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Sistemas Dinámicos para Economistas parte1 ( CEIICH UNAM México )

10-sep-2013 "Sistemas Dinámicos para Economistas" Dr Ricardo Mansilla Corona Seminario Complejidad y Economía CEIICH UNAM México https://sites.google.com/sit...
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Videos del Seminario de Complejidad y Economía CEIICH - UNAM México

 

"Dynamical systems for Economists"

CEIICH  UNAM México

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Fama, Hansen, and Shiller win Nobel Prize in Economics

Eugene F. Fama, Robert J. Shiller and Lars Peter Hansen win the 2013 Nobel Prize in Economic Sciences. “The Laureates have laid the foundation for the current understanding of asset prices. It relies in part on fluctuations in risk and risk attitudes, and in part on behavioral biases and market frictions.” stated the Royal Swedish Academy of Sciences.


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Duncan Watts on the future of marketing

The principal research scientist at Yahoo! Research discusses the limits of intuition, and how conventional wisdom keeps being overturned as marketers apply ...
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Explore – How the economy really-really works, animated....

Explore – How the economy really-really works, animated.... | Economia y sistemas complejos | Scoop.it
How the economy really-really works, animated. Pair with this indispensable read on how to worry less about money, then revisit legendary economist John Bernard Keynes’s optimistic 1930 vision for...

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Managing Market Complexity - Springer

Managing Market Complexity - Springer | Economia y sistemas complejos | Scoop.it

Managing Market Complexity

The Approach of Artificial Economics

Editors: Andrea Teglio, Simone Alfarano, Eva Camacho-Cuena, Miguel Ginés-Vilar


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Control of the socio-economic systems using herding interactions. (arXiv:1309.6105v1 [physics.soc-ph]) - Quantitative Finance at arXiv's blog - MoneyScience

Collective behavior of the complex socio-economic systems is heavily influenced by the herding, group, behavior of individuals. The importance of the herding be
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First Degree Price Discrimination Using Big Data


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Economics 2.0: The Natural Step towards a Self-Regulating, Participatory Market Society

Despite all our great advances in science, technology and financial innovations, many societies today are struggling with a financial, economic and public spending crisis, over-regulation, and mass unemployment, as well as lack of sustainability and innovation. Can we still rely on conventional economic thinking or do we need a new approach? Is our economic system undergoing a fundamental transformation? Are our theories still doing a good job with just a few exceptions, or do they work only for “good weather” but not for “market storms”? Can we fix existing theories by adapting them a bit, or do we need a fundamentally different approach? These are the kind of questions that will be addressed in this paper. I argue that, as the complexity of socio-economic systems increases, networked decision-making and bottom-up self-regulation will be more and more important features. It will be explained why, besides the “homo economicus” with strictly self-regarding preferences, natural selection has also created a “homo socialis” with other-regarding preferences.(...)

 

Economics 2.0: The Natural Step towards a Self-Regulating, Participatory Market Society
Dirk Helbing

Evolutionary and Institutional Economics Review Vol. 10 (2013) No. 1 p. 3-41

https://www.jstage.jst.go.jp/article/eier/10/1/10_3/_article


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june holley's curator insight, September 18, 2013 1:17 PM

This understanding is key for those of us committed to a more just and inclusive economy.

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The Power of Networks | World Economic Forum 2012

Nowadays, any organization should employ network scientists/analysts who are able to map and analyse complex systems that are of importance to the organization (e.g. the organization itself, its activities, a country’s economic activities, transportation networks, research networks).
Interconnectivity is beneficial but also brings in vulnerability: if you and I are connected we can share resources; meanwhile your problems can become mine and vice versa.
The concept of “crystallized imagination” refers to things that are first in our head and then become reality. This concept can be turned into network applied research on economic complexity of a country’s economic activities and development prospects.


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Erika Harrison's curator insight, August 9, 2013 1:43 PM

"*Nowadays, any organization should employ network scientists/analysts who are able to map and analyse complex systems that are of importance to the organization (e.g. the organization itself, its activities, a country’s economic activities, transportation networks, research networks).

