The Effects of Social Ties on Coordination: Conceptual Foundations for an Empirical Analysis

International audienceThis paper investigates the influence that social ties can have on behavior. After defining the concept of social ties that we consider, we introduce an original model of social ties. The impact of such ties on social preferences is studied in a coordination game with outside option. We provide a detailed game theoretical analysis of this game while considering various types of players, i.e., self-interest maximizing, inequity averse, and fair agents. In addition to these approaches that require strategic reasoning in order to reach some equilibrium, we also present an alternative hypothesis that relies on the concept of team reasoning. After having discussed the differences between the latter and our model of social ties, we show how an experiment can be designed so as to discriminate among the models presented in the paper

An Evaluation of Methods for Inferring Boolean Networks from Time-Series Data

Regulatory networks play a central role in cellular behavior and decision making. Learning these regulatory networks is a major task in biology, and devising computational methods and mathematical models for this task is a major endeavor in bioinformatics. Boolean networks have been used extensively for modeling regulatory networks. In this model, the state of each gene can be either ‘on’ or ‘off’ and that next-state of a gene is updated, synchronously or asynchronously, according to a Boolean rule that is applied to the current-state of the entire system. Inferring a Boolean network from a set of experimental data entails two main steps: first, the experimental time-series data are discretized into Boolean trajectories, and then, a Boolean network is learned from these Boolean trajectories. In this paper, we consider three methods for data discretization, including a new one we propose, and three methods for learning Boolean networks, and study the performance of all possible nine combinations on four regulatory systems of varying dynamics complexities. We find that employing the right combination of methods for data discretization and network learning results in Boolean networks that capture the dynamics well and provide predictive power. Our findings are in contrast to a recent survey that placed Boolean networks on the low end of the ‘‘faithfulness to biological reality’’ and ‘‘ability to model dynamics’’ spectra. Further, contrary to the common argument in favor of Boolean networks, we find that a relatively large number of time points in the timeseries data is required to learn good Boolean networks for certain data sets. Last but not least, while methods have been proposed for inferring Boolean networks, as discussed above, missing still are publicly available implementations thereof. Here, we make our implementation of the methods available publicly in open source at http://bioinfo.cs.rice.edu/

How to Adapt to Changing Markets: Experience and Personality in a Repeated Investment Game

Investment behavior is traditionally investigated with the assumption that it is on average advantageous to invest. However, this may not always be the case. In this paper, we experimentally studied investment choices made by students and financial professionals facing alternately an advantageous and disadvantageous environment in a multi-round investment game. Expected returns from investment in the advantageous environment were higher than a safe alternative, while expected returns were lower in the disadvantageous environment. We investigate how experience and personality are related to choices. Investment behavior does not differ dependent on expected returns and professionals do not significantly differ from students. Personality predicts behavior and in particular we observe that openness to experience was an asset in unfavorable markets, leading to reduced risk taking

The ORFEUS II Echelle Spectrometer: Instrument description, performance and data reduction

During the second flight of the ORFEUS-SPAS mission in November/December 1996, the Echelle spectrometer was used extensively by the Principal and Guest Investigator teams as one of the two focal plane instruments of the ORFEUS telescope. We present the in-flight performance and the principles of the data reduction for this instrument. The wavelength range is 90 nm to 140 nm, the spectral resolution is significantly better than lambda/(Delta lambda) = 10000, where Delta lambda is measured as FWHM of the instrumental profile. The effective area peaks at 1.3 cm^2 near 110 nm. The background is dominated by straylight from the Echelle grating and is about 15% in an extracted spectrum for spectra with a rather flat continuum. The internal accuracy of the wavelength calibration is better than +/- 0.005 nm.Comment: 8 pages, 8 figure

Negative Reciprocity and its Relation to Anger-Like Emotions in Homogeneous and Heterogeneous Groups

Several studies have shown that social identity fosters the provision of public goods and enhances the willingness to reciprocate cooperative behavior of group members dependent on the social environment. Yet, the question of how social identity affects negative reciprocity in identityhomogeneous and -heterogeneous groups has received only little attention. Consequently, we seek to fill this gap by examining whether social identity affects individuals' willingness to sanction deviating group members in a public good context. Moreover, we devote particular attention to the role of anger-like emotions in negative reciprocity. To test our hypotheses we employ one-shot public good games in strategy method with induced social identity. Our results indicate that members of identity homogeneous groups punish much less often and in smaller amounts than of identity heterogeneous groups when they face contributions smaller than their own. We also find that anger-like emotions influence punishment behavior much stronger when individuals are matched with members of different identities than in identity homogenous groups. These findings contribute to the better understanding of the nature of social identity and its impact on reciprocity, improving economists ability to predict behavior taking emotions also into consideration

Preferences and Biases in Educational Choices and Labor Market Expectations: Shrinking the Black Box of Gender

Standard observed characteristics explain only part of the differences between men and women in education choices and labor market trajectories. Using an experiment to derive students' levels of overconfidence, and preferences for competitiveness and risk, this paper investigates whether these behavioral biases and preferences explain gender differences in college major choices and expected future earnings. In a sample of high ability undergraduates, we find that competitiveness and overconfidence, but not risk aversion, is systematically related with expectations about future earnings: individuals who are overconfident and overly competitive have significantly higher earnings expectations. Moreover, gender differences in overconfidence and competitiveness explain about 18% of the gender gap in earnings expectations. These experimental measures explain as much of the gender gap in earnings expectations as a rich set of control variables, including test scores and family background, and they are poorly proxied by these same control variables, underscoring that they represent independent variation. While expected earnings are related to college major choices, the experimental measures are not related with college major choice

Mise en place d'une expérience avec le grand public: entre recherche, vulgarisation et pédagogie

Methodological considerations on implementing a participative experimentWe present the implementation of an economic experiment conducted simultaneously in 11 French cities, with over 2700 participants, during four uninterrupted hours, during a popular-science event held in September 2015. Our goal is both to provide a roadmap for a possible replication and to discuss how the discipline can be used in new fields (science popularization, popular education, public communication)

Naturalizing Institutions: Evolutionary Principles and Application on the Case of Money

In recent extensions of the Darwinian paradigm into economics, the replicator-interactor duality looms large. I propose a strictly naturalistic approach to this duality in the context of the theory of institutions, which means that its use is seen as being always and necessarily dependent on identifying a physical realization. I introduce a general framework for the analysis of institutions, which synthesizes Searle's and Aoki's theories, especially with regard to the role of public representations (signs) in the coordination of actions, and the function of cognitive processes that underly rule-following as a behavioral disposition. This allows to conceive institutions as causal circuits that connect the population-level dynamics of interactions with cognitive phenomena on the individual level. Those cognitive phenomena ultimately root in neuronal structures. So, I draw on a critical restatement of the concept of the meme by Aunger to propose a new conceptualization of the replicator in the context of institutions, namely, the replicator is a causal conjunction between signs and neuronal structures which undergirds the dispositions that generate rule-following actions. Signs, in turn, are outcomes of population-level interactions. I apply this framework on the case of money, analyzing the emotions that go along with the use of money, and presenting a stylized account of the emergence of money in terms of the naturalized Searle-Aoki model. In this view, money is a neuronally anchored metaphor for emotions relating with social exchange and reciprocity. Money as a meme is physically realized in a replicator which is a causal conjunction of money artefacts and money emotions