This article surveys computational approaches to classical-Marxian economics. These approaches include a range of techniques - such as numerical simulations, agent-based models, and Monte Carlo methods - and cover many areas within the classical-Marxian tradition. We focus on three major themes...

We show that the Value Function Iteration (VFI) algorithm has difficulties approximating models with jump discontinuities in policy functions. We find that VFI fails to accurately identify both the location and size of jump discontinuities while the Endogenous Grid Method (EGM) and the Finite...

This paper uses a computational framework to analyse the equilibrium dynamics of exploitation and inequality in accumulation economies with heterogeneous labour. A novel index is presented which measures the intensity of exploitation at the individual level and the dynamics of the distribution...

Unlike linear ones, nonlinear business cycle models can generate sustained fluctuations even in the absence of shocks (e.g., via limit cycles/chaos). A popular approach to solving nonlinear models is perturbation methods. I show that, as typically implemented, these methods are incapable of...

I demonstrate how the discrete model of optimum income taxation can be used to derive the structure of optimal income tax rates. I compare simulations of the discrete and continuous models of optimum income taxation under identical circumstances, based on U.S. wage data. The two models produce...

This paper uses an economic agent-based model of land use in a growing community on the urban fringe to explore the importance of key economic variables on the spatial patterns of development over time. Understanding dispersed patterns of urban development is important for designing policies for...

While there is an extensive literature on identifying the asymptotic properties of adaptive learning algorithms, little is explicitly mentioned on how to actually implement these algorithms on the computer to analyze the quantitative effects of learning in dynamic macroeconomic models. The aim...

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...