We propose to combine smoothing, simulations and sieve approximations to solve for either the integrated or expected value function in a general class of dynamic discrete choice (DDC) models. We use importance sampling to approximate the Bellman operators defining the two functions. The random...

We present a fast and accurate computational method for solving and estimating a class of dynamic programming models with discrete and continuous choice variables. The solution method we develop for structural estimation extends the en- dogenous grid-point method (EGM) to discrete-continuous...

We introduce a computationally tractable dynamic equilibrium model of the automobile market where new and used cars of multiple types (e.g. makes/models) are traded by heterogeneous consumers. Prices and quantities are determined endogenously to equate supply and demand for all car types and...

We revisit the comparison of mathematical programming with equilibrium constraints (MPEC) and nested fixed point (NFXP) algorithms for estimating structural dynamic models by Su and Judd (SJ, 2012). They used an inefficient version of the nested fixed point algorithm that relies on successive...