 

*Interconnectivity is beneficial but also brings in vulnerability: if you and I are connected we can share resources; meanwhile your problems can become mine and vice versa.

 

*The concept of “crystallized imagination” refers to things that are first in our head and then become reality. This concept can be turned into network applied research on economic complexity of a country’s economic activities and development prospects".

Jason Leong's curator insight, November 6, 2014 9:23 PM

Network science — the mapping and visualisation of the networked systems that make up our society, economies, and organisations — is set to become the new tool for informing design. (It's about time!)

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Transdisciplinary electric power grid science

When a tenth of humanity lost power over 2 days in India in July 2012, technical failure was not the only culprit. Like many recent blackouts, this outage resulted from couplings among systems, including extreme weather exacerbated by climate change, human operator errors, suboptimal policies, and market forces. Predictions that climate change intensifies droughts and tropical cyclones presage more weather-induced blackouts. Even without weather disasters, small disturbances can trigger cascading failures, and so can ill-designed electricity markets (1) and dependence on cyber infrastructure.

 

Transdisciplinary electric power grid science
Charles D. Brummitt, Paul D. H. Hines, Ian Dobson, Cristopher Moore, and Raissa M. D'Souza

http://dx.doi.org/10.1073/pnas.1309151110
PNAS July 23, 2013 vol. 110 no. 30 12159


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A Complex Systems Science Approach to Healthcare Costs and Quality

There is a mounting crisis in delivering affordable healthcare in the US. For decades, key decision makers in the public and private sectors have considered cost-effectiveness in healthcare a top priority. Their actions have focused on putting a limit on fees, services, or care options. However, they have met with limited success as costs have increased rapidly while the quality isn't commensurate with the high costs. A new approach is needed. Here we provide eight scientifically-based steps for improving the healthcare system. The core of the approach is promoting the best use of resources by matching the people and organization to the tasks they are good at, and providing the right incentive structure. Harnessing costs need not mean sacrificing quality. Quality service and low costs can be achieved by making sure the right people and the right organizations deliver services. As an example, the frequent use of emergency rooms for non-emergency care demonstrates the waste of resources of highly capable individuals and facilities resulting in high costs and ineffective care. Neither free markets nor managed care guarantees the best use of resources. A different oversight system is needed to promote the right incentives. Unlike managed care, effective oversight must not interfere with the performance of care. Otherwise, cost control only makes care more cumbersome. The eight steps we propose are designed to dramatically improve the effectiveness of the healthcare system, both for those who receive services and those who provide them.

 

A Complex Systems Science Approach to Healthcare Costs and Quality
Yaneer Bar-Yam with Shlomiya Bar-Yam, Karla Z. Bertrand, Nancy Cohen, Alexander S. Gard-Murray, Helen P. Harte, Luci Leykum

http://arxiv.org/abs/1207.0034


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5th Annual Complexity in Business Conference

The Annual Complexity in Business Conference endeavors to be the premier meeting for the intersection of Complex Systems and Business. The 5th annual conference will be a one and a half day event and will include talks by thought leaders and an audience blend of academics and industry practitioners. We are very excited to announce that this year we will be having a concurrent track during the conference and will be accepting abstract submissions from the public. We are looking forward to a lively set of interactions among a very distinguished group of researchers and business leaders. On Thursday, November 7 at 3:00 p.m. a series of talks at the Ronald Reagan Building will kick off the conference, followed by a cocktail reception and dinner at a D.C. restaurant.

 


5th Annual Complexity in Business Conference Thursday and Friday, November 7 and 8, 2013 • Washington, DC 

http://www.rhsmith.umd.edu/ccb/conference/2013/


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Modelling Complexity for Policy: Opportunities and Challenges


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NESS's curator insight, October 10, 2013 7:30 PM

"Several modelling approaches from complexity science are briefly described, with notes as to their abilities and limitations. These approaches include system dynamics, network theory, information theory, cellular automata, and agent-based modelling. (...)"

