Individuals can learn by interacting with the environment and experiencing a difference between predicted and obtained outcomes (prediction error). However, many species also learn by observing the actions and outcomes of others. In contrast to individual learning, observational learning cannot be based on directly experienced outcome prediction errors. Accordingly, the behavioral and neural mechanisms of learning through observation remain elusive. Here we propose that human observational learning can be explained by two previously uncharacterized forms of prediction error, observational action prediction errors (the actual minus the predicted choice of others) and observational outcome prediction errors (the actual minus predicted outcome received by others). In a functional MRI experiment, we found that brain activity in the dorsolateral prefrontal cortex and the ventromedial prefrontal cortex respectively corresponded to these two distinct observational learning signals.prediction error | reward | vicarious learning | dorsolateral prefrontal cortex | ventromedial prefrontal cortex I n uncertain and changing environments, flexible control of actions has individual and evolutionary advantages by allowing goaldirected and adaptive behavior. Flexible action control requires an understanding of how actions bring about rewarding or punishing outcomes. Through instrumental conditioning, individuals can use previous outcomes to modify future actions (1-4). However, individuals learn not only from their own actions and outcomes but also from those that are observed. One of the most illustrative examples of observational learning happens in Antarctica, where flocks of Adelie penguins often congregate at the water's edge to enter the sea and feed on krill. However, the main predator of the penguins, the leopard seal, is often lurking out of sight beneath the waves, making it a risky prospect to be the first one to take the plunge. As this waiting game develops, one of the animals often becomes so hungry that it jumps, and if no seal appears the rest of the group will all follow suit. The following penguins make a decision after observing the action and outcome of the first (5). This ability to learn from observed actions and outcomes is a pervasive feature of many species and can be absolutely crucial when the stakes are high. For example, predator avoidance techniques or the eating of a novel food item are better learned from another's experience rather than putting oneself at risk with trial-and-error learning. Although we know a fair amount about the neural mechanisms of individuals learning about their own actions and outcomes (6), almost nothing is known about the brain processes involved when individuals learn from observed actions and outcomes (7). This lack of knowledge is all the more surprising given that observational learning is such a wide-ranging phenomenon.In this study, 21 participants engaged in a novel observational learning task based on a simple two-armed bandit problem (Fig. 1A) while being scanne...

Typically, modern economics has steered away from the analysis of sociological and psychological factors and has focused on narrow behavioural assumptions in which expectations are formed on the basis of mathematical algorithms. Blending together ideas from the social and behavioural sciences, this paper argues that the behavioural approach adopted in most economic analysis, in its neglect of sociological and psychological forces and its simplistically dichotomous categorization of behaviour as either rational or not rational, is too narrow and stark. Behaviour may reflect an interaction of cognitive and emotional factors and this can be captured more effectively using an approach that focuses on the interplay of different decision-making systems. In understanding the mechanisms affecting economic and financial decision-making, an interdisciplinary approach is needed which incorporates ideas from a range of disciplines including sociology, economic psychology, evolutionary biology and neuroeconomics.

Opinion of geological experts is often formed despite a paucity of data and is usually based on prior experience. In such situations humans employ heuristics (rules of thumb) to aid analysis and interpretation of data. As a result, future judgements are bootstrapped from, and hence biased by, both the heuristics employed and prior opinion.This paper reviews the causes of bias and error inherent in prior information derived from the probabilistic judgements of people. Parallels are developed between the evolution of scientific opinion on one hand and the limits on rational behaviour on the other. We show that the combination of data paucity and commonly employed heuristics can lead to herding behaviour within groups of experts. Elicitation theory mitigates the effects of such behaviour, but a method to estimate reliable uncertainties on expert judgements remains elusive.We have also identified several key directions in which future research is likely to lead to methods that reduce such emergent group behaviour, thereby increasing the probability that the stock of common knowledge will converge in a stable manner towards facts about the Earth as it really is. These include: (1) measuring the frequency with which different heuristics tend to be employed by experts within the geosciences; (2) developing geoscience-specific methods to reduce biases originating from the use of such heuristics; (3) creating methods to detect scientific herding behaviour; and (4) researching how best to reconcile opinions from multiple experts in order to obtain the best probabilistic description of an unknown, objective reality (in cases where one exists).

