In the Long Run We Are all Dead: Hey Keynes, What Is Long in the Contemporary US Case?

The idea of declinism of the US had emerged in every decade after the World War Two and so it was as well after the end of the Cold War. The article argues that such a phenomenon may be attributed to the nature of the international system, where through the globalization the US enables ‘the rest’ to grow on its expense. China and other export led economies, made great benefit of the US open market that is functioning as a ‘big vacuum cleaner’. The focal question of article is two-folded: first, is ‘the raise of the rest’ causing the geoeconomic centre of power to shift from the Atlantic to Pacific; second, is the US in decline? Article presents economic data that show that there are no economic incentives for the geoeconomic shift. The geopolitical centre may indeed by shifting, but not due to the geoeconomic reasons, but rather due to military, political, and ideological power factors. The US has been in relative decline since the end of the WW2—other international actors seized the chance that the international system created by the US provided. Thus, the relevant question about declinism is—is the US in absolute decline? The article argues that the 2008 financial shock was not cyclical in nature, but rather systemic. It is the first time since the WW2 that the US was unable to answer to the challenge adequately. The main reason for that is not external, namely, the relative decline of the US—G8 was replaced by G20—but internal—the US is not tackling the core of its systemic economic problem. This suggests that the US is marching towards an absolute decline. To avoid its demise, the US has to change its Keynesian pragmatic short-sighted economic mentality and do the well needed structural reforms.     

Are Migrants Overrepresented Among Individual Welfare Beneficiaries?

The level of immigrant welfare dependency is the subject of heated debate in the majority of developed countries, which have experienced a significant increase in immigration in recent years. In both Europe and the US, the problem of potential excessive use of social transfers is beginning to bring real policy consequences. This article addresses this issue by presenting a quantitative assessment of welfare receipt in 17 European countries, as well as Yun decomposition of its differences between natives and immigrants. It adds to existing literature by comparing the levels of welfare dependence among EU and non-EU migrants for individual benefits including and excluding pensions, using recent data from EU-SILC. Results suggest that immigrants rely on welfare less often than natives, and receive lower benefits when they do. Those conclusions are reversed, however, when old-age benefits are not considered – especially in the case of non-EU migrants.     

The Development of Multiple Self‐Concept Dimensions During Adolescence

The purpose of this research was to analyze the development of self‐concept during adolescence. Participants included 484 teenagers (226 boys and 258 girls) from middle‐class families in the Basque Country region of Spain (M_age = 14.99, SD = 1.81 in Time 1 and M_age = 15.64, SD = 1.80 in Time 2). Longitudinal analysis found differences in the general school dimension. Six dimensions (math, verbal, general school, physical abilities, parent relationships and same‐sex relationships) reported a linear trend with a decreasing monotonic pattern; self‐esteem fit a cubic trend and physical appearance a quadratic trend line. Males showed higher means in self‐esteem, math, physical abilities, physical appearance, emotional stability and parent relationships; and females had higher values in verbal and general school.     

An intuitive risk factors search algorithm: usage of the Bayesian network technique in personalized medicine

The article focuses on the application of the Bayesian networks (BN) technique to problems of personalized medicine. The simple (intuitive) algorithm of BN optimization with respect to the number of nodes using naive network topology is developed. This algorithm allows to increase the BN prediction quality and to identify the most important variables of the network. The parallel program implementing the algorithm has demonstrated good scalability with an increase in the computational cores number, and it can be applied to the large patients database containing thousands of variables. This program is applied for the prediction for the unfavorable outcome of coronary artery disease (CAD) for patients who survived the acute coronary syndrome (ACS). As a result, the quality of the predictions of the investigated networks was significantly improved and the most important risk factors were detected. The significance of the tumor necrosis factor-alpha gene polymorphism for the prediction of the unfavorable outcome of CAD for patients survived after ACS was revealed for the first time.     

Quality of Life in Transition Countries: Central East Europe with Special Reference to Croatia

With the historical change of the socio-economic system in ex-communist European countries quality of life of the population changed dramaticaly, improving in some components and within certain social strata and deteriorationg in others. These changes are analysed within the framework of authentic development and quality of life components: economic, social, political, environmental, cultural and human. The major aspect of the changes is the enlargement of human choices in all of the components, and to different extents in different countries in transition. The future of the whole transition process lies in its sustainablity and ability to draw on its past experience as well as on the experience of the Western world.     

Local orthogonal polynomial expansion for density estimation

A local orthogonal polynomial expansion (LOrPE) of the empirical density function is proposed as a novel method to estimate the underlying density. The estimate is constructed by matching localised expectation values of orthogonal polynomials to the values observed in the sample. LOrPE is related to several existing methods, and generalises straightforwardly to multivariate settings. By manner of construction, it is similar to local likelihood density estimation (LLDE). In the limit of small bandwidths, LOrPE functions as kernel density estimation (KDE) with high-order (effective) kernels inherently free of boundary bias, a natural consequence of kernel reshaping to accommodate endpoints. Consistency and faster asymptotic convergence rates follow. In the limit of large bandwidths LOrPE is equivalent to orthogonal series density estimation (OSDE) with Legendre polynomials, thereby inheriting its consistency. We compare the performance of LOrPE to KDE, LLDE, and OSDE, in a number of simulation studies. In terms of mean integrated squared error, the results suggest that with a proper balance of the two tuning parameters, bandwidth and degree, LOrPE generally outperforms these competitors when estimating densities with sharply truncated supports.     

Resilience of Cyber Systems with Over‐ and Underregulation

Recent cyber attacks provide evidence of increased threats to our critical systems and infrastructure. A common reaction to a new threat is to harden the system by adding new rules and regulations. As federal and state governments request new procedures to follow, each of their organizations implements their own cyber defense strategies. This unintentionally increases time and effort that employees spend on training and policy implementation and decreases the time and latitude to perform critical job functions, thus raising overall levels of stress. People's performance under stress, coupled with an overabundance of information, results in even more vulnerabilities for adversaries to exploit. In this article, we embed a simple regulatory model that accounts for cybersecurity human factors and an organization's regulatory environment in a model of a corporate cyber network under attack. The resulting model demonstrates the effect of under‐ and overregulation on an organization's resilience with respect to insider threats. Currently, there is a tendency to use ad‐hoc approaches to account for human factors rather than to incorporate them into cyber resilience modeling. It is clear that using a systematic approach utilizing behavioral science, which already exists in cyber resilience assessment, would provide a more holistic view for decisionmakers.     

Health-Based Population Forecasting: Effects of Smoking on Mortality and Fertility

A microsimulation model, allowing one to forecast short- and long-term population changes conditional on the prevalence of a risk factor in a population, is presented. In this model, population changes result from the aggregation of changes in individual event histories, which, in turn, result from mortality and infertility rates recalculated in accordance with their known relative risks in population groups exposed to a risk factor. Smoking, being the most widespread and influential preventable public health risk factor, is chosen to demonstrate the abilities of the model to forecast the population effects of different hypothetical smoking prevalences. The demographic and population health effects on 20-, 50-, and 100-year projections with the current, hypothetically doubled, and hypothetically halved the current smoking prevalence are analyzed in detail. The model predicts an increase in life expectancy (0.99 year for males and 0.64 years for females), and an increase in population size (2.2-7.5% dependent on the age group) if smoking prevalence is reduced by half. Sensitivity analyses of all findings are performed. The generalization of the model to account for multiple risk factors (e.g., the simultaneous effects of alcohol consumption, obesity, and smoking) and effects on medical expenditures are discussed.