Dynamic Unstructured Bargaining with Private Information: Theory, Experiment, and Outcome Prediction via Machine Learning

We study dynamic unstructured bargaining with deadlines and one-sided private information about the amount available to share (the “pie size”). Using mechanism design theory, we show that given the players’ incentives, the equilibrium incidence of bargaining failures (“strikes”) should increase with the pie size, and we derive a condition under which strikes are efficient. In our setting, no equilibrium satisfies both equality and efficiency in all pie sizes. We derive two equilibria that resolve the trade-off between equality and efficiency by favoring either equality or efficiency. Using a novel experimental paradigm, we confirm that strike incidence is decreasing in the pie size. Subjects reach equal splits in small pie games (in which strikes are efficient), while most payoffs are close to either the efficient or the equal equilibrium prediction, when the pie is large. We employ a machine learning approach to show that bargaining process features recorded early in the game improve out-of-sample prediction of disagreements at the deadline. The process feature predictions are as accurate as predictions from pie sizes only, and adding process and pie data together improves predictions even more

Single dose testosterone administration impairs cognitive reflection in men

In nonhumans, the sex steroid testosterone regulates reproductive behaviors such as fighting between males and mating. In humans, correlational studies have linked testosterone with aggression and disorders associated with poor impulse control, but the neuropsychological processes at work are poorly understood. Building on a dual-process framework, we propose a mechanism underlying testosterone’s behavioral effects in humans: reduction in cognitive reflection. In the largest study of behavioral effects of testosterone administration to date, 243 men received either testosterone or placebo and took the Cognitive Reflection Test (CRT), which estimates the capacity to override incorrect intuitive judgments with deliberate correct responses. Testosterone administration reduced CRT scores. The effect remained after we controlled for age, mood, math skills, whether participants believed they had received the placebo or testosterone, and the effects of 14 additional hormones, and it held for each of the CRT questions in isolation. Our findings suggest a mechanism underlying testosterone’s diverse effects on humans’ judgments and decision making and provide novel, clear, and testable predictions

Reflecting on the Evidence: A Reply to Knight, McShane, et al. (2020)

Knight, McShane, et al. (2020) report three experiments on testosterone’s effect on the Cognitive Reflection Test (CRT). The experiments were designed and executed independently of each other and of our previous work (Nave, Nadler, Zava & Camerer, 2017). We thank Knight, McShane, et al. for conducting these experiments and summarizing their results, and we agree that one experiment is obviously not enough for establishing an empirical fact. The individual experiments and their meta-analytic summary are consistent with both the null hypothesis and Nave et al.’s conclusions (see Table S6 in Knight, McShane, et al.’s Supplemental Material), and there is evidence for variation in effects across experiments. In what follows, we reflect on design differences among the experiments and the collective evidence that their data contain

Reflecting on the Evidence: A Reply to Knight, McShane, et al. (2020)

Knight, McShane, et al. (2020) report three experiments on testosterone’s effect on the Cognitive Reflection Test (CRT). The experiments were designed and executed independently of each other and of our previous work (Nave, Nadler, Zava & Camerer, 2017). We thank Knight, McShane, et al. for conducting these experiments and summarizing their results, and we agree that one experiment is obviously not enough for establishing an empirical fact. The individual experiments and their meta-analytic summary are consistent with both the null hypothesis and Nave et al.’s conclusions (see Table S6 in Knight, McShane, et al.’s Supplemental Material), and there is evidence for variation in effects across experiments. In what follows, we reflect on design differences among the experiments and the collective evidence that their data contain

