Continuous-time stochastic games with a finite number of states have substantial computational and conceptual advantages over the more common discrete-time model. In particular, continuous time avoids a curse of dimensionality and speeds up computations by orders of magnitude in games with more...

We explore the implications of ownership concentration for the recently-concluded incentive auction that re-purposed spectrum from broadcast TV to mobile broadband usage in the U.S. We document significant multi-license ownership of TV stations. We show that in the reverse auction, in which TV...

We study industries where the price that a firm sets serves as an investment into lower cost or higher demand. We assess the welfare implications of the ensuing competition for the market using analytical and numerical approaches to compare the equilibria of a learning-by-doing model to the...

We explore the extent to which the huge race gap in wealth can be explained with properly constructed income and demographic variables. In some instances we explain the entire wealth gap with income and demographics provided that we estimate the wealth model on a sample of whites. However, we...

We document the evolution of the newly created market for frequency response within the UK electricity system over a six-year period. Firms competed in price while facing considerable initial uncertainty about market demand and rival behavior. We show that over time prices stabilized, converging...

We examine the problem of optimal taxation in a dynamic economy with imperfectly competitive markets. We find that the optimal tax system will tend to provide subsidies for the purchase of capital goods to offset gaps between price and marginal cost. The average tax on capital income will be...

We use the stochastic simulation algorithm, described in Judd, Maliar and Maliar (2009), and the cluster-grid algorithm, developed in Judd, Maliar and Maliar (2010a), to solve a collection of multi-country real business cycle models. The following ingredients help us reduce the cost in...

We develop a projection method that can solve dynamic economic models with a large number of state variables. A distinctive feature of our method is that it operates on the ergodic set realized in equilibrium: we simulate a model, distinguish clusters on simulated series and use the clusters'...

We introduce a technique called "precomputation of integrals" that makes it possible to compute conditional expectations in dynamic stochastic models in the initial stage of the solution procedure. This technique can be applied to any set of equations that contains conditional expectations, in...

Numerical dynamic programming algorithms typically use Lagrange data to approximate value functions over continuous states. Hermite data is easily obtained from solving the Bellman equation and can be used to approximate value functions. We illustrate this method with one-, three-, and...