- Department: Economics and Related Studies
- Module co-ordinator: Mr. Simon Weber
- Credit value: 20 credits
- Credit level: D
- Academic year of delivery: 2023-24
- See module specification for other years: 2024-25
This module aims to give you a cutting edge methodological training at the graduate level.
Occurrence | Teaching period |
---|---|
A | Semester 2 2023-24 |
This module's objectives would be threefold.
Provide the students with a solid theoretical foundation on a variety of decision models. The course would cover the unitary models, non–unitary models and matching models.
Introduce the students to structural estimation techniques. We would cover both the parametric and nonparametric (e.g. revealed preferences) approaches to estimating these models.
Discuss programming and computational challenges pertaining to the estimation of these models, and familiarise the students (if needed) to programming languages such as Matlab or Julia
Upon completing this module, students should be able to:
Understand and critically analyse one and two-sided decision making models
Learn and apply the related structural estimation techniques on their own data and empirical setting of interest
Identify areas where further research needs to be done, and where it might have a good chance of making progress given current knowledge.
The module will include the following topics
Economic decision making models
(a) Unitary models (parametric and nonparametric structural analysis of individual behaviour with applications to consumption, time-use, labour supply, production, etc.)
(b) Nonunitary models (cooperative and noncooperative bargaining models for group decision making with applications to household analysis, multi-selves models, etc.)
(c) Intertemporal models (static, full and limited commitment models with applications)
Two-sided matching models
(a) Frictionless matching models (in NTU, TU and ITU settings with applications to school choices, medical matching, marriage market, labour market, etc.)
(b) Search and matching models with applications to labour market, marriage markets, etc.
(c) Advanced topics (optimal transport models, discrete choice models, gravity equations/trade, etc.)
Task | Length | % of module mark |
---|---|---|
Essay/coursework Essay : Quantitative Research Methods |
N/A | 75 |
Oral presentation/seminar/exam Presentation : Quantitative Research Methods |
N/A | 25 |
None
Coursework (75%). Students will be asked to choose a paper related to the topics covered in class and to either write a referee report on it or replicate it.
Oral presentation (25%). Students will be asked to present the paper they chose for their coursework.
Coursework only reassessable as a revise and resubmit of the original work
Task | Length | % of module mark |
---|---|---|
Essay/coursework Essay : Quantitative Research Methods |
N/A | 75 |
Feedback will be given in line with University guidelines
Bertsekas, Dimitri. 2012. Dynamic Programming and Optimal Control: Volume I. Athena Scientific.
Bertsekas, Dimitri. 2016. Nonlinear Programming. Athena Scientific.
Browning, Martin, Pierre-André Chiappori, and Yoram Weiss. 2014. Economics of the Family. Cambridge University Press.
Chiappori, Pierre-André. 2017. Matching with Transfers: The Economics of Love and Marriage. Princeton University Press.
Galichon, Alfred. 2016. Optimal Transport Methods in Economics. Princeton University Press.
Roth, Alvin E., and Marilda A. Oliveira Sotomayor. 1990. Two-Sided Matching: A Study in Game-Theoretic Modeling and Analysis. Cambridge University Press.
Train, Kenneth E. 2009. Discrete Choice Methods with Simulation. 2nd ed. Cambridge University Press.
Vohra, Rakesh V. 2004. Advanced Mathematical Economics. Routledge Advanced Texts in Economics and Finance. London, England: Routledge