Automated Market Makers (AMMs) are a relatively new mechanism that allow people to trade cryptocurrencies instantly. Unlike typical centralized trades that utilize order-books, AMMs are decentralized, so they do not require the matching of buyers and sellers for exchanges; rather, they use a pre-determined formula to offer prices for trades. AMMs have recently gained popularity within the blockchain ecosystem, with the value of cryptocurrencies locked in decentralized finance reaching 89.23 billion USD; however, AMMs remain relatively unstudied by economists. This paper provides an introductory analysis of AMMs through agent-based modeling, using the mTree Microeconomic Systems framework. Utilizing the framework, we model a decentralized finance environment, blockchain and AMM institutions, and different agent types, incentivized to trade for various reasons. With computer simulations, different behaviors of agents using AMMs and different characteristics of AMMs are modeled as treatments and run numerous times. We specifically analyze arbitrage agents, a trader-type who uses token price differences in various markets to make low-risk profits and equilibrate the prices of cryptocurrencies across markets. Since arbitrage agents have not been studied through simulations, we provide the first analysis of arbitrage activity using this method and explore how their behavior can influence an AMM's efficiency. We find that an AMM's liquidity depth impacts the performance of agents and the volatility of prices, indicating that this, and other features should be considered when using and creating AMMs.

Holt and Laury introduce a risk elicitation mechanism, providing rules and procedures for decision-makers who are asked to make a sequence of choices between pairs of lotteries in an ordered table of binary lotteries. In their mechanism, a theoretical agent will switch their choice once from the higher variance lottery to the lower variance lottery. The theoretical switching point implies a range of risk coefficients for a subject who is assumed to have the same class of preferences and uses the same decision rule as the theoretical agent. Holt and Laury use their mechanism in a sequence of experiments to measure risk coefficients as they vary payoff size and whether the payoffs are real or hypothetical. The authors find that subjects exhibit increasing risk aversion as the scale of real payoffs increases. By comparison, inferred risk aversion does not increase when the scale of hypothetical payoffs increases.

Using a three-player dictator-game experiment, we find that similar performance during a shared experience with a real-effort task causes a redistributor to privilege the stakeholder who performed similarly. We generate the shared experience by varying whether a third-party decision maker and a stakeholder acquire money through an effortful activity or through random selection of a ticket. Our results have implications for how perceptions of one's own self-determination and social connectedness based on perceived similarities affect redistributive preferences.

In this chapter, we discuss some ways in which neuroeconomic research can inform legal scholarship. Given the limitations on space of this chapter, we cannot discuss anything like all of the neuroeconomic research that has been done in the last few years, even all of that which is of relevance to legal scholarship. Therefore, this chapter is a highly selective review of the research that we believe is useful to legal scholars. The focus of the chapter is on neuroeconomic research related to financial decisions and its relevance to legal scholarship.

This paper proposes a general methodology to study economic laws defined in terms of the computations performed by economic systems. Using this methodology, a new economic law is proposed where economic computations move towards minimum cost solutions. This law is applied to a review of some of the relevant literature on exchange systems. Finally, a research program is proposed to further explore the consequences of cost-minimizing computations in the study of exchange.

This paper uses subjects recruited from an online employment exchange to study the robustness of the triadic trust design with a different subject pool. In running our experiments we tried to take advantage of the cost reducing features of the micro-employment culture found on Amazon’s Mechanical Turk. We find that first mover trust is robust to the change in subject pool, but second mover reciprocity was not.

We design a public goods laboratory experiment in both a virtual world environment and an abstract computerized environment, each with and without communication and visibility, to investigate how communication and visibility of other participants affect individual contributions to public goods. In both environments, the presence of communication significantly and consistently improves public good contributions. However, the interaction between communication and visibility differs in the two environments. While the two dimensions are substitutes in the abstract computerized environment, they work in a complementary way to increase public goods contributions in the virtual world environment. Chat content analysis further shows that positive reinforcement and monitoring have a positive impact on cooperation, but dissent has a negative impact.

Southern Economic JournalVolume 83, Issue 3 p. 649-654 Symposium in Honor of Vernon Smith Vernon Smith's Support for Education in Virtual Worlds Kevin McCabe, Kevin McCabe Department of Economics, George Mason University, 4400 University Drive, Fairfax, VA 22030, USA; E-mail: kmccabe@gmu.edu.Search for more papers by this author Kevin McCabe, Kevin McCabe Department of Economics, George Mason University, 4400 University Drive, Fairfax, VA 22030, USA; E-mail: kmccabe@gmu.edu.Search for more papers by this author First published: 29 January 2017 https://doi.org/10.1002/soej.12199 Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Volume83, Issue3January 2017Pages 649-654 RelatedInformation

Detecting deception in natural language is a problem amenable to economic analysis.Economics typically assumes that individuals are self-interested, which leads them to perform actions in accord with their own goals.The field of experimental economics emerged to construct environments wherein human subjects make decisions so as to test economic hypotheses.Experimental economists recently have developed virtual worlds to better situate experiment subjects in more realistic environments.Virtual word experiments represent an exciting new area for deception research as they offer insight into individuals both acting out and communicating in accord with their intentions.This paper describes the use of virtual world experiments for economic research incorporating the detection of deceptive individuals.

Neuroeconomics is interested in understanding the interrelationship between computational mechanisms that exist in our evolved brains and computational mechanisms that exist in our constructed institutions. Game theory examines the way in which incentives affect decisions in strategic environments, and as such is an ideal tool for neuroeconomics studies because it links individual decision making to group level outcomes using clearly defined mechanisms. This chapter discusses the way game theory has been used to generate hypotheses in neuroeconomics, and reviews key concepts in the design and analysis of game theory and neuroeconomics experiments used to draw inferences regarding these hypotheses. The chapter concludes by indicating the way results from these experiments may point to a neuroeconomic theory of game playing.

Several scholars have argued that abundant natural resources can be harmful to economic performance under bad institutions and helpful when institutions are good. These arguments have either been theoretical or based on naturally-occurring variation in natural resource wealth. We test this theory using a laboratory experiment to reap the benefits of randomized control. We conduct this experiment in a virtual world (Second LifeTM) to make institutions more visceral. We find support for the theory.

This online supplement contains additional materials related to "The Determinants of Territorial Property Rights in a Spatial Commons Experiment". The paper to which these Appendices apply is available at the following URL: http://ssrn.com/abstract=2503260

The experiment presented here provides evidence that, in the presence of first possession and inequality, the degree to which a third-party re-distributor honors preexisting entitlements is bounded. Using a third-party redistributive task, the design examines how impartial decision makers redistribute the income of an advantaged stakeholder to a disadvantaged stakeholder. The results show that redistribution significantly decreases when entitlements to income are legitimized either by having an endowed stakeholder earn the right to his advantageous position or by having him earn his income. When both rights and income are earned, however, redistribution does not decrease further.

This volume consists of papers presented at a conference in memory of John Dickhaut. The conference, sponsored by the Economic Science Institute at Chapman University, focused on four areas of John's research interests during his career: Accounting and Society, Methodology in Experimental Economics, Neural Economics and Trust and Reciprocity. All of the papers make novel, interesting contributions to the study of human behavior in economic institutions and should interest readers in a range of fields including accounting, anthropology, economics, finance, neurology and psychology.