We introduce a novel approach to solving dynamic programming problems, such as those in many economic models, on a quantum annealer, a specialized device that performs combinatorial optimization ...

This course covers reinforcement learning aka dynamic programming, which is a modeling principle capturing dynamic environments and stochastic nature of events. The main goal is to learn dynamic ...

An error correction model is derived from a stochastic dynamic programming problem incorporating rational expectations. A parametric restriction is derived that ...

We review existing approaches to the specification and estimation of dynamic microeconomic models of fertility. Dynamic fertility models explain the evolution of fertility variates over the life-cycle ...

Traditional problem-solving approaches, reliant on extensive data analysis and statistical methods, can often prove to be time-consuming and ineffective. Enter the dynamic learning model, which I ...