# optimization, # recursive method, # discrete time analysis, # macroeconomics modelling, # numerical analysis, # Matlab codes
Dynamic programming is a method of solving optimization problems that involve time. Depending on model specifications, various numerical methodologies are applied. This lecture tries to explain which methods can be used in which settings. Theories are general but practical cases diverge. Pedagogical examples in Part II will be helpful in this sense.
Chapter 0. Overview of Dynamic Programming [PDF]
Chapter 1. Value Function Iteration
Chapter 2. Euler Equation Approach
Chapter 3. Solving Linear Rational Expectation Models
Chapter 4. Log Linearization
Chapter 5. Linear Quadratic Dynamic Programming
Chapter 6. Theories into Computers
Chapter 7.[VFI] McCall Search Model
Chapter 8.[VFI] Search and Separation
Chapter 9.[VFI] Deterministic Growth Model
Chapter 10.[VFI] Stochastic Growth Model
Chapter 11.[BK] Real Business Cycle Model
Chapter 12.[BK] New Keynesian Model
Chapter 13.[LQ] Optimal Consumption: Finite Horizon
Chapter 14.[LQ] Optimal Consumption: Infinite Horizon
Chapter 15.[LQ] Optimal Consumption: Age-Dependent Income
Chapter 16.[LQ] Optimal Consumption with Retirement
[VFI] stands for "Value Function Interation"; [BK] is for "Blanchard-Kahn Method"; [LQ] is for "Linear Quadratic Control".