SemesterSpring Semester, 2021
DepartmentPhD Program of Economics, First Year PhD Program of Economics, Second Year
Course NameMacroeconomic Theory(IV)
Course TypeRequired
Course Objective
Course Description
Course Schedule

General Specification:

(a) The student is expected to spend 12 hours per week on this course, which means 9-hour preparation and review work plus 3-hour class attendance.

(b) The assignment (the reading and the homework) will be given at the end of each ppt of the lecture.

(c) There will be a total of 16 lectures given in the class, the rest of the two weeks are one reserved for the midterm (Week 9, April 19) and one reserved for the final exam (Week 18, June 21). 

Weekly Progress

Week One (Lectured on Feb 22, 2021)

The Overview of the Class

(a) Wherefore Agent-Based Modeling

(b) The Crisis of Economy and the Crisis of Economics

(c) Market Origin of Agent-Based Modeling

(d) From the Non-Tanonnement Process to Macroeconomics

(e) Micro-Macro Link

Week Two (Lectured on March 1, 2021)

228 Memorial Days; No Class.

Week Three (Lectured on March 8, 2021)

An Introduction to Computational Social Science

(a) Computational Thinking of Social Phenomena

(b) John von Neumann (1903-1957) and his work 

(c) NetLogo

(d) Schelling-Sakoda Model

Week Four (Lectured on March 15, 2021)

Earliest Agent-Based Models: Cellular Automata (CA)

(a) Why Should We Take a Serious Look at CA?

(b) Biological Origin of Cellular Automata

(c) John Conway's Game of Life

(d) Stephen Wolfram’s Elementary Cellular Automata

(e) NetLogo, Computer Science, Cellular Automata

Week Five (Lectured on March 22, 2021)

Cellular Automata in Macroeconomic Modeling (I)

(a) Sentiment Dynamics and Economic Fluctuation

(b) Model of Market Sentiment

Week Six (Lectured on March 29, 2021)

Cellular Automata in Macroeconomic Modeling (II)

(a) Kalman Filter Learning, Belief Formation, and Multiple Equilibria

(b) Computational Irreducibility of Economic Policy

Week Seven (Lectured on April 5, 2021)

Tomb Sweeping Day; No Class.

 Week Eight (Lectured on April 12, 2021)

Network-Based Agent-Based Models: Development before and after the Late 1990s

(a) The First Generation (before the late 1990s)

(b) Spatial Games

(c) The Salient Break (the middle and late 1990s): Causes for Missing Networks

(d) The Second Generation (after the late 1990s)

(e) Small-World Networks and Market Efficiency

(f) Network Topologies and Cooperative Behavior

Week Nine (April 19, 2021)

Midterm Exam

Week Ten (Lectured on April  26, 2021)

ACE and Macroeconomic Experiments

(a) Rational Expectations

(b) Cobweb Model

(c) Macroeconomic Experiments on the Cobweb Model

(d) Learning to Optimize

(e) Genetic Algorithms

(f) Agent-based Cobweb Model Simulation via Genetic Algorithm Learning

Week Eleven (Lectured on May 3, 2021)

Agent-Based Modeling of Cobweb Models

(a) Learning to Forecast

(b) Genetic Programming

(c) Agent-based Cobweb Models and Simulation via, Genetic Programming

Week Twelve (Lectured on May 10, 2021)

Agent-Based Modeling of OLG Models (I)

(a) OLG Models in Economics

(b) OLG Inflation Experiments

(c) Two-Period OLG Model

(d) The Arifovic Model (Arifovic, 1996)

Week Thirteen (Lectured on May 17, 2021)

Agent-Based Modeling of OLG Models (II)

(a) The Chen-Yeh Model

(b) The Bullard-Duffy Model

(c) The Grandmont Model (Grandmont, 1985)

Week Fourteen(Lectured on May 24, 2021)

Agent-Based Modeling of Exchange Rate Dynamics (I)

(a) The Kareken-Wallace Model (Kareken and Wallace, 1981)

(b) OLG Experiments of Exchange Rates

(c) The Arifovic Model (Arifovic, 1996)

