It is increasingly clear that simple decisions are made by computing decision values for the options under consideration, and then comparing these values to make a choice. Computational models of this process suggest that it involves the accumulation of information over time, but little is known about the temporal course of valuation in the brain. To examine this, we manipulated the available decision time and observed the consequences in the brain and behavioral correlates of choice. Participants were scanned with functional magnetic resonance imaging while they chose to eat or not eat basic food items, in two conditions differing in the amount of time provided for choice. After identifying valuation-related regions with unbiased whole-brain general linear models, we analyzed two regions of interest: ventromedial prefrontal cortex (VMPFC) and dorsolateral prefrontal cortex (DLPFC). Finite impulse response models of the upsampled estimated neural activity from those regions allowed us to examine the onset, duration and termination of decision value signals, and to compare across regions. We found evidence for the immediate onset of value computation in both regions, but an extended duration with longer decision time. However, this was not accompanied by behavioral changes in either the accuracy or determinants of choice. Finally, there was modest evidence that DLPFC computation correlated with, but lagged behind, VMPFC computation, suggesting the sharing of information across these regions. These findings have important implications for models of decision value computation and choice.
The brain seeks to combine related inputs from different senses (e.g., hearing and vision), via multisensory integration. Temporal information can indicate whether stimuli in different senses are related or not. A recent human fMRI study (Noesselt et al. [2007]: J Neurosci 27:11431-11441) used auditory and visual trains of beeps and flashes with erratic timing, manipulating whether auditory and visual trains were synchronous or unrelated in temporal pattern. A region of superior temporal sulcus (STS) showed higher BOLD signal for the synchronous condition. But this could not be related to performance, and it remained unclear if the erratic, unpredictable nature of the stimulus trains was important. Here we compared synchronous audiovisual trains to asynchronous trains, while using a behavioral task requiring detection of higher-intensity target events in either modality. We further varied whether the stimulus trains had predictable temporal pattern or not. Synchrony (versus lag) between auditory and visual trains enhanced behavioral sensitivity (d') to intensity targets in either modality, regardless of predictable versus unpredictable patterning. The analogous contrast in fMRI revealed BOLD increases in several brain areas, including the left STS region reported by Noesselt et al. [2007: J Neurosci 27:11431-11441]. The synchrony effect on BOLD here correlated with the subject-by-subject impact on performance. Predictability of temporal pattern did not affect target detection performance or STS activity, but did lead to an interaction with audiovisual synchrony for BOLD in inferior parietal cortex.
Optimal choices benefit from previous learning. However, it is not clear how previously learned stimuli influence behavior to novel but similar stimuli. One possibility is to generalize based on the similarity between learned and current stimuli. Here, we use neuroscientific methods and a novel computational model to inform the question of how stimulus generalization is implemented in the human brain. Behavioral responses during an intradimensional discrimination task showed similarity-dependent generalization. Moreover, a peak shift occurred, i.e., the peak of the behavioral generalization gradient was displaced from the rewarded conditioned stimulus in the direction away from the unrewarded conditioned stimulus. To account for the behavioral responses, we designed a similarity-based reinforcement learning model wherein prediction errors generalize across similar stimuli and update their value. We show that this model predicts a similarity-dependent neural generalization gradient in the striatum as well as changes in responding during extinction. Moreover, across subjects, the width of generalization was negatively correlated with functional connectivity between the striatum and the hippocampus. This result suggests that hippocampus-striatal connections contribute to stimulus-specific value updating by controlling the width of generalization. In summary, our results shed light onto the neurobiology of a fundamental, similarity-dependent learning principle that allows learning the value of stimuli that have never been encountered.
This paper examines the evolution of female labor market outcomes from 1987 to 2008 by assessing the role of changing labor demand requirements in four developing countries: Brazil, Mexico, India and Thailand. The results highlight the importance of structural change in reducing gender disparities by decreasing the labor demand for physical attributes. The results show that India, the country with the greatest physical labor requirements, exhibits the largest labor market gender inequality. In contrast, Brazil's labor requirements have followed a similar trend seen in the United States, reducing gender inequality in both wages and labor force participation.
This paper investigates how precisely short-term, job-search oriented training programs as opposed to long-term, human capital intensive training programs work. We evaluate and compare their effects on time until job entry, stability of employment, and earnings. Further, we examine the heterogeneity of treatment effects according to the timing of training during unemployment as well as across different subgroups of participants. We find that participating in short-term training reduces the remaining time in unemployment and moderately increases job stability. Long-term training programs initially prolong the remaining time in unemployment, but once the scheduled program end is reached participants exit to employment at a much faster rate than without training. In addition, they benefit from substantially more stable employment spells and higher earnings. Overall, long-term training programs are well effective in supporting the occupational advancement of very heterogeneous groups of participants, including those with generally weak labor market prospects. However, from a fiscal perspective only the low-cost short-term training schemes are cost efficient in the short run.
A key aspect of generating new ideas is drawing from different elements of preexisting knowledge and combining them into a new idea. In such a process, the diversity of ideas plays a central role. This paper examines the empirical question of how the internet affected the diversity of new research by making the existing literature accessible online. The internet marks a technological shock which affects how academic scientists search for and browse through published documents. Using article-level data from economics journals for the period 1991 to 2009, we document how online accessibility lead academic economists to draw from a more diverse set of literature, and to write articles which incorporated more diverse contents.
Charness and Dufwenberg (American Economic Review, June 2011, 1211-1237) have recently demonstrated that cheap-talk communication raises efficiency in bilateral contracting situations with adverse selection. We replicate their finding and check its robustness by introducing competition between agents. We find that communication and competition act as "substitutes:" communication raises efficiency in the absence of competition but lowers efficiency with competition, and competition raises efficiency without communication but lowers efficiency with communication. We briefly review some behavioral theories that have been proposed in this context and show that each can explain some but not all features of the observed data patterns. Our findings highlight the fragility of cheap-talk communication and may serve as a guide to refine existing behavioral theories.
When workers are faced with the threat of unemployment, their relationship with a particular firm becomes valuable. As a result, a worker may comply with the terms of a relational contract that demands high effort even when performance is not enforceable by a third party. But can relational contracts motivate high effort when workers can easily find alternative jobs? We examine how competition for labor affects the emergence of relational contracts and their effectiveness in overcoming moral hazard in the labor market. We show that effective relational contracts do emerge in a market with excess demand for labor. Long-term relationships turn out to be less frequent when there is excess demand for labor than they are in a market characterized by exogenous unemployment. However, stronger competition for labor does not impair labor market efficiency: higher wages induced by competition lead to higher effort out of concerns for reciprocity.
It is still an open question when groups perform better than individuals in intellectual tasks. We report that in a company takeover experiment, groups placed better bids than individuals and substantially reduced the winner’s curse. This improvement was mostly due to peer pressure over the minority opinion and to learning. Learning took place from interacting and negotiating consensus with others, not simply from observing their bids. When there was disagreement, what prevailed was not the best proposal but the one of the majority. Groups underperformed with respect to a “truth wins” benchmark although they outperformed individuals deciding in isolation.
We show that professional soccer players exhibit reference-dependent behavior during matches. Controlling for the state of the match and for unobserved heterogeneity, we show on a minute-by-minute basis that a player breaches the rules of the game, measured by the referee’s assignment of cards, with a significantly higher probability if his team is behind the expected match outcome, measured by pre-play betting odds of large professional bookmakers. We derive these results in two independent data sets, one from ten seasons of the German Bundesliga, the other from eight seasons the English Premier League, each with more than half a million minutes of play.
