经济学中的统计方法

学分：6

本课程将重点讲述基本实证研究法、定量结果解释法及金融学与经济学模型评估，着重要求学生理解定量方法、模型评估及经济学和商科领域实证研究法等。本课程将首先讲述一般经济学概念，然后讲述普通最小二乘法、异方差性、自相关函数、多重共线性、模型设定和时间序列分析等理论的基本原理和扩展。而且，学生需在学习过程中动手操作，运用 SAS 统计分析软件构建和计算模型、解释模型计算结果并做出预测，从而获得实践经验。学生可在本教学大纲末页查阅临时课程表。

在本课程结课时，学生应能够：

• 展示在统计方法领域学习的知识，以及对统计推断程序（用于分析现实世界数据）本质的理解

• 构建模型，以解答一些实证经济学问题

• 运用恰当的统计方法和技术，以理解变量之间的关系

• 确认并解释数值计算结果

• 评估各种模型之间的差异，表达自己对应用统计分析理论中幂和界限的理解

• 通过统计计算程序获得实践经验

• 运用相关数据和统计工具开展研究活动并展示研究成果

Statistical Methods in Economics 经济学中的统计方法

Credits: 6

The course emphasizes the techniques for fundamentally empirical research, interpretation of quantitative results and model evaluations in finance and economics. It emphasizes the understanding of quantitative methods, model evaluations, and the techniques for empirical studies in economics and business. The module starts with an introduction to general economic concepts, and then it will cover the basics and extension of ordinary least square methods, heteroskedasticity, autocorrelation, multicollinearity, model specifications, and time series analysis. Furthermore, students will gain hands-on experience formulating and estimating models, interpreting results, and making forecasts using SAS. A tentative class schedule can be found on the last page of the syllabus.

By the end of this module, students should be able to:

• demonstrate their knowledge of statistical methods, as well as an understanding of the nature of statistical inferential procedures involved in analysing real-world data;

• formulate models to solve some empirical economic problems;

• apply appropriate statistical methods and techniques to understand relationships among variables;

• identify and interpret the numeric outcomes;

• evaluate differences in types of models, and demonstrate an understanding of the power and limitations of applied statistical analysis;

• gain hands-on experience in using statistical computing program;

• perform and present research by using relevant data and statistical tools