AØKK08207U Dynamic Programming - Theory, Computation, and Empirical Applications
The overall purpose of the course is to provide a fundamental
understanding of dynamic programming (DP) models and their
empirical application. The DP framework has been extensively used
in economic modeling because it is sufficiently rich to model
almost any problem involving sequential decision making over time
and under uncertainty. Prominent examples are saving/consumption
decisions, retirement behavior, investment, labor supply/demand,
housing decisions. The course will first introduce participants to
theoretical concepts, and then focus on empirical applications
covering both discrete and continuous decision problems as well as
the estimation of dynamic games.
The purpose of the lectures and the exercise classes is that the student should
- Acquire knowledge about stochastic dynamic programming and the involved computational hurdles (Curse of dimensionality, high dimensional integration, multiplicity of solutions, etc.)
- Acquire knowledge about solution methods for dynamic structural models of sequential decision making under uncertainty of both finite and infinite horizons (backward recursion, value function iterations, policy iterations, and Mathematical Programming with Equilibrium Constraints (MPEC), Carroll's method of endogenous gridpoints (EGM)).
- Acquire knowledge about estimation methods (full solution methods: Mathematical Programming with Equilibrium Constraints (MPEC) and Nested Fixed Point Algorithm (maximum likelihood, minimum distance, indirect inference, GMM and simulation versions of these); Non-full solution methods: CPP-estimator, Nested Pseudo likelihood (policy iteration estimators); GMM using Euler equations).
- Acquire knowledge about numerical techniques to evaluate integrals (Quadrature methods and Monte Carlo integration) involved in evaluating expectations future states of the world and to integrate unobservable out of the sample criterion used in estimation (e.g. the likelihood function).
- Acquire knowledge about the numerical approximation and interpolation techniques required to approximate value functions over continuous state variables (splines, orthogonal polynomials, neural net).
- Acquire knowledge about a variety of dynamic structural models
- Acquire knowledge about how evaluate policy initiatives by means of counter factual simulations
- Get hands on experiences with solving and/or estimating relatively simple models (cake eating, stochastic growth, consumption/savings, investment, labor demand/supply and simple dynamic games).
The purpose of the term paper is to make students combine many of the simplified building blocks we covered in the computer exercises. By combining these building blocks, students should be able to solve and estimate more sophisticated model.In particular the students should be able to
- Solve and estimate dynamic games or single agent models and test hypotheses using solution and estimation methods discussed in the course. Ideally students should be able to replicate the results from an already published paper and thereby get hands on experience with the involved techniques.
- Investigate the consequences policy proposals by means of counterfactual simulations program the estimators applied in the paper using MATLAB (or GAUSS, FOTRAN and C).
- Present the analysis in a short and focused term paper.
Hence, after completing the course, the student should have acquired the tools necessary to understand papers and undertake empirical analysis on a (simple) dynamic structural model and to present the analysis in a short and focused paper. The acquired skills in dynamic programming theory and practice provide a strong background that enable students to do empirical analyses at a high level suitable for a Master or even a PhD thesis.
- Jérome Adda and Russell Cooper: “Dynamic Economics: Quantitative Methods and Applications” MIT Press 2003, ISBN: 978-0-262-01201-0
- Kenneth Judd: “Numerical Methods in Economics” MIT Press 1998, ISBN: 978-0-262-10071-7
- 15-20 papers: Ranging from classic seminal contributions to recent state of the art work from the research frontier.
The lectures focus on theory whereas the class provides hands on knowledge of solution and estimation of the models. Ideally, the whole process of estimating a dynamic structural model empirically is learned by writing a term paper that has to be handed in at the end of the semester.
Time and room:
Time and room for the lectures and exercise classes: Please press the link under "Se skema" (See schedule). 15F means Spring (Forår) 2015
The springsemester is available partly in English at this link:
https://skema.ku.dk/KU1415/reporting/textspreadsheet?objectclass=module&idtype=id&identifier=43809&t=SWSCUST+module+textspreadsheet&days=1-5&weeks=27-52&periods=1-68&template=SWSCUST+module+textspreadsheet
The first lecture in the springsemester will be the 2.th of February 2015 at 8.00 o´clock (AM). The exercise classes begins in week 6.
- Category
- Hours
- Class Instruction
- 24
- Exam
- 0,42
- Lectures
- 42
- Preparation
- 160
- Total
- 226,42
- Credit
- 7,5 ECTS
- Type of assessment
- Written assignmentOral examination, 25 min under invigilationA written termal paper and an oral exam without preparation.
- Exam registration requirements
- Project description and term paper should be handed in before deadline.
- Aid
All aids can be used to the project assignment.
The student can only take the project assignment in to the oral examination otherwice it is a closed book examination.
- Marking scale
- 7-point grading scale
- Censorship form
- External censorship
100 % censorship
- Exam period
- For the Spring semester 2015: From 26 May to 28 June 2015 The projct description has to be uploaded not later than monday the 6. of April 2015. The deadline for the assignment will be informed by the teacher in the begin of the semester. The oral exam wil be in the week number 22 of 2015. More information is available at https://intranet.ku.dk/economics_ma/examination/Pages/default.aspx
- Re-exam
- As ordinary with the same assignment.
Criteria for exam assesment
The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.
Course information
- Language
- English
- Course code
- AØKK08207U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 semester
- Placement
- Spring
- Schedule
- Spring (week 6-21)
- Continuing and further education
- Price
320 DKK per ECTS
- Study board
- Department of Economics, Study Council
Contracting department
- Department of Economics
Course responsibles
- Bertel Schjerning (17-4e717e8071783a5f6f7476717e7a757a734c716f7b7a3a77813a7077)
- Thomas Høgholm Jørgensen (18-81757c7a6e803b753b777c7f74727b80727b4d72707c7b3b78823b7178)
Lecturers
Spring 2015:
Lecturers:
Bertel Schjerning
Thomas Høgholm Jørgensen
Exercise class: Patrick Mogensen