We introduce an algorithm for solving dynamic economic models that merges stochastic simulation and projection … approaches: we use simulation to approximate the ergodic measure of the solution, we construct a fixed grid covering the support … support of the ergodic measure roughly uniformly. The proposed algorithm is tractable in problems with high dimensionality …

volume of data available. Yet comparing the algorithm to the judge proves complicated. First, the data are themselves … set of preferences than the single variable that the algorithm focuses on; for instance, judges may care about racial … concerns, our results suggest potentially large welfare gains: a policy simulation shows crime can be reduced by up to 24 …

? (2) Is it reachable through a decentralized algorithm? (3) What welfare properties does it possess? We prove that a … allocation achieved via sequential pairwise trades, but lends only weak support to the dynamic algorithm itself …

A new algorithm for the group minimization problem (GP) is proposed. The algorithm can be broadly described as follows …-known algorithm of Glover, and checked for non-negativity. The first non-negative point is an optimal solution of (GP). Advantages and … disadvantages of the algorithm are discussed; in particular, the implementation of the algorithm (which can be easily extended so as …

number of possible approaches to these problems and develops a particular algorithm based on the work of Powell and Dennis …

algorithm herself, her equity preference has no effect on the training procedure. So long as the data, however biased, contain … signal, they will be used and the learning algorithm will be the same. Equity preferences alone provide no reason to alter …

thinking may be important. Our results suggest that information-processing heuristics may be important even in markets with …