Rewards in the natural environment are rarely predicted with complete certainty. Uncertainty relating to future rewards has typically been defined as the variance of the potential outcomes. However, the asymmetry of predicted reward distributions, known as skewness, constitutes a distinct but neuroscientifically underexplored risk term that may also have an impact on preference. By changing only reward magnitudes, we study skewness processing in equiprobable ternary lotteries involving only gains and constant probabilities, thus excluding probability distortion or loss aversion as mechanisms for skewness preference formation. We show that individual preferences are sensitive to not only the mean and variance but also to the skewness of predicted reward distributions. Using neuroimaging, we show that the insula, a structure previously implicated in the processing of reward-related uncertainty, responds to the skewness of predicted reward distributions. Some insula responses increased in a monotonic fashion with skewness (irrespective of individual skewness preferences), whereas others were similarly elevated to both negative and positive as opposed to no reward skew. These data support the notion that the asymmetry of reward distributions is processed in the brain and, taken together with replicated findings of mean coding in the striatum and variance coding in the cingulate, suggest that the brain codes distinct aspects of reward distributions in a distributed fashion.
How effectively do democratic institutions provide public goods? Despite the incentives an elected leader has to free ride or impose majority tyranny, our experiment demonstrates that electoral delegation results in full provision of the public good. Analysis of the experimental data suggests that the result is primarily due to electoral selection: groups elect prosocial leaders and replace those who do not implement full contribution outcomes. However, we also observe outcomes in which a minimum winning coalition exploits the contributions of the remaining players. A second experiment demonstrates that when electoral delegation must be endogenously implemented, individuals voluntarily cede authority to an elected agent only when preplay communication is permitted. Our combined results demonstrate that democratic delegation helps groups overcome the free-rider problem and generally leads to outcomes that are often both efficient and equitable.
This paper reports an experiment examining the effect of social norms on pro-social behavior. We test two predictions derived from work in psychology regarding the influence of norms. The first is a “focusing” influence, whereby norms only impact behavior when an individual’s attention is drawn to them; and the second is an “informational” influence, whereby a norm exerts a stronger impact on an individual’s behavior the more others he observes behaving consistently with that norm. We find support for both effects. Either thinking about or observing the behavior of others produces increased pro-social behavior – even when one expects or observes little pro-social behavior on the part of others – and the degree of pro-social behavior is increasing in the actual and expected pro-social behavior of others. This experiment eliminates strategic influences and thus demonstrates a direct effect of norms on behavior.
In this paper we show that the recent model by Gilles Duranton [Duranton, G., 2007. Urban evolutions: The fast, the slow, and the still. American Economic Review 97, 197-221] performs remarkably well in replicating the city size distribution of West Germany, much better than the simple rank-size rule known as Zipf's law. The main mechanism of this theoretical framework is the "churning" of industries across cities. Little is known in urban economics about the determinants of local industry turnover so far. We present an empirical analysis of the excess churning index for West German cities, which describes the strength of intra-city industry reallocations over time. We find that urban growth and industry turnover are not notably correlated: Some, but not all fast-growing cities have notably changed. Secondly, human capital is positively related to growth and turnover, but only among successful cities. Industrial change within unsuccessful cities is driven by the disappearance of old-fashioned and declining sectors such as agriculture or mining. On a more general level our results suggest that the recent model by Duranton is a powerful description of the urban growth process. Still there are some aspects that are not captured by that model, which are at the core of other theories of urban growth.
Neuroeconomics combines methods and theories from neuroscience psychology, economics, and computer science in an effort to produce detailed computational and neurobiological accounts of the decision-making process that can serve as a common foundation for understanding human behavior across the natural and social sciences. Because neuroeconomics is a young discipline, a sufficiently sound structural model of how the brain makes choices is not yet available. However, the contours of such a computational model are beginning to arise; and, given the rapid progress, there is reason to be hopeful that the field will eventually put together a satisfactory structural model. This paper has two goals: First, we provide an overview of what has been learned about how the brain makes choices in two types of situations: simple choices among small numbers of familiar stimuli (like choosing between an apple or an orange), and more complex choices involving tradeoffs between immediate and future consequences (like eating a healthy apple or a less-healthy chocolate cake). Second, we show that, even at this early stage, insights with important implications for economics have already been gained.