Week Fifteen (Lectured on May 31, 2021)

Agent-Based Modeling of Exchange Rate Dynamics (II)

(a) Econometric Analysis of Exchange Rates (Arifovic and Gencay, 2000)

(b) Capital Flight

(c) An agent-based model of Inflation and Exchange Rate (Arifovic, 2001)

(d) Currency Collapse

(e) Single Currency Equilibrium (Arifovic, 2002)

Week Sixteen (Lectured on June 7, 2021)

Agent-Based Financial Markets

(a) Programmed Agents and H-Type Models

(b) General Description

(c) Brock-Hommes’s ABS Models (Brock and Hommes, 1997, 1998)

(d) The Lux Model

(e) Stochastic Mechanics

(f) Jump Processes, Master Equation, and Fokker-Plank Equation

(g) Autonomous Agents and Santa Fe Artificial Stock Market

(h) Empirically-Based Agent-Based ModelsAgent-Based Modeling of Exchange Rate Dynamics (III)

Week Seventeen (Lectured on June 14, 2021)

Dragonboat Festival; No Class.

Week Eighteen (Lectured on June 21, 2021):

Final Exam



Teaching Methods
Teaching Assistant

The teaching assistant shall help the instructor to supervise and assist students' term project progress. The assistant shall assist the instructor in classroom preparation, such as the projector, internet connection, etc. The assistant shall help the instructor to grade the term project and help answer various administration problem associated with the class, such as classroom

change (if needed), information announcement, lecture notes upload, etc.


The course will be taught in English.  The course will proceed in lectures.  All lectures are prepared in power points, and the students will be able to get these power points before or after the classes.  Students are encouraged to use skype to interact with the instructor outside the classes.  The students have to read the materials, mainly, the ppt of the lecture, in advance. The lecture will only highlight the ppt, but will not follow the ppt. During the class, the students are invited to ask questions based on their readings of the preparatory materials and are also required to answer questions posed to them by the instructor. 30% of the score will be based on the in-class interacting performance of the student.

The evaluation of the student performance will be based on a term project (20%), a midterm exam (20%), a final exam (30%), and in-class interactions (30%).

For the term project, the student needs to choose a broad subject related to the class, and write an overview essay on it, for example, Chen, Chang, and Du (2012) and Chen and Gostoli (2014). These two are just examples to show how the term project looks like, but the student does not have to choose so wide and write so extensively. To choose a subject in a proper way, the

student is required to use the search engine, such as Google Scholar, to target a subject with 5 to 7 coherent articles on that subject, then read and write an overview on it. Alternatively, the student can choose to write a book review of a book published recently, say after 2015. Again, the book chosen has to be related to the class, for example, Di Guilmi, Gallegati, and Landini (2017). A good overview and review will be further polished and promoted to be published in a Scopus-Indexed

journal. The term project is due on Sep 1, 2021, and the late submission will not be accepted. The student is very welcome to discuss what they plan to do with the instructor using office hours or skype.  Both the midterm and the final exam will be open-book, and the student will be given one week for the midterm and two weeks for the final to work on it. So, for example, if the final exam is on June 21, 18:00 pm sharp, then the student only needs to submit his/her answer before June

28, 18:00 pm. Late submission will not be accepted.

Chen, S. H., Chang, C. L., & Du, Y. R. (2012). Agent-based economic models and econometrics. The Knowledge Engineering Review, 27(2), 187-219.

Chen, S. H., & Gostoli, U. (2014). Behavioral macroeconomics and agent-based macroeconomics. In Distributed Computing and Artificial Intelligence, 11th International Conference (pp. 47-54). Springer, Cham.

Di Guilmi, C., Gallegati, M., & Landini, S. (2017). Interactive macroeconomics: stochastic aggregate dynamics with heterogeneous and interacting agents. Cambridge University Press.


Textbook & Reference

Chen, Shu-Heng (2015), Agent-Based Computational Economics: How the idea originated and where it is going, Routledge.

Namatame, Akira and Shu-Heng Chen (2016), Agent-Based Modelling and Network Dynamics, Oxford.

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