The Emergent Firm (EF) model is based on the premise that firms arise out of individuals choosing to work together to advantage themselves of the benefits of returns-to-scale and coordination. The Emergent Firm (EF) model is a new implementation and extension of Rob Axtell’s Endogenous Dynamics of Multi-Agent Firms model. Like the Axtell model, the EF model describes how economies, composed of firms, form and evolve out of the utility maximizing activity on the part of individual agents. The EF model includes a cash-in-advance constraint on agents changing employment, as well as a universal credit-creating lender to explore how costs and access to capital affect the emergent economy and its macroeconomic characteristics such as firm size distributions, wealth, debt, wages and productivity.

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.

A curious aspect of the Covid-19 pandemic is the clustering of outbreaks. Evidence suggests that 80\% of people who contract the virus are infected by only 19% of infected individuals, and that the majority of infected individuals faile to infect another person. Thus, the dispersion of a contagion, $k$, may be of more use in understanding the spread of Covid-19 than the reproduction number, R0.

The Virus Transmission with Super-spreaders model, written in NetLogo, is an adaptation of the canonical Virus Transmission on a Network model and allows the exploration of various mitigation protocols such as testing and quarantines with both homogenous transmission and heterogenous transmission.

The model consists of a population of individuals arranged in a network, where both population and network degree are tunable. At the start of the simulation, a subset of the population is initially infected. As the model runs, infected individuals will infect neighboring susceptible individuals according to either homogenous or heterogenous transmission, where heterogenous transmission models super-spreaders. In this case, k is described as the percentage of super-spreaders in the population and the differing transmission rates for super-spreaders and non super-spreaders. Infected individuals either recover, at which point they become resistant to infection, or die. Testing regimes cause discovered infected individuals to quarantine for a period of time.

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.

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Policymakers decide on alternative policies facing restricted budgets and uncertain future. Designing public policies is further difficult due to the need to decide on priorities and handle effects across policies. Housing policies, specifically, involve heterogeneous characteristics of properties themselves and the intricacy of housing markets and the spatial context of cities. We propose PolicySpace2 (PS2) as an adapted and extended version of the open source PolicySpace agent-based model. PS2 is a computer simulation that relies on empirically detailed spatial data to model real estate, along with labor, credit, and goods and services markets. Interaction among workers, firms, a bank, households and municipalities follow the literature benchmarks to integrate economic, spatial and transport scholarship. PS2 is applied to a comparison among three competing public policies aimed at reducing inequality and alleviating poverty: (a) house acquisition by the government and distribution to lower income households, (b) rental vouchers, and (c) monetary aid. Within the model context, the monetary aid, that is, smaller amounts of help for a larger number of households, makes the economy perform better in terms of production, consumption, reduction of inequality, and maintenance of financial duties. PS2 as such is also a framework that may be further adapted to a number of related research questions.

The model explores how two types of information - social (in the form of pheromone trails) and private (in the form of route memories) affect ant colony level foraging in a variable enviroment.

The SWE models firms search behaviour as the performance landscape shifts. The shift represents society’s pricing of negative externalities, and the performance landscape is an NK structure. The model is written in NetLogo.

The purpose of this model is to explore the effects of different power structures on a cross-functional team’s prosocial decision making. Are certain power distributions more conducive to the team making prosocial decisions?

The model simulates interactions in small, task focused groups that might lead to the emergence of status beliefs among group members.

Motivated by the emergence of new Peer-to-Peer insurance organizations that rethink how insurance is organized, we propose a theoretical model of decision-making in risk-sharing arrangements with risk heterogeneity and incomplete information about the risk distribution as core features. For these new, informal organisations, the available institutional solutions to heterogeneity (e.g., mandatory participation or price differentiation) are either impossible or undesirable. Hence, we need to understand the scope conditions under which individuals are motivated to participate in a bottom-up risk-sharing setting. The model puts forward participation as a utility maximizing alternative for agents with higher risk levels, who are more risk averse, are driven more by solidarity motives, and less susceptible to cost fluctuations. This basic micro-level model is used to simulate decision-making for agent populations in a dynamic, interdependent setting. Simulation results show that successful risk-sharing arrangements may work if participants are driven by motivations of solidarity or risk aversion, but this is less likely in populations more heterogeneous in risk, as the individual motivations can less often make up for the larger cost deficiencies. At the same time, more heterogeneous groups deal better with uncertainty and temporary cost fluctuations than more homogeneous populations do. In the latter, cascades following temporary peaks in support requests more often result in complete failure, while under full information about the risk distribution this would not have happened.