主办单位：南京财经大学 公共财政研究中心 / 财政与税务学院
学习时间：2020年7月5日至2020年7月15日
学习方式：腾讯会议系统（报名后统一告知\提前发Slides预习、上机Code）
学员对象：经管类各层次学生与感兴趣的教师，报名邮箱1804144595@qq.com
活动性质：不收费的公益教学与学术项目
报名要求：感兴趣的高年级本科生（定位拔尖人才）、硕博士研究生、高校教师
截止日期：2020.6.30
学习证明：全勤给予结业证书
项目支持：社会资助/中心研究人员项目资助/政府项目资助
纪律要求：遵纪守法，严格遵守主办方的管理安排
上课时间：上午9:00-12:00（课程讲授） 下午14:30-16:30（上机为主）
授课语言：全英文教学
学习准备：提前阅读朱军编著《高级财政学II——DSGE的视角及应用前沿》1-6章。个人电脑安装Matlab和Dynare软件包，熟悉基本的Matlab操作。
朱军著《高级财政学II——DSGE的视角及应用前沿：模型分解与编程》2019年5月，上海财经大学出版社。全书配套Code：地址
http://csxy.nufe.edu.cn/info/1012/1681.htm
预期效果：掌握RBC模型建模及其中的财政政策
掌握NK-DSGE模型建模及其中的财政（货币）政策
掌握DSGE模型的算法、估计基本原理、前沿发展
了解高级财政理论研究和应用的前沿
暑期课程的主要内容(Topics and Literature)：
In line with the course objectives, two blocks of topics are covered in the lecture sequence. The primary focus of the first block is on the benchmark DSGE models and the macroeconomic theories behind. The basic principles and conditions for building a DSGE model is also covered:
1.Introduction
2.The basic real business cycle (RBC) model, dynamic programming and the Lagrangian approach
3.Loglinearization and the Blanchard and Kahn condition
4.Fiscal policy in a RBC environment
5.A classic monetary model
6.The basic New Keynesian model and monetary policy
The second block is devoted to the methods and tools used in solving and estimating the DSGE models in a general setting:
1.Perturbation in DSGE models
2.The Kalman filter
3.Bayesian estimation of state space models
4.Bayesian estimation of DSGE models
5.Estimating DSGE models with the generalized method of moments (GMM)
All the lectures are based on the selected articles and (chapters of) books. The main references include Ljungqvist and Sargent (2012), Judd (1998) and Herbst and Schorfheide (2016).
Course Policy
While this course is positioned itself as a public program, regular attendance is essential and is advised for participants to develop a comprehensive and consistent understanding of the topics.
表1 2020.7.5-7.15暑期学校的授课安排
注：tentative上机课时，会根据授课进度调整为授课。
Lecturer: Hong Lan. Dr. Hong Lan graduated from the School of Business and Economics, Humboldt University of Berlin (HU) with a MSc and a PhD in economics, and he currently is an assistant professor at the School of Finance, University of International Business and Economics (UIBE). His primary research interests focus on the numerical methods and their application to the analysis of the dynamic stochastic general equilibrium models (DSGE). In this subject, Dr. Lan and his coauthor Dr. Alexander Meyer-Gohde developed the nonlinear moving average solution algorithm of DSGE (https://github.com/lanhongken/nlma), which was published in the Journal of Economic Dynamics and Control. He is also interested in the search theory and its applications in macroeconomics, and has published his own result on this subject in the Computational Economics.
During his stay in HU, Dr. Lan gave both lecture and tutorial session of advanced macroeconomic analysis to PhD students for years. That course covered a range of, based on Ljungqvist and Sargent's textbook, modern macroeconomic theories and methodologies. He also gave research seminars of functional analysis for PhD students who was interested in computational economics.
报名需要提供的信息：
1.姓名、性别、单位、在读班级或工作经历、手机号、邮箱；
2.遵守我校校纪校规、遵守线上教学纪律的承诺；
电子邮件报名邮箱：
1804144595@qq.com
