In Search of Homo Economicus: Behavioral Experiments in 15 Small- Scale Societies,

Homo Economicus, Behavioral Experiments, Small-Scale Societies,

Behavioral experiments in health economics

The state-of-the-art literature at the interface between experimental and behavioral economics and health economics is reviewed by identifying and discussing ten areas of potential debate about behavioral experiments in health. By doing so, the different streams and areas of applications of the growing field of behavioral experiments in health are reviewed, by discussing which significant questions remain to be discussed, and by highlighting the rationale and the scope for the further development of behavioral experiments in health in the years to come

In Search of Homo Economicus: Behavioral Experiments in 15 Small-Scale Societies

We can summarize our results as follows. First, the canonical model is not supported in any society studied. Second, there is considerably more behavioral variability across groups than had been found in previous cross-cultural research, and the canonical model fails in a wider variety of ways than in previous experiments. Third, group-level differences in economic organization and the degree of market integration explain a substantial portion of the behavioral variation across societies: the higher the degree of market integration and the higher the payoffs to cooperation, the greater the level of cooperation in experimental games. Fourth, individual-level economic and demographic variables do not explain behavior either within or across groups. Fifth, behavior in the experiments is generally consistent with economic patterns of everyday life in these societies

“Economic man” in cross-cultural perspective: Behavioral experiments in 15 small-scale societies

Researchers from across the social sciences have found consistent deviations from the predictions of the canonical model of self-interest in hundreds of experiments from around the world. This research, however, cannot determine whether the uniformity results from universal patterns of human behavior or from the limited cultural variation available among the university students used in virtually all prior experimental work. To address this, we undertook a cross-cultural study of behavior in ultimatum, public goods, and dictator games in a range of small-scale societies exhibiting a wide variety of economic and cultural conditions. We found, first, that the canonical model – based on self-interest – fails in all of the societies studied. Second, our data reveal substantially more behavioral variability across social groups than has been found in previous research. Third, group-level differences in economic organization and the structure of social interactions explain a substantial portion of the behavioral variation across societies: the higher the degree of market integration and the higher the payoffs to cooperation in everyday life, the greater the level of prosociality expressed in experimental games. Fourth, the available individual-level economic and demographic variables do not consistently explain game behavior, either within or across groups. Fifth, in many cases experimental play appears to reflect the common interactional patterns of everyday life

The Experiment Factory: Standardizing Behavioral Experiments

The administration of behavioral and experimental paradigms for psychology research is hindered by lack of a coordinated effort to develop and deploy standardized paradigms. While several frameworks (de Leeuw (2015); McDonnell et al. (2012); Mason and Suri (2011); Lange et al. (2015)) have provided infrastructure and methods for individual research groups to develop paradigms, missing is a coordinated effort to develop paradigms linked with a system to easily deploy them. This disorganization leads to redundancy in development, divergent implementations of conceptually identical tasks, disorganized and error-prone code lacking documentation, and difficulty in replication. The ongoing reproducibility crisis in psychology and neuroscience research (Baker (2015); Open Science Collaboration (2015)) highlights the urgency of this challenge: reproducible research in behavioral psychology is conditional on deployment of equivalent experiments. A large, accessible repository of experiments for researchers to develop collaboratively is most efficiently accomplished through an open source framework. Here we present the Experiment Factory, an open source framework for the development and deployment of web-based experiments. The modular infrastructure includes experiments, virtual machines for local or cloud deployment, and an application to drive these components and provide developers with functions and tools for further extension. We release this infrastructure with a deployment (http://www.expfactory.org) that researchers are currently using to run a set of over 80 standardized web-based experiments on Amazon Mechanical Turk. By providing open source tools for both deployment and development, this novel infrastructure holds promise to bring reproducibility to the administration of experiments, and accelerate scientific progress by providing a shared community resource of psychological paradigms

Towards a neural-level cognitive architecture: modeling behavior in working memory tasks with neurons

Constrained by results from classic behavioral experiments we provide a neural-level cognitive architecture for modeling behavior in working memory tasks. We propose a canonical microcircuit that can be used as a building block for working memory, decision making and cognitive control. The controller controls gates to route the flow of information between the working memory and the evidence accumulator and sets parameters of the circuits. We show that this type of cognitive architecture can account for results in behavioral experiments such as judgment of recency, probe recognition and delayedmatch- to-sample. In addition, the neural dynamics generated by the cognitive architecture provides a good match with neurophysiological data from rodents and monkeys. For instance, it generates cells tuned to a particular amount of elapsed time (time cells), to a particular position in space (place cells) and to a particular amount of accumulated evidence.http://sites.bu.edu/tcn/files/2019/05/Cogsci2019_TiganjEtal.pdfAccepted manuscrip

Selection into skill accumulation: evidence using observational and experimental data

This paper combines unique survey and experimental data to examine the determinants of self-selection into a vocational training program. Women residing in selected disadvantaged areas in New Delhi, India were invited to apply for a 6-month long free training program in stitching and tailoring. A random subset of applicants and non-applicants were invited to participate in a set of behavioral experiments and in a detailed socio-economic survey. We find that applicants and non-applicants differ both in terms of observables (captured using survey data) and also in terms of a number of intrinsic traits (captured via the behavioral experiments). Overall our results suggest that there is valuable information to be gained by dissecting the black box of unobservables using behavioral experiments.Labor Market Training Programs, Selection, Survey Data, Field Experiments, Risk, Competition

Designing Optimal Behavioral Experiments Using Machine Learning

Computational models are powerful tools for understanding human cognition and behavior. They let us express our theories clearly and precisely, and offer predictions that can be subtle and often counter-intuitive. However, this same richness and ability to surprise means our scientific intuitions and traditional tools are ill-suited to designing experiments to test and compare these models. To avoid these pitfalls and realize the full potential of computational modeling, we require tools to design experiments that provide clear answers about what models explain human behavior and the auxiliary assumptions those models must make. Bayesian optimal experimental design (BOED) formalizes the search for optimal experimental designs by identifying experiments that are expected to yield informative data. In this work, we provide a tutorial on leveraging recent advances in BOED and machine learning to find optimal experiments for any kind of model that we can simulate data from, and show how by-products of this procedure allow for quick and straightforward evaluation of models and their parameters against real experimental data. As a case study, we consider theories of how people balance exploration and exploitation in multi-armed bandit decision-making tasks. We validate the presented approach using simulations and a real-world experiment. As compared to experimental designs commonly used in the literature, we show that our optimal designs more efficiently determine which of a set of models best account for individual human behavior, and more efficiently characterize behavior given a preferred model. At the same time, formalizing a scientific question such that it can be adequately addressed with BOED can be challenging and we discuss several potential caveats and pitfalls that practitioners should be aware of. We provide code and tutorial notebooks to replicate all analyses

Altruism and vaccination intentions:Evidence from behavioral experiments

Vaccine hesitancy has been on the rise throughout the past two decades, especially in high income countries where existing pro-vaccination public health communication strategies have proven ineffective. We argue that appealing to other-regarding preferences is one way of improving the effectiveness of public health communication strategies. To test this argument, we assess how vaccination intentions are influenced by the presence of people who cannot vaccinate, such as the immunosuppressed, newborns or pregnant women, using a laboratory experiment where there is a passive player whose welfare depends on the decisions of other, active players. Results suggest that pro-vaccine messages targeting altruism can increase vaccination intentions by: (i) invoking past experiences of dependence and vulnerability; (ii) stressing cooperation as a social norm; and (iii) emphasizing the presence of vulnerable individuals in a given society