The Modern Wage Dynamics Model is a generative model of coupled economic production and allocation systems. Each simulation describes a series of interactions between a single aggregate firm and a set of households through both labour and goods markets. The firm produces a representative consumption good using labour provided by the households, who in turn purchase these goods as desired using wages earned, thus the coupling.

Each model iteration the firm decides wage, price and labour hours requested. Given price and wage, households decide hours worked based on their utility function for leisure and consumption. A labour market construct chooses the minimum of hours required and aggregate hours supplied. The firm then uses these inputs to produce goods. Given the hours actually worked, the households decide actual consumption and a market chooses the minimum of goods supplied and aggregate demand. The firm uses information gained through observing market transactions about consumption demand to refine their conceptions of the population’s demand.

The purpose of this model is to explore the general behaviour of an economy with coupled production and allocation systems, as well as to explore the effects of various policies on wage and production, such as minimum wage, tax credits, unemployment benefits, and universal income.

…

Agent-Based Computational Model of the cryptocurrency Bitcoin with a realistic market and transaction system. Bitcoin’s transaction limit (i.e. block size) and Bitcoin generation can be calibrated and optimized for wealth and network’s hashing power by the Non-Dominated Sorted Genetic Algorithm - II.

The General Housing Model demonstrates a basic housing market with bank lending, renters, owners and landlords. This model was developed as a base to which students contributed additional functions during Arizona State University’s 2020 Winter School: Agent-Based Modeling of Social-Ecological Systems.

This research aims to uncover the micro-mechanisms that drive the macro-level relationship between cultural tolerance and innovation. We focus on the indirect influence of minorities—specifically, workers with diverse domain expertise—within collaboration networks. We propose that minority influence from individuals with different expertise can serve as a key driver of organizational innovation, particularly in dynamic market environments, and that cultural tolerance is critical for enabling such minority-induced innovation. Our model demonstrates that seemingly conflicting empirical patterns between cultural tightness/looseness and innovation can emerge from the same underlying micro-mechanisms, depending on parameter values. A systematic simulation experiment revealed an optimal cultural configuration: a medium level of tolerance (t = 0.6) combined with low consistency (κ = 0.05) produced the fastest adaptation to abrupt market changes. These findings provide evidence that indirect minority influence is a core micro-mechanism linking cultural tolerance to innovation.

Subjective biases and errors systematically affect market equilibria, whether at the population level or in bilateral trading. Here, we consider the possibility that an agent engaged in bilateral trading is mistaken about her own valuation of the good she expects to trade, that has not been explicitly incorporated into the existing bilateral trade literature. Although it may sound paradoxical that a subjective private valuation is something an agent can be mistaken about, as it is up to her to fix it, we consider the case in which that agent, seller or buyer, consciously or not, given the structure of a market, a type of good, and a temporary lack of information, may arrive at an erroneous valuation. The typical context through which this possibility may arise is in relation with so-called experience goods, which are sold while all their intrinsic qualities are still unknown (such as untasted bottled fine wines). We model this “private misvaluation” phenomenon in our study. The agents may also be mistaken about how their exchange counterparties are themselves mistaken. Formally, they attribute a certain margin of error to the other agent, which can differ from the actual way that another agent misvalues the good under consideration. This can constitute the source of a second-order misvaluation. We model different attitudes and situations in which agents face unexpected signals from their counterparties and the manner and extent to which they revise their initial beliefs. We analyse and simulate numerically the consequences of first-order and second-order misvaluation on market equilibria.

Simple population dynamics model used in Introduction to Agent-Based Modeling by Marco Janssen. For more information see https://intro2abm.com/

This model simulates the behaviour of the agents in 3 wine markets parallel trading systems: Liv-ex, Auctions and additionally OTC market (finally not used). Behavioural aspects (impatience) is additionally modeled. This is an extention of parallel trading systems model with technical trading (momentum and contrarian) and noise trading.

In this Repast model the ‘Consumat’ cognitive framework is applied to an ABM of the Dutch car market. Different policy scenarios can be selected or created to examine their effect on the diffusion of EVs.

The dynamic agent based model of system which turn out the self-adjusting system, are considered in this text.

3 simple models to illustrate diffusion of innovations.
The models are discussed in Introduction to Agent-Based Modeling by Marco Janssen. For more information see https://intro2abm.com/