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Information in Digital, Economic, and Social Networks

Digital technologies have made networks ubiquitous. A growing body of research is examining these networks to gain a better understanding of how firms interact with their consumers, how people interact with each other, and how current and future digital artifacts will continue to alter business and society. The increasing availability of massive networked data has led to several streams of inquiry across fields as diverse as computer science, economics, information systems, marketing, physics, and sociology. Each of these research streams asks questions that at their core involve “information in networks”—its distribution, its diffusion, its inferential value, and its influence on social and economic outcomes. We suggest a broad direction for research into social and economic networks. Our analysis describes four kinds of investigation that seem most promising. The first studies how information technologies create and reveal networks whose connections represent social and economic relationships. The second examines the content that flows through networks and its economic, social, and organizational implications. A third develops theories and methods to understand and utilize the rich predictive information contained in networked data. A final area of inquiry focuses on network dynamics and how information technology affects network evolution. We conclude by discussing several important cross-cutting issues with implications for all four research streams, which must be addressed if the ensuing research is to be both rigorous and relevant. We also describe how these directions of inquiry are interconnected: results and ideas will pollinate across them, leading to a new cumulative research tradition.

 

Information in Digital, Economic, and Social Networks
Arun Sundararajan, Foster Provost, Gal Oestreicher-Singer and Sinan Aral

http://dx.doi.org/10.1287/isre.1120.0472
Information Systems Research March 2013 isre.1120.0472


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Cartels Are an Emergent Phenomenon, Say Complexity Theorists | MIT Technology Review

Cartels Are an Emergent Phenomenon, Say Complexity Theorists | MIT Technology Review | Economia y sistemas complejos | Scoop.it
Under certain market conditions, cartels arise naturally without collusion. This raises important questions over how the behavior should be controlled.
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Cartels Are an Emergent Phenomenon, Say Complexity Theorists | MIT Technology Review

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The Uses of Big Data in Cities

There is much enthusiasm currently about the possibilities created by new and more extensive sources of data to better understand and manage cities. Here, I explore how big data can be useful in urban planning by formalizing the planning process as a general computational problem. I show that, under general conditions, new sources of data coordinated with urban policy can be applied following fundamental principles of engineering to achieve new solutions to important age-old urban problems. I also show, that comprehensive urban planning is computationally intractable (i.e. practically impossible) in large cities, regardless of the amounts of data available. This dilemma between the need for planning and coordination and its impossibility in detail is resolved by the recognition that cities are first and foremost self-organizing social networks embedded in space and enabled by urban infrastructure and services. As such the primary role of big data in cities is to facilitate information flows and mechanisms of learning and coordination by heterogeneous individuals. However, processes of self-organization in cities, as well as of service improvement and expansion, must rely on general principles that enforce necessary conditions for cities to operate and evolve. Such ideas are the core a developing scientific theory of cities, which is itself enabled by the growing availability of quantitative data on thousands of cities worldwide, across different geographies and levels of development. These three uses of data and information technologies in cities constitute then the necessary pillars for more successful urban policy and management that encourages, and does not stifle, the fundamental role of cities as engines of development and innovation in human societies.

 

The Uses of Big Data in Cities
Luís M. A. Bettencourt

http://www.santafe.edu/research/working-papers/abstract/1c669193b79cb42f44ce5e0e63928bb0/


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june holley's curator insight, October 7, 2013 8:03 AM

More about self-organizing in here.

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War, space, and the evolution of Old World complex societies

How did human societies evolve from small groups, integrated by face-to-face cooperation, to huge anonymous societies of today? Why is there so much variation in the ability of different human populations to construct viable states? We developed a model that uses cultural evolution mechanisms to predict where and when the largest-scale complex societies should have arisen in human history. The model was simulated within a realistic landscape of the Afroeurasian landmass, and its predictions were tested against real data. Overall, the model did an excellent job predicting empirical patterns. Our results suggest a possible explanation as to why a long history of statehood is positively correlated with political stability, institutional quality, and income per capita.

 

War, space, and the evolution of Old World complex societies
Peter Turchin, Thomas E. Currie, Edward A. L. Turner, and Sergey Gavrilets

http://dx.doi.org/10.1073/pnas.1308825110
PNAS September 23, 2013


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Yannis Corovesis's curator insight, October 4, 2013 10:01 AM

Peter Turchin is the son of Valentin Fiodorovitch

Thomas Owens's curator insight, January 25, 2014 12:47 AM

I wish I had more time to study this so I'm going to mark it.

