Timing Effects on Divorce: 20th Century Experience in the United States

Period divorce measures can misrepresent the underlying behavior of birth cohorts as changes in cohort timing produce changes in period probabilities of divorce. Building on methods used to adjust period fertility and marriage measures, we adjust U.S. period divorce rates for timing effects, calculating a timing index for every year between 1910 and 2000. The adjusted probability of divorce, PMED*, increases nearly linearly from 1910 through 1990, remaining at about that level through 2000. Period measures greatly exaggerate divorce risks from the early 1970s to the mid‐1980s, but understate them at other times. Adjusted values for recent years do not suggest a decline in the likelihood of divorce, with year 2000 values indicating a divorce probability of 0.43 – 0.46.     

Nonparametric local polynomial approximation of the time-varying frequency and amplitude

The problem of estimating the time-varying frequency, phase and amplitude of a real-valued harmonic signal is considered. It is assumed that the frequency and amplitude are unspecified rapidly time-varying functions of time. The technique is based on fitting a local polynomial approximation of the phase and amplitude which implements a high-order nonlinear nonparametric estimator. The estimator is shown to be strongly consistent and Gaussian. In particular, the convergence ratesO(h^-3/2 )and O(h^-5/2 ), where $i;h$ei; is the number of observations, are obtained for the frequency estimator when the amplitude is unknown constant or linear in time respectively. The orders of the bias and Gaussian distribution are obtained for a class of the time-varying frequency and amplitude with bounded second derivatives. The a priori amplitude information about the unknown time-varying frequency and amplitude and their derivatives can be incorporated to improve the accuracy of the estimation. Simulation results are given.     

Simulation Modeling of Anthrax Spore Dispersion in a Bioterrorism Incident

Recent events have increased awareness of the risk posed by terrorist attacks. Bacillus anthracis has resurfaced in the 21st century as a deadly agent of bioterrorism because of its potential for causing massive civilian casualties. This analysis presents the results of a computer simulation of the dispersion of anthrax spores in a typical 50-story, high-rise building after an intentional release during a bioterrorist incident. The model simulates aerosol dispersion in the case of intensive, small-scale convection, which equalizes the concentration of anthrax spores over the building volume. The model can be used to predict the time interval required for spore dispersion throughout a building after a terrorist attack in a high-rise building. The analysis reveals that an aerosol release of even a relatively small volume of anthrax spores during a terrorist incident has the potential to quickly distribute concentrations that are infectious throughout the building.     

Mortality in Belarus, Lithuania, and Russia: Divergence in Recent Trends and Possible Explanations

Before the collapse of the Soviet Union, Belarus, Lithuania, and Russia were quite comparable in terms of their socioeconomic development. Despite some differences in overall mortality levels, the three former Soviet republics were also very close to each other in terms of directions of mortality trends and age- and cause-specific mortality patterns. After 1991, all the three countries experienced substantial political and social transformations, and the challenges associated with the transition from a socialist to a market economy system. The sudden changes brought numerous problems, such as rapid growth in unemployment, falling standards of living, and growing social and income inequalities. These factors contributed to the significant deterioration of the health situation in all the countries, but the size and the nature of the mortality crisis was different in Belarus than it was in Lithuania and Russia. The marked similarities in socioeconomic and mortality trends in the countries up to 1991 contrast with their notable divergence during the subsequent years. The nature and success of market reforms seems to be the most plausible explanation for these differences. Russia and Lithuania have chosen more radical forms of economic and political transformations, which have led to massive privatization campaigns. The reforms were more sustainable and systematic in Lithuania than in Russia. By contrast, Belarus has chosen a gradual and slow transition path. Recent mortality trends in Belarus are explored in detail here, and are contrasted with those observed in Lithuania and Russia. Including a cause-of-death analysis sheds more light on the plausible determinants of the variations in mortality levels between the countries.     

Critical phenomena in complex contagions

Why do some contagions “go viral” and others do not? Research on “small world” networks (Watts and Strogatz, 1998) shows how a very small number of long-range ties that bridge between clusters can allow contagions to spread almost as rapidly as on a random network of equal density. Recent research shows how long-range ties that accelerate the spread of information and disease can impede the spread of complex contagions—behaviors, beliefs and preferences that diffuse via contact with multiple adopters ( Centola and Macy, 2007). In confirming this result analytically and extending the analysis from small world to power law networks, we discovered that complex contagions require a critical mass of infected nodes that corresponds to a phase transition in the ability of the contagion to take advantage of the “shortcuts” created by long-range ties. We demonstrate how this critical mass is related to the dynamics of the contagion process and identify implications for modeling behaviors that spread via social influence, such as viral marketing and social movements.     

To Farm or Not to Farm: Rural Dilemma in Russia and Ukraine

Abstract Employing primary data collected in the summer of 1991 in a representative survey of two farming areas in the territory of the republics of Russia and Ukraine, this study addresses the issue of the future involvement of collective and state-farm workers in private farming. Through the use of a LISREL model, it is argued that those who have been involved in small-scale private farming show no interest in expanding their farm operations or in buying or leasing additional land for farming. Moreover, it is maintained that those who intend to become farmers in privately owned and operated farms are more likely to be young, educated, and to some extent, ideologically committed to the free market system. A combination of structural constraints and a lack of knowledge regarding what to expect in the future can be viewed as possible explanations of the answers provided by respondents.