数量经济学研讨会  
题目：Macroeconomic Forecasting Methods with Big Data
报告人：吴柏林 教授 
时间： 2016年6月17日（周五） 10:30-12:00
地点：明德楼主楼734会议室
Abstract：Economic forecasting mostly comes after economic model construction. Model construction are mainly based on historic data.  A fundamental drawback is that: with these well-constructed models people are still hesitated to predict future trends or market changes in practice. Since historical time series analysis has difficult to prove the relationship/causality with future events. Especially in the case of a structural change, the future is full of high uncertainty, ambiguity and unexpected. Construction of Big Data platform will be a new technique provides to solve the structured change and uncertain problem.  According to its artificial intelligence evolution and on line improvement to the market conditions, it will do a better response to prevailing future event. The object of this research is to construct macroeconomic forecasting in big data context, including consumer behavior, market information and structural changes, nonlinear pattern recognition, panel and spatial patterns, semantic processing mode of artificial intelligence. Empirical study will be illustrated in an efficient way with the entropy itself, the market behavior and forecasting trend.
Keywords: macroeconomic, forecasting methods, big data, entropy, art future intelligent
 
报告人简介：台湾政治大学教授，曾任斯坦福大学、早稻田大学、首尔大学、北京大学等多所大学客座教授。美国印第安纳大学统计学博士。研究领域为时间序列分析与预测、模糊数学、人工智能以及应用统计。发表英文论文百余篇，中文论文50余篇，著作10余部。

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