《应用时间序列分析》是时间序列分析的入门课程，主要讲解经济学中分析时间序列数据的主要方法和工具。课程内容包括：平稳ARMA模型、向量自回归模型（VAR）、非平稳模型及单位根检验、协整与误差修正模型、以及状态空间模型。这些主题通过以下主线贯穿起来：从平稳到非平稳、从单变量到多变量。课程的主要目标是使学生掌握基本且必要的时间序列工具，以便为进一步学习高级宏观经济学课程以及进行涉及时间序列数据的实证研究做好准备。 （课程简介英文版） “Time Series Analysis” serves as an introduction to time series analysis, focusing on key methods and tools for analyzing time series data within the context of economics. The topics include stationary ARMA models, vector autoregressions, non-stationary models with unit root tests, cointegration and error correction models, and state space models. These topics are unified by a central progression: moving from stationary to non-stationary models, from univariate to multivariate approaches. The course aims to provide students with essential time series analysis skills, enabling them to pursue advanced macroeconomic studies and conduct empirical research involving time series data. |