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Agent-based and macroscopic modeling of the complex socio-economic systems. (arXiv:1303.3693v1 [physics.soc-ph]) - Quantitative Finance at arXiv's blog - MoneyScience

The current economic crisis has provoked an active response from the interdisciplinary scientific community. As a result many papers suggesting what can be improved...

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Stopping Financial Avalanches By Random Trading Alessio Emanuele Biondo, Alessandro Pluchino, Andrea Rapisarda, Dirk Helbing

Link to Pdf: http://arxiv.org/pdf/1309.3639v1.pdf


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FuturICT's curator insight, September 17, 2013 9:36 AM

Building on similarities between earthquakes and extreme financial events, we use a self-organized criticality-generating model to study herding and avalanches dynamics in financial markets.

 

We consider a community of interacting investors, distributed on a small world network, who bet on the bullish (increasing) or bearish (decreasing) behavior of the market compared to the day before, following the S&P500 historical time series. Remarkably, we find that the size of herding-related avalanches in the community can be strongly reduced by the presence of a relatively small percentage of trader s, randomly distributed inside the network, who adopt a random investment strategy.

 

These results suggest a promising strategy to limit the size of financial bubbles and crashes. We also find that the final wealth distribution of all traders corresponds to the well-known Pareto power law, while that one of random traders only is exponential. In other words, for technical traders, the risk of losses is much greater than the probability of gains compared to those of random traders.

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Is the Voter Model a model for voters?

The voter model has been studied extensively as a paradigmatic opinion dynamics' model. However, its ability for modeling real opinion dynamics has not been addressed. We introduce a noisy voter model (accounting for social influence) with agents' recurrent mobility (as a proxy for social context), where the spatial and population diversity are taken as inputs to the model. We show that the dynamics can be described as a noisy diffusive process that contains the proper anysotropic coupling topology given by population and mobility heterogeneity. The model captures statistical features of the US presidential elections as the stationary vote-share fluctuations across counties, and the long-range spatial correlations that decay logarithmically with the distance. Furthermore, it recovers the behavior of these properties when a real-space renormalization is performed by coarse-graining the geographical scale from county level through congressional districts and up to states. Finally, we analyze the role of the mobility range and the randomness in decision making which are consistent with the empirical observations.

 

Is the Voter Model a model for voters?
Juan Fernández-Gracia, Krzysztof Suchecki, José J. Ramasco, Maxi San Miguel, Víctor M. Eguíluz

http://arxiv.org/abs/1309.1131


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Cities are a new kind of complex system: Part social reactor, part network

Cities are a new kind of complex system: Part social reactor, part network | Economia y sistemas complejos | Scoop.it
Scientists have derived a series of mathematical formulas that describe how cities' properties vary in relation to their population size, and then posits a novel unified, quantitative framework for understanding how cities function and grow.

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judycurtis's curator insight, June 23, 2013 3:58 PM

New, fascinating research led by Luis Bettencourt and the Santa Fe Institute's Cities & Urbanization research team has bearing on the Smart Cities concept. In a paper published in the magazine Science (week of June 20, 2013) Bettencourt proposes a framework for understanding how cities function and grow.

 

His framework has practical implications for planners and policy makers, he says. The paper shows how obstacles to socialization, such as crime or segregation, and enablers that promote the ability of people to connect, such as transportation and electricity, all become part of the same equation.

luiy's curator insight, June 24, 2013 3:02 PM

New research by Santa Fe Institute Professor Luis Bettencourt suggests a city is something new in nature -- a sort of social reactor that is part star and part network, he says.

 

"It's an entirely new kind of complex system that we humans have created," he says. "We have intuitively invented the best way to create vast social networks embedded in space and time, and keep them growing and evolving without having to stop. When that is possible, a social species can sustain ways of being incredibly inventive and productive."

 

In a paper published this week in Science, Bettencourt derives a series of mathematical formulas that describe how cities' properties vary in relation to their population size, and then posits a novel unified, quantitative framework for understanding how cities function and grow.

