Динамическое программирование и приложения
- The main aim of "Dynamic Programming and Applications" course is to provide students with the overview of the standard methods for the solution of problems with intertemporal trade-offs.
- By the end of the course student will understand the basics of the dynamic programming, will be able to define and solve problems with intertemporal trade-offs.
- To get the students acquainted with the method of dynamic programming for solving problems with intertemporal trade-offs.
- To give the understanding of the applicability of the dynamic programming in various fields of economics, business and IT.
- To introduce the students into the basics of macroeconomic modelling with the relation to the dynamic programming method.
- To define further directions for self-study and professional development in the field of structural macroeconomic modelling with a stress on the applicability of the studied numerical methods.
- Introduction to Dynamic Programming, Part 1.Introduction to the concept of DP, scope of application; Motivational examples: inventory control, deterministic scheduling problem; More of motivational examples: machine replacement, chess match strategy.
- Introduction to Dynamic Programming, Part 2.Definition of the basic problem of DP in discrete time; The DP algorithm, principle of optimality; Applying the DP algorithm on the deterministic scheduling example; The DP algorithm with inventory control; Linear quadratic problem.
- DP in (Macro)Economics, Part 1.Indirect utility: firms and consumers; Cake-eating problem: direct attack vs. DP approach; Cake-eating problem with infinite horizon; Example of analytical solution for the DP problem.
- DP in (Macro)Economics, Part 2.Taste shocks and discrete choice; General formulation: stationarity and discounting; Consumption problem: two-period problem, stochastic income, infinite horizon, endogenous labor supply.
- Numerical Methods.Value function iteration: general principle and illustration on cake-eating problem; Policy function iteration: principle and advantages over the value function iteration.
- Introduction to the problem of optimal control.Definition of the simplest problem in continuous time; Hamiltonian function and the maximum principle; Application to the problem of energy use and environmental quality.
- DP Applications.Investment problem; Dynamics of employment adjustment; Price setting problem; McCall labor search model; Inflation and unemployment: Phillips tradeoff.
- Промежуточная аттестация (4 модуль)0.5 * Final Exam + 0.15 * Homework Tasks + 0.1 * In-class Participation + 0.25 * Midterm
- Chiang, A. C. (2012). Elements of dynamic optimization. Waveland Press.
- Dynamic economics : quantitative methods and applications, Adda, J., Cooper, R., 2003
- Kenneth L. Judd. (1998). Numerical Methods in Economics. The MIT Press.
- Bertsekas, D. P. (2017). Stable Optimal Control and Semicontractive Dynamic Programming.