Money Mining and Price Dynamics

We develop a random-matching model to study the price dynamics of monies produced privately according to a time-consuming mining technology. For our leading example, there exists a unique equilibrium where the value of money increases over time and reaches a steady state. There is also a continuum of perfect-foresight equilibria where the price of money inflates and bursts gradually over time. Initially, money is held for a speculative motive, but it acquires a transactional role as it becomes sufficiently abundant. We study fiat, commodity, and crypto monies, endogenous acceptability, and adopt implementation and equilibrium approaches. (JEL E31, E42, E51, N13, N14, N23, N24)

Record-Keeping and Cooperation in Large Societies

We introduce a new model of repeated games in large populations with random matching, overlapping generations, and limited records of past play. We prove that steady-state equilibria exist under general conditions on records. When the updating of a player’s record can depend on the actions of both players in a match, any strictly individually rational action can be supported in a steady-state equilibrium. When record updates can depend only on a player’s own actions, fewer actions can be supported. Here we focus on the prisoner’s dilemma and restrict attention to strict equilibria that are coordination-proof, meaning that matched partners never play a Pareto-dominated Nash equilibrium in the one-shot game induced by their records and expected continuation payoffs. Such equilibria can support full cooperation if the stage game is either “strictly supermodular and mild” or “strongly supermodular,” and otherwise permit no cooperation at all. The presence of “supercooperator” records, where a player cooperates against any opponent, is crucial for supporting any cooperation when the stage game is “severe.”

Clustering and Combinatorial Optimization Based Approach for Learner Matching in the Context of Peer Assessment

Peer assessment is a method that has shown a positive impact on learners' cognitive and metacognitive skills. It also represents an effective alternative to instructor-provided assessment within computer-based education and, particularly, in massive online learning settings such as MOOCs. Various platforms have incorporated this mechanism as an assessment tool. However, most of the proposed implementations rely on the random matching of peers. The contributions introduced in this article are intended to step past the randomized approach by modeling learner matching as a many to many assignment problem, and then its resolution by using an appropriate combinatorial optimization algorithm. The adopted approach stands on a matching strategy that is also discussed in this article. Furthermore, we present two key steps on which both the matching strategy and the representation of the problem depend: 1) modeling the learner as an assessor, and 2) clustering assessors into categories that reflect learners’ assessment competency. Additionally, a methodology for increasing the accuracy of peer assessment by weighting the scores given by learners is also introduced. Finally, compared to the random allocation of submissions, the experimentation of the approach has shown promising results in terms of the validity of assessments and the acceptance of peer feedback.

A Few Bad Apples Spoil the Barrel: An Anti-Folk Theorem for Anonymous Repeated Games with Incomplete Information

We study anonymous repeated games where players may be “commitment types” who always take the same action. We establish a stark anti-folk theorem: if the distribution of the number of commitment types satisfies a smoothness condition and the game has a “pairwise dominant” action, this action is almost always taken. This implies that cooperation is impossible in the repeated prisoner's dilemma with anonymous random matching. We also bound equilibrium payoffs for general games. Our bound implies that industry profits converge to zero in linear-demand Cournot oligopoly as the number of firms increases. (JEL C72, C73, D83)

Abstract 13718: Automatic Microvolt-level Measurement of ST Level at J-point on 12-lead Electrocardiography Can Distinguish Takotsubo Syndrome and Acute Anterior Myocardial Infarction

Introduction: ST elevation/depression on 12-leads electrocardiography (ECG) at onset was recognized difficult to distinguish Takotsubo syndrome (TTS) and acute anterior myocardial infarction (ant AMI). Diagnostic performance of automatic microvolt-level measurement of the ST levels was not elucidated. Hypothesis: Microvolt-level differences of ST level at J-point on ECG can distinguish TTS and ant AMI in acute phase. Methods: We firstly enrolled consecutive 40 patients of TTS, and among 500 ant AMI patients, one to two random matching was done by their age and gender. Finally, 40+80 patients (74.5±11.2 years, 87 females) were enrolled. ECG at onset of both group was measured by automated system (ECAPs12c: Nihon-Koden). Results: ST level of TTS at J-point in I/II/V4-6 lead was significantly elevated comparing to that of ant AMI. Conversely, Conversely, significant ST depression in aVR and no ST elevation in V1 of TTS was observed in TTS. Logistic regression analysis revealed that ST elevation in I lead and no ST elevation in V1 lead showed high odds ratio and low P value. Conclusions: Automated measurement of microvolt-level difference of ST level at J-point was a powerful tool to distinguish TTS and ant AMI at onset.

Flexibility and Reputation in Repeated Prisoner’s Dilemma Games

We study how three matching institutions, differing in how relationships are dissolved, affect cooperation in a repeated prisoner’s dilemma and how cooperation rates are affected by the presence of a reputation mechanism. Although cooperation is theoretically sustainable under all institutions, we show experimentally that cooperation rates are lowest under random matching, highest under fixed matching, and intermediate in a flexible matching institution, where subjects have the option to dissolve relationships. Our results also suggest important interactions between the matching institution and reputation mechanism. Under both the random matching and flexible matching institutions, both subjective (based on subjects’ ratings) and objective (based on subjects’ actions) reputation mechanisms lead to substantial increases in cooperative behavior. However, under fixed matching, only the subjective reputation mechanism leads to higher cooperation. We argue that these differences are due to different reputation mechanisms being more forgiving of early deviations from cooperation under certain matching institutions, which gives subjects the ability to learn the value of cooperation rather than getting stuck with a bad reputation and, consequently, uncooperative relationships. This paper was accepted by Yan Chen, decision analysis.