Guest Editorial: The Ethics of Reviewing

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67095/2/10.1177_00220345760550050201.pd

Hollywood blockbusters and long-tailed distributions: An empirical study of the popularity of movies

Numerical data for all movies released in theaters in the USA during the period 1997-2003 are examined for the distribution of their popularity in terms of (i) the number of weeks they spent in the Top 60 according to the weekend earnings, and (ii) the box-office gross during the opening week, as well as, the total duration for which they were shown in theaters. These distributions show long tails where the most popular movies are located. Like the study of Redner [S. Redner, Eur. Phys. J. B 4, 131 (1998)] on the distribution of citations to individual papers, our results are consistent with a power-law dependence of the rank distribution of gross revenues for the most popular movies with a exponent close to -1/2.Comment: 4 pages, 4 figure

Multiple Tipping Points and Optimal Repairing in Interacting Networks

Systems that comprise many interacting dynamical networks, such as the human body with its biological networks or the global economic network consisting of regional clusters, often exhibit complicated collective dynamics. To understand the collective behavior of such systems, we investigate a model of interacting networks exhibiting the fundamental processes of failure, damage spread, and recovery. We find a very rich phase diagram that becomes exponentially more complex as the number of networks is increased. In the simplest example of $n=2$ interacting networks we find two critical points, 4 triple points, 10 allowed transitions, and two "forbidden" transitions, as well as complex hysteresis loops. Remarkably, we find that triple points play the dominant role in constructing the optimal repairing strategy in damaged interacting systems. To support our model, we analyze an example of real interacting financial networks and find evidence of rapid dynamical transitions between well-defined states, in agreement with the predictions of our model.Comment: 7 figures, typos corrected, references adde

The uniqueness of company size distribution function from tent-shaped growth rate distribution

We report the proof that the extension of Gibrat's law in the middle scale region is unique and the probability distribution function (pdf) is also uniquely derived from the extended Gibrat's law and the law of detailed balance. In the proof, two approximations are employed. The pdf of growth rate is described as tent-shaped exponential functions and the value of the origin of the growth rate distribution is constant. These approximations are confirmed in profits data of Japanese companies 2003 and 2004. The resultant profits pdf fits with the empirical data with high accuracy. This guarantees the validity of the approximations.Comment: 6 pages, 5 figure

Monte Carlo-based tail exponent estimator

In this paper we propose a new approach to estimation of the tail exponent in financial stock markets. We begin the study with the finite sample behavior of the Hill estimator under {\alpha}-stable distributions. Using large Monte Carlo simulations, we show that the Hill estimator overestimates the true tail exponent and can hardly be used on samples with small length. Utilizing our results, we introduce a Monte Carlo-based method of estimation for the tail exponent. Our proposed method is not sensitive to the choice of tail size and works well also on small data samples. The new estimator also gives unbiased results with symmetrical confidence intervals. Finally, we demonstrate the power of our estimator on the international world stock market indices. On the two separate periods of 2002-2005 and 2006-2009, we estimate the tail exponent

Pareto's Law of Income Distribution: Evidence for Germany, the United Kingdom, and the United States

We analyze three sets of income data: the US Panel Study of Income Dynamics PSID), the British Household Panel Survey (BHPS), and the German Socio-Economic Panel (GSOEP). It is shown that the empirical income distribution is consistent with a two-parameter lognormal function for the low-middle income group (97%-99% of the population), and with a Pareto or power law function for the high income group (1%-3% of the population). This mixture of two qualitatively different analytical distributions seems stable over the years covered by our data sets, although their parameters significantly change in time. It is also found that the probability density of income growth rates almost has the form of an exponential function.Comment: Latex2e v1.6; 16 pages with 5 figure

Growth and Fluctuations of Personal Income

Pareto's law states that the distribution of personal income obeys a power-law in the high-income range, and has been supported by international observations. Researchers have proposed models over a century since its discovery. However, the dynamical nature of personal income has been little studied hitherto, mostly due to the lack of empirical work. Here we report the first such study, an examination of the fluctuations in personal income of about 80,000 high-income taxpayers in Japan for two consecutive years, 1997 and 1998, when the economy was relatively stable. We find that the distribution of the growth rate in one year is independent of income in the previous year. This fact, combined with an approximate time-reversal symmetry, leads to the Pareto law, thereby explaining it as a consequence of a stable economy. We also derive a scaling relation between positive and negative growth rates, and show good agreement with the data. These findings provide the direct observation of the dynamical process of personal income flow not yet studied as much as for companies.Comment: 9 pages, 4 figure