We compare the numerical methods that are most widely applied in the computation of the standard business cycle model with flexible labor. The numerical techniques imply economically insignificant differences with regard to business cycle summary statistics except for the volatility of...

This paper presents an efficient solution method for solving stochastic overlapping generations (S-OLG) models. We use the Chebyshev parameterized expectation algorithm (C-PEA) developed by Christiano and Fisher (2000) to solve the life cycle block of S-OLGs. The method is well suited for this...

This chapter is concerned with numerical simulation of dynamic economic models. We focus on some basic algorithms and assess their accuracy and stability properties. This analysis is useful for an optimal implementation and testing of these procedures, as well as to evaluate their performance....

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 study a generalized version of Coleman (1990)'s time iteration method (GTI) for solving dynamic optimization problems. Our benchmark framework is an irreversible investment model with labor-leisure choice. The GTI algorithm is simple to implement and provides advantages in terms of speed...

We develop an envelope condition method (ECM) for dynamic programming problems -- a tractable alternative to expensive conventional value function iteration. ECM has two novel features: First, to reduce the cost, ECM replaces expensive backward iteration on Bellman equation with relatively cheap...

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 introduce an envelope condition method (ECM) for solving dynamic programming problems. ECM iterates on the Bellman equation forward and is much faster than conventional value function methods that iterate backward. In the studied examples, ECM is comparable in accuracy and cost to Carroll's...

We study a generalized version of Coleman (1990)’s time iteration method (GTI) for solving dynamic optimization problems. Our benchmark framework is an irreversible investment model with labor-leisure choice. The GTI algorithm is simple to implement and provides advantages in terms of speed...

Computational methods both open the frontiers of economic analysis and serve as a bottleneck in what can be achieved. Using the quantum Monte Carlo (QMC) algorithm, we are the first to study whether quantum computing can improve the run time of economic applications and challenges in doing so....