His resulting theoretical framework predicts very closely dozens of statistical relationships observed in thousands of real cities around the world for which reliable data are available.

 

"As more people lead urban lives and the number and size of cities expand everywhere, understanding more quantitatively how cities function is increasingly important," Bettencourt says. "Only with a much better understanding of what cities are will we be able to seize the opportunities that cities create and try to avoid some of the immense problems they present. This framework is a step toward a better grasp of the functioning of cities everywhere."

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Why The Future Of Innovation Is Simulation

The result is now clear to just about everyone on the planet.  The smartest guys in the room were no match for terabytes of data and smart algorithms.  There is no one “theory of the case” anymore, but thousands of them, being run constantly.  The point isn’t to be right, but to become less wrong over time.


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ComplexInsight's curator insight, July 27, 2013 2:41 AM

Eric Bonabeau's team at Icosystems have helped pioneer commercial application of agent based modelling applications. It's nice to see them get some recognition in the Forbes article. However the article itself would have been much stronger if it had opened its scope and mentioned other teams such as Argonne National Labs (Repast), George Mason University (Mason), Uri Wilensky and the CCL team at NorthWestern (NetLogo). Technical University of Berlin/Federal Institute Zurich and Senozon (Matsim) amongst many others. All these teams have built platforms that are slowly but surely moving agent based simulation from academic theory to important real world applications and adoption. Nevertheless - good article and nice to see this being covered by the wider press.

luiy's curator insight, September 4, 2013 4:27 PM

When the Thomas Edison was asked about success amidst failure, he said that “If I find 10,000 ways something won’t work, I haven’t failed. I am not discouraged, because every wrong attempt discarded is another step forward.”


If Thomas Edison was alive today he would say that innovation is 1% inspiration and 99% simulation (Photo credit: Wikipedia)

With that kind of dedication, it’s no wonder that Edison  was awarded over 1000 patents, including the light bulb, the phonograph and the motion picture camera, making him one of the most prolific inventors in history.

It also becomes clear why he regarded success as “1% inspiration and 99% perspiration.”  Failing 10,000 times is a physical and mental undertaking that far exceeds most people’s endurance.  Today, however, a new breed of innovators are outsourcing failure to computer simulations and it’s changing everything we thought we knew about business strategy.

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Protest in the connected society

Protest in the connected society | Economia y sistemas complejos | Scoop.it

From New York to Istanbul, and Rio to Tunis, waves of social unrest have been sweeping across the world. Whatever they are called – Occupy Wall Street in New York, the Jasmine Revolution in Tunisia or the Arab Spring beyond, and the Salad Uprising in Brazil – the mass mobilisations share several common features.
Espousing public discontent over a range of sometimes unrelated, even conflicting issues, they were driven largely by new communication technologies coupled with an abiding distrust of government policies.
Unlike the formal, planned protests of earlier times, the latest ones are, for the most part, informal and relatively spontaneous. As such, scientists say, they reflect a shift away from conventional social hierarchies towards what some call leaderless networks.


Read more: http://www.theage.com.au/digital-life/digital-life-news/protest-in-the-connected-society-20130726-2qoyd.html#ixzz2b87OWggE


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The Diffusion of Microfinance

How do the network positions of the first individuals in a society to receive information about a new product affect its eventual diffusion? To answer this question, we develop a model of information diffusion through a social network that discriminates between information passing (individuals must be aware of the product before they can adopt it, and they can learn from their friends) and endorsement (the decisions of informed individuals to adopt the product might be influenced by their friends’ decisions). We apply it to the diffusion of microfinance loans, in a setting where the set of potentially first-informed individuals is known. We then propose two new measures of how “central” individuals are in their social network with regard to spreading information; the centrality of the first-informed individuals in a village helps significantly in predicting eventual adoption.

The Diffusion of Microfinance
Abhijit Banerjee, Arun G. Chandrasekhar, Esther Duflo, Matthew O. Jackson

Science 26 July 2013:
Vol. 341 no. 6144
http://dx.doi.org/10.1126/science.1236498


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