We propose a new methodology for structural estimation of dynamic discrete choice models. We combine the Dynamic … Programming (DP) solution algorithm with the Bayesian Markov Chain Monte Carlo algorithm into a single algorithm that solves the …

We propose a new methodology for structural estimation of dynamic discrete choice models. We combine the Dynamic … Programming (DP) solution algorithm with the Bayesian Markov Chain Monte Carlo algorithm into a single algorithm that solves the …

Structural discrete choice dynamic programming models have been shown to be a valuable tool for analyzing a wide range … develops a regression based approach to interpolating value functions during the solution of dynamic programming models that … to be excellent, and it greatly reduces the computational burden of estimating the parameters of a dynamic programming …

This paper formulates a structural dynamic programming model of preschool investment choices of altruistic parents and …

suitably restricted set. The proposed algorithm introduces a probabilistic relaxation technique that uses Dynamic Programming …

substitution method, the Hamiltonian method, and the dynamic programming approach) derives the conditions that must be satisfied by …

dynamic programming decomposition techniques widely used for traditional revenue management to develop an intuitive capacity …