We introduce the market resources method (MRM) for solving dynamic optimization problems. MRM extends Carroll’s (2006) endogenous grid point method (EGM) for problems with more than one control variable using policy function iteration. The MRM algorithm is simple to implement and provides...

We present the first necessary and sufficient conditions for the existence of a unique perfect-foresight solution, returning to a given steady-state, in an otherwise linear model with occasionally binding constraints. We derive further conditions on the existence of a solution in such models,...

This paper presents and compares Newton-based methods from the applied mathematics literature for solving the matrix quadratic that underlies the recursive solution of linear DSGE models. The methods are compared using nearly 100 different models from the Macroeconomic Model Data Base (MMB) and...

This paper applies structure preserving doubling methods to solve the matrix quadratic underlying the recursive solution of linear DSGE models. We present and compare two Structure-Preserving Doubling Algorithms (SDAs) to other competing methods - the QZ method, a Newton algorithm, and an...

We show that the standard Value Function Iteration (VFI) algorithm has difficulties approximating models with jump discontinuities in policy functions. We find that VFI fails to accurately identify the location and size of jump discontinuities while other methods - such as the Endogenous Grid...

This paper discusses how to design, solve and estimate dynamic programming models using the open source package niqlow. Reasons are given for why such a package has not appeared earlier and why the object-oriented approach followed by niqlow seems essential. An example is followed that starts...

We introduce a fast upper-envelope scan (FUES) method to compute solutions for dynamic programming problems with continuous and discrete choices. The FUES method builds on the standard endogenous grid method (EGM). Standard EGM applied to problems with continuous and discrete choices does not by...

This chapter discusses computational methods for approximating portfolio and asset pricing problems. Formulation of these problems is usually specified along with components, preferences, payoffs, etc., that are analytic functions. This implies that the solutions to these problems acquire this...

We introduce a novel approach to solving dynamic programming problems, such as those in many economic models, on a quantum annealer, a specialized device that performs combinatorial optimization. Quantum annealers attempt to solve an NP-hard problem by starting in a quantum superposition of all...

The development and use of forward-looking macro models in policymaking institutions has proceeded at a pace much slower than predicted in the early 1980s. An important reason is that researchers have not had access to robust and efficient solution techniques for solving nonlinear...