Given that the range of rewarding and punishing outcomes of actions is large but neural coding capacity is limited, efficient processing of outcomes by the brain is necessary. One mechanism to increase efficiency is to rescale neural output to the range of outcomes expected in the current context, and process only experienced deviations from this expectation. However, this mechanism comes at the cost of not being able to discriminate between unexpectedly low losses when times are bad versus unexpectedly high gains when times are good. Thus, too much adaptation would result in disregarding information about the nature and absolute magnitude of outcomes, preventing learning about the longer-term value structure of the environment. Here we investigate the degree of adaptation in outcome coding brain regions in humans, for directly experienced outcomes and observed outcomes. We scanned participants while they performed a social learning task in gain and loss blocks. Multivariate pattern analysis showed two distinct networks of brain regions adapt to the most likely outcomes within a block. Frontostriatal areas adapted to directly experienced outcomes, whereas lateral frontal and temporoparietal regions adapted to observed social outcomes. Critically, in both cases, adaptation was incomplete and information about whether the outcomes arose in a gain block or a loss block was retained. Univariate analysis confirmed incomplete adaptive coding in these regions but also detected nonadapting outcome signals. Thus, although neural areas rescale their responses to outcomes for efficient coding, they adapt incompletely and keep track of the longer-term incentives available in the environment.

The focus of this paper is to investigate the importance of the capital stock in the determination of wages and unemployment in a range of EMU countries and to compare the results across countries. A timeseries analysis is conducted in the case of nine euro area countries, which were selected solely on the basis of data availability and consistencySpain. The paper begins with a short review of the literature on capital stock and unemployment, before it deals with the theoretical model. This is followed by estimation and testing of the theoretical model put forward, using both time-series and panel data. The results are supportive of the main hypothesis of the paper: capital stock is an important determinant of unemployment and wages in the countries considered for the purposes of the paper.

Like other species, humans are sensitive to the decisions and actions of conspecifics, which can lead to herd behavior and undesirable outcomes such as stock market bubbles and bank runs. However, how the brain processes this socially derived influence is only poorly understood. Using functional magnetic resonance imaging (fMRI), we scanned participants as they made decisions on whether to buy stocks after observing others’ buying decisions. We demonstrate that activity in the ventral striatum, an area heavily implicated in reward processing, tracked the degree of influence on participants’ decisions arising from the observation of other peoples’ decisions. The signal did not track non-human, non-social control decisions. These findings lend weight to the notion that the ventral striatum is involved in the processing of complex social aspects of decision making and identify a possible neural basis for herd behavior.

This paper assesses the impacts of globalisation on the cross-country comparative patterns of growth and development. In the theoretical section, some of the key linkages between growth, development and globalisation are explored including the positive and negative impacts of globalisation and the constraints on effective development in a globalised world. Some of the key factors emphasised include trade and capital flows as well as computerisation. These issues are then analysed empirically using σ and club convergence models, estimated using panel techniques. The empirical evidence presented indicates that globalisation has been associated with increasing trade and financial flows to less developed countries. It has also coincided with increasing penetration of the Internet suggesting that increases in informational flows have complemented economic and financial linkages, but the empirical evidence also shows that the current era of globalisation has not been associated with convergence in economic outcomes; instead less-developed countries have suffered from increases in international income inequality. In the final section, conclusions and policy implications are presented including a discussion of how international and national development policies could be designed properly to ameliorate tendencies towards growing international disparities in economic growth.Globalisation, growth, development, convergence,

The reduction of regional unemployment disparities is a key prerequisite for the achievement of socioeconomic cohesion in an integrated European Union. This article examines recent trends in the evolution of regional unemployment disparities across a number of European member states to determine whether and how far this reduction is occurring. There is in fact little indication of any widespread convergence of regional unemployment rates. Instead, regional unemployment disparities across Europe appear to be characterized by a high degree of persistence. Furthermore, the evidence suggests that this persistence is an equilibrium phenomenon rather than the result of prolonged disequilibrium in regional labour markets.