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Course title |
Computation in Macroeconomics |
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Semester |
112-2 |
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Designated for |
COLLEGE OF SOCIAL SCIENCES GRADUATE INSTITUTE OF ECONOMICS |
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Instructor |
HSUAN-LI SU |
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Curriculum Number |
ECON7202 |
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Curriculum Identity Number |
323EM6770 |
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Class |
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Credits |
3.0 |
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Full/Half Yr. |
Half |
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Required/ Elective |
Elective |
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Time |
Thursday 2,3,4(9:10~12:10) |
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Remarks |
Restriction: MA students and beyond OR Restriction: Ph. D students The upper limit of the number of students: 20. |
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Course introduction video |
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Table of Core Capabilities and Curriculum Planning |
Table of Core Capabilities and Curriculum Planning |
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Course Syllabus
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Please respect the intellectual property rights of others and do not copy any of the course information without permission
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Course Description |
This course teaches computational techniques in the new research frontier, called Distributional Macroeconomics. I will cover heterogeneous agents (HA) models in both discrete time and continuous time. HA modeling is now widely used in macroeconomics, labor, international trade, industrial organization, and finance. This type of models can generate endogenous distributions of income, wealth, or firm-size, and hence offers a framework to study inequality, intergeneration mobility, macro-prudential policy, firm size distributions, firm values, and policy issues in industry organization. This course will teach relevant numerical methods in this field. I hope this course can help more students conduct research in this area. |
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Course Objective |
Know how to solve for heterogeneous agent models in discrete time and continuous time via computer. Students will learn methodology and relevant techniques to conduct research in this field. Students need to write programming codes every week and submit a research proposal in the middle of May. Hardworking is required. |
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Course Requirement |
Prerequiste: Macroeconomics Theory (I), probability theory, familiar with dynamic programming, and familiar with at least one programming language, like Matlab, Python, C/C++. |
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Student Workload (Expected weekly study hours before and/or after class) |
There will be 8 to 10 coding assignments. |
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Office Hours |
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Designated reading |
待補 |
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References |
待補 |
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Grading |
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Adjustment methods for students |
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Teaching methods |
Provide students with flexible ways of attending courses |
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Assignment submission methods |
Written report replaces oral report |
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Exam methods |
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Others |
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