Dynamic programming is the foundation of dynamic economic analysis and often requires numerical solution methods. Standard methods are either slow or unstable. These instabilities are avoided when one uses modern methods from numerical optimization and approximation. Furthermore, large dynamic...

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...

This paper describes the first model considered in the computational suite project that compares different numerical algorithms. It is an incomplete markets economy with a continuum of agents and an inequality (borrowing) constraint.

Recent developments in public finance in the analysis of dynamic government debt policies have emphasized effects on the distribution of real resources across generations. At the same time, macroeconomists have emphasized the importance of the length of the time horizon over which agents...

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...

Recent advances in the examination of efficiency gains from dynamic tax reforms have used simulation models to isolate intragenerational and/or intergenerational effects. Important considerations having to do with uncertainty or capital market imperfections are frequently missing from such a...

It is often argued that incumbent firms may deter entry by preemptive investment in new goods. We show that these conclusions are reserved when multiproduct incumbent firms may exit in response to entry. Once entrants are in an industry, an incumbent will often want to withdraw some goods to...

Using the author's own experiences, this chapter shows how agent-based modeling (ABM) can address research questions common to many disciplines, facilitate interdisciplinary collaboration, provide a useful multidisciplinary tool when the math is intractable, and reveal unity across disciplines....

This chapter presents an overview of the existing learning models in the economic literature. Furthermore, it discusses the choice of models that should be used under various circumstances and how adequate learning models can be chosen in simulation approaches. It gives advice for using the many...

Computer automation has the potential, just starting to be realized, of transforming the design and operation of markets, and the behaviors of agents trading in them. We discuss the possibilities for automating markets, presenting a broad conceptual framework covering resource allocation as well...