The model explores the impact of public disclosure on tax compliance among diverse agents, including individual taxpayers and a tax authority. It incorporates heterogeneous preferences and income endowments among taxpayers, captured through a utility function that considers psychic costs subtracted from expected pecuniary utility. These costs include moral, reciprocity, and stigma costs associated with norm violations, leading to variations in taxpayers’ risk attitudes and related parameters. The tax authority’s attributes, such as the frequency of random audits, penalty rate, and the choice between partial or full disclosure, remain fixed throughout the simulation. Income endowments and preference parameters are randomly assigned to taxpayers at the outset.

Taxpayers maximize their expected utility by reporting income, taking into account tax, penalty, and audit rates. They make annual decisions based on their own and their peers’ behaviors from the previous year. Taxpayers indirectly interact at the societal level through public disclosure conducted by the tax authority, exchanging tax information among peers. Each period in the simulation collects data on total reported income, average compliance rates per income group, distribution of compliance rates, counts of compliers, full evaders, partial evaders, and the numbers of taxpayers experiencing guilt and anger. The model evaluates whether public disclosure positively or negatively impacts compliance rates and quantifies this impact based on aggregated individual reporting behaviors.

This model is a replication of that described by Peterson (2002) and illustrates the ‘spread’ feedback loop type described in Millington (2013).

This model expands approaches from social practice theories and is used to investigate the ability of the underlying conceptual model to explain the emergence of social practices, defined as routine behaviour that is similar amoung peers.

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 ABM looks at the effect of multiple reviewers and their behavior on the quality and efficiency of peer review. It models a community of scientists who alternatively act as “author” or “reviewer” at each turn.

We use a threshold model to drive our simulated network analysis testing public support for candidates in invisible primaries. We assign voter thresholds for candidates and vary number of voters, attachment to candidates and decay. Results of the algorithm show effects of size of lead, attachment and size of decay.

This model was developed as part of a class project, and explores the population dynamics and spread of an invasive insect, Emerald Ash Borer, in a county.

This theoretical model includes forested polygons and three types of agents: forest landowners, foresters, and peer leaders. Agent rules and characteristics were parameterized from existing literature and an empirical survey of forest landowners.

This is a coupled conceptual model of agricultural land decision-making and incentivisation and species metacommunities.

A spatial prisoner’s dilemma model with mobile agents, de-coupled birth-death events, and harsh environments.