed model. We present three distinct estimation methods for the MMAR model, investigate their statistical properties, and provide numerical simulations to corroborate them. Moreover, we integrate the MMAR model with connectedness network analysis to concurrently model the macroeconomic matrix time series of China's 31 provinces and a vector time series comprising the economic policy uncertainty index, trade policy uncertainty index, and China's geopolitical risk. By constructing multi-modal connectedness networks, we delve into the intricate interrelationships between China's regional economy and macroeconomic regulation. The findings of this study provide valuable insights for further research and policy-making in the relevant domains.
