One question that social scientists and economists have long puzzled over is how corruption arises in different cultures and why it is more prevalent in some countries than others. But it has always been difficult to find correlations between corruption and other measures of economic or social activity.
Michal Paulus and Ladislav Kristoufek at Charles University in Prague, Czech Republic have for the first time found a correlation between the perception of corruption in different countries and their economic development.
The data they use comes from Transparency International, a non-profit campaigning organisation based in Berlin, Germany, and which defines corruption as the misuse of public power for private benefit. Each year, this organisation publishes a global list of countries ranked according to their perceived levels of corruption. The list is compiled using at least three sources of information but does not directly measure corruption, because of the difficulties in gathering such data.
The growth of an economy can be divided into two parts: growth of population, and growth of output per person, which is commonly known as "productivity." The McKinsey Global Institute looks at these patterns over th
We show that the behaviour of Bitcoin has interesting similarities to stock and precious metal markets, such as gold and silver. We report that whilst Litecoin, the second largest cryptocurrency, closely follows Bitcoin's behaviour, it does not show all the reported properties of Bitcoin. Agreements between apparently disparate complexity measures have been found, and it is shown that statistical, information-theoretic, algorithmic and fractal measures have different but interesting capabilities of clustering families of markets by type. The report is particularly interesting because of the range and novel use of some measures of complexity to characterize price behaviour, because of the IRS designation of Bitcoin as an investment property and not a currency, and the announcement of the Canadian government's own electronic currency MintChip.
By W. Brian Arthur; External Professor, Santa Fe Institute; Visiting Researcher, Palo Alto Research Center.
Economics is a stately subject, one that has altered little since its modern foundations were laid in Victorian times. Now it is changing radically. Standard economics is suddenly being challenged by a number of new approaches: behavioral economics, neuroeconomics, new institutional economics. One of the new approaches came to life at the Santa Fe Institute: complexity economics.
Complexity economics got its start in 1987 when a now-famous conference of scientists and economists convened by physicist Philip Anderson and economist Kenneth Arrow met to discuss the economy as an evolving complex system. That conference gave birth a year later to the Institute’s first research program – the Economy as an Evolving Complex System – and I was asked to lead this. That program in turn has gone on to lay down a new and different way to look at the economy.
Which famous economist are you most similar to? To find out, answer the questions below and watch your dot move around the graph. Click on blue circles to see economist webpages. Click on questions to see survey data.
All questions and data were taken from the excellent IGM Economic Experts Panel, a survey of a diverse set of economists.
To understand market perturbations like crashes and bubbles, SFI Distinguished Professor Geoffrey West and three co-authors advocate a revised view that treats an economy like biologists would think about an ecosystem rife with evolutionary dynamics. "Here, we emphasize the importance of an ecosystems perspective: it is precisely due to the web of interdependencies among all companies that the unrestrained growth of one, or a few, companies leads to systematic imbalance." The growth of such imbalances, they say, is a result of evolutionary processes often leading to feedback loops. Drawing on their recent paper in Proceedings of the Royal Society A, for example, the authors suggest that two mechanisms "act as catalysts for the emergence of a crisis. The first is banks copying the business models of the most (short-term) successful bank, which leads to loss of both diversity and resilience. The second is investors such as fund managers increasing their appetite for risk by trying to outperform competitors."
Economic models of animal behaviour assume that decision-makers are rational, meaning that they assess options according to intrinsic fitness value and not by comparison with available alternatives. This expectation is frequently violated, but the significance of irrational behaviour remains controversial. One possibility is that irrationality arises from cognitive constraints that necessitate short cuts like comparative evaluation. If so, the study of whether and when irrationality occurs can illuminate cognitive mechanisms. We applied this logic in a novel setting: the collective decisions of insect societies. We tested for irrationality in colonies of Temnothorax ants choosing between two nest sites that varied in multiple attributes, such that neither site was clearly superior. In similar situations, individual animals show irrational changes in preference when a third relatively unattractive option is introduced. In contrast, we found no such effect in colonies. We suggest that immunity to irrationality in this case may result from the ants’ decentralized decision mechanism. A colony's choice does not depend on site comparison by individuals, but instead self-organizes from the interactions of multiple ants, most of which are aware of only a single site. This strategy may filter out comparative effects, preventing systematic errors that would otherwise arise from the cognitive limitations of individuals.
Network analysis — the mathematical analysis of relationships between elements or actors in a complex system — has become popular among transportation planners and spatial analysts, but its use remains relatively limited among architects and urban designers, whose day-to-day work demands more visioning than analysis. Now, researchers at the joint MIT-SUTD International Design Center (IDC) have created a free network analysis plugin for Rhinoceros 3-D modeling software, one of the most popular software platforms among architects and urban designers. The new Urban Network Analysis (UNA) plugin enables urban planners and architects to describe spatial patterns of cities using mathematical network analysis methods.
