Dynamic Optimization Methods with Applications

Lecture Notes

SES #	TOPICS	LECTURE NOTES
Discrete time: deterministic models
1-7	Vector spaces The principle of optimality Concavity and differentiability of the value function Euler equations Deterministic dynamics Models with constant returns to scale Nonstationary models	Lecture 1 (PDF) Lecture 2 (PDF) Lecture 3 (PDF) Lecture 4 (PDF) Lecture 5 (PDF) Lecture 6 (PDF) Lecture 7 (PDF)
Discrete time: stochastic models
8-9	Stochastic dynamic programming Stochastic Euler equations Stochastic dynamics	Lecture 8 (PDF) Lecture 9 (PDF)
Continuous time
10-12	Calculus of variations The maximum principle Discounted infinite-horizon optimal control Saddle-path stability	Lecture 10 (PDF)