- 20 October 2012
Redistribution spurs growth by using a portfolio effect on human capital
Jan Lorenz, Fabian Paetzel, Frank Schweitzer
We demonstrate by mathematical analysis and systematic computer simulations
that redistribution can lead to sustainable growth in a society. The human
capital dynamics of each agent is described by a stochastic multiplicative
process which, in the long run, leads to the destruction of individual human
capital and the extinction of the individualistic society. When agents are
linked by fully-redistributive taxation the situation might turn to individual
growth in the long run. We consider that a government collects a proportion of
income and reduces it by a fraction as costs for administration (efficiency
losses). The remaining public good is equally redistributed to all agents. We
derive conditions under which the destruction of human capital can be turned
into sustainable growth, despite the losses from the random growth process and
despite the administrative costs. Sustainable growth is induced by
redistribution. This effect could be explained by a simple portfolio-effect
which re-balances individual stochastic processes.
<br />The findings are verified for three different tax schemes: proportional tax,
taking proportional more from the rich, and proportionally more from the poor.
We discuss which of these tax schemes is optimal with respect to maximize
growth under a fixed rate of administrative costs, or with respect to maximize
the governmental income. This leads us to some general conclusions about
governmental decisions, the relation to public good games, and the use of
taxation in a risk taking society.
- 31 May 2012
A Simple, Direct Finite Differencing of the Einstein Equations
We investigate a simple variation of the Generalized Harmonic method for
evolving the Einstein equations. A flat space wave equation for metric
perturbations is separated from the Ricci tensor, with the rest of the Ricci
tensor becoming a source for these wave equations. We demonstrate that this
splitting method allows for the accurate simulation of compact objects, with
gravitational field strengths less than or equal to those of neutron stars.
This method could thus provide a straightforward path for general relativistic
effects to be added to astrophysics simulations, such as in core collapse,
accretion disks, and extreme mass ratio systems.
- 31 May 2012
Quantifying the influence of scientists and their publications: distinguishing between prestige and popularity
Yan-Bo Zhou, Linyuan Lü1, and Menghui Li
The number of citations is a widely used metric for evaluating the scientific credit of papers, scientists and journals. However, it so happens that papers with fewer citations from prestigious scientists have a higher influence than papers with more citations. In this paper, we argue that by whom the paper is being cited is of greater significance than merely the number of citations. Accordingly, we propose an interactive model of author–paper bipartite networks as well as an iterative algorithm to obtain better rankings for scientists and their publications. The main advantage of this method is twofold: (i) it is a parameter-free algorithm; (ii) it considers the relationship between the prestige of scientists and the quality of their publications. We conducted real experiments on publications in econophysics, and used this method to evaluate the influence of related scientific journals. The comparison between the rankings by our method and simple citation counts suggests that our method is effective in distinguishing prestige from popularity. [more]
- 28 July 2011
[News and announcements]:
IMT Lucca - Ph.D. Program - Economics, Markets, Institutions
IMT has opened the call for applications for the Ph.D. Program in Economics, Markets, Institutions (deadline September 28th, 2011). [more]
- 19 July 2011
FuturICT and Social Sciences: Big Data, Big Thinking
Rosaria Conte, Nigel Gilbert, Giulia Bonelli, and Dirk Helbing
Imagine storing all the computational information produced in the world in just one year: you would have a pile of DVDs able to reach the Moon and back. How about all the data collected since the beginning of the computer era? The quantity is so huge that traditional units of measurement cannot cope. For this reason a few years ago computer scientists started talking about “Big Data”, referring to the gathering, formatting, analysing and manipulating of a massive amount of digital information. [more]
- 18 April 2011
Achilles' heels of current economic theories - The debate
Dirk Helbing, ETHZ, Switzerland
A guest editorial by Dirk Helbing (ETHZ, Switzerland) presenting an ongoing debate on the Achilles' heels of current economic theories. [more]
- 12 April 2010
Worrying signs of “new thinking”
During the spectacular financial market crashes and the resulted recession, there has been renewed assault on the Efficient Market Hypothesis (EMH) and its theoretical basis—mainstream economics. George Soros announced Oct. 2009 that he will put 50 million dollars over ten years to establish an “Institute for New Economic Thinking”. [more]
- 6 April 2010
Limited knowledge shilling attacks in collaborative filtering systems
R Burke, B Mobasher, R Bhaumik
Recent research in recommender systems has shown that collaborative filtering algorithms are
highly susceptible to attacks that insert biased profile data. Theoretical analyses and empirical
experiments have shown that certain attacks can have a significant impact on the ... [more]
- 3 November 2009
[News and announcements]:
Networks: A Framework for cross-disciplinary applications
The Institute for Biocomputation and Physics of Complex Systems (BIFI) of the University of Zaragoza, Spain, is organizing the Conference "Networks: A Framework for cross-disciplinary applications" that will take place from February 3 to February 6, 2010. More information can be found at http://bifi.unizar.es/events/bifi2010/
Complex Networks have been the subject of intense research during the last decade. After the burst of activity in this field, it has been increasingly recognized that network theory has become an essential ingredient for understanding and modeling the structure and dynamics of complex systems. The application of complex networks concepts and tools has rapidly spread across disciplines as diverse as Epidemiology, Sociology, Neuroscience and Computer Science. The common methodological framework provided by network theory is thus a crossroads in which different scientific perspectives share efforts and gain knowledge to their own applications.
The aim of BIFI2010 is to bring together scientists studying complex systems in Physics, Sociology, Computer Science, Neuroscience and Biology that strongly rely on the use of complex networks for their research. The topics to be covered include, but is not limited to, the following scientific problems:
- Predictive power of Network Theory.
- Complex Networks in Technology, including communication and wireless networks.
- Structure and Dynamics of Biological Networked Systems at all organizational levels (from the genome to ecosystems).
- Social Networks.
- Evolutionary Game and Graphs Dynamics.
- Algorithms in and for Complex Networks.
- Synchronization in Complex Networks, including Brain and neural networks.
- Epidemic Spreading in Heterogeneous Populations. [more]