Does Oxytocin Increase Trust in Humans? A Critical Review of Research

Behavioral neuroscientists have shown that the neuropeptide oxytocin (OT) plays a key role in social attachment and affiliation in nonhuman mammals. Inspired by this initial research, many social scientists proceeded to examine the associations of OT with trust in humans over the past decade. To conduct this work, they have (a) examined the effects of exogenous OT increase caused by intranasal administration on trusting behavior, (b) correlated individual difference measures of OT plasma levels with measures of trust, and (c) searched for genetic polymorphisms of the OT receptor gene that might be associated with trust. We discuss the different methods used by OT behavioral researchers and review evidence that links OT to trust in humans. Unfortunately, the simplest promising finding associating intranasal OT with higher trust has not replicated well. Moreover, the plasma OT evidence is flawed by how OT is measured in peripheral bodily fluids. Finally, in recent large-sample studies, researchers failed to find consistent associations of specific OT-related genetic polymorphisms and trust. We conclude that the cumulative evidence does not provide robust convergent evidence that human trust is reliably associated with OT (or caused by it). We end with constructive ideas for improving the robustness and rigor of OT research

Dynamic Unstructured Bargaining with Private Information: Theory, Experiment, and Outcome Prediction via Machine Learning

We study dynamic unstructured bargaining with deadlines and one-sided private information about the amount available to share (the “pie size”). Using mechanism design theory, we show that given the players’ incentives, the equilibrium incidence of bargaining failures (“strikes”) should increase with the pie size, and we derive a condition under which strikes are efficient. In our setting, no equilibrium satisfies both equality and efficiency in all pie sizes. We derive two equilibria that resolve the trade-off between equality and efficiency by favoring either equality or efficiency. Using a novel experimental paradigm, we confirm that strike incidence is decreasing in the pie size. Subjects reach equal splits in small pie games (in which strikes are efficient), while most payoffs are close to either the efficient or the equal equilibrium prediction, when the pie is large. We employ a machine learning approach to show that bargaining process features recorded early in the game improve out-of-sample prediction of disagreements at the deadline. The process feature predictions are as accurate as predictions from pie sizes only, and adding process and pie data together improves predictions even more

Vasopressin increases human risky cooperative behavior

The history of humankind is an epic of cooperation, which is ubiquitous across societies and increasing in scale. Much human cooperation occurs where it is risky to cooperate for mutual benefit because successful cooperation depends on a sufficient level of cooperation by others. Here we show that arginine vasopressin (AVP), a neuropeptide that mediates complex mammalian social behaviors such as pair bonding, social recognition and aggression causally increases humans’ willingness to engage in risky, mutually beneficial cooperation. In two double-blind experiments, male participants received either AVP or placebo intranasally and made decisions with financial consequences in the “Stag hunt” cooperation game. AVP increases humans’ willingness to cooperate. That increase is not due to an increase in the general willingness to bear risks or to altruistically help others. Using functional brain imaging, we show that, when subjects make the risky Stag choice, AVP down-regulates the BOLD signal in the left dorsolateral prefrontal cortex (dlPFC), a risk-integration region, and increases the left dlPFC functional connectivity with the ventral pallidum, an AVP receptor-rich region previously associated with AVP-mediated social reward processing in mammals. These findings show a previously unidentified causal role for AVP in social approach behavior in humans, as established by animal research

Predicting the replicability of social science lab experiments

We measure how accurately replication of experimental results can be predicted by black-box statistical models. With data from four large-scale replication projects in experimental psychology and economics, and techniques from machine learning, we train predictive models and study which variables drive predictable replication. The models predicts binary replication with a cross-validated accuracy rate of 70% (AUC of 0.77) and estimates of relative effect sizes with a Spearman rho of 0.38. The accuracy level is similar to market-aggregated beliefs of peer scientists [1, 2]. The predictive power is validated in a pre-registered out of sample test of the outcome of [3], where 71% (AUC of 0.73) of replications are predicted correctly and effect size correlations amount to rho = 0.25. Basic features such as the sample and effect sizes in original papers, and whether reported effects are single-variable main effects or two-variable interactions, are predictive of successful replication. The models presented in this paper are simple tools to produce cheap, prognostic replicability metrics. These models could be useful in institutionalizing the process of evaluation of new findings and guiding resources to those direct replications that are likely to be most informative