Computational Methods in Agent Based Economics and Policy Simulation
Postgraduate: Level 7
Monday 13 January 2020
Friday 20 March 2020
11 April 2019
Requisites for this module
In the first half of the course, we will run the training in Java on the development of an agent-based computational economics model (ACE). It is accompanied by laboratory sessions which will cover macro-economic modelling, Java software development, object-oriented programming and implementation. It is a "how to design, programme and implement" module for ACE models with spec¬¬¬ific applications to building large scale data based driven flow of funds and financial network type agent based macro-economic models. The fundamental of simulation techniques is also covered.
In the second half of the course, we will run the training in R on the development of the main tools of the search-matching approach. Several policy issues can be addressed using these models, e.g., the design of unemployment insurance systems, the impact of hiring and firing costs, etc. We discuss both theoretical and empirical literature.
The aim of the course is to provide first step assistance to students towards the development of agent-based models and search-matching models
Upon successful completion of this course students will have acquired computational programming and modelling techniques necessary for modern macroeconomic and policy analysis
Compulsory for MSc Computational Economics, Financial Markets and Policy
Ten 2 hour lectures and ten 2 hour labs and classes.
Feedback for this module will occur through class meetings where we will go over the answers to problem sets and where you will be able to ask questions about your own method of solution; answers that will be posted on the website for the module that will give you written guidance on the appropriate method to approach the problems, assignments, and tests; and office hours where any additional questions can be addressed. You should be sure that you use these methods to understand how to improve your own performance.
- Lengnick, Matthias. (2013-2) 'Agent-based macroeconomics: A baseline model', in Journal of Economic Behavior & Organization. vol. 86, pp.102-120
- Gaffeo, Edoardo; Delli Gatti, Domenico; Desiderio, Saul; Gallegati, Mauro. (2008-10) 'Adaptive Microfoundations for Emergent Macroeconomics', in Eastern Economic Journal. vol. 34 (4) , pp.441-463
- Bontemps, Christian; Robin, Jean-Marc; Van den Berg, Gerard J. (1999-11) 'An Empirical Equilibrium Job Search Model With Search on the Job and Heterogeneous Workers and Firms', in International Economic Review. vol. 40 (4) , pp.1039-1074
- Abowd, John M.; Kramarz, Francis; Margolis, David N. (1999-03) 'High Wage Workers and High Wage Firms', in Econometrica. vol. 67 (2) , pp.251-333
- Burdett, Kenneth; Mortensen, Dale T. (1998-05) 'Wage Differentials, Employer Size, and Unemployment', in International Economic Review. vol. 39 (2) , pp.257-
The above list is indicative of the essential reading for the course. The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students. Further reading can be obtained from this module's reading list.
Assessment items, weightings and deadlines
|Coursework / exam
Module supervisor and teaching staff
Dr Ran Gu, email: email@example.com.
Mr Ran Gu
For further information, send a message to firstname.lastname@example.org
Dr Francis Kiraly
Available via Moodle
Of 85 hours, 0 (0%) hours available to students:
85 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).
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