Why Information Grows: The Evolution of Order, from Atoms to Economies [Cesar Hidalgo] on Amazon.com. *FREE* shipping on qualifying offers. What is economic growth? And why, historically, has it occurred in only a few places? Previous efforts to answer these questions have focused on institutions
What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch—Economic Complexity—have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita . This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method— the selective predictability scheme —in which we adopt a strategy similar to the methods of analogues , firstly introduced by Lorenz, to assess future evolution of countries.
Matthieu Cristelli , Andrea Tacchella, Luciano Pietronero
In social dilemmas punishment costs resources, not just from the one who is punished but often also from the punisher and society. Reciprocity on the other side is known to lead to cooperation without the costs of punishment. The questions at hand are whether punishment brings advantages besides its costs, and how its negative side-effects can be reduced to a minimum in an environment populated by agents adopting a form of reciprocity. Various punishment mechanisms have been studied in the economic literature such as unrestricted punishment, legitimate punishment, cooperative punishment, and the hired gun mechanism. In this study all these mechanisms are implemented in a simulation where agents can share resources and may decide to punish other agents when the other agents do not share. Through evolutionary learning agents adapt their sharing/punishing policy. When the availability of resources was restricted, punishment mechanisms in general performed better than no-punishment, although unrestricted punishment was performing worse. When resource availability was high, performance was better in no-punishment conditions with indirect reciprocity. Unrestricted punishment was always the worst performing mechanism. Summarized, this paper shows that, in certain environments, some punishment mechanisms can improve the efficiency of cooperation even if the cooperating system is already based on indirect reciprocity.
NESS held a workshop on this theme with local policy makers in Rochdale, a borough in Greater Manchester. John Blundell is an elected local councillor and is Deputy Chairman of the Economic Regeneration Committee in Rochdale. Paul Ormerod is a member of the committee of the NESS project.
In this short paper, (available here: http://nessnet.eu/docs/NessRochdaleJuly2014.pdf), Blundell and Ormerod identify key principles of non-equilibrium, complexity based social science which are of direct policy relevance to relatively deprived, post-industrial towns across the EU, of which Rochdale is an example:
* Lock-in and path dependence. Once a local area becomes relatively deprived, this tends to persist for long periods of time
* Positive feedbacks. Agglomeration effects, namely the benefits which arise from high densities of employment in a local area, raise productivity levels across the local economy as a whole, and make it an even more attractive location for companies
* Resilience. The ability of a local economy to respond to shocks, whether general or specific, is an important issue. This is not a timeless phenomenon, in which we simply compare one equilibrium with the new one, the process by which this happens is crucial
* Tipping points. There is a critical mass of agglomeration, beyond which further rises in employment density bring considerably greater increases in productivity
The field of Big Data requires more clarity and I am a big fan of simple explanations. This is why I have attempted to provide simple explanations for some of the most important technologies and terms you will come across if you’re looking at getting into big data.
THIRTY kilometres south of central Chennai, just out of earshot of the honking, hand-painted lorries roaring up Old Mahabalipuram Road, you seem to have reached rural India. The earth road buckles and heaves. Farmers dressed in Madras-checked dhotis rest outside huts roofed with palm leaves. Goats wander about. Then you turn a corner, go through a gate, and arrive in California. Lakewood Enclave is a new development of 28 large two-storey houses, wedged tightly together. The houses are advertised as “Balinese-style”, although in truth they are hard to tell apart from any number of suburban homes around the world. Outside, the houses are painted a pale pinkish-brown; inside, the walls are white, the floors are stone and the design is open-plan. They each have three bedrooms (middle-class Tamil families are small these days) and a covered driveway to protect a car from the melting sun. Just one detail makes them distinctively Indian: a cupboard near the door for Hindu gods. (...)
As more and more users access social network services from smart devices with GPS receivers, the available amount of geo-tagged information makes repeating classical experiments possible on global scales and with unprecedented precision. Inspired by the original experiments of Milgram, we simulated message routing within a representative sub-graph of the network of Twitter users with about 6 million geo-located nodes and 122 million edges. We picked pairs of users from two distant metropolitan areas and tried to find a route between them using local geographic information only; our method was to forward messages to a friend living closest to the target. We found that the examined network is navigable on large scales, but navigability breaks down at the city scale and the network becomes unnavigable on intra-city distances. This means that messages usually arrived to the close proximity of the target in only 3–6 steps, but only in about 20% of the cases was it possible to find a route all the way to the recipient, in spite of the network being connected.
Complexity in Economics: Cutting Edge Research (New Economic Windows) [Marisa Faggini, Anna Parziale] on Amazon.com. *FREE* shipping on qualifying offers. In this book, leading experts discuss innovative components of complexity theory and chaos theory in economics. The underlying perspective is that investigations of economic phenomena should view these phenomena not as deterministic
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